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TITLE: SURFACE-BASED CHARACTERIZATION OF HEALTHY HUMAN ADULT CORTEX: AN INVESTIGATION OF ITS MORPHOLOGICAL VARIABILITY, LATE MATURATION AND ASYMMETRIES ABSTRACT:

Studying the complexity of the human brain anatomy requires the characterization of multimodal and multiscale features obtained by recent in vivo neuroimaging techniques. In the present thesis, we benefited from up to date automated surface-based brain image analysis software to extract structural phenotypes of the human cerebral cortex, namely the cortical thickness, the surface area, the sulcal depth, the curvature and the intracortical myelin content. The principal aim of this work was to characterize multimodal structural variables on a large database of 450 healthy adults aged from 18 to 57 years (the BIL&GIN database) in order to describe the inter-individual variability of brain structural organization and notably the research of candidate markers for brain maturation and lateralization. We first took the example of the Heschl's gyrus hosting the primary auditory cortex and having high variability due to the presence of different pattern of gyrus duplication coupled with strong interhemispheric differences. We showed that the partial or complete duplication of the Heschl's gyrus was associated to loco-regional modifications in terms of cortical thickness, surface area and myelin located posteriorly to this gyrus and in the planum temporale, this two regions being implied in language processing. In a second study, we investigated the cortical structural modifications associated to late maturation (between 18 and 30 years) and cortical atrophy linked to aging. We revealed that the computation of a maturation index based on an integration of cortical thickness and intracortical myelin improved the discrimination of two different patterns of grey matter changes during these different stages of life. Finally, we characterized cortical asymmetries using a specific hemisphere surface matching which removed differences in sulcal morphology and position between both hemispheres. We highlighted regions where thickness and surface area asymmetries were concordant (leftward or rightward asymmetry for both anatomical variables) and regions of opposite asymmetries (leftward for one and rightward for the other). About 20% of regions that showed cortical thickness and surface area asymmetries presented negative correlation between these variables. It is striking that the two regions with the strongest anatomical asymmetries; the planum temporale and the superior temporal sulcus had rather positive asymmetry correlations. The planum temporale presented a leftward asymmetry of both cortical thickness and area while the superior temporal sulcus showed a right asymmetry of the two variables. This study demonstrated that there were correlations between thickness and surface area asymmetries, characteristics of the cortex organization. These areas are key sites for which it now remains to study the anatomical relevance as markers of brain lateralization and its functional correlates.

KEYWORDS: neuroimaging, human brain anatomy, interindividual variability, Heschl's gyrus, maturation, asymmetry, surface-based morphometry.

TITRE : CARACTERISATION SURFACIQUE DU CORTEX CEREBRAL CHEZ L'HOMME ADULTE SAIN : VARIABILITE MORPHOLOGIQUE, MATURATION TARDIVE ET ASYMETRIES

RESUME :

L'étude de la complexité de l'anatomie du cerveau humain nécessite la caractérisation des paramètres multimodaux et multi-échelle obtenus par des techniques de neuroimagerie récentes. Pour ce travail de thèse nous avons tiré profit d'un logiciel automatique actuel d'analyse surfacique d'images cérébrales afin d'extraire les phénotypes structuraux du cortex cérébral humain, c'est-à-dire l'épaisseur corticale, l'aire de la surface, la profondeur sulcale, la courbure et le contenu en myéline intracorticale. L'objectif principal de ce travail a été de caractériser des variables structurales multimodales sur une large base de données de plus de 450 adultes sains âgés de 18 à 57 ans (base de données BIL&GIN) dans le but de décrire la variabilité interindividuelle de l'organisation structurale du cerveau et notamment la recherche de marqueurs de la maturation cérébrale et de la latéralisation. Nous avons tout d'abord pris l'exemple du gyrus de Heschl, support anatomique du cortex auditif primaire, qui possèdent une grande variabilité en lien avec l'existence de différents profils de duplication du gyrus couplée à de fortes différences interhémisphériques. Nous avons montré qu'une duplication partielle ou complète du gyrus de Heschl était associée à des modifications locorégionales d'épaisseur corticale, d'aire de la surface et de myéline localisée postérieurement à ce gyrus et dans le planum temporale, ces deux régions étant impliquées dans le traitement du langage. Dans une deuxième étude, nous avons recherché les modifications structurales du cortex associées à la maturation tardive (entre 18 et 30 ans) et à l'atrophie corticale liée au vieillissement. Nous avons montré que l'établissement d'un index de maturation basé sur l'intégration de l'épaisseur corticale et de la myéline intracorticale améliorait la discrimination entre les 2 profils de modifications de la substance grise pendant ces deux périodes de la vie. Finalement, nous avons caractérisé les asymétries corticales en utilisant un recalage surfacique des hémisphères qui s'affranchit des différences de morphologie sulcale et de position entre les deux hémisphères. Nous avons mis en évidence des régions pour lesquelles les asymétries d'épaisseur et de surface étaient concordantes (asymétrie gauche ou droite pour les deux variables anatomiques) et des régions pour lesquelles les asymétries étaient opposées (gauche pour l'une des variables et droite pour l'autre). Environ 20% des régions qui montraient une asymétrie d'épaisseur et d'aire présentaient des corrélations négatives entre ces variables. Il est frappant de constater que les deux régions ayant les asymétries les plus fortes, le planum temporale et le sillon temporal supérieur, ont des corrélations positives entre leurs asymétries d'épaisseur et d'aire. Le planum temporale possède une asymétrie gauche à la fois pour l'épaisseur et l'aire alors que le sillon temporal supérieur a une asymétrie droite pour les deux variables. Cette étude démontre qu'il existe des corrélations entre les asymétries d'épaisseur et d'aire qui sont caractéristiques de l'organisation du cortex. Ces régions sont des sites clé pour lesquels il reste maintenant à étudier la pertinence en tant que marqueurs de la latéralisation cérébrale et leurs corrélats fonctionnels.

MOTS CLEFS : neuroimagerie, anatomie du cerveau humain, variabilité interindividuelle, gyrus de Heschl, maturation, asymétrie, morphométrie surfacique.

LABORATOIRE :

REMERCIEMENTS

Je tiens à remercier les rapporteurs de ma thèse, Pierre-Louis Bazin et Olivier Coulon pour avoir accepté d'évaluer mon travail de thèse, ainsi que Jean-François Mangin pour sa participation au jury.

Je remercie mon directeur de thèse, Fabrice Crivello, avec qui j'ai pris un réel plaisir à travailler. Merci de m'avoir fait confiance tout au long de ce travail, de m'avoir prodigué des conseils avisés, d'avoir consacré du temps au travers de relectures et réécritures et merci toutes les opportunités offertes.

Je voudrais aussi remercier très sincèrement Bernard Mazoyer et Nathalie Tzourio-Mazoyer pour m'avoir accueillie au GIN et formée à la recherche. Promis Bernard je ne divulguerai plus vos secrets ! Je remercie Bernard pour ses relectures, toujours pertinentes et son esprit critique. Nathalie, que je ne remercierai jamais assez pour sa patience, son incroyable passion pour la recherche qu'elle a réussi à me transmettre, son sens de la rigueur et de la persévérance jusqu'à obtenir le travail le plus abouti, et qui fera partie de ces personnes qui comptent dans une carrière tant par les travaux que nous aurons mené ensemble que par ses qualités humaines.

Je souhaite également remercier tous les chercheurs et maîtres de conférence du laboratoire pour leur accueil, chacun de vous aura contribué d'une certaine manière à cette thèse : Emmanuel Mellet pour toutes ses blagues auxquelles j'ai ri de bon coeur et surtout pour tous ses conseils et discussions quant à mon avenir ; Laurent Petit pour son humour et ses explications toujours claires ; Laure Zago pour son extrême gentillesse et ses précieux conseils pour la préparation des cours ; Marc Joliot pour sa franchise et les discussions intéressantes et toujours animées que l'on a pu avoir ; Gaël Jobard pour son expérience de maître de conférence qui m'aura beaucoup aidée à préparer les cours que j'ai dû assurer ; Isabelle Hesling pour sa gentillesse et la relecture (en express) de ce manuscrit.

Je remercie aussi Pierre-Yves Hervé, Gaëlle Leroux et Christophe Delalande pour leur patience quant à mon manque de connaissance en informatique, pour leurs « trucs » et astuces sur Linux et Matlab dont je me sers tous les jours. Je remercie aussi Nicolas Vinuesa, argentin « italien », qui m'aura bien aidée à écrire des scripts qui me sont toujours utiles, ça a été un plaisir de travailler avec toi.

Je tiens aussi à remercier Anita Foro, qui était là lors de mon stage de Master et le début de ma thèse, pour son immense gentillesse, sa disponibilité et tous les délicieux gâteaux qu'elle nous faisait ; et bien sûr Guy Perchey pour avoir eu la patience de me mettre dans l'IRM, pour nos discussions sportives plus ou moins houleuses et pour tous ces moments conviviaux et simples que nous avons partagés.

Je souhaite aussi remercier les doctorants et post-doctorants ayant travaillé au laboratoire : Quentin Duriez, Damien Marie, Janice Hau, Sanja Budisavljevic et Solveig Badillo. Quentin et Damien, merci de m'avoir accueillie et supportée, les bureaux me paraissent un peu vides sans vous ! Je tenais à remercier particulièrement Damien pour le travail que l'on a réalisé ensemble sur le « sacrosaint » gyrus de Heschl, ça n'aura pas été facile mais nous avons terminé…enfin jusqu'au prochain ! Sanja, merci de m'avoir forcée à parler anglais, depuis que tu es parti mon niveau ne s'est clairement pas amélioré, et pour tous ces moments à Hambourg et Genève. Je remercie aussi Julie Panzieri, que j'ai eu le plaisir de coencadrer pendant son stage de Master 1. Cette mission a été intéressante et m'a montré que toutes les questions, même les plus simples étaient toujours pertinentes. J'espère que nous serons amenées à retravailler ensemble.

J'aimerai enfin remercier mes amis qui m'auront soutenue et encouragée pendant ma thèse : mes amis d'enfance Mathilde et Yannick, les MOCS, chacun et chacune de vous, Hortense ma future propriétaire, Alice, Delphine, Laura, Louise, Marine, Océane, Marie-Ange et Thomas, vous le savez c'est en partie grâce à vous que ma carrière va prendre un chemin parallèle. Je remercie toutes mes coéquipières de volley et beach volley grâce à qui je me suis dépassée et changée les idées tout au long de l'année. Je remercie tout spécialement Mahé d'avoir gentiment relu ce manuscrit.

Enfin et surtout je remercie ma famille pour leur soutien et surtout ma mère pour m'avoir donné autant de chance pour réussir, et Marc pour m'avoir supportée pendant ces dernières semaines difficiles. Sans son aide et son soutien je n'aurais sans doute pas pu tout mener à bien.

RÉSUMÉ EN FRANCAIS

Le cerveau humain est une machinerie complexe composé de près de 100 milliards de neurones et de 10 000 fois plus de synapses qui assurent la transmission de l'influx nerveux entre deux neurones. Cette incroyable complexité repose sur son organisation macroscopique et microscopique dont la compréhension à différentes échelles constitue l'un des défis scientifiques majeurs du 21 ème siècle.

Les neurosciences cognitives ont ainsi tiré profit, depuis les deux dernières décennies, des remarquables avancées des techniques de neuroimagerie. Celles-ci permettent en effet l'étude de l'anatomie et de la fonction cérébrale in vivo dans de larges populations, grâce notamment à l'essor de l'imagerie par résonance magnétique (IRM). Les développements récents et rapides de la neuroimagerie ont ainsi favorisé la production d'une très grande quantité d'informations numériques concernant le cerveau humain sain et pathologique.

La neuroimagerie in vivo est une discipline remarquablement diverse et multimodale, permettant l'étude de l'anatomie, la fonction et la connectivité cérébrale [START_REF] Glasser | A multi-modal parcellation of human cerebral cortex[END_REF]). La flexibilité de l'IRM donne accès à un certain nombre de variables macroscopiques (telles que l'épaisseur régionale du cortex ou le volume de structures spécifiques), microscopiques (telles que l'anisotropie de diffusion dans les faisceaux de substance blanche ou le contenu en myéline dans le ruban cortical) et fonctionnelles du cerveau (activation lors de tâche ou connectivité fonctionnelle au repos).

La morphométrie cérébrale permet d'extraire des mesures anatomiques des structures du cerveau à partir des images IRM pondérées en T1 et constitue le support de l'intégration multimodale et multi-échelle. L'étude de l'anatomie cérébrale humaine a notamment pour but de décrire les relations anatomo-fonctionnelles afin de fournir des connaissances approfondies quant à la neuroanatomie cognitive et la mise en place des fonctions cérébrales. Celle-ci doit intégrer le fait que l'organisation structurale du cerveau change constamment, en lien avec le développement [START_REF] Giedd | Anatomical brain magnetic resonance imaging of typically developing children and adolescents[END_REF]), le vieillissement [START_REF] Crivello | Longitudinal assessment of global and regional rate of grey matter atrophy in 1,172 healthy older adults: modulation by sex and age[END_REF], l'expérience et l'apprentissage [START_REF] Draganski | Temporal and spatial dynamics of brain structure changes during extensive learning[END_REF]). L'établissement de « normes » quant à l'anatomie du cerveau sain au cours du développement et tout au long de la vie permet de rechercher de potentielles déviations par rapport à cette base de référence, conséquences de maladies neurodéveloppementales ou neurodégératives. La connaissance précise de la dynamique temporelle de l'évolution de l'anatomie cérébrale est essentielle dans la recherche de biomarqueurs de maladies neurologiques (maladie d'Alzheimer, Desikan et al. 2009), psychiatriques (schizophrénie, Brent et la. 2013) ou neurodéveloppementales (autisme, [START_REF] Courchesne | Brain growth across the life span in autism: age-specific changes in anatomical pathology[END_REF]. Cependant, le signal IRM ne constitue qu'une mesure indirecte.

Les méthodes d'analyse d'images ont permis d'améliorer l'extraction de phénotypes cérébraux les plus précis possibles, avec notamment l'utilisation d'approche multimodale et l'IRM quantitative. Grâce aux progrès informatiques permettant la reconstruction des surfaces externe et interne du cerveau, des méthodes de morphométrie surfacique permettent d'extraire des phénotypes anatomiques variés tels que l'épaisseur corticale, la surface ou des index de gyrification avec la courbure ou la profondeur des sillons. L'épaisseur corticale a ainsi été montrée comme étant moins variable [START_REF] Hutton | A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging[END_REF]), plus reproductible [START_REF] Dickerson | Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths[END_REF][START_REF] Clarkson | A comparison of voxel and surface based cortical thickness estimation methods[END_REF], Redolfi et al. 2015) et plus sensible [START_REF] Burggren | Reduced cortical thickness in hippocampal subregions among cognitively normal apolipoprotein E e4 carriers[END_REF]) que le volume ou plus précisément la densité de substance grise, initialement utilisé dans les études de morphométrie cérébrale. Plus récemment, certaines techniques de neuroimagerie ont été proposées afin d'évaluer la quantité de myéline au sein du ruban cortical. En effet, le cortex n'est pas seulement composé des corps cellulaires de neurones mais aussi d'axones entourés d'un gaine de myéline qui isole, protège et augmente la vitesse de communication électrique entre les neurones.

La complexité de l'organisation cérébrale est en partie due au fait que les circonvolutions corticales sont très variables d'un individu à l'autre. L'étude du profile de gyrification permettrait de fournir une meilleure compréhension de la variabilité anatomique [START_REF] Mangin | A framework to study the cortical folding patterns[END_REF]). Certaines unités gyro-sulcales présentent une localisation et une étendue plus reproductibles d'un individu à l'autre (ex : sillon central, scissure calcarine, scissure de Sylvius) en lien avec leur mise en place précoce lors du développement foetal. Malgré cela, le sillon central peut présenter un décalage allant jusqu'à 2 cm d'un individu à l'autre et certaines structures corticales telles qu'un second gyrus transverse temporal (ou gyrus de Heschl) [START_REF] Penhune | Interhemispheric anatomical differences in human primary auditory cortex: probabilistic mapping and volume measurement from magnetic resonance scans[END_REF] ou le sillon paracingulaire [START_REF] Paus | Human Cingulate and Paracingulate Sulci: Pattern, Variability, Asymmetry, and Probabilistic Map[END_REF], ne sont pas visibles chez l'ensemble de la population. Cette variabilité interindividuelle est associée à une sensibilité régionale différentielle au développement, à la maturation et à la plasticité liée à l'expérience (Hill et al. 2010b). Bien que la morphologie générale du cerveau adulte soit bien établie dès la naissance, une maturation régionale mesurable via des modifications des caractéristiques structurales du cortex continue d'avoir lieu chez les jeunes adultes, et les corrélats locaux de cette maturation tardive doivent être étudiés dans de grandes populations.

Une autre caractéristique importante de l'organisation du cerveau humain est l'existence de différences entre les hémisphères, que cela soit en terme d'anatomie ou de fonction. Bien que les hémisphères gauche et droit subissent un développement symétrique, un certain nombre de différences structurales mesurables via l'IRM existent entre les deux côtés du cerveau [START_REF] Watkins | Structural Asymmetries in the Human Brain :a Voxel-based Statistical Analysis of Collins 142 MRI Scans[END_REF][START_REF] Hervé | Finger tapping, handedness and grey matter amount in the Rolando's genu area[END_REF], Luders et al. 2006a[START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF], Van Essen et al. 2012[START_REF] Chiarello | Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification[END_REF], et chaque hémisphère est dominant pour le traitement de tâches cognitives spécifiques [START_REF] Duboc | Asymmetry of the Brain: Development and Implications[END_REF][START_REF] Hervé | Revisiting human hemispheric specialization with neuroimaging[END_REF]. Néanmoins, les implications des asymétries anatomiques sur la fonction cérébrale sont très complexes à prédire [START_REF] Eckert | Uncoupled leftward asymmetries for planum morphology and functional language processing[END_REF][START_REF] Ocklenburg | Intrahemispheric white matter asymmetries: the missing link between brain structure and functional lateralization[END_REF]) et seulement des corrélations locales subtiles ont été mises en évidence entre la latéralisation d'une fonction et le degré d'asymétrie de substance grise [START_REF] Josse | Predicting language lateralization from gray matter[END_REF]. En somme, le support neuroanatomique de cette latéralisation fonction reste une question ouverte. Leur recherche nécessite l'utilisation de variables anatomiques robustes qui ne seraient pas biaisées par la méthode mise en place, et l'étude de leur distribution et de leur interaction pourrait constituer une piste pour la définition de marqueurs de différence entre les hémisphères cérébraux.

Ce travail de thèse repose sur l'utilisation d'un logiciel récent d'analyse d'IRM anatomiques cérébrales qui se base sur une méthode automatique de reconnaissance des surfaces externe et interne du cortex, permettant ainsi l'extraction et la génération de phénotypes anatomiques variés. Les différentes études qui vont suivre ont tiré profit de l'exploitation d'une grande base de données acquises par le laboratoire (BIL&GIN pour Brain Imaging of Lateralization & Groupe d'Imagerie Neurofonctionnelle) afin de rechercher les corrélats de la variabilité interindividuelle, son évolution lors de la maturation cérébrale tardive et les différences anatomiques entre les deux hémisphères.

Le Chapitre 1 s'intéresse aux conséquences de la variabilité du gyrus de Heschl's sur l'ensemble du cortex. Cette structure héberge le cortex auditif primaire qui est la première étape de traitement des sons au niveau cérébral. De plus, ce gyrus se caractérise par une très grande variabilité anatomique entre les individus, mais également entre les deux hémisphères chez un même individu. Il peut comporter un seul pli cérébral, le gyrus de Heschl, ou être double et dans ce dernier cas on distingue les duplications partielles ou complètes en fonction de la profondeur et de la longueur du sillon séparant les deux gyri. L'objectif de cette première étude a été d'utiliser des marqueurs anatomiques multimodaux pour caractériser les modifications locales liées à la présence d'un second gyrus.

A partir des données d'une étude précédente [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF] où nous avions catégorisé les configurations des gyri de Heschl chez 430 participants sains, nous avons utilisé des logiciels de morphométrie permettant de mesurer l'épaisseur du cortex, la surface et la myéline intracorticale pour suivre leurs variations en fonction de la présence et du type de duplication. Pour ce faire nous avons crée une image de cerveau composé de 40 sujets : 20 sujets avec un gyrus unique bilatéral, 10 avec une duplication partielle bilatérale et 10 avec une duplication complète bilatérale. Ce cerveau moyen a servi de « gabarit » pour le recalage de chaque cerveau de notre population nécessaire à la comparaison des sujets entre eux.

Cette étude montre à la fois des différences locales, au niveau du gyrus de Heschl, directement liées à des changements morphologiques et des variations à distance qui pourraient être en relation avec des différences d'organisation anatomique et/ou fonctionnelle (Figure 1). En effet, les participants ayant une duplication présentent localement une augmentation d'épaisseur corticale postérieure au premier gyrus de Heschl, au niveau du second gyrus de la duplication. A distance, à gauche on note en plus une diminution de surface corticale du planum temporale des sujets présentant une duplication complète ou partielle. Dans l'hémisphère droit les duplications s'accompagnent d'une augmentation de surface corticale du gyrus de Heschl et du sillon temporal supérieur droit.

Lorsque l'on s'intéresse à la distribution de la myéline, évaluée grâce à la mesure du ratio T1/T2 [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF], au sein du ruban cortical, nos résultats montrent une forte densité de myéline, caractéristique propres aux aires corticales primaires, au niveau du gyrus de Heschl's qui s'étend au second gyrus (postérieur) dans le cas d'une duplication (Figure 2). Le signal semble malgré tout moins intense qu'au niveau du gyrus antérieur. Ces résultats montrent aussi une extension du fort signal de myéline dans le planum temporale de l'hémisphère gauche seulement.

Figure 1 -Variations significatives d'épaisseur corticale et de surface pour les contrastes « CPD-single » i.e. « duplication complète -gyrus unique », « CSD-single » i.e. « duplication partielle -gyrus unique », et « CPD-CSD » i.e. « duplication complèteduplication partielle ». A. Variations significatives d'épaisseur corticale. B.

Variations significatives de surface, la vue latérale du lobe temporal droit est fournie pour illustrer l'augmentation de surface localisée sur la partie médiane du sillon temporal supérieur pour la comparaison « duplication partielle -gyrus unique ». Les variations significatives sont superposées au lobe temporal moyen de chacun des groupes (« CPD-single » et « CSD-single » : représentation moyenne issue de 48 sujets avec une duplication complète gauche et 96 sujets avec une duplication complète droite ; « CSD-single » : représentation moyenne issue de 98 sujets avec une duplication partielle gauche et 95 sujets avec une duplication partielle droite). P < 0.05 corrigé FDR pour les comparaisons multiples, taille limite de cluster < 20 mm 2 ; les couleurs chaudes indiquent une variation positive et les couleurs froides une variation négative.

Les différences de groupes montrent que la présence d'une duplication est associée à une diminution de la quantité de myéline postérieurement au gyrus de Heschl, plus précisément au niveau du sillon qui le sépare du planum temporale, traduisant une dépendance morphologique de la distribution de myéline au sein du cortex (Figure 3). L'observation de ces variations dans des aires impliquées, à gauche dans le traitement acoustique temporel (les variations acoustiques extrêmement rapides s'opèrent en quelques dizaines de millisecondes) et à droite dans le traitement acoustique spectral (détection de variations fines de tonalité concernant certains aspects de la musique ou la prosodie de la voix humaine), sont importantes pour la recherche dans le domaine de la perception du langage et de la musique et de leur développement. En effet, les duplications du gyrus de Heschl ont été associées avec une expertise musicale ou phonologique chez les sujets sains dont l'augmentation d'épaisseur corticale pourrait être le support. Mais on observe également plus fréquemment des duplications en cas de dyslexie ce qui suggère qu'une augmentation d'épaisseur corticale pourrait représenter un avantage cognitif ou non selon que le développement cortical est normal ou pathologique.

Une des perspectives de ce travail est la recherche de potentielles asymétries de myéline au niveau du gyrus de Heschl et du planum temporale, et la caractérisation de nouveaux marqueurs pour la latéralisation du langage via l'exploitation des données de myéline. De plus, grâce à la mise en place d'une collaboration avec le « Brain and Langage Lab » (dirigé par Narly Golestani), nous envisageons d'utiliser ces cartes de myéline pour améliorer la reconnaissance automatique du cortex auditif, notamment les limites antérieures et postérieures du gyrus de Heschl et ce en utilisant un « apprentissage machine ». La perte de volume de gris est un phénomène majeur lors du développement et du vieillissement. Celle-ci participe à la bonne mise en place de l'organisation anatomo-fonctionnelle du cerveau humain. Dans le Chapitre 2 nous avons donc cherché à différencier les phénomènes d'atrophie liés au vieillissement de l'amincissement du cortex au cours de la maturation tardive chez les jeunes adultes par la quantification des modifications d'épaisseur et de myéline intracorticale. En effet, ces deux processus sont sous-tendus par des mécanismes neurobiologiques différents avec notamment le pruning synaptique, la réduction du nombre de cellules gliales et la prolifération de la myéline dans le neuropile lors de la maturation [START_REF] Shaw | Neurodevelopmental trajectories of the human cerebral cortex[END_REF], et la perte progressive des neurones et des axones myélinisés, la rétractation des corps cellulaires et la diminution de la densité synaptique lors du vieillissement [START_REF] Hof | The aging brain: morphomolecular senescence of cortical circuits[END_REF]. Pour cela, nous avons défini deux sous-populations, les adultes jeunes âgés de 18 à 30 ans (n = 341) et les adultes d'âge moyen âgés de 30 à 57 ans et nous avons ensuite étudié l'effet de l'âge sur l'épaisseur corticale et la myéline. On observe ainsi, chez les jeunes adultes, une diminution de l'épaisseur corticale sur la quasi-totalité du cortex avec essentiellement les aires associatives associé à une préservation des cortex sensorimoteur et visuel. De plus, les taux de diminution de l'épaisseur corticale sont plus importants entre 18 et 30 ans qu'entre 30 et 57 ans avec un amincissement deux fois plus élevé au niveau global hémisphérique (-10 µm/an vs. -5 µm/an) et la différence pouvant varier localement d'un facteur 10. En parallèle on a une augmentation de la myélinisation intracorticale dans les régions primaires et au niveau des lobes frontaux chez les jeunes adultes avec des taux d'augmentation significativement plus important au niveau du cortex précentral droit en comparaison des adultes d'âge moyen.

En somme, chez les jeunes adultes on observe donc une forte diminution d'épaisseur corticale concomitante à une augmentation de myéline intracorticale. Ce phénomène de dynamique inversée nous a conduit à générer un index de maturation à partir de ces 2 variables afin de maximiser ces deux effets en calculant le ratio entre l'épaisseur et la myéline. Cela nous a permis de mieux différencier les modifications structurales liées à la maturation essentiellement localisées au niveau frontal et cingulaire qui sont des régions qui supportent les fonctions exécutives (Figure 4).

Une perspective de ce travail est d'appliquer cet index de maturation à l'exploration des modifications structurales ayant lieu lors d'une période d'apprentissage intensif i.e. au début de l'âge adulte et de rechercher la fréquence et les conséquences de certaines maladies telles que la dépression ou l'anxiété. Dans cette optique, la génération automatique des cartes surfacique de myéline et de l'index de maturation sera appliquée à la cohorte I-Share qui va rassembler 2000 étudiants âgés de 18 à 25 ans.

L'une des caractéristiques anatomiques du cerveau est la présence de 2 hémisphères qui sont le siège de fonctions cognitives différentes. Dans le Chapitre 3 nous avons donc chercher à mieux comprendre le pattern d'asymétries anatomiques interhémisphériques et la relation entre les différentes variables afin d'apporter des éléments nouveaux quant à la caractérisation fonctionnelle du cerveau.

Nous avons ainsi sélectionné 250 sujets ayant une latéralisation fonctionnelle « typique » gauche pour le langage évalué par une mesure d'index d'asymétrie hémisphérique pendant une tâche de production de langage [START_REF] Mazoyer | Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness[END_REF]) afin d'éviter que la variabilité de la latéralisation pour le langage soit une variable de confusion pour caractériser le profil d'asymétries anatomiques standard [START_REF] Greve | A surface-based analysis of language lateralization and cortical asymmetry[END_REF].

L'étude des asymétries surfaciques corticales nécessite la mise en place d'une méthodologie d'analyse basée sur le recalage précis des sillons entre les deux hémisphères. Nous avons pour cela générer un template symétrique présentant une correspondance précise entre une région d'un hémisphère et son homologue dans l'autre. Nous avons ainsi mis en évidence des asymétries d'épaisseur et d'aire concordantes et corrélées notamment au niveau d'asymétries d'apparition très précoces sans doute d'origine génétique, différenciables des autres régions qui présentent un profil plus complexe.

La caractérisation de ces phénotypes corticaux d'asymétries s'intègre dans le projet MULTI-LATERAL (Multi-level Integrative Analysis of Brain Lateralization for Language) qui vise à rechercher des déterminants génétiques des asymétries anatomiques.

L'approche méthodologique que j'ai mise en place au cours de cette thèse et qui combine l'exploitation d'une large base de données et l'utilisation combinée de nouvelles variables plus proches de la biologie m'a permis de caractériser à l'échelle mésoscopique des éléments essentiels de l'organisation corticale du cerveau adulte sain. J'ai pu montrer, que la survenue d'un gyrus supplémentaire induit une organisation anatomique différente des structures adjacentes. J'ai pu caractériser de manière beaucoup plus fine les différences d'organisation anatomique des deux hémisphères et ainsi proposer une nouvelle carte des asymétries corticales. Enfin cette approche m'a également permis de différencier au sein d'un mécanisme commun à l'évolution du cortex au cours de la vie, ce qui relevait de la maturation et du vieillissement. Cette approche ouvre d'importantes perspectives pour la compréhension des phénomènes qui sous tendent les rapports anatomo-fonctionnels en relation avec la cognition. Something like 20,000 active genes specify a functional brain structure with 100 billion neurons and a quadrillion synapses. This incredible complexity is present considering the macroscopic and microscopic organization, and the characterization at different scales of the healthy human brain anatomy is a great scientific challenge of the 21 st century. Cognitive neuroscience benefits since the two past decades from the outstanding advancements of neuroimaging technologies making it possible to study both the anatomy and the function of the brain in vivo and in large populations. Actually, in vivo neuroimaging, such as Magnetic Resonance Imaging (MRI), is not unimodal but, rather, remarkably diverse -examining brain anatomy, function, and connectivity [START_REF] Glasser | A multi-modal parcellation of human cerebral cortex[END_REF]. The flexibility of MRI allows for the measurements of macrostructural features (such as the regional thickness of the cortex or the volume of specific structures), microstructural features (such as diffusion anisotropy within white matter tracts or the myelin content of the cortical ribbon) and functional brain characteristics (from task-driven activation to restingstate intrinsic connectivity) and clearly requires the management and integration of this enormous amount of information about neural structure and/or function.

LIST OF ABBREVIATIONS AND ACRONYMS

The fast and recent developments of neuroimaging have produced huge quantities of digital information about the healthy and pathological human brain and one can now consider that human neuroimaging is a "big data" science [START_REF] Van Horn | Human neuroimaging as a "Big Data" science[END_REF]. In this framework, the numbers of national and international largescale projects such as Human Connectome Project (HCP), Brain Research through Advancing Innovative Neurotechnologies ® (BRAIN) initiative in the United States and the Human Brain Project (HBP) in Europe, have been increasing in recent years. Some international consortiums have also focused on the research of biomarkers as predictors for diseases such as Alzheimer's Disease Neuroimaging Initiative (ADNI) or the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE). All these projects have led to an explosive growth of the amount of openly available and shared neuroimaging data.

Other scientific fields, like astronomy, natural history or genetics, have demonstrated the benefits of databasing and datasharing [START_REF] Poline | Data sharing in neuroimaging research[END_REF]. These practices allow for the testing of relationships between data that are derived from different experiments, using different methods, to study different aspects of the brain, on different subjects, from different laboratories (Toga, 2002). It maximizes the potential benefit to society of the subject's participation by providing greater opportunities for scientific discovery and it enables new questions such as the characterization of common latent neural networks that underlie many different cognitive tasks [START_REF] Poldrack | Making big data open: data sharing in neuroimaging[END_REF]. For example, databases such as Brainmap (http://www.brainmap.org) and Neurosynth (http://neurosynth.org) aggregate coordinate-based structural and functional MRI results derived from the scientific literature, and several publications have validated the use of such resources to perform meta-analytic studies. However, the reliability between a study using the original functional contrast maps and those derived from the coordinates alone has been shown to be poor [START_REF] Salimi-Khorshidi | Metaanalysis of neuroimaging data: a comparison of image-based and coordinatebased pooling of studies[END_REF], providing an argument for the need to share original and derived images, not only the Talairach coordinates which are often published in journal articles. The datasharing also enhances reliability and reproducibility of scientific research to overcome the major concern of low statistical power of many published studies [START_REF] Button | Power failure: why small sample size undermines the reliability of neuroscience[END_REF]. It allows for the generation of sample sizes that would not be accessible to a single laboratory, which is notably necessary for genetic association studies and publications by multi-site consortia are now the norm [START_REF] Bis | Common variants at 12q14 and 12q24 are associated with hippocampal volume[END_REF][START_REF] Medland | Whole-genome analyses of whole-brain data: working within an expanded search space[END_REF]. We can cite the example of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium which is a collaborative network of researchers working together on a range of largescale studies that integrate data from 70 institutions worldwide, of which the "Groupe d'Imagerie Neurofonctionnelle" is a part [START_REF] Medland | Whole-genome analyses of whole-brain data: working within an expanded search space[END_REF]. Knowing that neuroimaging research is costly both in terms of the data acquisition and the significant time spent in data retention and management, sharing databases could participate to the reduction of the cost of research and to the increase of the return on current research investments. Nevertheless, such a practice raises a number of continuing challenges: the quality control to ensure the integrity of the data, the sharing of all analyses and automated and robust processing code, which is as important as sharing raw data, and several numerous ethical and legal issues.

Among this huge quantity of neuroimaging data the brain morphometry that concerns the measurement of brain structures from T1-weighted imaging represents the support of multimodal and multiscale integration. One aspect of studying the healthy brain anatomy is to describe structure-function relationships in order to provide comprehensive understanding of cognitive neuroanatomy and the settlement of cognitive functions. Given its structural and functional complexity, this is a particularly challenging task when applied to the brain. The investigation of brain anatomy should integrate the fact that the structural organization of brain circuitry is constantly changing as a function of development [START_REF] Giedd | Anatomical brain magnetic resonance imaging of typically developing children and adolescents[END_REF], aging [START_REF] Crivello | Longitudinal assessment of global and regional rate of grey matter atrophy in 1,172 healthy older adults: modulation by sex and age[END_REF], experience and learning [START_REF] Draganski | Temporal and spatial dynamics of brain structure changes during extensive learning[END_REF]. Establishing brain anatomy "norm" across development and lifespan (Dima et al., in revision) allows for investigating potential deviation from this baseline due to neurodevelopmental or neurodegenerative diseases. Knowledge about the temporal dynamics of brain anatomy is essential to investigate the consequences of neurological (Alzheimer's disease, Desikan et al., 2009), psychiatric (schizophrenia, Brent et al., 2013), or neurodevelopmental pathologies (autism, [START_REF] Courchesne | Brain growth across the life span in autism: age-specific changes in anatomical pathology[END_REF].

Nevertheless, MRI signal is only an indirect measure of the actual brain structure, for example the measurement of cortical does actually provide quantitative information on neuronal density. Feeling the gap between the changes being examined with structural MRI and the neurobiological bases of brain modifications such as neuronal migration, synaptogenesis, synaptic pruning, myelination, neuronal atrophy [START_REF] Poldrack | Interpreting developmental changes in neuroimaging signals[END_REF], is a timely challenge. For example, the neurobiological changes that occur from childhood to young adulthood are related to both the inherited structural development of the human brain and the experience-dependent cortical plasticity, such as changes in the cellular organization or myelin content of the cerebral cortex. Moreover, markers of these changes on imaging signals are partly accessible. For example, the modifications of the cortical thickness in relation to age or pathology are difficult to interpret by oneself and the implications of such changes for functional imaging signals are still not fully understood. From a simplistic neurobiological point of view, a loss of cortical thickness is interpreted as a sign of neuronal loss, while an increase is considered as a correlate of use-dependant brain plasticity [START_REF] Zatorre | Predispositions and plasticity in music and speech learning: neural correlates and implications[END_REF][START_REF] Draganski | Computational anatomy for studying usedependant brain plasticity[END_REF]. Actually, depending on to the age range, the cortical thinning measured with structural MRI data can be either in relation with cortical processes supporting brain maturation in children and early adulthood or to neuronal atrophy in the elderly [START_REF] Walhovd | Through Thick and Thin: a Need to Reconcile Contradictory Results on Trajectories in Human Cortical Development[END_REF]. Indeed, morphological brain changes detected from standard T1-weighted anatomical MRI data reflect macroscopic morphological brain changes linked to different physiological processes.

To progress on this issue, multimodal MRI approach and quantitative MRI have been recently developed to allow for the extraction of different brain structural phenotypes from MRI images mapped at the same location. The first quantitative method used to analyse structural MRI images was the Voxel-Based Morphometry that assessed the grey matter density in a volumetric representation of the brain [START_REF] Ashburner | Voxel-based morphometry--the methods[END_REF][START_REF] Good | Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains[END_REF]. Computational advances in surface reconstruction of inner and outer cortical boundaries have allowed for the development of Surface-Based Morphometry methods which provide new anatomical phenotypes such as cortical thickness, cortical surface area or gyrification assessed by the curvature and the sulcal depth. In addition to this corpus of structural variables, it is also essential to accurately register structural phenotypes in hundred of individuals in a common reference space, providing a way to assess their variability pattern and changes over time or across groups.

One key anatomical feature is the cortical thickness that has been revealed to be less variable, more reproducible and more sensitive than the volume. Dickerson et al. showed that an automated method for the measurement of cortical thickness from MRI data is remarkably reliable across different scanners and magnetic field strength for the detection and quantification of regional cortical thickness correlates of cognitive performance [START_REF] Dickerson | Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths[END_REF][START_REF] Clarkson | A comparison of voxel and surface based cortical thickness estimation methods[END_REF]. Hutton et al. highlighted that, for a given age, the regional cortical thickness has a lower interindividual variability than the cortical volume [START_REF] Hutton | A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging[END_REF]. Moreover, a study conducted on participants carrying the apolipoprotein E ε4 allele, the primary genetic risk factor for late-onset Alzheimer's disease, showed a decrease of cortical thickness in the entorhinal cortex and the subiculum, in comparison to non-carriers, whereas volumetric measurements did not reveal any differences in these regions [START_REF] Burggren | Reduced cortical thickness in hippocampal subregions among cognitively normal apolipoprotein E e4 carriers[END_REF]. The reproducibility of cortical thickness extraction algorithms (Redolfi et al., 2015) facilitates the pooling of MRI data across multiple centres and then the management of huge quantity of data. Furthermore, inflation or spherical mapping of the cortical surface mesh raises the buried sulci to the surface so that mapped functional activity in these regions can be easily visualized.

More recently, various MRI techniques have been developed for myelin assessment in the cortical ribbon. The myelin is a fatty substance that forms an insulating and protective sheath around the neuronal fibers -the axons, and serves to increase the speed of electrical communication between neurons.

How cortical thickness and myelin vary in case of differences in convolutions across individuals? This knowledge is a first step toward a better understanding of the structural variability between brains [START_REF] Mangin | A framework to study the cortical folding patterns[END_REF]. Some cortical landmarks are more consistent in terms of location and extent (central sulcus, calcarine sulcus and Sylvian fissure) because they take place earlier during fetal life. Despite all this, the central sulcus can vary in location by up to 2 cm between individuals, and some brain structures such as a second transverse temporal gyrus (also named Heschl's gyrus) [START_REF] Penhune | Interhemispheric anatomical differences in human primary auditory cortex: probabilistic mapping and volume measurement from magnetic resonance scans[END_REF] or the paracingulate sulcus [START_REF] Paus | Human Cingulate and Paracingulate Sulci: Pattern, Variability, Asymmetry, and Probabilistic Map[END_REF] are not visible in all subjects. This interindividual variability is associated with differential sensitivity of cortical regions to development, maturation (Hill et al., 2010b) and experience-related changes [START_REF] Zatorre | Predispositions and plasticity in music and speech learning: neural correlates and implications[END_REF]. Although adult cortical shape characteristics are already present at birth, regional maturation of cortical features is still occurring during young adulthood (Tamnes et al., 2010a) and regional correlates of late brain maturation need to be investigated in large population.

Human brain is constituted of two hemispheres that are functionally specialized and knowledge is missing on the difference between hemispheres in terms of anatomy. Although the left and right hemispheres develop with a high degree of symmetry, it has become clear that measurable structural differences exist between the two sides [START_REF] Watkins | Structural Asymmetries in the Human Brain :a Voxel-based Statistical Analysis of Collins 142 MRI Scans[END_REF][START_REF] Hervé | Finger tapping, handedness and grey matter amount in the Rolando's genu area[END_REF]Luders et al., 2006a;[START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF]Van Essen et al., 2012;[START_REF] Chiarello | Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification[END_REF] and that each hemisphere is dominant in processing specific cognitive tasks [START_REF] Duboc | Asymmetry of the Brain: Development and Implications[END_REF][START_REF] Hervé | Revisiting human hemispheric specialization with neuroimaging[END_REF]. Nevertheless, the implications of anatomical asymmetries on brain function are very complex to predict [START_REF] Eckert | Uncoupled leftward asymmetries for planum morphology and functional language processing[END_REF][START_REF] Ocklenburg | Intrahemispheric white matter asymmetries: the missing link between brain structure and functional lateralization[END_REF] and only subtle local correlations have been found between the lateralization of a function and the degree to which grey matter is lateralized [START_REF] Josse | Predicting language lateralization from gray matter[END_REF]. So, the neuroanatomical support of such a functional lateralization still remains a key issue. Their investigation requires the use of robust anatomical features and unbiased methodologies and could be elucidated through the study of their interaction to define markers of differences between hemispheres.

During this PhD work, I have benefited from up to date automated surfacebased brain image analysis software to extract various structural variables on a large database (see Annexes -2. The BIL&GIN database) to question the anatomical correlates of interindividual variability, its evolution during the late brain maturation and their differences between both hemispheres. Chapter 1 investigates the consequence of the gyrification pattern of Heschl's gyrus. The aim is to benefit from multimodal imaging and techniques to characterize the local modifications implicated by the presence of a second gyrus. Considering that variability of brain anatomy and its plasticity supports the settlement of brain functions, Chapter 2 focuses on the characterization of late cortical maturation occurring during earlyadulthood by assessing age-related modifications through cortical thickness and intracortical myelin content. Finally, Chapter 3 reports the patterns of surface-based morphometric asymmetries of cortical thickness, cortical surface area and sulcal depth and their intra-regional relationships in a subsample of the BIL&GIN database selected as having a typical leftward lateralization for language as measured (see .

INFLUENCE OF THE GYRIFICATION ON THE ANATOMICAL ORGANIZATION OF THE CORTEX:

EXAMPLE OF HESCHL'S GYRUS 1

INTRODUCTION

The cerebral anatomy is very similar across individuals with some constant landmarks such as the central sulcus that separates the motor precentral gyrus from the sensory postcentral gyrus, or the Sylvian lateral fissure that delineates the upper limit of temporal lobe. Cortical structures (gyri and sulci) set up during the development with a precise dynamic [START_REF] White | The development of gyrification in childhood and adolescence[END_REF][START_REF] Rolo | Development of fetal brain sulci and gyri: assessment through two and three-dimensional ultrasound and magnetic resonance imaging[END_REF][START_REF] Habas | Early folding patterns and asymmetries of the normal human brain detected from in utero MRI[END_REF]. For example the calcarine fissure appears on the 15 th week of gestation [START_REF] Huang | Anatomical characterization of human fetal brain development with diffusion tensor magnetic resonance imaging[END_REF] (Figure 1) while the transverse temporal gyrus (also named Heschl's gyrus) only between the 28 th week and the 31 th [START_REF] White | The development of gyrification in childhood and adolescence[END_REF].

Despite this precise developmental timeline for gyrification, some structures are very variable in terms of position, size, number of a specific gyrus or sulcal configuration. These variabilities appear in-between individuals as well as hemispheres, and make each brain unique. Concerning the differences existing between hemispheres, the planum temporale (PT) shows an important leftward asymmetry of its surface [START_REF] Geschwind | Human Brain: Left-Right Asymmetries in Temporal Speech Region[END_REF], the superior temporal sulcus (STS) is deeper in the right hemisphere and a vertex position analyse demonstrated an anterior displacement of the posterior ascending ramus of the Sylvian Fissure (SF) in the right hemisphere [START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF]. There is actually an important variability of the sulcal profile between individuals.

For example, Heschl's gyrus (HG), a region that has received a lot of attention in the frame of language and music processing, varies in gyrification pattern across individuals and hemispheres [START_REF] Leonard | Normal Variation in the Frequency and Location ofHuman Auditory Cortex Landmarks.Heschl's Gyrus: WhereIs It?[END_REF]. More, such variations of macroscopical anatomy have been associated with differences in speech sound and/or music processing (see 1.2). For example, previous research on this topic has reported differences in cortical thickness with relative pitch performances located nearby the Heschl's sulcus without taking into account variation in duplication across groups [START_REF] Foster | Cortical structure predicts success in performing musical transformation judgments[END_REF]. Whether such difference corresponds to actual differences of thickness or occurrence of duplication in participants with better performances remains an open question. To answer this question, the aim of the present work was to investigate the local variations associated with the occurrence of duplication that could support these behavioural differences.

VARIABILITY IN THE GYRIFICATION PATTERN OF HG

The quantification of the intersubject variability of the Heschl's gyrus, that hosts the human primary auditory cortex, has been first investigated by Galaburda and Sanides (1980). They found large interindividual differences in the size of auditory areas. Later, another study showed intersubject differences in position and extent of primary auditory cortex [START_REF] Rademacher | Topographical variation of the human primary cortices: implications for neuroimaging, brain mapping, and neurobiology[END_REF]. This high variability is associated with the existence of duplications already observed by Von [START_REF] Economo | Über Windungsrelief, Maße und Rindenarchitektonik der Supratemporalfläche, ihre individuellen und ihre Seitenunterschiede[END_REF].

The number of HG varies from 1 to 3 (even more) and can be different between hemispheres. According to the classification described by Abdul-Kareem and Sluming, 3 "classical" configurations of HG can be observed (Figure 2): a single HG, a Common Stem Duplication (CSD) corresponding to a partial split of the lateral part of the gyrus by the sulcus intermedius of Beck, and a Complete Posterior Duplication (CPD) that is a double HG (Abdul-Kareem and [START_REF] Sluming | Heschl gyrus and its included primary auditory cortex: structural MRI studies in healthy and diseased subjects[END_REF]. Interestingly, by studying a population enriched in musicians, Schneider attempts to describe not only 3 but 12 morphotypologies of HG such as triplifications and various subtypes of duplication which are more frequent than in non-musicians participants [START_REF] Seither-Preisler | Size and synchronization of auditory cortex promotes musical, literacy, and attentional skills in children[END_REF]. A previous study about the descriptive anatomy of HG was conducted in the laboratory on the same 430 participants from the BIL&GIN [START_REF] Mazoyer | BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization[END_REF] that will be considered in this chapter. A single neuroanatomist visually inspected all the brains and manually traced regions located in the supratemporal plane by using a knife-cut method based on the reconstruction of an oblique section plane going through the Sylvian fissure [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF]. Two different regions had been delineated in cases of duplication: the anterior part of HG corresponding to the first and anterior HG, and the posterior part, corresponding to the second and posterior HG. The sum was defined as the total HG region. The gyrification type was also identified on the individual's images. This study showed a large occurrence of duplication especially in the right hemisphere and partial duplication twice more frequent on the left hemisphere than complete duplication. The most frequent interhemispheric gyrification patterns were bilateral single HG (36%) and left single-right duplication (27%). Besides, the presence of duplication was associated with a decrease in the anterior HG and an increase in the total HG area [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF]. In the constraint space of cerebral volume, the appearance of more complex patterns of gyrification, i.e. duplication, involves anatomical repercussions in surrounding cortices.

Such modifications are not only visible with the size of the region but also in the microstructural properties of the cortex. Indeed, The cortical ribbon of the auditory core located in the medial two-third of the HG is characterized by high myelin content, a histological feature of primary areas [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF]. A recent article offered a cortical mapping using myeloarchitecture based on histological data from Vogt-Vogt school that is the study of local differences in the spatial organization of myelinated fibres in the cerebral cortex [START_REF] Nieuwenhuys | A new myeloarchitectonic map of the human neocortex based on data from the Vogt-Vogt school[END_REF]. Concerning the auditory cortex, Nieuwenhuys et al. benefited from the detailed studies of [START_REF] Hopf | Die Myeloarchitektonik des Isocortex temporalis beim Menschen[END_REF][START_REF] Hopf | Über die Verteilung myeloarchitektonischer Merkmale in der isokortikalen Schläfenlappenrinde beim Menschen[END_REF][START_REF] Hopf | Photometric studies on the myeloarchitecture of the human temporal lobe[END_REF] for the myeloarchitectural mapping of this area. They described 36 subregions in the supratemporal plane, in particular the 9 subregions 145 to 153 (ttr.1 or "subregio temporalis trans versa profunda" in Hopf's work) that delineated a very high myelin density area on HG (Figure 3A).

Besides, over 100 years ago, Paul Flechsig showed the regional timing emergence of white matter beneath the cortex by staining myelin in late term fetus and new-borns (Figure 3B). His results highlighted that heavily myelinated areas also myelinate early. Using myelin-stained sections, Pfeifer reported one of the first demonstrations of a coupling between acoustic radiations and the gyrus in single HG, while only in anterior HG in case of duplication (Pfeifer, 1920). Post-mortem probabilistic maps of acoustic radiations further confirmed Pfeifer's pioneering observations [START_REF] Rademacher | Stereotaxic localization, intersubject variability, and interhemispheric differences of the human auditory thalamocortical system[END_REF]. However, these histopathological techniques can be used only post-mortem and are typically conducted for only on a limited number of regions, rather than on the whole brain.

To address these problems, non-invasive imaging tools based on MRI were proposed for myelin mapping. T1w myelin-related MR contrast provides images reflecting differences in lipids, free and myelin-bound water, and also in iron content, last being colocalized with myelin of the cortical grey matter [START_REF] Fukunaga | Layer-specific variation of iron content in cerebral cortex as a source of MRI contrast[END_REF]. This approach has been validated by animals and humans post-mortem investigations showing a correlation between T1w intensities and myelin content measured in actual brain slices [START_REF] Bock | Visualizing the entire cortical myelination pattern in marmosets with magnetic resonance imaging[END_REF][START_REF] Geyer | Microstructural Parcellation of the Human Cerebral Cortex -From Brodmann's Post-Mortem Map to in vivo Mapping with High-Field Magnetic Resonance Imaging[END_REF]. Indeed, the correlation between the T1w signal and the myelin profile is higher in the internal half of the cortical ribbon where axons are emerging [START_REF] Eickhoff | High-resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex[END_REF], Figure 4).

Figure 4 -Group average (four subjects each) profiles of the striate cortex for cyto-, myelo-and MR T1

architecture. Profiles were extracted from in vivo T1 MR images (solid lines), black-gold myelin (dashed line), and cell body-stained sections (cytoarchitecture, dotted line). Profiles were z-normalized to enable comparison of profiles with different absolute grey values. Adapted from [START_REF] Eickhoff | High-resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex[END_REF] By mapping longitudinal relaxation rate (R1, i.e. the reciprocal of T1) reflecting intracortical myelin content on 5 subjects, Sigalovsky et al. found high R1 in the posteromedial two-thirds of the first HG and sometimes in the PT [START_REF] Sigalovsky | Mapping an intrinsic MR property of gray matter in auditory cortex of living humans: a possible marker for primary cortex and hemispheric differences[END_REF]. In this study, they didn't discuss about the effect of duplication. However, the right hemisphere of subject #5 seems to display a CPD with high R1 located in the first and second gyri but the authors assumed a potential less accurate segmentation due to lower grey matter/white matter contrast, preventing them to conclude about the posterior extension of high R1 (Figure 5).

In order to increase the contrast to noise ratio between heavily and lightly myelinated areas, Glasser et al. calculated surface-based cortical myelin maps using the ratio of T1w and T2w image intensities. Note that this method also allows to mathematically correct for the MRI-related image intensity bias field [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF]. In the cortex surrounding the Sylvian fissure, Glasser et al. found a heavily myelinated auditory core and moderate to heavily myelinated association regions posteriorly (Figure 6). (bottom) superior temporal lobe of a given subject. High R1 regions are white if they overlap first HG and shaded (with diagonal lines) if they did not. A dashed line separates 3 hemispheres in which pattern of high R1 may be lass accurate because of lower grey/white matter contrast. Adapted from [START_REF] Sigalovsky | Mapping an intrinsic MR property of gray matter in auditory cortex of living humans: a possible marker for primary cortex and hemispheric differences[END_REF] This densely myelin-related region was assessed by high-resolution mapping in vivo using T1w/T2w* (acquired on 7T scanner with a resolution of 0.6 x 0.6 x 0.6 mm 3 ), extended to the areas in sulcus intermedius in case of partial duplication, or onto Heschl's sulcus and the medial extent of the second gyrus in case of complete duplication [START_REF] Martino | High-Resolution Mapping of Myeloarchitecture In Vivo: Localization of Auditory Areas in the Human Brain[END_REF]. For one subject, some parts of right planum temporale were also included in the region with the highest anatomical contrast related to myelin. However, the combination of high-resolution (800 µm) quantitative T1 mapping with phase-encoded tonotopic methods showed that this highly myelinated area runs over the medial two-thirds of HG in single gyrus and only over the anterior HG in duplications [START_REF] Dick | In vivo functional and myeloarchitectonic mapping of human primary auditory areas[END_REF]. Due to methodological considerations, these two latter studies were only based onto 6 subjects and larger investigation on the effect of duplication on the myelination content of the supratemporal plane is needed.

Besides, HG duplications have been proven to be an important finding in clinical studies. Increased frequency of HG duplication had been linked to phonological expertise [START_REF] Golestani | Born with an ear for dialects? Structural plasticity in the expert phonetician brain[END_REF] and dyslexia [START_REF] Leonard | Anomalous Cerebral Structure in Dyslexia Revealed With Magnetic Resonance Imaging[END_REF][START_REF] Altarelli | Planum temporale asymmetry in developmental dyslexia: Revisiting an old question[END_REF] in the left hemisphere and to musical skills and more precisely to absolute pitch in the right hemisphere [START_REF] Schneider | Structural and functional asymmetry of lateral Heschl's gyrus reflects pitch perception preference[END_REF]. [START_REF] Leonard | Anatomical risk factors for phonological dyslexia[END_REF] described an anatomical risk factor index consisting of seven brain measures including the presence of duplicated left HG and the size of a single left HG to separate subjects with phonologically based learning disability (problems in phonological decoding) from those with non-phonologically-based learning disability (problems with language comprehension and/or production). They also stated that this anatomical index could predict reading skill in normal children [START_REF] Leonard | Anatomical risk factors for phonological dyslexia[END_REF]. So, in addition to morphological modifications, the presence of a second gyrus seems to have functional consequences and could be responsible for cortical reorganization. This question was addressed by Da Costa et al. that demonstrated an extension of the tonotopic map of primary auditory cortex onto both gyri in case of duplication in 10 human participants [START_REF] Costa | Human primary auditory cortex follows the shape of Heschl's gyrus[END_REF].

Figure 6 -Myelin (A) and gradients of myelin (B) maps in the left perisylvian region on an inflated surface.

The left hemisphere is oriented obliquely with anterior in the upper quadrant and posterior in the lower quadrant. Adapted from [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF].

ANATOMO-FUNCTIONAL RELATIONSHIPS IN HG

There are numerous reports of associations between the anatomical characteristics of HG and long-term auditory learning for music and speech, or expertise in either domain (for reviews see [START_REF] Zatorre | Plasticity in gray and white: neuroimaging changes in brain structure during learning[END_REF][START_REF] Zatorre | Predispositions and plasticity in music and speech learning: neural correlates and implications[END_REF]. These reports are within the frame of the spectro-temporal framework of acoustic processing [START_REF] Zatorre | Spectral and temporal processing in human auditory cortex[END_REF][START_REF] Hickok | The cortical organization of speech processing[END_REF]. For example, Warrier has demonstrated a direct anatomo-functional relationship in HG during sound processing, where the volume of activation during the temporal processing of sound is positively correlated with the volume of anterior HG on the left but not the right, and the opposite is observed during the spectral processing of sound [START_REF] Warrier | Relating structure to function: Heschl's gyrus and acoustic processing[END_REF]. Schneider combined MRI with magnetoencephalography (MEG) to demonstrate a left hemispheric specialization for (missing) fundamental pitch perception and a right hemispheric specialization for spectral pitch perception, consistent with this spectro-temporal framework of acoustic processing [START_REF] Schneider | Structural and functional asymmetry of lateral Heschl's gyrus reflects pitch perception preference[END_REF]. In fact, he demonstrated that listeners who completed the pitch change judgments on the fundamental pitch had larger grey matter volumes in the left HG than did listeners performing the pitch change judgment on the basis of the spectral envelope, who instead had an increase in the right HG GM volume. Comparisons of the anatomical characteristics of HG with expertise also demonstrated lateralized results (summary in Table 1). In the left hemisphere, a larger volume of WM and/or GM of anterior HG or HG have been associated with good performances in phonological awareness and literacy abilities in 10-year-old children [START_REF] Sutherland | Anatomical correlates of dynamic auditory processing: relationship to literacy during early adolescence[END_REF], with expertise or proficiency in phonological processing of foreign speech sounds in adults [START_REF] Golestani | Brain structure predicts the learning of foreign speech sounds[END_REF][START_REF] Golestani | Born with an ear for dialects? Structural plasticity in the expert phonetician brain[END_REF][START_REF] Wong | Volume of left Heschl's Gyrus and linguistic pitch learning[END_REF] and with early bilingualism [START_REF] Ressel | An effect of bilingualism on the auditory cortex[END_REF]. Left HG duplications have been associated with phonological expertise [START_REF] Golestani | Born with an ear for dialects? Structural plasticity in the expert phonetician brain[END_REF] but also with phonological disorders and dyslexia [START_REF] Leonard | Anomalous Cerebral Structure in Dyslexia Revealed With Magnetic Resonance Imaging[END_REF][START_REF] Altarelli | Planum temporale asymmetry in developmental dyslexia: Revisiting an old question[END_REF]. Moreover, a large second HG has been reported in dyslexic adults [START_REF] Leonard | Anatomical risk factors for phonological dyslexia[END_REF].

On the right, a larger GM and/or WM volume of HG has been reported in professional musicians with absolute pitch compared to musicians without absolute pitch, and the proficiency of an individual's absolute pitch ability was proved to be positively correlated with the GM volume [START_REF] Wengenroth | Increased volume and function of right auditory cortex as a marker for absolute pitch[END_REF]. A greater GM density was observed in HG of musicians compared to non-musicians [START_REF] Bermudez | Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry[END_REF], and a lateral expansion of HG was detected in 6-year-old children who completed 15 months of instrumental training compared to control children [START_REF] Hyde | Musical training shapes structural brain development[END_REF]. Applying surface-based morphometry (SBM) on anatomical images allowed several investigators to report variations in CT in relation to music expertise or learning in HG (notably reviewed in [START_REF] Zatorre | Predispositions and plasticity in music and speech learning: neural correlates and implications[END_REF], such as a CT increase in the right HG associated with musicianship [START_REF] Bermudez | Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry[END_REF] and pitch discrimination performances [START_REF] Foster | Cortical structure predicts success in performing musical transformation judgments[END_REF]. Although, less direct, Liem who indicated that the N1 amplitude is an ERP component related to musical expertise, found a negative correlation between N1 amplitude and CT in HG [START_REF] Liem | Cortical thickness of supratemporal plane predicts auditory N1 amplitude[END_REF]. Finally, a high occurrence of right duplications has been notably observed in musicians having absolute pitch [START_REF] Schneider | Structural and functional asymmetry of lateral Heschl's gyrus reflects pitch perception preference[END_REF].

AIMS OF THE STUDY

The works cited above, which investigated the anatomo-functional relationships in HG in relation to performances during speech or musical sound processing, reported differences in the GM volume, CT, or the occurrence of duplications. Although we have recently shown that the presence of duplications is associated with a decrease in the surface area of the anterior HG [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF], the changes in CT or CSA associated with the occurrence of duplications are still unknown.

We applied SBM to the anatomical images of 430 participants who had previously been characterized by their HG macroscopical anatomy (single HG, CSD, and CPD, [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF] to observe the regional differences in the cortical mantle (CT and CSA) in groups with varying HG duplication patterns.

Previous studies using high resolution imaging to estimate intracortical myelin of a small numbers of subjects showed discrepant results about the myelination profile according to the HG duplication pattern [START_REF] Martino | High-Resolution Mapping of Myeloarchitecture In Vivo: Localization of Auditory Areas in the Human Brain[END_REF][START_REF] Dick | In vivo functional and myeloarchitectonic mapping of human primary auditory areas[END_REF]. So, we computed the T1w/T2w ratio to obtain the intracortical myelination of our 430 subjects to evaluate if the area of high myelination of the primary auditory cortex is limited to the first gyrus or extends to the second one in case of duplication. Furthermore, we extended this study to the whole supratemporal plane, including the PT, being situated at the level of the posterior limit of the first gyrus, which is considered as an associative unimodal auditory area implicated (on the left) in the treatment of sounds of language, particularly phonological. This chapter is the subject of a published article in Frontiers of Human Neuroscience [START_REF] Marie | Surface-Based Morphometry of Cortical Thickness and Surface Area Associated with Heschl's Gyri Duplications in 430 Healthy Volunteers[END_REF] Surface-Based Morphometry of Cortical Thickness and Surface Area Associated with Heschl's Gyri Duplications in 430 Healthy Volunteers. Front Hum Neurosci 10). The study part regarding HG myelination was part of the cosupervision of a master's student and lead to an article in preparation.

MATERIALS AND METHODS

PARTICIPANTS

The characteristics of the 430 participants are fully described in our previous article [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF]. All were free from brain abnormalities, and the Basse-Normandie's ethical committee approved the study. All participants provided their informed written consent and received compensation for their participation in the framework of the BIL&GIN database [START_REF] Mazoyer | BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization[END_REF].

Briefly, the population is balanced for handedness (self-report, 232 righthanders vs. 198 left-handers, Chi square = 2.69, p = 0.10), and gender (209 men vs. 221 women, Chi square = 0.33, p = 0.56). The average age of the participants is 26 years (SD,8). Each volunteer's skull perimeter was measured at the level of the eyebrows, passing at the top edge of the ears and along the occipital bump. The average skull perimeter was 57 cm (SD, 2) and men had larger skull perimeters than women did (+3 cm, t = 17.1, p < 0.0001). Note, that none of these individual variables differed according to the left or right HG number [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF].

IMAGE ACQUISITION

Anatomical images were acquired from 2007 to 2011 using the same 3T Philips Achieva scanner (Philips Medical Systems, Best, The Netherlands). High-resolution T1-weighted images were obtained using a 3D-FFE-TFE sequence (TR, 20 ms; TE, 4.6 ms; flip angle, 10°, inversion time, 800 ms; turbo field echo factor, 65; Sense factor, 2; field of view, 256 × 256 × 180 mm; and isotropic voxel, 1 mm 3 ). For each participant, the line between the anterior and posterior commissures was identified on the midsagittal plane, and the T1-MRI volume was acquired after orienting the brain in the bi-commissural coordinate system. T2-weighted images were also acquired during the same session (TR, 5500 ms; TE, 80 ms, 1x1x2 mm) for 425 participants (five missing).

IMAGE ANALYSIS

DEFINITION OF THE HG GYRIFICATION PATTERNS

A single expert (NT-M) identified HG and its gyrification type on individual images in the native space as fully described elsewhere [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF]. Briefly, the definition of the number of HG was optimized through the knife-cut method, which is based on the reconstruction of an oblique section plane going through the Sylvian fissure [START_REF] Kulynych | Three-dimensional surface rendering in MRI morphometry: a study of the planum temporale[END_REF]Tzourio-Mazoyer et al., 2010b) computed with the aid of dedicated software (Voxeline, [START_REF] Diallo | VoxeLine: a software program for 3D real-time visualization of biomedical images[END_REF]). An oblique section plane parallel to the Sylvian fissure was generated by uncovering the superior temporal plane and going through the point where HG is the largest. Axial, coronal, sagittal, and oblique slices are displayed simultaneously for identifying duplications.

The gyrification pattern of HG (single HG, common stem duplication or CSD, or complete posterior duplication, or CPD) was defined according to the anatomical criteria reviewed in Abdul-Kareem and Sluming (2008) (Figure 2). In cases with a single HG, the anterior border is constituted by the temporal transverse sulcus, and the posterior border is Heschl's sulcus. In cases with a CSD, the gyrus is partially split by the sulcus intermedius of Beck (SI), which never reaches the internal border of the gyrus. We considered a CSD to be present if the SI length was at least one-third of the length of HG. There are two Heschl's sulci in cases with a CPD; the first Heschl's sulcus splits the gyrus medially into two parts and the second Heschl's sulcus becomes the posterior border of HG. As previously reported, we identified 284 single HG (66%), 98 CSDs (23%), and 48 CPDs (11%) in the left hemisphere, and 239 single HG (56%), 95 CSDs (22%), and 96 CPDs (22%) in the right hemisphere [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF].

REPRODUCIBILITY OF THE IDENTIFICATION OF THE GYRIFICATION

PATTERN

Reproducibility was measured by a second assessment of 40 randomly selected brains (80 hemispheres) by the same observer. The concordance between the two evaluations was measured with the chance corrected Kappa statistics (JMP pro 11). The Kappa statistics for the concordance of the two assessments of the number of gyri was 0.84 ± 0.06 (p < 0.0001). The Kappa statistics for the concordance of the two assessments of the HG pattern (single, CPD or CSD) was 0.82 ± 0.06 (p < 0.0001). According to Cohen's original paper, a Kappa value > 0.81 attests of an excellent reproducibility [START_REF] Cohen | The coefficient of agreement for nominal scales[END_REF]. Non-concordant classification occurred in eight cases (10% of the hemispheres). Four of the non-concordant associations corresponded to a confusion between CPD and CSD; in two cases, the non-concordance was between CSD and single, and in two others, it was between single and CPD in the right hemisphere.

SURFACE-BASED MORPHOMETRY

The cortical surfaces were reconstructed and the anatomical features were measured for each participant with the FreeSurfer 5.3.0 image analysis suite (http://surfer.nmr.mgh.harvard.edu/, [START_REF] Dale | Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction[END_REF]Fischl et al., 1999a;Fischl et al., 1999b;[START_REF] Fischl | Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex[END_REF][START_REF] Fischl | Whole Brain Segmentation: Neurotechnique Automated Labeling of Neuroanatomical Structures in the human Brain[END_REF][START_REF] Fischl | Automatically Parcellating the Human Cerebral Cortex[END_REF][START_REF] Fischl | Measuring the thickness of the human cerebral cortex from magnetic resonance images[END_REF]Fischl, 2012). The FreeSurfer analysis stream includes intensity bias field removal optimized for the present 3T acquisitions and skull stripping. In the native anatomical space of the subject, FreeSurfer constructs models of the cortical surface that can be represented as a mesh of triangles and tessellated into over 160,000 vertices for each hemisphere. The vertex positions are adjusted such that the surface follows the T1 intensity gradient between the cortical WM and GM. This highly folded surface, called "white surface," can be inflated to see buried surfaces within the sulci. A second surface, called the "pial surface," is fit to the outer GM surface of the brain. The hemispheres are processed separately through a precise estimation of the interhemispheric fissure plane.

QUALITY CONTROL

The problems of estimating the surfaces around the thin temporal lobe strands that border the tip of the lateral ventricle have been identified with the FreeSurfer segmentation procedure [START_REF] Dale | Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction[END_REF]. In this case, a reduction of the intensity of the voxels in the corresponding white matter leads to a misclassification of voxels and an inaccurate definition of the white and pial surfaces. To overcome this limitation, we visually checked (SM) each of the 430 pial and white surfaces on each axial, sagittal, and coronal section from each participant twice and identified surface reconstruction errors in 44 cases (10%). A correction procedure consisting of manually adding an average of nine control points (SD, 7) in the misclassified white matter was then applied in the 44 individuals. Then, the FreeSurfer procedure was launched a second time for these corrected individuals, resulting in more accurate surface reconstructions (Figure 7).

CALCULATION OF THE MORPHOMETRIC VARIABLES IN THE NATIVE SPACE OF EACH PARTICIPANT

For each vertex, CT is defined as the distance between the white and pial surfaces and CSA is defined as the average area of the triangles to which the vertex belongs. The cortical surface curvature (CURV) parameter was also extracted and used to drive the non-linear surface-based inter-subject registration. The curvature is estimated as 1/r, where r is the radius of the inscribed circle to each point (or vertex) of the white surface.

DEFINITION OF A SPECIFIC TEMPLATE FOR BETWEEN-SUBJECT REGISTRATION AND SMOOTHING

Because of the unequal distribution of duplications across hemisphere in the general population, it was necessary to ensure that the FreeSurfer default procedure correctly estimated the morphology of HG. To do so, we first used VBM to compute mean images of groups with varying duplications. More precisely, 6 mean images (left single HG, left CSD, left CPD and the same for the right hemisphere, Figure 8a) obtained with VBM inter-subject registration were computed using SPM5 software. The individual T1-weighted volumes had previously been spatially normalized to the reference template from the BIL&GIN database, as described elsewhere (Mazoyer et al., 2015). A similar approach was then applied using FreeSurfer procedure by computing the same set of 6 mean images that had been surface-based registered in the Fsaverage default surface template. The curvature values were displayed on the mean morphology to have a better view of the gyri (red) and sulci (blue) (Figure 8) and visually compare these mean surface-based images to the mean voxel-wise images. Considering the right CPD, a clear complete duplication was visible, with two well-defined gyri (Figure 8b, right hemisphere). However, the mean images of the 48 individuals having a left CPD, obtained after registration in the Fsaverage default surface template exhibited a loose definition of the second gyrus (Figure 8b, left hemisphere) upon visual inspection, which was very different from what was observed in the mean images of the same group deriving from VBM (Figure 8a, left hemisphere).

The discrepancy observed by visual inspection between the mean images of left CPD obtained with VBM and SBM processing prompted us to develop a specific surface-based template to optimize the inter-subject surface-based normalization of HG by taking into account the distribution of the duplications in our sample. We therefore computed a specific surface-based template (the 40-average SBM template) including images from individuals with identical HG duplication patterns in the left and right hemispheres to avoid a left alignment weighted towards the single HG scenario and a right alignment weighted towards the duplication scenario. Forty individuals were included (26 men, 18 right-handers), corresponding to 20 bilateral single HG and 20 bilateral duplications (10 CSD and 10 CPD). The procedure for computing this specific surface-based template is illustrated in Figure 9.

Figure 8 -Mean images of groups varying in gyrification pattern after Voxel-Based

Morphometry and Surface-Based Morphometry processing. a) VBM processing was completed using the BIL&GIN template constituted of 80 healthy volunteers of the sample. The supratemporal plane view was obtained using the knife-cut method corresponding to the generation of an oblique slice passing through HG and parallel to the Sylvian fissure. b) SBM processing was completed using the "Fsaverage" template. c) SBM processing was completed using our specific "40average space". For the two SBM processing, the rendering of the mean curvature parameters is superimposed on the supratemporal patch described previously, with gyri in red and sulci in blue, (HG: Heschl's gyrus; CSD: Common Stem Duplication; CPD: Common Posterior Duplication; L: left; R: right; N: number of averaged hemispheres).

Figure 9 -Flowchart of the iterative algorithm used for the computation of our specific "40-average space" used for the surface-based inter-subject alignment.

Non-linear surface-based normalization of the 430 CT and CSA individual maps to this specific template was then applied. An additional step was performed by adding a Jacobian correction to the CSA maps to account for any stretching or compression in the registration that occurred during the nonlinear registration [START_REF] Winkler | Measuring and comparing brain cortical surface area and other areal quantities[END_REF]. Note, that this correction is not needed for the CT maps because CT is measured along a vector normal to any stretching or compression.

After registration, the individual CT and CSA maps were surface-smoothed by a 10 mm FWHM Gaussian filter size, statistical power of both features benefiting from such optimal smoothing filter size as demonstrated by [START_REF] Liem | Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly[END_REF]. However, minimal detectable differences depending on smoothing filter size [START_REF] Liem | Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly[END_REF], individual CT maps of two groups (left CPD, and left single HG) were also surface-smoothed with a 5 mm FWHM Gaussian filter in a complementary analysis in order to evaluate the impact of a reduced filter size on structural differences detected between HG anatomical patterns.

CURVATURE VARIANCE MAPS

To characterize the intrinsic anatomical variability of each HG configuration, we computed CURV variance maps in the 40-average space in both hemispheres. For each vertex, we calculated a CURV variance value using MATLAB 7.11.1 (R2010b), which was defined as the mean of the square minus the square of the mean for a given group (for example the calculation of curvature variance in the left hemisphere for the 284 subjects with single HG).

GENERATION OF THE SURFACE-BASED T1W/T2W RATIO IMAGES

Each individual T2w images was rigidly registered to the corresponding T1w images using the "SPM12 co-register" routine and resampled using a trilinear interpolation. The T1w volume was then divided by the T2w one, creating a T1w/T2w ratio 3D volume (Figure 10A, B andC).

We then sampled this T1w/T2w values vertex-wise at mid-thickness distance (light blue line in the Figure 11A andB) into the grey matter ribbon from the white surface boundary using "FreeSurfer's mri_vol2surf" tool [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF][START_REF] Grydeland | Intracortical myelin links with performance variability across the human lifespan: results from T1-and T2-weighted MRI myelin mapping and diffusion tensor imaging[END_REF], yielding T1w/T2w ratio surfaces for each participant in their individual space. We assigned a T1w/T2w value of zero for vertices located in the non-cortical medial wall and that had a null CT value.

All individuals T1w/T2w surface maps were then surface-based spatially normalized to the BIL&GIN specific "40-average space" (Figure 11D).

Figure 10 -The ratio of T1w (A) to T2w (B) signal intensity is calculated to obtain the T1w/T2w ratio image (C). This is done to improve the mapping by increasing the contrast between different myelinated structures. The signal in the "deep white matter", displayed in yellow in the panel D, was used to normalize the intensity between subjects.

Finally, the T1w/T2w surface maps intensities across subjects were adjusted using the mean intensity value of the deep white matter region extracted from the T1w/T2w ratio volume. This 3D white matter region of interest was obtained by the Freesurfer parcellation routine (Figure 10D). This intensity normalization allows taking into account of global variations of the signal between individuals and produces T1w/T2w maps which are statistically quantitatively comparable.

The average T1w/T2w maps were calculated using Matlab V 8.6 (R2015b), using the non-smoothed, registered individual data. They were calculated for each HG configuration in each hemisphere, so we obtained six maps corresponding to the six configuration groups (Figure 10).

STATISTICAL ANALYSIS

CT AND CSA

To compare the groups with varying HG duplication patterns, we ran two independent ANCOVA in each hemisphere on CT and CSA separately, with the HG Figure 11 -A

. Sagittal view of a T1w/T2w ratio image of one subject with the pial surface (in red), the mid-thickness surface (in light blue) and the white surface (in yellow) with a zoom on Heschl's gyrus in the panel B. Individual surface-based map of T1w/T2w in the native space (C) and registered in the "40-average space" (D).

Values are thresholded at 0.25.

pattern as the main factor. All analyses were performed with the QDEC module included in FreeSurfer, and the participant's skull perimeter was included as a confounding variable to account for differences in head size. The statistical threshold was set at p < 0.05 FDR corrected, and an additional cluster extension threshold was set at 20 mm 2 .

To display the results on the supratemporal plane, a specific patch of the temporal lobe was computed for the mean image of each group and hemisphere by merging the corresponding labels of Desikan's parcellation provided by FreeSurfer [START_REF] Desikan | An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest[END_REF]. The removal of the fusiform, entorhinal, and parahippocampal gyri was performed to clean up the patch (Figure 14).

The statistical analyses presented in this study were performed on images that have been registered to the 40-average SBM template. The same group comparisons were also performed on the images that had been normalized on the FSaverage default SBM template to evaluate whether the use of different SBM templates modulate the statistical results.

A second analysis of CT variations between left CPD and single left HG has been conducted using a 5 mm surface-based smoothing FWHM Gaussian filter of CT maps instead of 10 mm.

T1W/T2W RATIO MYELIN

In each hemisphere, the T1/T2 maps of the three configurations were compared to the other two (and so six comparisons) taking into account the curvature in the vertex-analyses. For each analysis, the study was limited to the vertices of the supratemporal plane with a statistical threshold of p < 0.01 uncorrected for the number of tests since this was an exploratory approach.

RESULTS

IMPACT OF THE "40-AVERAGE TEMPLATE" ON HG DUPLICATION PATTERN ANATOMY

The visual inspection of the mean image of left CPD after surface-based registration on the "40-average template" showed a qualitative improvement of the macroscopical anatomy of the left CPD compared to the registration on the Fsaverage default template (Figure 8B andC). More precisely, the 2 nd posterior HG was better defined and was two times larger than the one obtained with the Fsaverage default template, and was thus closer to the mean image of the CPD group obtained with the VBM procedure (Figure 8A).

MACROSCOPIC ANATOMICAL VARIABILITY OF HG CONFIGURATION ACROSS HEMISPHERES: ANALYSIS OF THE CURV VARIANCE MAPS

In cases with a single HG, the variability was low, except in the antero-lateral border of the left HG (Figure 12A). In cases with a CSD in the right hemisphere, a small cluster of high variability was observed in the sulcus intermedius of Beck (Figure 12B), similar to that on the left, which corresponded to a variation in the width of the mid-part of the second sulcus. A high variability of left CPD was observed and corresponded to the variation in the curvature pattern of the posterior position of the first Heschl's sulcus. On the right, a comparable pattern was present, but with a much lower amplitude.

MYELIN MAPS

In the left hemisphere, the myelination profile appeared to be more or less independent of the HG configuration (Figure 13A). The first gyrus was myelinated along its entire length, and the second gyrus was also myelinated in both cases, albeit less intense at the level of the second gyrus in cases of CPD. Across the three configurations the signal was strong on the PT, especially in the single HG and CSD maps. Note that the signal was stronger at the level of the left PT compared to the right.

In the right hemisphere, the myelination profile seemed also to be independent of the HG configuration (Figure 13B). Again, the first gyrus was myelinated along its length. The second gyrus was also myelinated in both cases, but the signal was less strong than that of the first gyrus, particularly at the level of the anterior part of the second gyrus of the CSD, and on the entire second gyrus for the CPD.

MORPHOMETRIC CHANGES ACCORDING TO THE DUPLICATION TYPES

CT DIFFERENCES

A larger CT was observed in the CSD group compared to the single HG group all along Heschl's sulcus and the second gyrus (Table 2, Figure 14). A larger CT was also observed in the medial part of the second HG in both hemispheres in the CPD group compared to the single HG group, but it was more medially situated on the right. Note, that there was no difference between CSD and CPD.

These increases in CT in case of duplication, whatever the side and whatever the type of comparison (either CSD or CPD minus single), were located at the ventral limit of the second gyrus. In addition, in case of CSD, the increase in CT extended from the ventral part of the second gyrus toward the sulcus intermedius of Beck (Figure 16).

Figure 14 -Significant variations of Cortical Thickness (CT) and Cortical Surface Area (CSA) in the "CPD-single HG", "CSD-single HG" and "CPD-CSD" contrasts in the left and right hemispheres showing the spatial overlap of CT and CSA variations. (A). Significant variations in cortical thickness. (B). Significant variations in cortical surface area, the lateral view of the right temporal lobe is provided to illustrate the increase in CSA located in the midpart of the STS in the "CSD-single HG" comparison. Significant variations are superimposed on the mean patch of each corresponding group ("CPD-single" and "CPD-CSD" contrasts: mean patch of 48 left CPD, mean patch of 96 right CPD; "CSD-single HG" contrast: mean patch of 98 left CSD and 95 right CSD; CSA: cortical surface area; CT, cortical thickness; CPD, common posterior duplication; CSD, common stem duplication; HG, Heschl's gyrus; p < 0.05 FDR corrected for multiple comparison; cluster extension threshold, 20 mm 2 ; hot colour indicates a positive variation; cold colour, indicates a negative variation; light grey, gyri; dark grey, sulci).

Table 2 -Local variations of Cortical Thickness (CT) detected in "CPD-single HG", "CSD-single HG" and "CPD-CSD" contrasts.

We reproduced the analysis of CT variations between left CPD and left single HG using a surface-smoothing kernel size two times smaller (i.e. 5 mm) in 1-the default template, and 2-the optimized template. This contrast was chosen because of the previous demonstration that the computation of a mean image from subjects with a left CPD after registration of those individuals on the default template was not optimal. Clusters of CT detected by these two analyses performed separately with each template (p < 0.05 FDR) were very close to those detected by analyses performed with the surface-smoothing size of 10 mm in terms of localization and significance, although the extent was slightly smaller (Figure 16). There was no impact of the template on the results provided by analyses performed using a smoothing filter of 5 mm.

CSA DIFFERENCES

In the right hemisphere, the CSA was significantly smaller in the medial part of aHG in the CPD group compared to the single HG or CSD groups, whereas a larger CSA was observed in the lateral part of the second HG of the CPD group compared to the other two groups (Table 3,Figure 14). In the left hemisphere, a decreased CSA was detected on the medial part of the second gyrus of CPD as compared to the single HG group, corresponding to the location of the PT in single HG cases.

50

In the middle part of Heschl's sulcus, smaller CSA values were observed in both hemispheres of the CSD group compared to the single HG group. Interestingly, the extent of the cluster was larger on the left and expanded in the PT.

In the medial part of the temporal transverse sulcus, a larger CSA was also detected in both hemispheres of the CSD group compared to the single HG group. Moreover, in the right hemisphere, a larger CSA was observed directly under the lateral part of HG in the depth of the middle part of the STS (Figure 16).

Vertex-wise analyses of anatomical differences between groups established according to their HG gyrification pattern were also performed with individual maps registered in the default template namely Fsaverage (Figure 15). Except the disappearance of a small cluster of CSA on the left in the comparison between CPD and single HG that was present in the analysis performed after registration on the 40average SBM template (see B) and is absent in the present results obtained after registration on Fsaverage, results were similar in terms of significance, location and cluster size. It suggests that the SBM method is very robust and does not depend on the template used.

MYELIN DIFFERENCES

In the left hemisphere, there is no significant difference in signal between the configurations at the level of HG, regardless of the duplication type. The difference between the groups is always situated posterior to HG. When we compared single HG vs. CPD, the cluster of myelin difference was located at the level of PT and just posterior to the second gyrus in case of CPD (Figure 17A). The comparison of single HG vs. CSD showed some myelin differences in the sulcus that separates HG from PT. There is very little difference between the two types of duplications. Projecting the myelination difference maps on the corresponding configurations confirms that the difference in cortical myelin is not due to morphological differences, and that it is really situated at the level of the PT for the contrast single HG -CPD.

In the right hemisphere there is no difference in cortical myelination at the level of HG. Similarly to the left hemisphere, the most marked difference between the single and the CSD, as well as for the single and the CPD (although less strongly) is situated posteriorly to HG, in the depth of Heschl's sulcus (Figure 17B). However on the right there is a difference in the myelinisation of the sulcus between the two types of duplication that is not seen on the left.

DISCUSSION

SBM allowed us to investigate changes in macroscopical neuroanatomy without being limited to the intrinsic voxel resolution [START_REF] Fischl | Measuring the thickness of the human cerebral cortex from magnetic resonance images[END_REF]. The high spatial normalization provided by the surface-based inter-subject alignment of curvature in Freesurfer enabled us to describe the changes in CT and CSA associated with the HG gyrification patterns, completing the results previously obtained by measuring the aHG surface area using manual delineation [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF].

METHODOLOGICAL CONSIDERATIONS

The identification of the HG gyrification patterns had an excellent reproducibility according to the Kappa measure. A first type of non-concordance was related to the distinction between a single gyrus and a CSD because the criterion for CSD was the minimal length of the sulcus intermedius of Beck (30%). A second type of non-concordance was the confusion between CPD and CSD, which was related to In both hemispheres, each group was compared to the two others, then projected onto the anatomical surfaces of the two groups being compared. In the top row (left hemisphere) and the bottom row (right hemisphere), from left to right: single -CPD on single and CPD, single -CSD on single and CSD, CSD -CPD on CSD and CPD. Only the statistically significant results are shown, with a threshold of p < 0.01; when a difference is positive, the colour scale is "hot" (yellow corresponding to the most significant vertices) and when the difference is negative, the colour scale is "cold" (with green corresponding to the most significant vertices).

the determination of whether the sulcus splitting the gyrus reaches the internal limit of HG or not. This ambiguity is generally solved by applying the second criteria based on the shape of the duplication, which looks like an "M" on sagittal and coronal slices in cases with a CPD or a "heart" in cases with a CSD. The two cases of confusion between single and CPD were located in the right hemisphere, and corresponded to a difficulty in discriminating a second gyrus from the right PT.

The development of a specific surface-based template aimed at enhancing the inter-subject registration providing a more accurate localization of the structural variations associated with the different HG gyrification patterns. The averaging of the images from individuals with a left CPD after their registration to the default surfacebased template (Fsaverage) did not show two distinct gyri, while it was highlighted in VBM registered images, but only showed a small lateral stem of a second gyrus (see Figure 15b). Considering that the Fsaverage default surface-based template is constructed from the general population, it is very likely that it includes a high proportion of single HG on the left (66% of the 430 participants from our sample, [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF]. The use of this default surface-based template could bias individual HG anatomy towards a single HG due to the alignment procedure in the left hemisphere, and, consequently, be less representative of the duplication patterns. On the contrary, in the right hemisphere, there is a balanced proportion of duplications and single gyrus in the general population (56% have a single gyrus, [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF]. The mean images from the right HG are thus likely less weighted towards a single HG and more representative of the different configurations (single and duplication), preventing bias in the inter-subject registration procedure in the right hemisphere. Actually, in the right hemisphere, the mean images of the CPD group registered with the volumetric VBM template, and the mean images averaged after registration on the default surface-based Fsaverage template or our specific 40average surface-based template were very similar (Figure 15A, B and C, right part). In contrast, the visual inspection of the mean images of the left CPD obtained with the 40-average template (Figure 15C) showed an improvement in the second gyrus definition as compared to mean image computed on images registered on the Fsaverage template (Figure 15B). The mean image of the left CPD obtained with the 40-average template was very comparable to the mean image from the VBM approach. Although we did not statistically quantified the improvement related to the definition of the specific 40-average template compared to the default Fsaverage because of the different surface model representations of the two surface-based templates, we hypothesize that the enhanced proportion of duplications in the left 40-average template improved the inter-subject registration of the CPD sample. However this qualitative improvement (i.e. mean images of normalized individual surfaces on the 40-average template being more respectful of the individual HG anatomy manually identified than mean images computed after normalization on Fsaverage) did not translate into improved sensitivity of the statistical results. The results obtained with individual images registered on the 40average template (Figure 14) were very close to those obtained with images normalized on the Fsaverage default surface-based template (Figure 15). Indeed, the mean curvature images (computed using the Fsaverage or the specific 40-average templates) have a spatial resolution close to that of the native MRI images (close to 1 mm 3 resolution). At this high spatial resolution, the reduction of the residual intersubject variability after spatial normalization onto a specific surface-based template in regions surrounding the HG leads to an improvement of the mean images (see Figure 8). On the other hand, the group comparisons are performed at lower spatial resolution because of the smoothing procedure completed before the statistical analysis (10 mm surface-smoothing of the CT and CSA maps). This smoothing process, by decreasing the spatial resolution, could diminish the gain in curvature alignment provided by the specific template. This might likely explain the absence of difference between the analyses performed with the different surface-based templates. Finally, the two fold decrease of the surface-based smoothing filter size (from 10 to 5 mm) did not impact the statistical differences detected between left CPD and left single HG, demonstrating the consistency of the results we obtained with SBM.

VARIABILITY OF EACH HG PATTERN

We conducted an analysis of variance on CURV, which clearly showed a high variance on the left, increasing from single to CSD to CPD. In fact, difference of variability between hemispheres might not be significant (due to the absence of any equivalence between the vertices of the two hemispheres, statistical comparison was not possible). In both hemispheres, a high variance was located in the most lateral part of HG for the single group and in the medial part for the CSD and CPD groups, and a low variance was observed in the internal part of HG. In the stereotactic space, Leonard et al. described the probability of the position of the sulcus intermedius of Beck and the second Heschl's sulcus in cases with duplications. They demonstrated differences in the position of the second sulcus across hemispheres, with a second sulcus that does not angle as sharply on the left as it does on the right (Figure 6 of [START_REF] Leonard | Normal Variation in the Frequency and Location ofHuman Auditory Cortex Landmarks.Heschl's Gyrus: WhereIs It?[END_REF], but they did not report any difference in the variability of sulci positions across hemispheres.

MORPHOLOGICAL SUPPORT OF CT AND CSA VARIATIONS

The present work report both local differences directly related to morphological changes associated with duplication and more distant variations that may relate to differences in anatomical and/or functional organization associated with differences in gyrification. The location of CT increases, consistently located at the second gyrus in case of CPD, and along the sulcus intermediary of Beck in case of CSD, suggests that it corresponds to a morphological change from Heschl's sulcus to the second (complete or partial) gyrus. As it had been underline by [START_REF] Van Essen | A tension-based theory of morphogenesis and compact wiring in the central nervous system[END_REF], CT might be larger in top of gyri than in the depth of sulci [START_REF] Van Essen | A tension-based theory of morphogenesis and compact wiring in the central nervous system[END_REF].

Concerning CSA the picture was different depending on hemispheres and on the type of duplication. The modifications we report could not be attributed solely to local morphological changes in relation with differences in gyrification for HG.

OPPOSITE PATTERN OF MODIFICATION BETWEEN CT AND CSA

DIFFERENCES

Interestingly, when an overlap of CT and CSA modifications occurred, it always corresponded to an increase of CT in case of duplication associated with a local decrease of CSA, an opposite profile of structural modification of these two anatomical features. These results have to be linked to the study of Hogstrom on local correlations of CT and CSA through the whole cortex. By studying 322 healthy adults aged from 20 to 85 years old thanks to surface-based method, they observed that CSA and CT were negatively correlated in a per-vertex general linear model that took into account the age and gender of the participants [START_REF] Hogstrom | The structure of the cerebral cortex across adult life: age-related patterns of surface area, thickness, and gyrification[END_REF], corresponding, as in the present study, to opposite differences in CT and CSA variations.

DUPLICATIONS ARE ASSOCIATED WITH A LARGER CT IN THE SECOND HG: A CANDIDATE SUPPORT FOR INCREASED ABILITIES ASSOCIATED WITH DUPLICATIONS IN HEALTHY INDIVIDUALS

Bilateral increases in the CT could represent a morphological support for the great abilities reported in individuals having duplications. As reviewed in the introduction, expertise in pitch processing based on the spectral envelope has been associated with a right duplication [START_REF] Schneider | Structural and functional asymmetry of lateral Heschl's gyrus reflects pitch perception preference[END_REF], while the ability to rapidly learn foreign speech sounds [START_REF] Golestani | Brain structure predicts the learning of foreign speech sounds[END_REF] and phonetic expertise [START_REF] Golestani | Born with an ear for dialects? Structural plasticity in the expert phonetician brain[END_REF] were related to a left duplication. Musicianship was also associated to a larger cortical thickness all along the posterior supra-temporal plane surface posterior to HG, thereby including the second gyrus of duplication, when one is present [START_REF] Bermudez | Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry[END_REF]. Finally, the CT of the right Heschl's sulcus has been positively associated with performances in a relative pitch detection task [START_REF] Foster | Cortical structure predicts success in performing musical transformation judgments[END_REF]. The locations across studies are consistent and the larger CT we observed in the present study overlapping with the increased CT reported by Foster's study in cases with a CSD, whereas it was in a slightly posterior position in cases with a CPD [START_REF] Foster | Cortical structure predicts success in performing musical transformation judgments[END_REF]. According to the literature, increase in CT could relate to an increased number and/or size of cells within a column, their packing density, or the number of connections and extent of myelination [START_REF] Rakic | A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution[END_REF][START_REF] Eickhoff | High-resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex[END_REF].

On the other hand, the increased CT associated with duplications that we report here is similar to the CT of the Heschl's sulcus label of the Destrieux parcellation [START_REF] Destrieux | Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature[END_REF], which has been shown to be anti-correlated with the amplitude of the N1 component of auditory-evoked potentials in the right hemisphere [START_REF] Liem | Cortical thickness of supratemporal plane predicts auditory N1 amplitude[END_REF]. As reviewed by Liem and colleagues, the N1 amplitude reflects the first step of auditory processing and is modulated by auditory experience, such as musical training [START_REF] Pantev | Timbre-specific enhancement of auditory cortical representations in musicians[END_REF][START_REF] Baumann | Enhancement of auditory-evoked potentials in musicians reflects an influence of expertise but not selective attention[END_REF]. [START_REF] Liem | Cortical thickness of supratemporal plane predicts auditory N1 amplitude[END_REF] postulated that a refinement in the synaptic circuitry might have resulted in a thinner cortex, allowing neurons to be better synchronized and generate the electrophysiological signal. This hypothesis agrees with Hyde's proposal that a thicker cortex might be less efficient in terms of neural processing [START_REF] Hyde | Cortical thickness in congenital amusia: when less is better than more[END_REF]. Hyde et al. reported a thicker cortex in the right inferior frontal gyrus and the right auditory cortex in amusic patients compared to musically intact controls, and suggested that they were related to cortical malformations in the amusic brain. A recent study in dyslexics also showed an increase in the CT of the right superior temporal gyrus extending to HG and the PT, which resulted in a rightward CT asymmetry that was different from the healthy volunteers [START_REF] Ma | Cortical thickness abnormalities associated with dyslexia, independent of remediation status[END_REF].

Thus, the increased CT observed in cases with HG duplications may or may not represent an advantage, depending on the population studied. A thicker cortex could be associated with cognitive impairments in cases with abnormal development, while, on the other hand, it would be associated with improved abilities in the context of normal development. This hypothesis needs further exploration, but it could partially explain the apparently contradictory associations of HG duplications with both expertise and dyslexia [START_REF] Leonard | Anomalous Cerebral Structure in Dyslexia Revealed With Magnetic Resonance Imaging[END_REF][START_REF] Leonard | Magnetic resonance imaging of cerebral anomalies in subjects with resistance to thyroid hormone[END_REF][START_REF] Leonard | Normal Variation in the Frequency and Location ofHuman Auditory Cortex Landmarks.Heschl's Gyrus: WhereIs It?[END_REF][START_REF] Leonard | Anatomical risk factors for phonological dyslexia[END_REF][START_REF] Altarelli | Planum temporale asymmetry in developmental dyslexia: Revisiting an old question[END_REF].

THE LEFT CSD IS ASSOCIATED WITH A SMALLER CSA IN THE PT, WHILE, ON THE RIGHT, IT IS ASSOCIATED WITH A LARGER CSA IN THE STS

In our previous work using manual delineation of the anterior HG [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF], we have shown that left duplication is associated with decreased left aHG surface area. The present study also shows that left duplication is associated with a decreased left PT surface area. Such an association might have been previously overlooked because the second HG is usually included in the PT in cases with a complete duplication (as reviewed by [START_REF] Shapleske | The planum temporale: a systematic, quantitative review of its structural, functional and clinical significance[END_REF]. Decrease of left aHG size had been associated with a lower leftward lateralization of the temporal processing sounds [START_REF] Warrier | Relating structure to function: Heschl's gyrus and acoustic processing[END_REF], and indirectly with lateralization during speech listening (Tzourio-Mazoyer et al., 2015), while a lower left PT surface area had also been associated with lower leftward asymmetry during speech listening [START_REF] Tzourio | Left planum temporale surface correlates with functional dominance during story listening[END_REF][START_REF] Josse | Left planum temporale: an anatomical marker of left hemispheric specialization for language comprehension[END_REF][START_REF] Josse | Hemispheric specialization for language: Brain volume matters[END_REF]. The question of whether these decreased surface areas and related anatomical asymmetries are detrimental to speech perception in healthy subjects is an open issue; the work conducted by Leonard and others suggests, that it might be the case in dyslexics that exhibit more HG duplications [START_REF] Leonard | Anomalous Cerebral Structure in Dyslexia Revealed With Magnetic Resonance Imaging[END_REF][START_REF] Leonard | Magnetic resonance imaging of cerebral anomalies in subjects with resistance to thyroid hormone[END_REF][START_REF] Leonard | Normal Variation in the Frequency and Location ofHuman Auditory Cortex Landmarks.Heschl's Gyrus: WhereIs It?[END_REF][START_REF] Leonard | Anatomical risk factors for phonological dyslexia[END_REF][START_REF] Altarelli | Planum temporale asymmetry in developmental dyslexia: Revisiting an old question[END_REF].

Increased CSA was located in the middle part of the STS when a right CSD occurred. STS is rightward asymmetrical for grey matter volume [START_REF] Watkins | Structural Asymmetries in the Human Brain :a Voxel-based Statistical Analysis of Collins 142 MRI Scans[END_REF][START_REF] Barrick | Automatic analysis of cerebral asymmetry: an exploratory study of the relationship between brain torque and planum temporale asymmetry[END_REF] and sulcal depth (Van Essen, 2005; [START_REF] Leroy | New human-specific brain landmark: The depth asymmetry of superior temporal sulcus[END_REF].

Human-specific rightward STS asymmetry is organized early in development, as shown by [START_REF] Glasel | A robust cerebral asymmetry in the infant brain: the rightward superior temporal sulcus[END_REF]. The rightward asymmetries of STS described in the abovementioned works are located ventrally to the right HG, as in the present study. From a functional point of view, the right HG, and STS are two major anatomical supports of the spectral processing and pitch analysis, and they constitute the neural support of the analysis of spectral envelope independently of the fine spectrotemporal structure. Warren suggested, that STS may have a generic role in the spectral analysis of sound [START_REF] Warren | Analysis of the spectral envelope of sounds by the human brain[END_REF] and specified that this role did not exclude the possibility that specific subregions of the STS are functionally specialized for higher order analysis of specific sound classes. In fact, the middle STS has been involved in syllables [START_REF] Jäncke | Phonetic perception and the temporal cortex[END_REF][START_REF] Poeppel | Auditory lexical decision, categorical perception, and FM direction discrimination differentially engage left and right auditory cortex[END_REF], speech [START_REF] Binder | Human temporal lobe activation by speech and nonspeech sounds[END_REF], and voice processing [START_REF] Belin | Voice-selective areas in human auditory cortex[END_REF]. Interestingly, one study showed that the acoustic parameters of voices are extracted in the right middle STS for vocal tract parameters, and in the right HG for glottal fold parameters [START_REF] Kreitewolf | A neural mechanism for recognizing speech spoken by different speakers[END_REF]. Because these two distinct anatomical areas could share a close functional role, one might suggest they have associated anatomical variations. Regarding the diversity of auditory processing mediated by the middle part of the STS, further studies are needed to conclusively determine the functional correlates of this increase in CSA in the middle STS in cases with a CSD.

Compared to a single HG in both hemispheres, CSD was also characterized by an increase of medial CSA at the interface between the temporal transverse sulcus and aHG. These increases in the CSA could relate to the growth of the wide common stem supporting the two merging gyri in cases with a CSD.

CPD AND CSD EXHIBIT ANATOMICAL DIFFERENCES IN THE CSA IN THE RIGHT AHG

The differences across duplication patterns were limited to variations in CSA on the right. This result is only partially consistent with our previous report of an absence of significant differences in the reduced surface area of anterior HG between the CSD and CPD groups [START_REF] Marie | Descriptive anatomy of Heschl's gyri in 430 healthy volunteers, including 198 left-handers[END_REF], that might be in relation with the increased sensitivity provided by the examination of CSA extracted by SBM as compared to manual delineation. Anterior HG and the PAC primarily overlap in the medial part of aHG [START_REF] Penhune | Interhemispheric anatomical differences in human primary auditory cortex: probabilistic mapping and volume measurement from magnetic resonance scans[END_REF][START_REF] Rademacher | Probabilistic mapping and volume measurement of human primary auditory cortex[END_REF], where a decreased CSA was observed in the CPD group. This decrease may correspond to a decrease in the number/spacing of the minicolumns of the PAC, according to the radial-unit hypothesis of cortical development initially proposed by [START_REF] Rakic | A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution[END_REF][START_REF] Rakic | A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution[END_REF]) and acknowledged as a potential interpretation of such variations by others [START_REF] Elmer | Increased cortical surface area of the left planum temporale in musicians facilitates the categorization of phonetic and temporal speech sounds[END_REF][START_REF] Meyer | Cortical Surface Area and Cortical Thickness Demonstrate Differential Structural Asymmetry in Auditory-Related Areas of the Human Cortex[END_REF]. The radial-unit hypothesis postulates that the morphology of the CSA of a given brain region is principally driven by the number and spacing of the ontogenetic or radial cortical columns, rather than by the number and size of cells within a column, packing density, or number of connections [START_REF] Rakic | A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution[END_REF][START_REF] Eickhoff | High-resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex[END_REF], a functional cortical column of the brain corresponding to several radial columns [START_REF] Rakic | Specification of cerebral cortical areas[END_REF][START_REF] Rakic | A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution[END_REF]. Under this hypothesis, CSA variations presently observed could relate to changes in the number and spacing of minicolumns and, consequently, to differences in processing power. Further investigations are needed to test such hypothesis and evaluate the potential behavioral correlates. Actually there is no consensus regarding the underlying cellular mechanisms associated with variations in CSA, although numerous mechanisms such as neurogenesis or myelin changes have been proposed as potential candidates for CT/grey matter, or white matter variations, respectively, [START_REF] Draganski | Training-induced structural changes in the adult human brain[END_REF][START_REF] Zatorre | Plasticity in gray and white: neuroimaging changes in brain structure during learning[END_REF]. This lack of knowledge applies also to grey matter density evaluated by VBM that does not correlate with histological measurements of neuronal density [START_REF] Eriksson | Quantitative grey matter histological measures do not correlate with grey matter probability values from in vivo MRI in the temporal lobe[END_REF] pointing toward a need for understanding of the microstructural changes that underlie these macrostructural variations detected by computational neuroanatomy.

PATTERN OF MYELINATION IN THE SUPRATEMPORAL PLANE

Our T1w/T2w maps showed an intense myelination of HG, which extended onto the second gyrus in case of duplication. This is in agreement with the results found in De Martino's six participants, where the second gyrus was systematically at least partially myelinated [START_REF] Martino | High-Resolution Mapping of Myeloarchitecture In Vivo: Localization of Auditory Areas in the Human Brain[END_REF]. Furthermore, Da Costa's tonotopic maps showed a functional reorganization of sound treatment in cases of duplication (Figure 18). This concordance of results across techniques, combined with the large sample of our study, suggest that the primary auditory cortex could extend to the second gyrus in case of partial or complete duplication.

The group comparisons revealed explicitly that myelination at the level of the HG is rather independent of the HG configuration. If the quantity and surface area of [START_REF] Costa | Human primary auditory cortex follows the shape of Heschl's gyrus[END_REF] myelination are not dependent of the morphology and the gyrification pattern (already in place during developmental myelination process), it is possible that the primary auditory cortex is a functional region of constant size under the control of a more global organization. The significant differences between HG configuration groups are systematically localized at the level of the PT, suggesting a strong interdependence of the anatomical organization of these two regions.

Figure 18 -Evidence of the extension of the tonotopic map of the primary auditory cortex on the whole HG. On the left, group averaged tonotopic maps across all 10 subjects. Sound stimuli were designed to induce a traveling wave of response across cortical tonotopic maps: fMRI responses peak sooner in map regions preferring low frequencies (in hot colours) and progressively later in regions preferring higher frequencies (cold colours). The table on the right shows an example of individual tonotopic maps according to HG configuration (axial orientation) and a scheme corresponding to the representation of two fields of the primary auditory cortex, A1 and R. Adapted from Da

The differences in linguistic or musical performance that can be observed according to the duplication profile (Table 1) could then be the result of these differences in cortical myelination, support of connectivity and auditory information treatment. The functional correlates of the size of PT remain to be determined, and it would also be interesting to see if the organization of the PT and the HG are independent or indeed complementary.

One of the most interesting results is the apparent difference in myelination between the two hemispheres, with higher myelin content in the left hemisphere and particularly at the level of PT, with an absence of strong myelination signal in the right hemisphere. Knowing that the left hemisphere is specialized for language in a very large proportion of the population [START_REF] Mazoyer | Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness[END_REF], this increased myelination in the primary and associative auditory areas could be the anatomical support of these mechanisms. It seems important to pursue investigations into these potential interhemispheric differences, to begin with at the level of HG, and then at the level of the PT. Due to the fact that T1w/T2w myelin maps were normalized for each hemisphere separately and that it exists some interhemispheric differences caused by acquisition inhomogeneity, even after best practice corrections [START_REF] Shafee | Gray matter myelination of 1555 human brains using partial volume corrected MRI images[END_REF], the investigation of asymmetries requires the development of a specific methodology.

CONCLUSION AND PERSPECTIVES

The present Surface-Based Morphometry study conducted in 430 participants explored the changes in cortical thickness, cortical surface area and intracortical myelin associated with Heschl's gyrus duplications.

Variations of cortical thickness and cortical surface area between groups of subjects differing in Heschl's gyrus configuration, which significance and location were independent of the template used for group analysis and of the smoothing of the images. They were observed in the left Heschl's gyrus and planum temporale while located on the right in the Heschl's gyrus and the mid superior temporal sulcus.

Interestingly, the strong intracortical myelin density specific to primary cortical areas extended to the second gyrus in case of duplication, albeit less intense than the anterior gyrus. Besides, the average myelin maps showed an extension of the heavily myelinated area in the left planum temporale only.

One perspective of this work is the investigation of the potential interhemispheric differences of cortical thickness and myelin content in the Heschl's gyrus and the planum temporale, and the characterization of these candidates marker of language lateralization. Besides, through a starting collaboration with the Brain and Language Lab in Geneva (directed by Narly Golestani), we plan to use myelin maps to improve the automatic labeling of auditory cortex, notably the anterior and posterior borders of Heschl's gyrus, thanks to machine learning approach.

INTRODUCTION

The human brain undergoes significant structural changes across the lifespan depending on genetic [START_REF] Chen | Hierarchical genetic organization of human cortical surface area[END_REF] and environmental factors such as cognitive development (Tamnes et al., 2010b), practice [START_REF] Maguire | Navigation-related structural change in the hippocampi of taxi drivers[END_REF][START_REF] Draganski | Changes in grey matter induced by training[END_REF] and aging [START_REF] Crivello | Longitudinal assessment of global and regional rate of grey matter atrophy in 1,172 healthy older adults: modulation by sex and age[END_REF]. For instance, the total cortical surface area increases 3-fold between term birth and young adulthood (Hill et al., 2010a) and then decreases by 10% during aging [START_REF] Lemaitre | Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume?[END_REF].

Although the majority of the sulci and gyri present in adulthood are already in place at the end of pregnancy (White et al., 2010, Figure 19), postnatal brain development results in cortical expansion and increasing complexity of the convolutions, particularly in regions implicated in higher cognitive functions (Hill et al., 2010b). The dorsal and medial prefrontal, lateral parietal areas and the lateral temporal areas are the last which expand in the course of both phylogeny and ontogeny (Hill et al., 2010b) and exhibit greater dendritic complexity in adults [START_REF] Elston | The Pyramidal Cell in Cognition: A Comparative Study in Human and Monkey[END_REF]. Neurogenesis and neural migration are almost ended at the end of gestation [START_REF] Marsh | Neuroimaging Studies of Normal Brain Development and Their Relevance for Understanding Childhood Neuropsychiatric Disorders[END_REF][START_REF] Feliciano | Newborn cortical neurons: only for neonates?[END_REF], and post-gestational cerebral growth is characterized by synaptogenesis, gliogenesis, increased dendritic arborization, intracortical myelination (Hill et al., 2010b) and the development of Very few studies have focused on differences in local structural changes between the end of maturation and aging stages. These two stages are associated with different physiological mechanisms in different regional patterns of cortical areas.

Thus, the goal of this study was to accurately characterize and compare late cortical maturation during early-(18 to 30 y) and mid-adulthood (30 to 57 y) using a multimodal maturation index derived from cortical thickness and intracortical myelin information.

THE

THICKNESS OF THE CEREBRAL CORTEX: A NEURODEVELOPMENTAL MARKER

As soon as the age of 13, brain volume starts a decrease that covers both end of childhood, early adulthood and aging [START_REF] Hedman | Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies[END_REF]. Grey and white matter structural changes underlying this large scale variation have different time-courses (Fjell et al., 2013, Figure 21), and grey matter volume decrease depends both on cortical surface area and cortical thickness reduction, two genetically independent variables [START_REF] Panizzon | Distinct genetic influences on cortical surface area and cortical thickness[END_REF]. Studies have shown that main contributor to the cortical volume reduction is the thinning of the cortex [START_REF] Lemaitre | Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume?[END_REF][START_REF] Storsve | Differential longitudinal changes in cortical thickness, surface area and volume across the adult life span: regions of accelerating and decelerating change[END_REF].

Although the topic is still debated, cortical thinning at later stage of cortical maturation could be the consequence of synaptic pruning, id est the selection/elimination of synapses depending on learning, the reduction of the number of glial cells together with the proliferation of myelin within the neuropil (Tamnes et al., 2010a). On the opposite, aging-related cortical atrophy is due to the progressive loss of neurons and myelinated axons, the shrinkage of cell bodies and the reduction of synaptic density [START_REF] Morrison | Life and Death of Neurons in the Aging Brain[END_REF][START_REF] Hof | The aging brain: morphomolecular senescence of cortical circuits[END_REF]. Maximal cortical thickness is reached between 7 and 10 years of age depending on the brain regions [START_REF] Shaw | Neurodevelopmental trajectories of the human cerebral cortex[END_REF] and begins to decrease in a nonlinear manner mainly in the parietal lobe, medial and superior regions of the frontal lobe, the cingulate cortex, and the occipital lobe (Tamnes et al., 2010a) (see Table 1). A recent study has shown that the cortical thinning may even start earlier in the young childhood and exhibit a continuous decrease from 3-4y to 30y [START_REF] Amlien | Organizing Principles of Human Cortical Development-Thickness and Area from 4 to 30 Years: Insights from Comparative Primate Neuroanatomy[END_REF]. As summarized Table 1 reviewing past decade's reports on cortical thinning throughout the lifespan, most studies that dealt with the issue of cortical age-related changes have recruited participants covering a wide range of age, most often between 18 and 80 years. Within this large age range, it is difficult to identify the exact period when thinning associated with development and maturation is changing into deleterious aging atrophy. Previous studies have shown that cortical thinning starts from the late twenties/early forties [START_REF] Westlye | Differentiating maturational and aging-related changes of the cerebral cortex by use of thickness and signal intensity[END_REF][START_REF] Fjell | Critical ages in the life course of the adult brain: nonlinear subcortical aging[END_REF]. Exponential modelling of age-related effects shows that 90% of thinning occurs before 30 years in a large set of regions including the cuneus, the inferior temporal, the lateral occipital, the lateral orbitofrontal, the orbital part of the inferior frontal gyrus, the pericalcarine cortex, the postcentral, the superior parietal and the frontal pole (Tamnes et al., 2010a). This last observation highlights the importance of cortical thinning during the latematuration period. During aging, that is to say after 60 years-old, transversal studies have shown heterogeneous effect of age on cortical thickness with some areas, such as the inferior temporal and parahippocampal gyrus, the cingulate cortex and the paracentral gyrus, more preserved as opposed to the frontal cortex exhibiting the largest thinning [START_REF] Fjell | High consistency of regional cortical thinning in aging across multiple samples[END_REF][START_REF] Lemaitre | Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume?[END_REF][START_REF] Hogstrom | The structure of the cerebral cortex across adult life: age-related patterns of surface area, thickness, and gyrification[END_REF]. Reports from longitudinal studies modulate this view by demonstrating that while temporal and occipital lobe show acceleration of cortical atrophy with age, the prefrontal and anterior cingulate cortices have a slower thinning than other cortical areas [START_REF] Storsve | Differential longitudinal changes in cortical thickness, surface area and volume across the adult life span: regions of accelerating and decelerating change[END_REF].

THE INTRACORTICAL MYELINATION: A FUNDAMENTAL FEATURE OF HUMAN BRAIN INTEGRITY AND FUNCTIONING

The cortical ribbon is not only constituted by neuronal cell bodies but also by myelinated axons that can be mapped with recent neuroimaging methods based on the integration of multimodal signals that provide in vivo information about myelin content of cerebral cortex (see Chapter 2).

To our knowledge only two studies attempted to map intracortical lifespan trajectories of myelin in vivo. In a population aged from 8 to 83 years, Grydeland et al. showed an inverted U-shaped age-related trajectory for T1w/T2w ratio indicating a three-staged process of cortical myelin changes: an accelerated myelination until 30 years of age, followed by a period of relative stability, and then by a decrease in myelin content starting in the late 50s [START_REF] Grydeland | Intracortical myelin links with performance variability across the human lifespan: results from T1-and T2-weighted MRI myelin mapping and diffusion tensor imaging[END_REF]. More recently, a study on a database of 1555 participants has focused on young adults (i.e. 18-35 years of age) demonstrating a positive linear age-dependence almost everywhere on the cortex [START_REF] Shafee | Gray matter myelination of 1555 human brains using partial volume corrected MRI images[END_REF].

AIM OF THE STUDY

Here to investigate late brain maturation in 447 healthy participants aged 18-57 years we have considered both cortical thickness and myelination variations with age to test whether multimodal imaging integration of these two anatomical variables could be used as a marker to differentiate the cortical change associated with late maturation and the start of aging [START_REF] Walhovd | Through Thick and Thin: a Need to Reconcile Contradictory Results on Trajectories in Human Cortical Development[END_REF]. Indeed, the apparent cortical thinning of late maturation could actually reflect increased myelination in the white matter tracts coursing within and nearby the deepest part of the cortical layer [START_REF] Erus | Imaging Patterns of Brain Development and their Relationship to Cognition[END_REF]. In other words the "grey" signal of the unmyelinated fibers could become "whiter" as myelin is deposited along maturation, justifying the coinvestigation of these variables. This chapter is the subject of an article in preparation. Positive linear correlation with higher rate of increase in primary motor and somatosensory cortex

MATERIALS AND METHODS

PARTICIPANTS

The present study was conducted using the data collected on the 447 participants from the BIL&GIN (http://www.gin.cnrs.fr/BILandGIN), a multimodal database designed for the study of human brain lateralization [START_REF] Mazoyer | BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization[END_REF]. Participants were aged from 18 to 57 years (mean 26.7 ± 7.8 years) and balanced for gender (51.2 % of women) and handedness (54.4 % of self-reported right-handers).

Participants were recruited at the same period through announcements made at the Caen University and selected as having French as their mother tongue. None of them had a past history of developmental disorders or neuropsychiatric diseases, notwithstanding possible ancient and cured episodes of depression. All participants were free of brain abnormalities as assessed by an expert neuroradiologist on their magnetic resonance imaging scans. The study was conducted with strict respect of French law on ethics in biomedical research: the protocol was approved by the Basse-Normandie's ethics committee, and all participants gave their informed written consent and received an allowance for their participation.

IMAGE ACQUISITION

Imaging was performed on a Philips Achieva 3Tesla MRI scanner. Structural MRI protocols consisted in a localizer scan, a high resolution 3D-FFE-TFE T1weighted volume acquisition (TR = 20 ms; TE = 4.6 ms; flip angle = 10°; inversion time = 800 ms; turbo field echo factor = 65; sense factor = 2; matrix size = 256 x 256 x 180; 1 mm 3 isotropic voxel size) and a 3D-TSE T2-weighted volume acquisition (TR = 5500 ms; TE = 80 ms; sense factor = 2; FOV = 256 mm; matrix size = 256 x 256 x 81; 1 x 1 x 2 mm voxels). The T2w volumes were acquired only for 447 participants.

IMAGE PROCESSING

SURFACE-BASED PROCESSING

Reconstruction of cortical surfaces and measurement of anatomical variables were performed for each participant using the FreeSurfer 5.3.0 image analysis suite (http://surfer.nmr.mgh.harvard.edu/, [START_REF] Dale | Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction[END_REF]Fischl et al., 1999b;Fischl et al., 1999a;[START_REF] Fischl | Measuring the thickness of the human cerebral cortex from magnetic resonance images[END_REF][START_REF] Fischl | Whole Brain Segmentation: Neurotechnique Automated Labeling of Neuroanatomical Structures in the human Brain[END_REF][START_REF] Fischl | Automatically Parcellating the Human Cerebral Cortex[END_REF]. The FreeSurfer analysis includes intensity bias field removal optimized for the present 3T acquisitions, and skull stripping. In the native anatomical space of the subject, FreeSurfer constructs models of cortical surface that can be represented as a mesh of triangles and tessellated into over 160,000 vertices for each hemisphere. The vertex positions were adjusted so that the surface follows the T1 intensity gradient between cortical white matter (WM) and cortical matter (GM). This highly folded surface, called "white surface", can be inflated to see buried surface within the sulci. A second surface was fit to the outer GM surface of the brain called the "pial surface". The hemispheres were processed separately through a precise estimation of interhemispheric fissure plane.

QUALITY CONTROL

Troubles in estimation of surfaces around the thin temporal lobe strands that border the tip of the lateral ventricle have been identified with the FreeSurfer segmentation procedure [START_REF] Dale | Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction[END_REF]. In a such case, a reduction of intensity of voxels in the corresponding white matter leads to misclassification of voxels and inaccurate definition of white and pial surfaces. To overcome this limitation we visually checked (SM) each of the 447 pial and white surfaces on each axial, sagittal and coronal section of each participant twice and identified segmentation error in 48 cases (11%). A correction procedure consisting in manually adding an average of 9 control points (SD, 7) in the misclassified white matter was then applied in these 48 individuals. Then the automatic FreeSurfer segmentation procedure was rerun on these subjects resulting in an accurate surface reconstruction after a novel visual round of quality control check.

CALCULATION OF MORPHOMETRIC VARIABLES IN THE NATIVE

SPACE OF EACH PARTICIPANT

For each vertex defining the surfaces, cortical thickness (CT) was defined as the distance between the white and pial surfaces (example of an individual CT map in the Figure 2A) and cortical surface area (CSA) as the average area of the triangles to which the vertex belongs. Sulcal depth parameter (SULC) was measured by integrating the dot product of the movement vector during inflation with the surface normal vector at each node. A cortical surface curvature (CURV) parameter was also extracted and used for driving the nonlinear surface-based intersubject registration and as covariate in statistical analyses. Integrating these variables over all vertices of the cortex surface, mean CT and total CSA were computed for each participant.

DEFINITION OF A SPECIFIC TEMPLATE FOR INTERSUBJECT SURFACE-BASED REGISTRATION

To optimize the inter-subject surface-based normalization we computed a homemade specific template including images of participants with identical demographic, contrast and signal to noise ratio characteristics. We already detailed the methodology in the Chapter 1, section 2.3.6). Briefly, the specific template creation started with an initiation step that consisted in creating a first "8-average" space by averaging 8 subjects (4 men, 4 right-handed) that were normalized to the default "Fsaverage" template. This step made it possible to initiate the specific template creation with an image having a higher signal to noise ratio than an individual image. Then, 40 participants representative of the BIL&GIN sample in term of age and balanced for sex and handedness were registered on the "8-average" space and further averaged to create a "40-average space_1". To limit the impact of the "Fsaverage" default template on our specific template, we repeated this step twice and finally obtained the final "40-average space".

GENERATION OF THE SURFACE-BASED CT, CSA AND SULC IMAGES

The last step consisted in the non-linear surface-based spatial normalization of the 447 CT, CSA and SULC individual maps to the BIL&GIN specific "40-average space", allowing for accurate vertex-wise analysis across individuals. An additional operation was performed by adding a Jacobian correction to the CSA maps in order to account for any stretching or compression in the registration occurring during the non linear registration [START_REF] Winkler | Measuring and comparing brain cortical surface area and other areal quantities[END_REF]. Note that this correction is not needed for CT and SULC maps because they are measured along a vector normal to any stretching or compression.

GENERATION OF THE SURFACE-BASED T1W/T2W RATIO IMAGES

The procedure to obtain the individual surface-based T1w/T2w map was detailed in the Chapter 1, section 2.3.8. Briefly, each individual T2w images was rigidly registered to the corresponding T1w images using the "SPM12 co-register" routine and resampled using a trilinear interpolation. The T1w volume was then divided by the T2w one, creating a T1w/T2w ratio 3D volume. We then sampled this T1w/T2w values vertex-wise at mid-thickness distance into the grey matter ribbon from the white surface boundary using "FreeSurfer's mri_vol2surf" tool [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF][START_REF] Grydeland | Intracortical myelin links with performance variability across the human lifespan: results from T1-and T2-weighted MRI myelin mapping and diffusion tensor imaging[END_REF], yielding T1w/T2w ratio surfaces for each participant in his individual space (see an example in Figure 22B). We assigned a T1w/T2w value of zero for vertices located in the non-cortical medial wall and having a null CT value. The T1w/T2w surface maps intensities across subjects were adjusted using the mean intensity value of the deep white matter region extracted from the T1w/T2w ratio volume. This 3D white matter region of interest was obtained by the Freesurfer parcellation routine. Finally, all individuals T1w/T2w surface maps were then surface-based spatially normalized to the BIL&GIN specific "40-average space".

DEFINITION OF A MATURATION INDEX

Structurally, the cerebral cortex is characterized by its thickness and its myelinated proportion, this latter variable being shown to be more discriminatory than the CT alone to disentangle changes in cortical myelination in bipolar disorder patients [START_REF] Rowley | Assessing intracortical myelin in the living human brain using myelinated cortical thickness[END_REF]. Furthermore, these 2 variables showing an opposite neurodevelopmental trajectory (see Table 4 and Figure 26) with a decrease of CT started in childhood associated to an increase of intracortical myelination until 30 y [START_REF] Grydeland | Intracortical myelin links with performance variability across the human lifespan: results from T1-and T2-weighted MRI myelin mapping and diffusion tensor imaging[END_REF]. According to these different trajectories, we defined a maturation index by combining these 2 cortical variables with the computation of the ratio between the CT and the T1w/T2w at each vertex. Individual maps registered in the template were smoothed with a 15 mm FWHM kernel for the following statistical analyses. A global maturation index was calculated by integrating the vertex-wise values of the entire cortex.

STATISTICAL ANALYSIS

In order to focus on the late maturation, subjects were classified into two age groups based on previous studies on age-related changes in CT (McGinnis et al., 2011;Tamnes et al., 2010a): young (or early-adulthood, 18-29 years old, n = 341) and middle-aged (or mid-adulthood, 30-57 years old, n = 106).

AGE EFFECT ON MEAN CT, TOTAL CSA, MEAN T1W/T2W RATIO AND GLOBAL MATURATION INDEX

Mean CT, total CSA, mean T1w/T2w ratio and global maturation index were entered in three separate analyses of covariance (ANCOVA), searching for main effects of age, group (2-levels: young and middle-aged), and an "age x group" interaction using total brain volume (eTIV estimated with FreeSurfer) as covariate. We then performed post-hoc analyses to test the age effect in each age group using total brain volume as covariate.

CT AND T1W/T2W RELATIONSHIP

Correlation analysis between CT and T1w/T2w ratio were calculated using the "partialcorr" function of Matlab with curvature as a per-vertex regressor. The individual CT and T1w/T2w maps were initially smoothed with a 2 mm FWHM (Full-Width-at-Half-Maximum) kernel. Pearson partial correlation coefficients were considered to be significant and shown in Figure 2C after False Discovery Rate (FDR) correction with q = 0.05.

AGE EFFECT ON VERTEX-WISE CT, CSA, T1W/T2W RATIO AND MATURATION INDEX

We used FreeSurfer's mri_glm-fit tool for performing, independently on each hemisphere, a vertex-wise exploratory search of age-related CT thinning maps, T1w/T2w ratio and local maturation index modifications in the young and middleage groups with the CURV map as a per-vertex regressor. The regression coefficients between age and CT or T1w/T2w were displayed on the BIL&GIN specific "40average space" surface-based template for each group respectively in Figure 4B and 5B. We did not consider the p-value of these analyses because the two age groups were different in term of number of subjects (341 vs. 106) making the comparison between both regression models impossible.

We also searched for differential age effects in the two age groups and the significant clusters thresholded at p < 0.05 FDR corrected for multiple comparisons were displayed in Figure 4A and 5A. In these analyses, individual maps were smoothed with a 15 mm FWHM kernel to improve signal to noise ratio and the curvature was used as a per-vertex regressor.

RESULTS

DEFINITION OF THE AGE GROUPS

Table 5 detailed the demographic characteristics of these two groups. The "young adults" group included participants from 18 to 30 years (23.2 ± 2.8, n = 341), whereas "the middle-aged adults" group included the other participants ranging from 31 to 57 years (38.1 ± 7.7 n = 106). The two groups did not differ in terms of educational level (15.2 ± 2.0 vs 15.0 ± 3.7 years, p = 0.40), sex ratio (52.8 vs 46.2 % of females, p = 0.24) or handedness (51.9 % vs 62.2% of right-handers, p = 0.06, for the young and middle-age groups respectively).

VERTEX-WISE CORRELATION BETWEEN CT AND T1W/T2W ESTIMATED MYELIN

The correlation between T1w/T2w and thickness was explored at each vertex of the cortex by controlling for curvature across our sample of 447 participants. Figure 22A andB shows an example of individual non-smoothed maps of CT and T1w/T2w ratio. Most of the cortex was characterized by regional negative correlations between CT and T1w/T2w suggesting that, when cortical regions of similar curvature are compared, thicker regions tend to have lesser T1wT2w ratio signal (Figure 22C).

Positive correlations were detected along the precentral gyrus, in the superior part of postcentral gyrus, in the left short insular gyrus and along bilateral inferior segment of the circular sulcus of the insula, the paracentral lobule, the pericallosal and entorhinal cortex, and in the occipital lobe, more precisely in the pericalcarine cortex and the lingual gyrus.

AVERAGE CT, T1W/T2W MYELIN AND VARIABILITY SULC MAPS

CORTICAL THICKNESS

For the whole sample, the average mean CT was 2.44 ± 0.11 mm. Mean CT was found regionally heterogeneous. Regions showing CT thinner than average (mean minus 4 standard deviations or less than 2 mm) were essentially located in sulcal regions (Figure 23). More precisely, the marginal part of cingulate sulcus, the calcarine fissure, the superior part of lingual gyrus, the inferior part of cuneus, the middle frontal and frontomarginal sulci, the central sulcus, the superior two-thirds of postcentral sulcus, the intraparietal sulcus, the posterior part of middle occipital sulcus, the pericallosal sulcus, the medial and lateral orbital sulcus, the anterior part of inferior frontal sulcus and the superior part of parieto-occipital sulcus had a thinner cortical sheet. The temporal pole, the inferior temporal gyrus except its middle part, the central part of insula, the posterior part of orbital gyrus, the parahippocampal gyrus and the anterior part of cingulate gyrus were thicker than average (mean plus 4 standard deviations or > 2.88 mm). Other brains regions such as the superior temporal gyrus and its verticalization in supramarginal gyrus, the middle temporal gyrus, the fusiform gyrus, from paracentral lobule along the precentral gyrus and until the opercular part of inferior frontal gyrus, the peripheral insular cortex, the posterior-dorsal part of cingulate gyrus, the internal part of superior frontal gyrus and the superior part of middle occipital gyrus had a thicker cortex.

MYELIN

Figure 24 displays average T1w/T2w ratio surface maps of the 447 participants for both hemispheres. Regions of heavy myelination included the motor-sensory strip in the central sulcus that medially extended to the paracentral lobule, the perisylvian cortices and more precisely the transverse temporal gyrus and posteriorly to the planum temporale, and even in the half posterior part of the superior temporal gyrus of the right hemisphere, the medial occipital lobe extended to the isthmus cingulate cortex.

The lightest myelination occurs in the middle and superior frontal cortices (lateral and medial part), the anterior insula, the temporal pole and the supramarginal gyrus.

SULCAL DEPTH VARIABILITY

Sulcal depth was less variable in the insula, the pre-and postcentral gyri, the temporal traverse gyrus, the superior temporal gyrus, the internal view of the frontal lobe, the orbital gyrus and the parahippocampal gyrus (Figure 25). On the contrary, the middle frontal gyrus, the inferior temporal gyrus, the precuneus gyrus and the angular and supramarginal gyri showed a large between-subject variability.

MODULATION OF ANATOMICAL VARIABLES DURING LATE MATURATION

ANALYSIS OF GLOBAL VARIABLES

Five-years moving averages of each anatomical variable are displayed in Figure 26.

CORTICAL THICKNESS

TIV and sex had no effect on global CT (p = 0.25 and p = 0.51 respectively). Considering the whole population, we found a global effect of age on CT (-10 µm/year, p < 0.0001). The difference in age-related CT thinning between the two groups was significant as attested by age x group interaction (p=0.01 for the "age x group" interaction). Post-hoc analyses revealed a rate of thinning twice larger for young adults (-10 µm/year, p < 0.0001, and -5 µm/year, p < 0.0001, respectively).

CORTICAL SURFACE AREA

CSA was slightly negatively correlated with age (-3 cm 2 /year, p = 0.02), similarly in the young (-3 cm 2 /year, p = 0.02) and middle-aged groups (-2 cm 2 /year, p = 0.002) ("age x group" interaction p = 0.67). A positive and significant effect of TIV on total CSA was also found (p < 0.0001), whereas sex had no significant proper effect (p = 0.10).

T1W/T2W RATIO

TIV and sex had no effect on mean T1w/T2w (p = 0.45 and p = 0.71 respectively). The whole population, as well as each group, showed highly significant increase of T1w/T2w ratio signal with age (+0.002/year, p < 0.0001 in all analyses and "age x group" interaction p = 0.27).

MATURATION INDEX

TIV and sex had no effect on global maturation index (p = 0.25 and p = 0.41 respectively). The whole population showed highly significant decrease of maturation index with age (-0.11/year, p < 0.0001) with a significant stronger effect of age during early-adulthood in comparison to middle-age participants (-0.11/year, p < 0.0001, and -0.06/year, p < 0.0001 respectively, with p=0.003 for the "age x group" interaction).

LOCAL CORTICAL GREY MATTER AGE-RELATED MODIFICATIONS

The CSA shows no significant regional effect of age.

Figure 26 -Five-years moving average and standard deviation of mean cortical thickness (A), total cortical surface area (B), mean T1w/T2w ratio (C) and mean maturation index (D). The sample numbers indicate the number of participants in each five-year window.

Considering young adults only, cortical mantle displayed the highest rate of thinning (i.e. > 20 µm/year) in the frontal lobe and in the insula, including the orbitofrontal region, the middle frontal sulcus, the inferior frontal gyrus (more specifically in the pars triangularis and pars opercularis), the medial superior frontal area and the cingulate gyrus (upper part of Figure 27A). On the contrary, some frontal regions such as the precentral and the caudal part of medial superior frontal gyrus were spared. In the temporal lobe, the superior temporal sulcus, more extend to the middle temporal gyrus in the right hemisphere, and the anterior part of the fusiform gyrus showed high thinning rates but the right temporal pole and the bilateral Heschl's gyrus were preserved. In the parietal lobe, the supramarginal gyrus displayed high decrease of CT contrary to the postcentral gyrus and the precuneus. Finally, the occipital lobe showed a stable CT during our age range.

The middle-age group showed lower local cortical thinning rate than young adults with greater reduction in the right hemisphere (lower part of Figure 27A). The highest rates of thinning were located in the rostral part of medial frontal area, the pars orbitalis of the inferior frontal gyrus and in the posterior insular cortex. In the temporal lobe, the Heschl's gyrus, the mid part of superior temporal sulcus and the middle temporal gyrus displayed higher decrease of CT than the overall cortex. Finally, contrary to the results obtained in early-adulthood, the pericalcarine cortex showed higher rate of thinning until 15 µm/year in the depth of the fissure. Comparing the two age groups, there were significant differences of age effects on cortical thickness with a loss per year stronger in young vs. middle-aged subjects (Figure 27B). These clusters are described in details in Table 6. The largest cluster was located in the right cingulate gyrus with a decrease more than 3 times greater in young adults (-21 µm/year, p < 0.0001, and -4 µm/year, p = 0.02, respectively).

Figure 27 -A. Vertex-wise analysis of age effect on cortical thickness for the 341 young adults and the 106 middle-aged. Colour coding represents the loss per year covaried by the curvature. B. Map of difference of age effect on cortical thickness between young and middle-aged adults.

p < 0.05 corrected for FDR with a different threshold for each hemisphere (<5.10 -4 for the left hemisphere and <2.10 -3 for the right one). All the clusters showed a loss per year stronger for young adults than middle-aged. Light grey for gyri and dark grey for sulci.

LOCAL INTRACORTICAL T1W/T2W MYELIN AGE-RELATED

MODIFICATIONS

The effect of age on the vertex-wise T1w/T2w estimated myelination of the cortex is illustrated in Figure 28A for each group. In the young population high rate of increase in myelin were present in larger cortical areas than in the middle-age group. Note that there were greater rates in the right hemisphere in young adults.

Young participants showed highest rate of intracortical myelination increase with age located in the frontal lobe more precisely in both banks of the central sulcus, extending anteriorly to the right precentral gyrus and sulcus, in the inferior frontal gyrus, and in the paracentral lobule and caudal part of superior frontal gyrus (upper part of Figure 28A). In the temporal lobe, larger myelination increase with age was located in the supratemporal plane extending to the superior temporal gyrus. In the occipital lobe, the right superior occipital gyrus showed significant high rate of increase. Finally, the right precuneus displayed stronger increase of myelination with age than other parietal areas.

Considering middle-aged group, the strongest increases of myelination with age were located the anterior bank of central sulcus and the bilateral paracentral lobule of the frontal lobe (lower part of Figure 28A). In the temporal lobe, the supratemporal plane (HG and PT), as in young adults, increased with age. Finally, the right cuneus was a site of myelination increase with age.

Statistical comparison of the two groups showed significant differences of age effects on the right precentral gyrus T1w/T2w myelin. Pots-hoc analyses showed that it was due to a twice-stronger gain per year in young than middle-aged subjects (Figure 28B and Table 7).

Figure 28 -A. Vertex-wise analysis of age effect on intracortical T1w/T2w ratio for the 341 young adults and the 106 middle-aged. Colour coding represents the increase per year covaried by the curvature. B. Map of difference of age effect on intracortical

T1w/T2w ratio between young and middle-aged adults. p < 0.05 corrected for FDR with a different threshold for each hemisphere (<7.10 -5 for the left hemisphere and <10 -3 for the right one). All the clusters showed an increase per year stronger for young adults than middle-aged. Light grey for gyri and dark grey for sulci.

LOCAL MATURATION INDEX AGE-RELATED MODIFICATIONS

Young adults showed highest rates of decrease of this maturation index in the whole frontal lobe, stronger in the right hemisphere, in the inferior parietal lobule (supramarginal and angular gyri) and in the superior and middle temporal gyri. On the contrary, the occipital lobe and the central sulcus were spared.

In the middle-aged group, the pattern of decreasing maturation index was equivalent to that of the early-adulthood group with lower rate of decrease and with a maximal reduction in the superior frontal gyrus.

Statistical comparison of the two groups showed significant differences of age effects on bilateral frontal lobe, and more specifically on inferior frontal, precentral and orbitofrontal gyri, and right parietal and mid-temporal region with a stronger decrease during early-adulthood (Figure 29 and Table 8).

Vertex-wise analysis of age effect on local brain maturation index for the 341 young adults and the 106 middle-aged. Colour coding represents the loss per year covaried by the curvature. B. Map of difference of age effect on local brain maturation index between young and middle-aged adults.

p < 0.05 corrected for FDR with a different threshold for each hemisphere (<7.10 -5 for the left hemisphere and <10 -3 for the right one). All the clusters showed an loss per year stronger for young adults than middle-aged. Light grey for gyri and dark grey for sulci.

DISCUSSION

METHODOLOGICAL ASPECTS

In the present study, we paid specific attention to build an adequate template. It is widely acknowledged that to obtain sensitive and accurate results one needs to normalize individual images to a template built from data acquired on the same magnet with the same characteristics than the data to be analysed [START_REF] Klein | Evaluation of volume-based and surface-based brain image registration methods[END_REF]. Ideally, in order to remove any systematic template bias in stereotaxic analyses, the template should be calculated from a population as close as possible to the studied population and, ideally, from the studied group itself [START_REF] Evans | Brain templates and atlases[END_REF]. Use of such specific-population template reduces areal shifts and biases caused by registration [START_REF] Winkler | Measuring and comparing brain cortical surface area and other areal quantities[END_REF]. Here we had to deal with the fact that the template provided by the FreeSurfer software (Fsaverage) was built from MRI data acquired in 40 nondemented individuals, with ages ranging from 18 to 93 (with no subjects between 30 to 65 years of age); besides, the Fsaverage template MRI data were acquired on a magnet different from ours. In order to optimize data analyses we developed a specific template for our sample aged from 18 to 57 years from 40 individuals of the BIL&GIN database and balanced this sample for gender and manual preference.

The relative lower spatial resolution of the present T2w images in comparison to the T1w ones and in comparison to other studies assessing surface-based intracortical myelin [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF][START_REF] Grydeland | Intracortical myelin links with performance variability across the human lifespan: results from T1-and T2-weighted MRI myelin mapping and diffusion tensor imaging[END_REF] could cause partial volume effects, especially in thin and heavily myelinated areas such as the pericalcarine cortex. Indeed, our results showed a large area with a high T1w/T2w ratio signal extended to the whole medial part of the occipital lobe (Figure 24), also displaying the thinnest cortex (Figure 23). Another study built T1w/T2*w ratio surface-based images by using high-resolution acquisition (0.6 mm isotropic) on 7T scanner [START_REF] Martino | High-Resolution Mapping of Myeloarchitecture In Vivo: Localization of Auditory Areas in the Human Brain[END_REF]. They obtained an average map with 6 subjects showing a relative lower signal in the occipital lobe in comparison to the central sulcus or the paracentral lobule suggesting an exacerbation of our signal due to partial volume effect. By increasing the intracortical contrast of their T1w images, Rowley et al. distinguished two divisions of the cortical ribbon along its depth: a lightly and a heavily myelinated portion. They highlighted a more limited occipital territory having high proportional myelinated thickness than in our study, located specifically around the calcarine fissure and not extended that much in the cuneus [START_REF] Rowley | Assessing intracortical myelin in the living human brain using myelinated cortical thickness[END_REF]. Nevertheless, despite the low resolution of present T2w images, the individual (Figure 22B) and average (Figure 24) myelin maps are concordant with other studies investigating intracortical myelin distribution [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF][START_REF] Grydeland | Intracortical myelin links with performance variability across the human lifespan: results from T1-and T2-weighted MRI myelin mapping and diffusion tensor imaging[END_REF][START_REF] Rowley | Assessing intracortical myelin in the living human brain using myelinated cortical thickness[END_REF][START_REF] Shafee | Gray matter myelination of 1555 human brains using partial volume corrected MRI images[END_REF].

GENERAL CHARACTERISTICS OF ANATOMICAL FEATURES IN THE PRESENT POPULATION

In the present study we found a global pattern of thinner cortex in the depths of the sulci and thicker cortex at the crowns of the gyri. These results are consistent with report from post-mortem study using high-field-strength MR imaging on brain slices [START_REF] Fatterpekar | Cytoarchitecture of the human cerebral cortex: MR microscopy of excised specimens at 9.4 Tesla[END_REF]. According to tension-based theory of folding developed by Van Essen, cells in deep layers should be stretched tangentially and compressed radially along inward folds or sulci, making these layers thinner. In contrast, along the outward folds corresponding to gyri, cells in deep layers should be stretched radially making these layers thicker (Van Essen, 1997).

The higher variability of sulcal depth we reported in the middle frontal region, the parietal lobe, the lateral and posterior part of the temporal lobe and the precuneus is consistent with other studies (Hill et al., 2010a;[START_REF] Mueller | Individual variability in functional connectivity architecture of the human brain[END_REF]. These areas are characterized by a recent expansion in human evolution together with a high postnatal cortical expansion (Hill et al., 2010b). [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF] reported a correlation with myelin maps with lesser myelination in the prefrontal, inferior parietal and lateral temporal cortices, in accordance with our results, and the corresponding subcortical myelination also happening later during development (Flechsig's myelogenetic maps, 1901). By studying macaque's brains, [START_REF] Elston | Spinogenesis and pruning scales across functional hierarchies[END_REF] showed that inferotemporal visual association and granular prefrontal cortices had a larger and late-developing dendritic arbors in comparison to primary visual cortex. Besides, multimodal association areas including superior temporal sulcus, inferior and superior parietal lobules and frontal cortices had relatively low neuronal densities in the macaques, in opposition to sensory areas that showed higher neuronal densities [START_REF] Collins | Neuron densities vary across and within cortical areas in primates[END_REF]. In addition, to commonalities with structural characteristics, the sulcal depth variability pattern overlapped the local intrinsic connectivity variability but no correlation was found with cortical thickness variability [START_REF] Mueller | Individual variability in functional connectivity architecture of the human brain[END_REF]. All these arguments together suppose that the later maturation of heteromodal areas allows for a more variable impact of postnatal environmental factors that leads to the diversity of neural connections and so to more functional variability.

The intracortical myelin distribution showed stronger myelination in primary cortical areas in accordance with other studies and techniques [START_REF] Glasser | Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI[END_REF][START_REF] Grydeland | Intracortical myelin links with performance variability across the human lifespan: results from T1-and T2-weighted MRI myelin mapping and diffusion tensor imaging[END_REF][START_REF] Lutti | Using high-resolution quantitative mapping of R1 as an index of cortical myelination[END_REF][START_REF] Ganzetti | Whole brain myelin mapping using T1and T2-weighted MR imaging data[END_REF][START_REF] Shafee | Gray matter myelination of 1555 human brains using partial volume corrected MRI images[END_REF][START_REF] Rowley | Assessing intracortical myelin in the living human brain using myelinated cortical thickness[END_REF]. These regions showing higher degree of cortical myelin content also displayed a strong homotopic interhemispheric connectivity (Tobyne et al., 2016). These two structural and functional characteristics are specific to primary cortical areas and the possible correlation between both is still an open question that needs to be investigated.

PHENOTYPIC RELATIONSHIP BETWEEN CT AND INTRACORTICAL

MYELINATION

The intracortical myelination plays a role in the stretching of the cortical surface along the tangential axis, leading to thinning of the cortex [START_REF] Lorio | Neurobiological origin of spurious brain morphological changes: A quantitative MRI study[END_REF] and this could explain the predominant negative correlation between regional CT and intracortical myelin content. Indeed, this phenomenon hypothesized to disentangle neighbouring neuronal columns and enable the relevant parts of the cortex to better differentiate afferent patterns and increase functional specialization. Interestingly, some regions showed a significant positive correlation between CT and myelin content including the areas displaying the earliest beneath white matter myelination (Flechsig 1901;[START_REF] Deoni | Cortical maturation and myelination in healthy toddlers and young children[END_REF] and the heaviest intracortical myelin content (Figure 24), pattern which is concordant with a study based on 1555 young adults between 18 and 35 years [START_REF] Shafee | Gray matter myelination of 1555 human brains using partial volume corrected MRI images[END_REF]. By using the myelin water fraction, Croteau-Chonka et al. investigated the dynamic relationships between cortical and white matter development across early childhood (i.e. from 1 to 6 years) by using the estimation of regional CT and corresponding cortical myelin water fraction. They only found 23% of significant correlation with exclusively negative associations [START_REF] Croteau-Chonka | Examining the relationships between cortical maturation and white matter myelination throughout early childhood[END_REF]. In comparison to our and Shafee's study in adults, this lack of results and correlation between CT and myelin could be due to the low resolution of the FreeSurfer's parcellation, especially in children's brain, in the contrary to the vertex-wise analysis. Besides, the estimation of MWF may be less sensitive than the T1w/T2w estimated myelin.

CHARACTERIZATION OF THE LATE BRAIN CORTICAL MATURATION

INDEX

In this study, we showed that the frontal lobe displayed a differential pattern of age-related maturation index modifications between young and mid-adulthood. This differential effect was more significant in the right hemisphere. This more tardive maturation of the right frontal lobe characterized by a greater decreased of the maturation index in the young group could be a correlate of the earlier development of the gyral complexity of this hemisphere [START_REF] Dubois | Structural asymmetries of perisylvian regions in the preterm newborn[END_REF] and earlier activation assessed by positron emission tomography within the right frontal regions in children between 1 and 3 years of age [START_REF] Chiron | The right brain hemisphere is dominant in human infants[END_REF]. Besides, the notion of non-verbal learning disability (i.e. developmental syndrome) describes the right hemisphere as particularly vulnerable to early insult [START_REF] Semrud-Clikeman | Right hemisphere dysfunction in nonverbal learning disabilities: Social, academic, and adaptive functioning in adults and children[END_REF]). The late structural maturation occurring until the third decade of life in the frontal lobe and in the cingulate gyrus could be linked to the development of executive functions including attention control, goal setting and cognitive flexibility knowing that these regions are known to be the anatomical support of these functions [START_REF] Bush | Cognitive and emotional influences in anterior cingulate cortex[END_REF].

CONCLUSION AND PERSPECTIVES

In the present work, we showed that the late structural cortical maturation, occurring until 30 years, was characterized by a stronger decrease of cortical thickness and a stronger increase of intracortical myelin than middle-aged adults. Defining a maturation index based on the integration of these two structural variables dramatically potentiated the discrimination both in terms of age-related cortical decline and cortical territories between these two age ranges. The present results highlight that young adulthood (i.e. late maturation period) is mainly associated with a stronger age-related decrease of the maturation index in bilateral frontal and cingulate cortices supporting executive functions.

The young adulthood is a period of intensive acquisition of knowledge and learning in various domains, which may have implications on brain structure and function [START_REF] Draganski | Temporal and spatial dynamics of brain structure changes during extensive learning[END_REF][START_REF] Wenger | Cortical thickness changes following spatial navigation training in adulthood and aging[END_REF]. Besides, this age range includes the age of onset for neuropsychiatric disorders such as schizophrenia and bipolar disorder, and also for alcohol and drug use disorders [START_REF] Whiteford | Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010[END_REF]. The T1w/T2w ratio, used in the present work to assess myelin content, is a generic approach that can be improved with the use of high resolution FLAIR (FLuid Attenuated Inversion Recovery) sequence imaging. Indeed, large-scale consortiums that focused on the research of disease-related biomarkers performed FLAIR acquisition, notably to detect white matter lesion. So, this approach can be used to define multimodal indexes based on cortical thickness and T1w/FLAIR ratio to characterize structural modifications due to pathological condition. Psychiatric disorders have been found to exhibit cortical abnormalities [START_REF] Van Haren | Changes in Cortical Thickness During the Course of Illness in Schizophrenia[END_REF][START_REF] Schmaal | Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group[END_REF] and differences of myelination [START_REF] Flynn | Abnormalities of myelination in schizophrenia detected in vivo with MRI, and post-mortem with analysis of oligodendrocyte proteins[END_REF][START_REF] Du | Myelin and axon abnormalities in schizophrenia measured with magnetic resonance imaging techniques[END_REF], the integration of cortical thickness and myelin to extract a hybrid feature optimizes the detection of structural differences between healthy and pathological individuals [START_REF] Rowley | Assessing intracortical myelin in the living human brain using myelinated cortical thickness[END_REF].

An important next step would be to apply this maturation index to explore the cortical changes occurring during a period of heavy learning and to investigate the frequency and the consequences of several diseases such as depression or anxiety disorder. In this perspective, the automatic generation of surface-based myelin and maturation index maps will be applied to the I-Share cohort (http://www.i-share.fr) that is acquired by our laboratory and will gather multimodal imaging for about 2000 students aged from 18 to 25y.

INTRODUCTION 1.ASYMMETRICAL ORGANIZATION OF THE HEALTHY HUMAN BRAIN

The two hemispheres of a human brain develop with a high degree of symmetry at both anatomical and functional level and may seem similar at first sight. However, the structure of the human cerebral cortex is largely asymmetrical [START_REF] Chiarello | Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification[END_REF] and each hemisphere is dominant in processing specific cognitive tasks such as speech production, spatial processing and face processing (i.e. hemispheric specialization) [START_REF] Duboc | Asymmetry of the Brain: Development and Implications[END_REF][START_REF] Zago | The association between hemispheric specialization for language production and for spatial attention depends on left-hand preference strength[END_REF] . The implications of anatomical interhemispheric differences on brain function are very complex to predict [START_REF] Ocklenburg | Intrahemispheric white matter asymmetries: the missing link between brain structure and functional lateralization[END_REF] and the investigation of their regional pattern and variability open new leads in the research for anatomical markers of hemispheric specialization.

The most prominent brain asymmetry is related to the so-called brain Yakovlevian anti-clockwise torque, associated with the left occipital and right frontal petalia, which corresponds to a greater protrusion of the right over the left frontal lobe and a greater protrusion of the left over the right occipital lobe [START_REF] Good | Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains[END_REF]Toga and Thompson, 2003;[START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF]. This asymmetrical brain shift creates positional structural asymmetries between the left and the right hemisphere. For instance, the right posterior ascending ramus of the Sylvian fissure curves upward more anteriorly than does the same structure in the left hemisphere [START_REF] Witelson | Sylvian Fissure Morphology and Asymmetry in Men and Women: Bilateral Differences in Relation to Handedness in Men[END_REF][START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF][START_REF] Glasel | A robust cerebral asymmetry in the infant brain: the rightward superior temporal sulcus[END_REF] (Figure 30). Conversely, the supramarginal and angular gyri are more posteriorly located in the left hemisphere [START_REF] Van Essen | Cortical cartography and Caret software[END_REF]. The more posterior leftward ascending termination of the Sylvian fissure is related to the leftward asymmetry of the planum temporale, an original finding by Geschwind et al. upon examination of a sample of 100 post-mortem brains [START_REF] Geschwind | Human Brain: Left-Right Asymmetries in Temporal Speech Region[END_REF]) that has been consistently reported in further neuroimaging studies [START_REF] Dorsaint-Pierre | Asymmetries of the planum temporale and Heschl's gyrus: relationship to language lateralization[END_REF][START_REF] Hervé | Handedness and cerebral anatomical asymmetries in young adult males[END_REF][START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF]Tzourio-Mazoyer et al., 2010b;[START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF]Van Essen et al., 2012;Li et al., 2013;[START_REF] Goldberg | Hemispheric asymmetries of cortical volume in the human brain[END_REF][START_REF] Chiarello | Structural asymmetry of anterior insula: behavioral correlates and individual differences[END_REF][START_REF] Guadalupe | Asymmetry within and around the human planum temporale is sexually dimorphic and influenced by genes involved in steroid hormone receptor activity[END_REF] (Figure 30B). These hemispheric anatomical asymmetries have been shown to appear very early during brain development, being already visible in utero [START_REF] Dubois | Structural asymmetries of perisylvian regions in the preterm newborn[END_REF][START_REF] Kasprian | The prenatal origin of hemispheric asymmetry: an in utero neuroimaging study[END_REF][START_REF] Habas | Early folding patterns and asymmetries of the normal human brain detected from in utero MRI[END_REF][START_REF] Li | Mapping Longitudinal Hemispheric Structural Asymmetries of the Human Cerebral Cortex From Birth to 2 Years of Age[END_REF] (Figure 32). Indeed, during the third trimester of gestation, the initial smooth brain surface becomes highly convoluted (Hill et al., 2010b) and gyrification of the cortex accompanies the cortical expansion, creating gyri and sulci. As early as the 23th gestational week, a leftward interhemispheric folding asymmetry can be observed at the Sylvian fissure site, which hosts the PT at its upper surface [START_REF] Habas | Early folding patterns and asymmetries of the normal human brain detected from in utero MRI[END_REF]. Moreover, at birth this asymmetry is as great as the asymmetry found in adults (Hill et al., 2010a). The right hemispheric counterpart is the asymmetry of the superior temporal sulcus (STS), which is observed as early as at the 26th gestational week; this rightward asymmetry in sulcal depth remains constant from birth throughout the lifespan [START_REF] Habas | Early folding patterns and asymmetries of the normal human brain detected from in utero MRI[END_REF][START_REF] Glasel | A robust cerebral asymmetry in the infant brain: the rightward superior temporal sulcus[END_REF][START_REF] Leroy | New human-specific brain landmark: The depth asymmetry of superior temporal sulcus[END_REF] . The early development of anatomical asymmetries contrasts with those of functional asymmetries that develop much later. Language areas' leftward functional asymmetries, for example, increase linearly with age but are still lower than adult values at 11 years of age (see review in [START_REF] Hervé | Revisiting human hemispheric specialization with neuroimaging[END_REF]. Anatomical asymmetries are the support of the setting up of lateralized functions such as language, but as upper mention the presence of major differences of sulcal positions across hemispheres makes the voxel/vertex between-hemisphere comparison of cortical thickness and cortical surface area difficult. The use of regions of interest also suffers from macroscopical hemispheric differences and whole brain accurate measures of anatomical asymmetries are still missing.

The first aim of this work was thus to define a method allowing to directly compare hemispheric anatomical features after sulcal alignment. Other source of confusion when aiming at defining anatomical asymmetries is the absence of knowledge of participant's hemispheric specialization. Because functional imaging is available only recently, numerous investigations of anatomical asymmetries in relation with hemispheric specialization have compared groups varying in handedness in the past. The second aim of the present study was thus to determine anatomical asymmetries in individuals typical for language and including lefthanders. Thanks to the BIL&GIN, the sample of typical left-handers was large enough to provide sufficient statistical power. Last question we tackled is that of the relationship between brain volume and hemispheric specialization. Actually several studies have shown an increase in asymmetries [START_REF] Hänggi | The hypothesis of neuronal interconnectivity as a function of brain size-a general organization principle of the human connectome[END_REF] and/or language lateralization [START_REF] Josse | Hemispheric specialization for language: Brain volume matters[END_REF], Tzourio-Mazoyer et al., 2010aand 2010b) in bulky brains. In the present work, we evaluated variation of anatomical asymmetries with increasing brain volume. To complete a comprehensive study of anatomical asymmetries we also investigated the spatial and quantitative relationships between cortical thickness and cortical surface area asymmetries.

METHODS AND VARIABLES TO EVALUATE ANATOMICAL ASYMMETRIES

Voxel-based morphometry (VBM) has been used to measure regional cerebral grey and white matter volume asymmetries in healthy adults [START_REF] Good | Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains[END_REF][START_REF] Watkins | Structural Asymmetries in the Human Brain :a Voxel-based Statistical Analysis of Collins 142 MRI Scans[END_REF][START_REF] Hervé | Handedness and cerebral anatomical asymmetries in young adult males[END_REF][START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF] and preterm newborns [START_REF] Dubois | Structural asymmetries of perisylvian regions in the preterm newborn[END_REF]. By studying 25 newborns from 26 to 36 weeks, Dubois et al. highlighted a deeper STS on the right side and larger posterior region of the perisylvian fissure on the left side [START_REF] Dubois | Structural asymmetries of perisylvian regions in the preterm newborn[END_REF]. Others studies in adults reported a rightward asymmetry for GM extending from prefrontal to temporoparietal regions and a leftward asymmetry in posterior brain regions. Concerning WM fractional anisotropy (FA) asymmetries, Takao et al. demonstrated leftward asymmetries of the cingulum, corticospinal tract and the arcuate fasciculus, this latter showing a significant positive correlation with the volume of the planum temporale [START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF] (Figure 33).

Results obtained with the VBM approach are very consistent and robust, but the lack of accurate correction for inter-hemispheric differences in sulci position results in asymmetries that are related to both differences in sulci position and tissue compartment volume differences without any possibility of disentangling these two components [START_REF] Lyttelton | An unbiased iterative group registration template for cortical surface analysis[END_REF]. Moreover, VBM analysis captures information about grey matter volume that is, by definition, the product of cortical surface area (CSA) and cortical thickness (CT) and so provides information on structural asymmetries that may be specific to a given anatomical feature.

Recent neuroimaging surface-based methods (SBM) allow the measurement of CSA and CT features independently and both at the local, regional and hemispheric levels. SBM studies have shown that although CSA and CT are both highly heritable, they seem to be unrelated genetically at the global, lobar and regional levels [START_REF] Panizzon | Distinct genetic influences on cortical surface area and cortical thickness[END_REF][START_REF] Winkler | Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies[END_REF][START_REF] Cai | A genome-wide search for quantitative trait loci affecting the cortical surface area and thickness of Heschl's gyrus[END_REF]. However, distinct sources of genetic influences do not imply an absence of phenotypic correlation, and Winkler et al. who investigated the correlation be-tween regional CSA and CT from a surfacebased parcellation, showed a strong correlation between CT and CSA in regions such as the frontal superior gyrus, the orbitofrontal cortex, the postcentral gyrus and the transverse temporal gyrus (also named Heschl's gyrus, HG). [START_REF] Hogstrom | The structure of the cerebral cortex across adult life: age-related patterns of surface area, thickness, and gyrification[END_REF] also examined the dynamic relationships between CSA and CT from a lifespan perspective. They observed that CSA and CT were negatively correlated in a pervertex general linear model that took into account the age and gender of the participants (Figure 34). By testing three age groups in adults, these investigators reported similar pat-terns of significant negative correlation between local CSA and Figure 33 -A [START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF]. [START_REF] Hogstrom | The structure of the cerebral cortex across adult life: age-related patterns of surface area, thickness, and gyrification[END_REF].

. Leftward volume asymmetry of the planum temporale (left) and leftward fractional anisotropy asymmetry of the arcuate fasciculus. B. Relationship between the grey matter volume of the planum temporale and fractional anisotropy of the arcuate fasciculus. The solid line indicates the major axis regression and the ellipse indicates the 95% bivariate normal ellipse. Adapted from

Figure 34 -Per-vertex relationships between cortical thickness and surface area covarying for age and gender. Adapted from

CT in areas including the orbitofrontal cortex, the posterior cingulate gyrus, the superior frontal gyrus, and parts of the temporal lobe bilaterally. These last results indicate that during aging there is an increase of local arealization associated with a decrease in CT in a set of regions that remains stable between 20 and 85 years of age. This anti-correlation pattern between CT and CSA suggests that a common neurophysiological mechanism drives this negative relationship.

Harasty has proposed that such a mechanism could be related to the expansion of white matter within a gyrus during development, such white matter increase leading to a local expansion of CSA and consequently to a mechanical thinning of the cortex [START_REF] Harasty | The left human speechprocessing cortex is thinner but longer than the right[END_REF]. Concerning correlations between asymmetries, previous studies have shown that CSA asymmetries of the PT were due to asymmetries of minicolumn width, spacing and number [START_REF] Galuske | Interhemispheric Asymmetries of the Modular Structure in Human Temporal Cortex[END_REF][START_REF] Chance | Minicolumnar structure in Heschl's gyrus and planum temporale: Asymmetries in relation to sex and callosal fiber number[END_REF]. Chance also reported leftward microstructural asymmetries in the mid-fusiform gyrus in terms of width of minicolumn and cell size, with larger pyramidal neurons in the left fusiform gyrus albeit without difference of cell density [START_REF] Chance | Hemispheric asymmetry in the fusiform gyrus distinguishes Homo sapiens from chimpanzees[END_REF]. Such differential pat-terns of hemispheric micro-organization could represent one mechanism supporting cortical thickness asymmetries. Other neurophysiological processes known to modulate cortical thickness during lifespan, such as synaptogenesis, spine formation or elimination, dendritic branching or pruning, angiogenesis, gliogenesis and myelination, could also be involved in the establishment of CT asymmetries [START_REF] Tardif | Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity[END_REF], the relative importance of these different factors being an open question.

CT and CSA asymmetry patterns have been investigated mainly with a regionsbased approach [START_REF] Chiarello | Structural asymmetry of anterior insula: behavioral correlates and individual differences[END_REF][START_REF] Chiarello | Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification[END_REF][START_REF] Meyer | Cortical Surface Area and Cortical Thickness Demonstrate Differential Structural Asymmetry in Auditory-Related Areas of the Human Cortex[END_REF][START_REF] Koelkebeck | The contribution of cortical thickness and surface area to gray matter asymmetries in the healthy human brain[END_REF][START_REF] Kang | Hemispheric asymmetries in cortical and subcortical anatomy[END_REF] using different cortical parcellations (i.e., either the Desikan or the Destrieux parcellation included with the FreeSurfer package: [START_REF] Desikan | An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest[END_REF][START_REF] Destrieux | Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature[END_REF]. By comparing Koelkebeck's and Chiarello's results, we can highlight some consistent profiles, for example with the leftward asymmetries of CSA in the postcentral gyrus and in the medial frontal gyrus, and the rightward asymmetries of CT in the inferior frontal gyrus, the middle temporal gyrus and the temporal pole but also some discrepancies with opposite pattern in the CSA asymmetry located in the paracentral lobule and in the inferior frontal gyrus (Figure 35). This approach, however, is limited in terms of spatial resolution in relation to the number and/or size of cortical regions explored.

To overcome this limitation, some studies have applied SBM combined with powerful cross-hemispheric structural registration tools for computing vertex-wise asymmetry maps of either CSA [START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF]Van Essen et al., 2012) or CT (Luders et al., 2006b;[START_REF] Plessen | Sex, age, and cognitive correlates of asymmetries in thickness of the cortical mantle across the life span[END_REF][START_REF] Shaw | Development of cortical asymmetry in typically developing children and its disruption in attention-deficit/hyperactivity disorder[END_REF][START_REF] Zhou | Cortical thickness asymmetry from childhood to older adulthood[END_REF]. [START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF] found that leftward asymmetry of CSA was focused in the supramarginal gyrus, planum temporale, anterior lateral temporal lobe and lateral orbitofrontal cortex, and rightward asymmetry was prominent in a band running around the anterior occipital lobe, in the cingulate and around the gyrus rectus (Figure 36A), mostly concordant with surface asymmetry map of Van Essen et al. (2012). Concerning CT asymmetries, the results are more discrepant with global pattern of leftward asymmetries in the anterior part of brain until the supramarginal gyrus, and rightward asymmetries in the posterior part including the posterior temporal lobe, the superior parietal lobule and the occipital area in the Plessen's study on 215 participants aged from 7 to 59 years of age. However, [START_REF] Zhou | Cortical thickness asymmetry from childhood to older adulthood[END_REF] reported significant leftward asymmetries of the superior parietal lobule and lateral occipital region, and rightward asymmetry of the inferior frontal gyrus (Figure 36B). Desikan's atlas and Bonferroni-corrected. In blue significant rightward asymmetries and in red significant leftward asymmetries.

Figure 35 -ROI-based asymmetries of cortical surface area (top row) and thickness (bottom row) from automatic parcellation provided by FreeSurfer. On the left, results from Chiarello's study using Destrieux's atlas and FDR corrected at p<0.05. Positive t-values indicate leftward asymmetries and negative t-values indicate rightward asymmetries. On the right, results from Koelkebeck's study using

To our knowledge, none of these studies have simultaneously investigated CSA and CT vertex-wise asymmetry maps or their relationships or in the same sample of participants. However, studies on how CT and CSA asymmetries are related to each other would be of great interest, especially for determining optimal brain phenotypes for studies of the genetic basis of brain lateralization [START_REF] Guadalupe | Asymmetry within and around the human planum temporale is sexually dimorphic and influenced by genes involved in steroid hormone receptor activity[END_REF] as well as for investigating the relationship between anatomical and functional lateralization (Tzourio-Mazoyer et al., 2015).

Here, we addressed this issue, taking advantage of the BIL&GIN [START_REF] Mazoyer | BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization[END_REF], a multidimensional, multimodal neuroimaging database specifically designed for the study of hemispheric lateralization in a large sample of individuals enriched in left-handers.

AIMS OF THE STUDY

We implemented a surface-based symmetrization procedure based on a fine interhemispheric structural registration across hemispheres to compute the spatial distribution of anatomical asymmetries of CT, CSA, CV and SULC at the vertex-wise level. The sample selected for the present study was composed of 250 participants of the BIL&GIN (120 left-handers), selected as typical from the results of an fMRI acquisition of language production [START_REF] Mazoyer | Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness[END_REF]. The use of such a large and homogenous sample allows us to report here the pattern of asymmetries of CT and CSA and the spatial and quantitative relationships between these asymmetries. This approach also allowed us to characterize the impact of handedness and brain volume on patterns of cortical asymmetry independently of language lateralization. FreeSurfer's processing provides automatic parcellations of the cortex (see Annexes -1.1.5) that had been used to investigate ROI based cortical asymmetries in terms of CT, CSA and CV [START_REF] Meyer | Cortical Surface Area and Cortical Thickness Demonstrate Differential Structural Asymmetry in Auditory-Related Areas of the Human Cortex[END_REF][START_REF] Goldberg | Hemispheric asymmetries of cortical volume in the human brain[END_REF][START_REF] Koelkebeck | The contribution of cortical thickness and surface area to gray matter asymmetries in the healthy human brain[END_REF][START_REF] Kang | Hemispheric asymmetries in cortical and subcortical anatomy[END_REF][START_REF] Chiarello | Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification[END_REF]. This automated approach enables comparisons between studies and across large-scale databases. Another objective of this chapter is to evaluate the reliability of using the parcellation of Destrieux [START_REF] Destrieux | Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature[END_REF] to compute anatomical asymmetries by taking advantage of the processing of flipped images from our database, and to compare with the vertexwise methodology to question the reproducibility of both methods and to evaluate the potential of using predefined ROI as marker of functional asymmetries. This chapter is the subject of a published article in Neuropsychologia special about the neural bases of hemispheric specialization (Maingault S, Tzourio-Mazoyer N, Mazoyer B, Crivello F (2016) Regional correlations between cortical thickness and surface area asymmetries: A surface-based morphometry study of 250 adults. Neuropsychologia. In press).

MATERIALS AND METHODS

PARTICIPANTS: CHARACTERISTICS OF THE TYPICAL SAMPLE

The sample of participants has been fully described elsewhere [START_REF] Mazoyer | BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization[END_REF]. Briefly, a sample of 250 healthy individuals, balanced for handedness and sex (130 RH, including 66 women; 120 LH, including 57 women) were included in the present study. A local ethics committee (CCPRB Basse-Normandie) approved the experimental protocol. Participants gave their informed, written consent, and received compensation for their participation in the study. All participants were free of brain abnormalities as assessed by inspection of their structural T1-MRI scans by a trained radiologist. The sample mean age was 25.5 years (S.D.=6.1 years, range: 18-57 years), and the sample mean level of education was 15.5 years ±2.3 years (range: 11-20 years) from elementary school. Handedness was self-reported by the subjects; their manual lateralization strength (MLS) was quantified using the Edinburgh inventory [START_REF] Oldfield | The assessment and analysis of handedness: the Edinburgh inventory[END_REF].

IMAGE ACQUISITION

From 2007 to 2011, cerebral structural images were acquired using the same 3 T Philips Achieva MRI scanner (Philips Medical Systems, Best, The Netherlands). The anatomical imaging protocol consisted of a localizer scan, a high-resolution 3D T1-weighted volume acquisition (IR-TFE sequence; TR or repetition time=20 ms; TE or echo time=4.6 ms; flip angle=10°; inversion time=800 ms; turbo field echo factor=65; sense factor=2; matrix size=256x256x180; 1 mm 3 isotropic voxel size), and a T2*-weighted multi-slice fast field echo (T2*-FFE; TR=3500 ms; TE=35 ms; flip angle=90°; sense factor=2; 70 axial slices; 2x2x2 mm 3 isotropic voxel size). Taskrelated functional images were acquired with a BOLD T2*-weigh-ted echo-planar sequence (T2*-EPI; 240 volumes; TR=2 s; TE=35 ms; flip angle=80°; 31 axial slices; 3.75x3.75x3.75 mm 3 isotropic voxel size) covering the same field of view as the T2*-FFE acquisition.

DEFINITION OF TYPICAL LATERALIZATION GROUP FOR LANGUAGE

We established the language lateralization using an index of asymmetry derived from functional MR maps contrasting covert production of sentences (SENT) to covert recitation of a list of overlearned words (list of the months of the year, LIST).

For each individual, we computed a Hemispheric Functional Lateralization Index (HFLI) using the LI-toolbox applied to the "SENT minus LIST" individual tmap. HFLI sample probability density function was modelled using a mixture of n Gaussian components and the optimal model was selected as having the lowest corrected Akaike's information criterion, an index that combines the goodness of fit with a penalty increasing with the number of model parameters. The optimal model, and corresponding optimal number of Gaussian functions (nopt), were then used for defining the different types of language hemispheric lateralization, using lower and upper HFLI thresholds best segregating the nopt Gaussian functions. The optimal fit was a mixture of 4 Gaussian functions with estimated means, variance and proportions equal to 67, 46, -4, and -63, respectively (Figure 37. The thresholds were then used for assigning each participant a language lateralization type based on his individual HFLI value. Typical individuals (leftward lateralized) were those belonging to the first two groups (n=250, HFLI>18), Ambilaterals corresponded to individuals with little lateralization (n=37, HFLI= [-50,18]) and Strong-atypicals to individuals strongly rightward-lateralized (n=10, HFLI<-50). Details on the methodology have been described in [START_REF] Mazoyer | Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness[END_REF]. 97

STRUCTURAL IMAGE PROCESSING

SURFACE-BASED PROCESSING

Reconstruction of cortical surfaces and measurement of anatomical variables were performed for each participant using the FreeSurfer 5.3.0 image analysis suite (http://surfer.nmr.mgh.harvard.edu/, [START_REF] Dale | Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction[END_REF]Fischl et al., 1999a;Fischl et al., 1999b;[START_REF] Fischl | Whole Brain Segmentation: Neurotechnique Automated Labeling of Neuroanatomical Structures in the human Brain[END_REF][START_REF] Fischl | Automatically Parcellating the Human Cerebral Cortex[END_REF][START_REF] Fischl | Measuring the thickness of the human cerebral cortex from magnetic resonance images[END_REF]. The FreeSurfer analysis includes intensity bias field removal optimized for the present 3 T acquisitions and skull stripping. In the native anatomical space of the subject, FreeSurfer constructs models of the cortical surface that can be represented as a mesh of triangles and tessellated into over 160,000 vertices for each hemisphere. The vertex positions are adjusted so that the surface follows the T1 intensity gradient between cortical white matter (WM) and cortical grey matter (GM). This highly folded surface, called "white surface", can be inflated to reveal the surface buried within the sulci. A second surface, called the "pial surface", is fit to the border between GM and CSF. The hemispheres are processed separately through an accurate definition of the inter-hemispheric fissure plane.

Difficulties in estimation of surfaces near the thin temporal lobe strands that border the tip of the lateral ventricle have been identified with the FreeSurfer segmentation procedure [START_REF] Dale | Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction[END_REF]. In such case, a reduction of intensity of voxels in the corresponding white matter leads to misclassification of voxels and inaccurate definition of white and pial surfaces. To overcome this limitation, we visually checked (SM) each of the pial and white surfaces on each axial, sagittal and coronal section of each participant twice and identified segmentation error in 48 cases (11%). A correction procedure consisting of manually adding an average of 9 control points (SD, 7) in the misclassified white matter was applied in these 48 cases. The automatic FreeSurfer segmentation procedure was then re-applied on these individuals, resulting in an accurate surface reconstruction after a novel round of quality control visual check.

For each vertex defining the surfaces, CT is defined as the distance between the white and pial surfaces, and CSA is defined as the average area of the triangles to which the vertex belongs. Cortical volume (CV) was computed as the CT CSA product. The sulcal depth parameter (SULC) is measured by integrating the dot product of the movement vector during inflation with the surface normal vector at each node. A cortical surface curvature (CURV) parameter is also extracted and used to drive the nonlinear surface-based intersubject registration. By integrating over all vertices of the cortical surface mean CT, total CSA and total CV are computed for each participant.

We finally computed individual global asymmetry index (AI) using the following formula:

VARAI=(VARLH-VARRH)/((VARLH+VARRH)/2), where VAR was either mean CT, total CSA, or total CV in the left hemisphere (LH) and right hemisphere (RH).

CROSS-HEMISPHERIC SULCAL REGISTRATION

FreeSurfer processes each hemisphere independently of the other and therefore constructs models of the cortical surface that differ between the two hemispheres, thus preventing direct left-right matching of these surface models (see Figure 38A).

To establish surface-based asymmetry maps, a precise alignment of vertices characterizing the left and right surfaces is therefore needed. To do this, we customized the symmetrization surface matching procedure proposed by [START_REF] Greve | A surface-based analysis of language lateralization and cortical asymmetry[END_REF] that is based on the removal of sulcal position asymmetries and the use of a symmetrical template.

Our implementation of this procedure begins with an initialization step that aims at minimizing the influence of the default symmetrical template provided by FreeSurfer (i.e., the "fsaverage_sym" surface-based template). First, the left hemisphere surfaces of a group of 8 participants balanced for sex and handedness were registered to the LH surface of the "fsaverage_sym" to create a first "LH_8 mean" surface. The same was done for the right hemisphere surfaces to generate a "RH_8 mean" surface. Then, both the LH and RH surfaces of another group of 40 subjects, also balanced for sex and handedness, were aligned to the initial "LH_8 mean" surface to create a "LH_80 mean" surface composed of a mixture of left and right hemispheres. These 80 surfaces (40 left and 40 right) were also registered to the "RH_8 mean" surfaces to generate an "RH_80 mean" surface that was also composed of a mixture of left and right hemispheres. Finally, an iterative process (N=20) was used to align these 80 surfaces to the "LH_80 mean" and "RH_80 mean" surfaces, respectively, to create final "LH_sym" and "RH_sym" sur-facebased templates. These final surface-based model representations were symmetric and free of sulcal morphology and position differences between the two hemispheres (see Figure 38B).

The left and right surfaces of the cerebral hemispheres of the 250 participants were then registered to the "LH_sym" surface-based templates, thereby producing individual CT, CSA, CV and SULC maps resampled to the "LH_sym". Again, the left and right surfaces of the 250 participants were also registered to the "RH_sym" surface-based templates, also producing individual CT, CSA, CV and SULC maps resampled to the "RH_sym". We added a Jacobian correction to the CSA and CV maps to account for stretching or compression during the surface-based registration [START_REF] Winkler | Measuring and comparing brain cortical surface area and other areal quantities[END_REF]. Note that this correction is not needed for CT and SULC maps because they are measured along a vector that is normal to the spatial deformation.

We then computed for each individual and for each variable (CT, CSA, CV, and SULC) two surface-based directional asymmetry index surface maps: a leftward asymmetry index surface map (L_AI) was obtained by mapping onto the "LH_sym" surface the positive values of (LH-RH)/mean(LH, RH) index for that variable, and a rightward asymmetry index surface map was obtained by mapping onto the "RH_sym" surface the negative values of the same index. These individual leftward and rightward AI maps were then surface-smoothed using a 10-mm FWHM Gaussian filter.

STATISTICAL ANALYSIS

HEMISPHERIC ANALYSIS

HEMISPHERIC ASYMMETRIES AND HANDEDNESS EFFECT ON

ASYMMETRIES

Statistical analyses performed with JMP Software (JMP 9.0 SAS Institute Inc.) were conducted separately on mean CT, total CSA and total CV AI's. We used the same ANCOVA design to investigate the effects of self-reported handedness and brain volume on cortical features, controlling for sex and age of the participants. The brain volume was automatically provided by FreeSurfer and corresponded to "estimated total intracranial volume" (eTIV). Pearson's correlation tests were performed to test the interrelationship between mean CT, total CSA and total CV as well as their asymmetry indexes.

VERTEX-WISE ANALYSIS

CT, CSA, CV AND SULC VERTEX-WISE ASYMMETRIES

A general linear model (one-sample group mean) was performed on the left and right hemisphere, respectively, to test the leftward and rightward CT, CSA, CV and SULC vertex-wise asymmetries, respectively, with a false discovery rate (FDR) threshold set at p<0.05 corrected for multiple comparisons and an additional cluster extension threshold of 100 mm 2 for reporting clusters.

HANDEDNESS EFFECT ON VERTEX-WISE ASYMMETRIES

Left-and right-handed participants were compared through 4 independent ANOVA with handedness as the main factor on CT, CSA, CV and SULC asymmetries. The statistical threshold was set at p<0.05 (FDR corrected). Based on the literature, which illustrates an effect of handedness on the anatomy of the central sulcus, we specifically focused our analysis on this area of interest.

BRAIN VOLUME EFFECT ON VERTEX-WISE ASYMMETRIES

Brain volume was directly estimated with the FreeSurfer software [START_REF] Buckner | A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume[END_REF]. A general linear model was run to test the effect of brain volume on CT, CSA, CV and SULC asymmetries. The statistical threshold was set at p<0.05 (FDR corrected).

CT AND CSA ASYMMETRIES RELATIONSHIP

Vertex-wise CT and CSA asymmetry maps allowed us to map overlapping sites of either concordant or opposite directional asymmetries for these two cortical features. Thirteen concordant sites corresponded to clusters exhibiting the same directional asymmetry for both CT and CSA (i.e., both leftward or both rightward), and 14 opposite sites corresponded to clusters with opposite directional asymmetry for CT and for CSA (i.e., one leftward and the other rightward). Within these clusters, individual CT and CSA asymmetry values were computed and their relationship investigated using a linear regression model. The same methodology was applied to clusters defined as the sites of overlap of CV asymmetries with either CSA or CT asymmetries. Maps and tables describing the results in these clusters are presented in the Figure 46, Table 16, Table 18, Table 17 andTable 19.

EVALUATION OF THE RELIABILITY OF AUTOMATIC PARCELLATION TO

COMPUTE ASYMMETRIES

PARTICIPANTS

For this analysis we considered the whole anatomical BIL&GIN database composed of 453 T1-weighted images [START_REF] Mazoyer | BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization[END_REF] with the same acquisition as it was described above.

STRUCTURAL IMAGES PROCESSING

We generated from these images their mirror by flipping them with the "fslswapdim" command and processed them in Freesurfer, leading to 2 datasets: nonflipped and flipped images. After the creation of cortical representations, all vertices were assigned neuroanatomical labels on a cortical surface model based on the automated labelling system, and the entire cortex of each hemisphere was parcellated into 74 brain regions [START_REF] Destrieux | Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature[END_REF].

Mean CT (in mm) and CSA (in mm 2 ) were calculated for each brain region for both hemispheres separately and for non-flipped and flipped images. We calculated the Laterality Index (LI) for CT and CSA of each brain region according to the formula of 2(left-right)/(left+right). To test the leftward or rightward asymmetry, we conducted one sample t-tests for LIs for each brain region. If the automatic parcellation is reliable, a significant asymmetry in non-flipped data will be in the opposite direction in the flipped data and also with the same effect size. To test this hypothesis, we also conducted a paired t-test to compare the means of a region based on non-flipped and flipped data. A good reliability is reflected by a non-significant pvalue. A significance level of P< 0.0007 (0.05/74 brain regions) was assumed due to Bonferroni corrections. All the results were compiled in the Table 22 andTable 21.

102

CT and CSA vertex-wise asymmetries were also computed for non-flipped and flipped data from the 453 participants by using the same threshold of p<10 -3 (less permissive than p<0.05 FDR corrected) (Figure 49 and Figure 50). We found no significant correlation between mean CT and total CSA values (R 2 =0.0003, p=0.80). This pattern was observed for both for left and right hemispheres (R 2 =2.10 _7 , p=0.99 and R 2 =0.0008, p=0.65, respectively). At the hemispheric level, we found rightward asymmetries for mean CT (AI=0.4%, p=0.002), total CSA (AI=0.1%, p=0.026), and total CV (AI=0.4%, p=0.002) (see Table 9).

RESULTS

HEMISPHERIC ASYMMETRIES

CT, CSA AND CV ASYMMETRIES

The asymmetry indexes of these two independent cortical phenotypes were also found to be independent at the hemispheric level, as illustrated by the absence of significant correlation between mean CT and total CSA AI's (R 2 =0.002, p=0.47) (see top of Figure 39). The CV being the direct product of the CT and the CSA, we logically found strong associations between total CV and mean CT (R 2 =0.22, p o 0.0001) and between total CV and total CSA (R 2 =0.78, p o 0.0001). The largest part of the CV variance is explained by the variance of the CSA. Interestingly, we also found a strong correlation between total CV and mean CT AI's (R 2 =0.74, po0.0001) and between total CV and total CSA AI's (R 2 =0.15, po0.0001) (see middle and bottom parts, respectively, of Figure 39). At the hemispheric level, the mean CT and total CSA AI's explained the major part of the total CV AI variance (R 2 =0.93), the largest portion being explained by the mean CT AI.

HANDEDNESS EFFECT ON ASYMMETRIES

Handedness has neither an effect on mean CT nor an effect on total CSA or total CV AI's (p=0.64, p=0.94 and p=0.87, respectively).

BRAIN VOLUME EFFECT ON ASYMMETRIES

Brain volume has also neither an effect on mean CT nor an effect on total CSA or total CV AI's (p=0.92, p=0.82 and p=0.92, respectively).

VERTEX-WISE ASYMMETRIES

CORTICAL THICKNESS ASYMMETRIES

In the frontal lobe, leftward asymmetries were seen along the precentral gyrus and the central sulcus (Figure 40A, Table 10). This large cluster extended to the parietal, temporal and occipital lobes. In the parietal lobe, the postcentral gyrus and sulcus, the angular gyrus, the supramarginal gyrus and the intraparietal sulcus were leftward asymmetrical. In the temporal lobe, a peak of leftward asymmetry located in the anterior part of the posterior third of the inferior temporal gyrus and ex-tending

Figure 40 -Vertex-wise analysis of anatomical asymmetries for CT (panel A), CSA (panel B), CV (panel C) and SULC (panel D).

The cortical asymmetries are displayed on inflated view of the symmetrical template. Light grey corresponds to gyri. Statistical threshold was set to 0.05 FDR corrected for multiple comparisons. Leftward asymmetries are displayed on the left hemisphere and rightward asymmetries on the right hemisphere. LH: left hemisphere, RH: right hemisphere.

104 dorsally through the middle temporal gyrus was significant. The temporal lobe also exhibited leftward asymmetries in the temporal pole, the transverse temporal sulcus and in the posterior part of the PT. Note that the entire fusiform gyrus showed significant leftward asymmetry. Finally, the insular cortex was left-ward asymmetrical in its anterior part and in the depth of the central sulcus.

Rightward asymmetries were located in the medial part of the frontal cortex extending to the most rostral part of the frontal gyrus, inside the superior frontal sulcus, in the gyrus rectus and along three-quarters of the cingulate cortex. Rightward asymmetries were also significant along the posterior border of the insula and in the pars opercularis and triangularis of the inferior frontal gyrus (IFG). Within the temporal lobe, rightward asymmetries were located in the anterior part of the PT, spreading towards the posterior border of HG and the middle part of the superior temporal gyrus and the STS. In the occipital lobe, rightward asymmetries of CT were also located in the lingual gyrus, in the depth of the calcarine fissure and in the cuneus

CORTICAL SURFACE AREA ASYMMETRIES

The frontal lobe showed leftward asymmetries located in the caudal part of the medial superior frontal region, the middle frontal gyrus, the middle part of the inferior frontal sulcus and in the pars orbitalis portion of the IFG extending to the anterior part of the insular cortex. A large cluster of leftward asymmetry of CSA covered the entire course of the central sulcus and the postcentral gyrus and sulcus extending to the supramarginal gyrus, the PT and planum parietale, and the HG (Figure 40B, Table 11). Another parietal cluster of leftward asymmetry was located in the precuneus. The temporal lobe exhibited leftward asymmetries in its anterior third, including the temporal pole, the anterior part of the fusiform gyrus and the parahippocampal gyrus. The occipital pole was leftward asymmetrical, with the same cluster of asymmetry extending to the posterior part of the fusiform gyrus.

SULCAL DEPTH ASYMMETRIES

Leftward SULC asymmetries were found in the anterior part of the circular sulcus of the insula and in the temporal pole (Figure 41B, Table 13). SULC rightward

HANDEDNESS EFFECT ON ASYMMETRIES

No clusters of differences between right-and left-handers were found after correction for multiple comparisons (p<0.05 FDR). Focusing on the central sulcus, a cortical area for which difference between right and left-handers have been evidence in the literature, we found a cluster of significant SULC difference (p=0.0019) at the level of the motor hand area, with a significant leftward asymmetry for right-handers (p=0.0154) and a significant rightward asymmetry for left-handers (p=0.0128), see Figure 42.

BRAIN VOLUME EFFECT ON VERTEX-WISE ASYMMETRIES

Brain volume had no significant effect on CT, CV and SULC asymmetries. By contrast, a significant correlation was found between brain volume and CSA asymmetries (Figure 43, Table 14). The inferior part of the anterior insula, the anterior part of the middle temporal gyrus, a cluster covering the medial part of PT, the planum parietale and the depth of the Sylvian fissure showed positive correlation between CSA asymmetries and brain volume. For the two latest regions, the larger the brain volume the larger is the leftward CSA asymmetry. The pericallosal sulcus also showed a positive correlation between CSA asymmetries and brain volume. On the contrary, the Rolandic operculum and the marginal branch of the cingulate sulcus exhibited negative correlation between CSA asymmetries and brain volume, revealing that the larger the brain volume, the larger the rightward CSA asymmetry.

RELATIONSHIP BETWEEN SULC ASYMMETRIES AND THE OTHERS ANATOMICAL FEATURES

All clusters showing significant SULC asymmetries were clusters with concordant directional asymmetries for CSA and CT asymmetries with the exception of the anterior insula cluster, which was leftward asymmetric for SULC and CSA and rightward asymmetric for CT.

CORTICAL SITES EXHIBITING CONCORDANT DIRECTIONAL ASYMMETRIES FOR CT AND CSA

We found multiple cortical sites with an overlap of significant and concordant directional asymmetries for CT and CSA (Figure 44). In the temporal lobe, concordant leftward asymmetry was located in the posterior part of the fusiform gyrus, including anteriorly its external part along the transverse collateral sulcus in the posterior part of the parahippocampal gyrus. Note that the left overlap covered the entire temporal pole.

In the parietal lobe, a concordant leftward asymmetry pattern overlapped along the postcentral gyrus and sulcus and in the anterior half of the supramarginal gyrus. A cluster of concordant leftward overlap was located in the most anterior part of the insular cortex. Note that there was no leftward overlap in the frontal lobe.

Concordant rightward asymmetries overlapped in the most rostral part of the superior frontal gyrus, including its medial part, and extended to the orbitofrontal cortex and gyrus rectus. An overlap was also present along the cingulate gyrus from the second half of its anterior part to its mid-part and extending upward in the depth of the paracentral sulcus. In the occipital region, consistent rightward asymmetries of CT and CSA were found all along the lingual gyrus and the calcarine fissure and in the posterior part of the cuneus gyrus. In the temporal lobe, the middle part of the STS was a site of rightward overlap of asymmetries. Lastly, note that the most posterior part of the insular cortex was rightward asymmetric for both CT and CSA.

CORTICAL SITES EXHIBITING OPPOSITE DIRECTIONAL ASYMMETRIES FOR CT AND CSA

Interestingly, some brain areas displayed an opposite pattern of asymmetries for CT and CSA (Figure 44). In the temporal lobe, this was true for the posterior part of the middle temporal gyrus and for the inferior temporal sulcus and STS extending posteriorly to the angular gyrus.

The insula displayed a peculiar pattern. Whereas the long insular gyrus was rightward asymmetrical for CSA but leftward asymmetrical for CT, the anterior part of the circular sulcus of the insula was leftward asymmetric for CSA and rightward asymmetric for CT. The same pattern was present in clusters located in the depth of the inferior frontal sulcus, in the middle frontal gyrus and in the caudal part of the medial frontal gyrus.

In the temporal lobe, HG, the PT and the middle part of the superior temporal gyrus were leftward asymmetric for CSA and rightward asymmetric for CT; this was also the case for the middle part of the inferior temporal gyrus. Note that small clusters located in the most rostral part of the anterior cingulate gyrus, in the precuneus and in the occipital pole exhibited the same pattern (Figure 44). Of the 27 clusters defined as sites of overlapping asymmetries (13 concordant and 14 opposite), significant correlation was observed in 12 clusters (5 concordant and 7 opposite; see Figure 45 and Table 15). By its very nature, the 7 clusters of opposite directional asymmetries presented negative correlation between CT and CSA asymmetries indicating that the larger the CT asymmetry in one direction, the larger the CSA asymmetry in the opposite direction. Two of the 5 clusters of concordant directional asymmetries presented also a negative correlation between CT and CSA asymmetries (the posterior fusiform gyrus and the anterior part of the insula). For these 2 clusters the larger the CSA asymmetry (respectively the CT asymmetry), the smaller is the CT asymmetry (respectively the CSA asymmetry). Finally, 3 remaining clusters of concordant directional asymmetries presented a significant positive correlation between CT and CSA asymmetries (a large cluster including the postcentral gyrus, the supramarginal gyrus and the PT, the STS and the mid-cingulate, see Figure 45 and Table 15). For these 3 positive correlations, the larger the CT asymmetry (leftward or rightward), the larger the CSA asymmetry in the same direction.

Figure 45 -Correlations between CT and CSA asymmetries in clusters of overlap.

Significant positive correlations were displayed in red and significant negative correlations were displayed in blue. The graphs showed the actual association between CT and CSA asymmetries in four clusters: the Heschl's gyrus (HG), the superior temporal sulcus (STS), the anterior insula and the fusiform gyrus. All clusters were displayed on the inflated external and internal views of the left hemisphere. Light grey corresponds to gyri.

EVALUATION OF THE RELIABILITY OF AUTOMATIC PARCELLATION TO COMPUTE ASYMMETRIES AND COMPARISON WITH VERTEX-WISE METHOD

REGION-OF-INTEREST ASYMMETRIES

CT

The Table 20 showed the LI for each region and the Figure 47 illustrated these data. Among the 74 cortical regions, 6 were symmetrical in both non-flipped and flipped data leaving 68 regions to discuss. 45/68 (i.e. 66%) regions changed the direction of their asymmetry value with the flipping of the images with 7 that were significantly equivalent (right column of the Table 20). Besides, 16/68 (i.e. 24%) were symmetrical in one case and significantly asymmetrical in the other, and 7 (i.e. 10%) kept the same direction despite the flipping of the images. -5.4 (9.3) <10 -4 2.0 (2.0) <10 -4 <10 -4 Anterior p. of the cingulate g. and s.

-8.5 (6.9) <10 -4 2.6 (1.7) <10 -4 <10 -4 Middle-anterior p. of the cingulate g. and s.

-8.2 (6.5) <10 -4 1.6 (1.7) <10 -4 <10 -4 Middle-posterior p. of the cingulate g. and s.

-3.1 (5.1) <10 -4 0.8 (1.3) <10 -4 <10 -4 Posterior-dorsal p. of the cingulate g.

-1.6 (4.9) <10 -4 0.6 (1.3) <10 -4 <10 -4 Posterior-ventral p. of the cingulate g.

-22.9 (13.5) <10 -4 -5.5 (3.5) <10 -4 Cuneus -1.3 (6. -3.0 (6.3) <10 -4 0.9 (1.5) <10 -4 <10 -4 Middle frontal s.

-8.0 (8.2) <10 -4 1.9 (2.1) <10 -4 <10 -4 Superior frontal s.

-4.0 (5. 2.4 (5.9) <10 -4 -0.3 (1.5) <10 -4 <10 -4 Anterior occipital s. and temporo-occipital incisure 1.4 (7.9) 0.0002 -1.1 (2.0) <10 -4 0.37 Lateral occipito-temporal s.

6.2 (8.7) <10 -4 -1.5 (2.1) <10 -4 <10 -4 Medial occipito-temporal s. and lingual s.

2.5 (5.1) <10 -4 -0.6 (1.3) <10 -4 <10 -4 Lateral orbital s.

-5.0 (15.1) <10 -4 1.4 (3.9) <10 -4 <10 -4 Medial orbital s.

-4.0 (11.6) <10 -4 1.4 (2.7) <10 -4 <10 -4 Orbital H-shaped s.

-3.3 (8.8) <10 -4 1.0 (2.1) <10 -4 <10 -4 Parieto-occipital s.

-0.1 (5.3) 0.60 -0.2 (1.3) 0.02

3.1.1.2 CSA
The Table 21 showed the LI for each region and the Figure 48 illustrated these data. Among the 74 cortical regions, 2 were symmetrical in both non-flipped and flipped data leaving 72 regions to discuss. 9/72 (i.e. 13%) regions changed the direction of their asymmetry value with the flipping of the images none that were significantly equivalent (right column of the Table 21). Besides, 13/72 (i.e. 24%) were symmetrical in one case and significantly asymmetrical in the other, and 30 (i.e. 42%) kept the same direction despite the flipping of the images.

Pericallosal s.

0.9 (14.7) 0.20 -1.3 (3.6) <10 -4 Postcentral s.

2.8 (5.8) <10 -4 -0.5 (1.4) <10 -4 Inferior part of the precentral s.

-1.0 (5.5) <10 -4 0.3 (1.4) <10 -4 0.0008 Superior part of the precentral s.

-0.7 (6.3) 0.03 0.2 (1.6) 0.001 Suborbital s.

-9.9 (17.3) <10 -4 1.8 (4.0) <10 -4 <10 -4 Subparietal s.

-2.0 (6.4) 19.5 (20.9) <10 -4 4.4 (5.2) <10 -4 Paracentral lobule and s. 10.7 (14.5) <10 -4 3.0 (3.6) <10 -4 Subcentral g. and s.

8.9 (14.5) <10 -4 3.8 (3.9) <10 -4 Transverse frontopolar g. and s.

-46.4 (18.5) <10 -4 -7.9 (4.5) <10 -4 Anterior p. of the cingulate g. and s.

-15.3 (10.0) <10 -4 -4.1 (2.3) <10 -4 Middle-anterior p. of the cingulate g. and s.

-8.1 (13.9) <10 -4 -2.2 (3.5) <10 -4 Middle-posterior p. of the cingulate g. and s.

-9.4 (12.7) <10 -4 -0.5 ( The Figure 49A and B illustrated vertex-wise CT asymmetries measured from non-flipped and flipped images of the same participants. The profile was very robust with reliable asymmetries in the overall cortex (Figure 49C) with 84% of perfect match (i.e. vertex-to-vertex). Some discrepancies were still visible: the anterior part Pericallosal s.

-34.4 (17.7) <10 -4 -7.4 (4.5) <10 -4 Postcentral s.

18.4 (15.2) <10 -4 1.2 (3.6) <10 -4 Inferior part of the precentral s.

-8.4 (18.9) <10 -4 -1.7 (4.8) <10 -4 Superior part of the precentral s.

-5.2 (21.8) <10 -4 -0.9 (5.5) 0.0003 Suborbital s.

63.1 (34.1) <10 -4 16.6 (8.1) <10 -4 Subparietal s.

-10.6 (20.5) <10 -4 -6.8 (5.1) <10 -4 Inferior temporal s. 9.5 (25.1) <10 -4 2.6 (6.4) <10 -4 Superior temporal s.

-7.5 (9. of the insula was leftward asymmetrical in both datasets and the posterior cingulate cortex showed a significant rightward asymmetry only in the flipped dataset. These non-reliable profiles were also revealed by the ROI-approach suggesting a nonimprovement of the method in these brains areas.

CSA

The Figure 50A and B illustrated vertex-wise CSA asymmetries measured from non-flipped and flipped images of the same participants. As for CT, the profile of local asymmetries was similar between both datasets with 72% of perfect vertex-wise overlap (Figure 50C). Some non-reliable asymmetries were reported in the central and posterior part of the insular cortex including the short gyrus, the central sulcus and the inferior part of the circular sulcus of the insula, and also in posterior cingulate gyrus.

DISCUSSION

We applied a surface-based symmetrization procedure; to demonstrate a robust vertex-wise pattern of CT, CSA, CV and SULC asymmetries in a large homogenous adult population. In addition we were able to identify cortical areas with significant associations between CT and CSA asymmetries. The description of these specific profiles of cortical asymmetries could potentially lead to the identification of hemispheric specialization structural markers, especially for the regions showing consistent directional patterns of asymmetry for both CT and CSA.

METHODOLOGICAL CONSIDERATIONS

One initial goal of the present study was to compute cortical grey matter asymmetries without introducing bias related to inter-hemispheric differences in sulcal positions. Of course, one of the main sources of cortical asymmetries is the gross morphological difference (the Yakovlevian torque, Toga and Thompson, 2003) and the position of the sulcal pattern across hemispheres as it had first been described for the Sylvian fissure [START_REF] Witelson | Sylvian Fissure Morphology and Asymmetry in Men and Women: Bilateral Differences in Relation to Handedness in Men[END_REF] or its posterior ascending ramus [START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF]. The characterization of these traits of structural asymmetries in adult is fundamental and have been well documented elsewhere [START_REF] Good | Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains[END_REF][START_REF] Watkins | Structural Asymmetries in the Human Brain :a Voxel-based Statistical Analysis of Collins 142 MRI Scans[END_REF][START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF][START_REF] Dorsaint-Pierre | Asymmetries of the planum temporale and Heschl's gyrus: relationship to language lateralization[END_REF][START_REF] Hervé | Handedness and cerebral anatomical asymmetries in young adult males[END_REF]. In the present study we chose to use a direct comparison between equivalent vertices by reducing positional sulcal differences between the two hemispheres. This symmetrization approach permits to distinguish the effects of structural translocation between left and right hemispheres and fine cortical asymmetries related to different anatomical variables (i.e. CT and CSA). Several surface-based approaches have been proposed for the alignment of vertices across hemispheres and for measuring vertex-wise asymmetries. [START_REF] Kang | Hemispheric asymmetries in cortical and subcortical anatomy[END_REF] used a method consisting in aligning left and right individual hemispheres by using a rigidbody spherical transformation in a spherical space. This latter procedure is equivalent to the one used in the present study with the exception of its starting point which consisted in registering two consistent and easily identified anatomical landmarks (the intersection of the superior temporal gyrus and the anterior Heschl's gyrus, and the bifurcation point on STG). Kang et al. method and the present one are difficult to compare because these authors used an ellipsoid flat map and Destrieux's parcellation for reporting CT and CSA asymmetry patterns while we analysed vertexwise asymmetries. Van Essen et al. ( 2012) also developed a surface-based symmetrization procedure using left-right hybrid target based on a landmark registration algorithm (the PALS-B12 atlas and 55 landmarks were used such as the central sulcus, the crown of the precentral gyrus or the circular sulcus of the insula) for computing vertex-wise asymmetries. With this semi-automated procedure they reported CSA asymmetries very close to the present ones, such as, for example, the leftward asymmetries of the Sylvian Fissure (parietal operculum and anterior to HG) and of the medial temporal cortex together with rightward asymmetries of the angular gyrus and of the medial prefrontal cortex. Comprehensive evaluation of the relative pro and cons of these different surface-based symmetrization procedures is The present study revealed no association between CT and total CSA AI's averaged over the whole hemispheres, indicating that the asymmetry indices of these two phenotypes are independent. However, vertex-wise analysis identified a set of 12 clusters where significant correlation between CT and CSA asymmetries were found. The spatial extent of these clusters corresponded to half of the spatial overlap occupied by both concordant and opposite clusters of CT and CSA directional asymmetries (49%), what represented less than 15% of the total number of vertices, thus explaining the absence of association at the hemispheric level.

Interestingly, the present analysis revealed a mixed pattern of correlation between CT and CSA asymmetries, the majority of them (64%) being positive. To some extent, this correlation pattern is consistent with patterns of correlation between CT and CSA asymmetries computed using cortical parcellation scheme [START_REF] Koelkebeck | The contribution of cortical thickness and surface area to gray matter asymmetries in the healthy human brain[END_REF][START_REF] Chiarello | Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification[END_REF] . For example, both studies evidenced, as we reported here, negative correlation in the fusiform gyrus, the insula and the superior frontal gyrus. The present study also highlighted a positive correlation between CT and CSA asymmetries in the cingulate cortex also found by Koelkebeck et al. (caudal anterior cingulate cortex and isthmus cingulate). Two additional clusters showing positive association between CT and CSA asymmetries were located in cortical areas with strong asymmetries appearing in utero. One was located in the PT, in which large and robust leftward asymmetries have been systematically evidenced whatever the methodology applied [START_REF] Shapleske | The planum temporale: a systematic, quantitative review of its structural, functional and clinical significance[END_REF], the other overlapped mid-STS, which strong rightward asymmetry was shown to be specific to humans [START_REF] Leroy | New human-specific brain landmark: The depth asymmetry of superior temporal sulcus[END_REF]. Interestingly, Chiarello et al. applying the Destrieux parcellation reported only one positive correlation between CT and CSA asymmetries located in the postcentral gyrus as in the present study where a large cluster of positive correlation overlapped the postcentral gyrus. Notably, this cluster extended to the supramarginal gyrus, a region that exhibited negative correlation in Chiarello's study. This potential discrepancy may come from differences in spatial resolution of the analysis performed in the two studies. The present vertex-wise analysis did not rely on anatomical a priori allowing to highlight opposite asymmetries in an area belonging to the same region in the Destrieux atlas (for example the PT or the STS). Another difference between the Chiarello study and the present one rely on the amount of negative correlations between CT and CSA asymmetries. While Chiarello et al. exclusively reported negative correlations, with the exception of the postcentral gyrus, we found approximately only one third of correlations to be negative. This is likely because in the present study we computed correlations between CT and CSA only in clusters showing both significant asymmetries for CT or CSA and concordant or opposite asymmetries. Applying these two criteria reduce the research territory to 30% total cortical surface. For example, the present analysis did not allow us to to have different positions and shapes in the left and the right hemispheres (Figure 38) [START_REF] Witelson | Sylvian Fissure Morphology and Asymmetry in Men and Women: Bilateral Differences in Relation to Handedness in Men[END_REF][START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF]. However, a significant but small cluster of leftward SULC asymmetry (42 mm 2 ) was evidenced, located near the PT, a location consistent with that reported by (Hill et al., 2010a).

Although SBM controls for sulcal position differences, the CSA asymmetry profile was the most comparable with VBM asymmetries around the perisylvian cortex. In particular, the important leftward asymmetry observed in the vicinity of the PT and supramarginal gyrus is in accordance with VBM studies [START_REF] Watkins | Structural Asymmetries in the Human Brain :a Voxel-based Statistical Analysis of Collins 142 MRI Scans[END_REF][START_REF] Good | Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains[END_REF][START_REF] Hervé | Handedness and cerebral anatomical asymmetries in young adult males[END_REF][START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF][START_REF] Glasel | A robust cerebral asymmetry in the infant brain: the rightward superior temporal sulcus[END_REF] as well as with reports using other surface based-methods [START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF][START_REF] Van Essen | Cortical cartography and Caret software[END_REF]. Importantly, the present results highlight that the leftward CSA asymmetry of the anterior PT and HG is associated with a rightward CT asymmetry, as has been previously shown for HG [START_REF] Meyer | Cortical Surface Area and Cortical Thickness Demonstrate Differential Structural Asymmetry in Auditory-Related Areas of the Human Cortex[END_REF]; this asymmetry is opposite to the leftward CT asymmetry of the posterior part of the PT. This anteroposterior dichotomy in asymmetry supports the existence of functionally distinct regions of the PT for auditory spatial perception (anterior part) and sensory-motor integration (posterior part) as postulated by [START_REF] Isenberg | Functionally distinct regions for spatial processing and sensory motor integration in the planum temporale[END_REF] in their study combining fMRI and DTI analyses. These authors showed that activation related to auditory motion was observed in anterior regions of the left PT, whereas activation during covert repetition of pseudowords (versus listening to pseudowords) was located in posterior regions of the left PT. Such a functional dichotomy is consistent with the differences in white matter connectivity of the anterior and posterior parts of the PT. Indeed, [START_REF] Isenberg | Functionally distinct regions for spatial processing and sensory motor integration in the planum temporale[END_REF] have also shown that the anterior and medial part of the PT exhibits projections through ventral portions of the superior longitudinal fasciculus (SLF), while the posterior PT projects more dorsally through the SLF. The significant rightward depth asymmetry of the middle part of the STS is consistent with [START_REF] Leroy | New human-specific brain landmark: The depth asymmetry of superior temporal sulcus[END_REF] report (Figure 52). In that study, the authors used the BrainVISA Morphologist pipeline to extract STS and discovered in this way a human-specific asymmetry that they named the 'superior temporal asymmetrical pit' (STAP); this asymmetry is visible in foetuses and across the lifespan. Interestingly, as mentioned above, the present results evidenced concordant rightward asymmetries of CT and CSA localized in the STS and showing positive correlation resulting in a rightward asymmetry of STS volume.

ANATOMICAL ASYMMETRIES OF THE VENTRAL PATHWAY

The present results also highlighted a strong leftward asymmetry along the ventral pathway that includes the ventral occipitotemporal cortex (or fusiform gyrus) and more specifically the visual word form area (VWFA) responsible for the identification of written words [START_REF] Cohen | The visual word form area Spatial and temporal characterization of an initial stage of reading in normal subjects and posterior split-brain patients[END_REF][START_REF] Cohen | Specialization within the ventral stream: the case for the visual word form area[END_REF]. Importantly, while this leftward asymmetry was significant for both CT and CSA where they overlapped, these two anatomical variables were negatively correlated, meaning that the stronger the leftward CSA asymmetry, the weaker the leftward CT asymmetry. This raises an important issue concerning the physiological meaning of this negative association between CT and CSA asymmetries and calls for further investigations in relation to reading development, performance and/or pathologies as well as for longitudinal studies to address whether this relationship is dynamic and plastic or whether it is acquired. A previous study by [START_REF] Ma | Cortical thickness abnormalities associated with dyslexia, independent of remediation status[END_REF] detected Figure 52 -A [START_REF] Leroy | New human-specific brain landmark: The depth asymmetry of superior temporal sulcus[END_REF] increased CT in the left fusiform gyrus of dyslexic children in a cluster that contains the VWFA, suggesting that a thicker cortex can be associated with altered cortical processing (here of the ventral reading pathway, [START_REF] Ma | Cortical thickness abnormalities associated with dyslexia, independent of remediation status[END_REF]). Moreover, left fusiform CT was positively correlated with performance in several reading tasks. The methodology using a vertex-wise approach evidenced a cluster in the posterior part of the fusiform gyrus that overlapped one of the present sites showing concordant leftward asymmetry of CT and CSA [START_REF] Zhang | The contribution of the left mid-fusiform cortical thickness to Chinese and English reading in a large Chinese sample[END_REF].

. Location of the STAP (yellow) relative to Heschl's gyrus (blue) and the ventral tip of the central sulcus (green) on both left and right inner cortical surfaces of an individual adult brain. B. Sulcal depth shown by colour coding of the sulcal mesh (upper), and sulcal depth profile in the right hemisphere of an individual subject (lower). C. Adult sulcal depth profile. The light orange overlay illustrates the STAP (deeper on the right). Adapted from

ANATOMICAL ASYMMETRIES OF THE INSULAR CORTEX

As for STS, the sulcal alignment showed that the anterior segment of the circular sulcus was deeper in the left hemisphere, whereas the inferior segment was deeper in the right hemisphere; this latter asymmetry was detected as early as 2 years of age [START_REF] Li | Mapping Longitudinal Hemispheric Structural Asymmetries of the Human Cerebral Cortex From Birth to 2 Years of Age[END_REF]. This sulcal asymmetry detected at 2 years of age appears thus to persist in adulthood, as highlighted by the present study. The insular cortex showed a profile of asymmetry consistent with that of sulcal depth for CSA and CT, with a large leftward asymmetry of CT in the first anterior two-thirds of the insula and extending to the insular central sulcus and a rightward asymmetry located in the depth of the inferior part of the circular sulcus. The present pattern is consistent with results obtained with a com-parable surface-based approach [START_REF] Chiarello | Structural asymmetry of anterior insula: behavioral correlates and individual differences[END_REF][START_REF] Lyttelton | Positional and surface area asymmetry of the human cerebral cortex[END_REF]. Such anterior insular leftward asymmetry, evidenced through CSA measurements as well as with voxel-based analyses in adults (Hervé et al., 2006;[START_REF] Takao | Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel-based morphometry and diffusion tensor imaging study[END_REF], is present at birth and increases with age [START_REF] Li | Mapping Longitudinal Hemispheric Structural Asymmetries of the Human Cerebral Cortex From Birth to 2 Years of Age[END_REF][START_REF] Dubois | Structural asymmetries of perisylvian regions in the preterm newborn[END_REF]. The present results show, in addition, that the left anterior insular cortex is not only larger in area but also thicker, with the exact opposite pattern in the posterior insula. Such a difference in anatomical asymmetries is likely to support differences in functional processing. Support of this hypothesis can be found in Chiarello's report of a positive association between the CSA asymmetry located in the anterior part of the insula and lateralization of word reading measured with divided fields [START_REF] Chiarello | Structural asymmetry of anterior insula: behavioral correlates and individual differences[END_REF]. By using multimodal imaging, Kelly et al. highlighted a clear antero-posterior parcellation of the insular lobe in both hemispheres. Their work was based on a meta-analysis of task-induced activations (2000 articles), on results obtained with intrinsic functional connectivity and also by the investigation of the structural covariance of grey matter volume. In their work, applying a high-resolution clustering they highlighted that the most anterior part of the right insular cortex is preferentially activated during language tasks [START_REF] Kelly | A convergent functional architecture of the insula emerges across imaging modalities[END_REF]. Two recent studies showed opposite results with a leftward the functional recruitment of the insula in association with left-hemisphere language dominance [START_REF] Oh | The role of the insula in speech and language processing[END_REF][START_REF] Zaccarella | Reflections of word processing in the insular cortex: a sub-regional parcellation based functional assessment[END_REF]. In the view of these elements, the relationship between local structural asymmetry and functional activation appears not to be straight-forward, even in the case of language, a strongly lateralized function.

Anteroposterior differential increases in insular volume have been reported to occur over the course of evolution. Investigating 30 primate species, Bauernfeind et al. showed a positive allometric relationship between total brain volume and left insular volume, thereby showing that an increase in primate brain size is associated with a proportionally larger increase in insular cortex volume. Notably, this differential rate of increase is larger for the anterior portions of the insular cortex [START_REF] Bauernfeind | A volumetric comparison of the insular cortex and its subregions in primates[END_REF]; this can be taken as an indication that the anterior insula is associated with human speciation. In relation to the present work, the same authors evidenced in 3 (of 5) human brains a very strong leftward asymmetry of the frontoinsular cortical cytoarchitecture in the most ventral anterior part of the agranular insular cortex. They speculated on a possible contribution of this human-specific hemispheric difference to the control of breathing during speech vocalization [START_REF] Ackermann | The contribution(s) of the insula to speech production: a review of the clinical and functional imaging literature[END_REF]. This is in accordance with the functional role of the left anterior insula as documented in healthy participants using functional imaging [START_REF] Oh | The role of the insula in speech and language processing[END_REF].

HANDEDNESS AND ANATOMICAL ASYMMETRIES

The present analysis shows an absence of handedness-related differences in anatomical asymmetries of CT, CSA, CV and SULC. Given that of the 250 individuals 120 were left-handers, the absence of difference is not due to lack of statistical power. Using an automatic cortical parcellation, (Guadalupe et al., 2014a) failed to find any regional differences in surface area asymmetries between 106 left-handers and 1960 right-handers; they found only a slight significant association with the superior precentral sulcus and the inferior temporal gyrus with reduced cortical surface for left-handers.

Among the results obtained from anatomical comparisons with VBM of right and left-handers, differences at the level of the Rolandic genu, hosting the hand motor cortex, have been consistently observed. We searched in this brain region to determine whether differences in CT, CSA, CV and/or SULC could be observed when lowering the threshold. The only cluster of difference be-tween right-and lefthanders was located in motor areas, more precisely at the level of the Rolando's genu area, with a significant leftward asymmetry of SULC in right-handers and a significant rightward asymmetry in left-handers. Amunts et al. showed that the left central sulcus is deeper than the right in 31 right-handers and vice-versa in lefthanders (n=14) with an equivalent asymmetry profile in neuropil volume in Brodmann's area 4, corresponding to the primary motor cortex [START_REF] Amunts | Asymmetry in the human motor cortex and handedness[END_REF]. VBM analysis of balanced groups of right-handers and left-handers also revealed significant clusters of asymmetry differences in the pre-central and central sulci, with greater leftward asymmetries for right-handers [START_REF] Hervé | Handedness and cerebral anatomical asymmetries in young adult males[END_REF]. By considering the macroscopic shape of the central sulcus, Sun et al. showed a handedness effect on the morphology and the localization of the Rolando's genu area or "hand-knob" [START_REF] Sun | The effect of handedness on the shape of the central sulcus[END_REF] that had been initially identified by [START_REF] Rumeau | Location of Hand Function in the Sensorimotor Cortex: MR and Functional Correlation[END_REF] based on combined magnetic resonance imaging and positron emission tomography. Moreover, handed-ness can also be viewed as a quantitative trait that can be measured using manual preference (MP) score. In order to test whether differences in MP strength were associated with differences in anatomical asymmetries, McDowell et al. compared consistent right-and left-handers, meaning individuals using exclusively their preferred hand for performing 5 unimanual movements, to participants with weaker MP (164 participants, 4 left-handers, (McDowell et al., 2015). By using an automatic parcellation [START_REF] Destrieux | Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature[END_REF], they found larger local gyrification index in the precentral gyrus, the central sulcus and the postcentral gyrus and sulcus of consistent right-handers [START_REF] Mcdowell | Neurostructural correlates of consistent and weak handedness[END_REF]. Their results are thus in agreement with those of the present study in terms of localization of the sulcal depth variation. However, the respective effect of the side and of the strength of manual preference still have to be disentangled.

Finally, the present study, including only individuals having a typical leftward language lateralization, showed no effect of handedness on hemispheric and regional asymmetries of CSA and CT. This is consistent with our previous report of identical profiles of regional functional asymmetries in typical right-and left-handed individuals language production areas [START_REF] Mazoyer | Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness[END_REF]. These observations suggest that in typical individuals there is neither anatomical nor functional differences in language production areas with handedness, meaning an absence of impact of handedness on the neural support of language.

BRAIN VOLUME AND ANATOMICAL ASYMMETRIES

Our results demonstrate that brain volume modulates local CSA asymmetries, with larger leftward or rightward asymmetries being associated with larger brain volume. This observation sup-ports Ringo's theory of a relationship between brain volume and lateralization of brain functions when there is a temporal pressure on the task to be completed: the larger the brain, the larger the intra-hemispheric clustering of the functional areas supporting a given function [START_REF] Ringo | Time is the essence: a conjecture that hemispheric specialization arises from interhemispheric conduction delay[END_REF]. In support of Ringo's theory, Hänggi et al. showed that structural intra-hemispheric connectivity measured with diffusion tensor imaging and tractography was stronger in larger brains, in line with the idea that such an organization compensates for increased conduction delays in transcallosal information transfer in bulky brains [START_REF] Hänggi | The hypothesis of neuronal interconnectivity as a function of brain size-a general organization principle of the human connectome[END_REF]. The present analysis can also be considered as supporting Ringo's model since the increase in leftward asymmetry we re-ported is located in the posterior part of the Sylvian fissure hosting the PT involved in speech processing and in the ant-STS that hosts the human voice area [START_REF] Belin | Voice-selective areas in human auditory cortex[END_REF]. Note that the present results are also consistent with previous reports from our laboratory showing positive correlation between brain volume and left PT surface (Tzourio-Mazoyer et al., 2010b), as well as between skull perimeter and leftward functional asymmetries of speech processing areas (Tzourio-Mazoyer et al., 2010a).

BETTER RELIABILITY OF VERTEX-WISE ASYMMETRIES THAN AUTOMATIC PARCELLATED ROI

This study showed that asymmetries calculated from automated parcellation of Destrieux provided by FreeSurfer were not reliable, especially for CSA asymmetries. Indeed, the flipping of the image didn't imply the flipping of the asymmetries, a problem that was solved by the vertex-wise analysis, except in the insula and the cingulate gyrus. Destrieux et al. evaluated the concordance between their automated labeling and a manual segmentation. They found about 85% for both hemispheres with noteworthy differences between structures. Indeed, lower concordance index (CI) values were found for variable/inconstant structures (anterior occipital sulcus, sulcus intermedius primus, suborbital sulcus), for structures without clear landmarks (subcallosal area), and for sulci not deep enough to be correctly and constantly recognized (subcentral and paracentral sulci, central sulcus of the insula) [START_REF] Destrieux | Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature[END_REF]. Besides, the orbital part of the inferior frontal gyrus showed the lowest CI, about 30% in the left hemisphere. This lack of concordance could be responsible of some inconsistencies in asymmetry measurement. Considering that the biases were leading by the regional asymmetries in the atlas used for the parcellation, they were similar in all participants. This equivalent image processing made possible to compare a population relatively to another (for example right-handers vs. lefthanders) but impossible to discuss about the absolute direction of the asymmetries that were too atlas-dependent.

The ROI-approach is a good to localize the clusters or the activation during a task but it is less reproducible to delineate precise regions, more specifically when they display high interindividual variability. This methodological limit of automatic parcellation in FreeSurfer to measure regional feature requires the using of more sensitive advanced technique to define cortical parcels with less biases as possible, such as a cortical parameterization method developed by Auzias et al. exploiting a set of primary and secondary sulci to create an orthogonal coordinate system on the cortical surface [START_REF] Auzias | MarsAtlas: A cortical parcellation atlas for functional mapping[END_REF].

Besides, the ROI-approach prevents for highlighting different patterns of asymmetry in a given ROI, decreasing the spatial resolution in comparison to vertexwise methodology. For example, the PT showed opposite asymmetry of CT in its posterior and anterior part.

CONCLUSION AND PERSPECTIVES

Cortical asymmetries, which represent a fundamental element of brain structural organization, can be characterized according to cortical thickness and cortical surface area. The results of the present work support the idea that cortical asymmetries are characterized by a regional pattern of concordant and opposite cluster sites of directional cortical thickness and cortical surface area asymmetries. Half of the regions showing a spatial overlap of cortical thickness and cortical surface area asymmetries presented an association between cortical thickness and cortical surface area asymmetries that was characterized by both positive and negative correlation. Strikingly, regions showing positive correlations between cortical thickness and cortical surface area asymmetries were those known to exhibit robust asymmetries across the lifespan, such as the leftward asymmetrical planum temporale and the rightward asymmetrical superior temporal sulcus. This study demonstrates that cortical thickness and cortical surface area asymmetries combine to produce specific patterns of brain structural organization. This specific pattern varied with brain volume confirming that brain volume acts mechanically and increases brain lateralization. Importantly, typical left-handers did not show any difference in hemispheric asymmetries except in the motor hand representation that had a reversal of sulcal depth asymmetry.

Besides, this work led to the development of a vertex-wise approach to characterize cortical asymmetries that proved to be more robust than the regional asymmetries obtained from automated parcellation performed in FreeSurfer.

One of the perspectives of this work is to use these accurate structural lateralization phenotypes assessed by exploratory surface-based approach as candidate markers of language lateralization. Indeed, this development will be part of the Multi-level Integrative Analysis of Brain Lateralization for Language (MULTI-LATERAL) project funding by FLAG-ERA JTC call that is setting up to contribute to the construction of the Human Brain Project Flagship project, and aims to identify the anatomical, functional and genetic determinants of brain lateralization for language.

The present thesis work, conducted in the Groupe d'Imagerie Neurofonctionelle, investigated the complexity of the healthy human adult brain cerebral anatomy through the conjoint characterization of key features of its organization, namely cortical thickness, cortical surface area, sulcal depth and intracortical myelin. These researches were performed thanks to the conjoint use of automated and robust techniques devoted to surface-based cortical analysis, the measure of multimodal structural characteristics applied to the BIL&GIN: a multimodal database of 453 participants. We investigated, 1-the loco-regional impact on the structure of the cortex of the gyrification variability of Heschl's gyri; 2the cortex changes induced by late maturation during early-adulthood and 3-the cortical structural differences between hemispheres.

The results obtained in these three studies revealed the advantage of using multimodal anatomical variables to uncover regional markers of subtle anatomical modifications resulting from changes in gyrification, late maturation and hemispheric asymmetries and their phenotypic correlation.

The quantification of relationships between the different surface-based morphological measures is a lead to identify structural lateralization brain markers, and this generic approach will serve the Multi-level Integrative Analysis of Brain Lateralization for Language (MULTI-LATERAL) project funding by European FLAG-ERA JTC call that aims at uncovering the anatomical, functional and genetic determinants of brain lateralization for language.

During this thesis, I have implemented automatic and robust approaches for the extraction and quantification of multimodal cortical anatomical variables. These procedures will be directly applied to the analysis of the wide corpus of imaging cohort (several thousand of participants) the GIN carries on its research projects: BIL&GIN (http://www.gin.cnrs.fr/BILandGIN), I-Share (http://www.i-share.fr/), UK-Biobank (http://www.ukbiobank.ac.uk/).

ANNEXES 1 SURFACE-BASED MORPHOMETRY WITH FREESURFER SOFTWARE

FreeSurfer is a suite of tools for the analysis of neuroimaging data that provides an array of algorithms to quantify the structural properties of the human brain. Note that the command lines and the outputs created by the processing of the data are in italic and between quotes.

PREPROCESSING OF T1W IMAGES

First, the image dimensions are changed to 256 x 256 x 256 voxels and the original T1w volume is registered to MNI305atlas (standard space) with an affine transformation ("orig.mgz", Figure 53A).

BIAS FIELD CORRECTION

A MRI varies in both intensity and contrast across the 3D images. This spatial intensity inhomogeneity is called the bias field effect. The presence of this artefact may adversely affect qualitative and quantitative image analysis. It is proportional to the scanners field strength and is caused by the radio frequency field inhomogeneities. Due to the bias fields effect, intra-class homogeneity cannot be assumed and accordingly identical tissue types will vary in intensities as a function of their spatial location. This is an undesirable condition for any segmentation method, where intensity information is used to classify voxels into different tissue types. The bias field effect is unique for each subject, which makes it challenging to correct it. Freesurfer uses the non-parametric non-uniform intensity normalization [START_REF] Sled | A nonparametric method for automatic correction of intensity nonuniformity in MRI data[END_REF], to correct for the bias field effect. This approach iterates between three main steps: histogram sharpening, bias field estimation (based on the obtained sharpened histogram) and B-spline smoothing. This normalization contains several adjustable parameters, such as smoothing distance, that is the distance between Bspline nodes. A recent study demonstrates the benefit of reducing this parameter to 50 mm for images acquired on 3T scanner, instead of the default value of 200 mm reported in the princeps paper and incorporated into FreeSurfer preprocessing [START_REF] Zheng | Improvement of brain segmentation accuracy by optimizing non-uniformity correction using N3[END_REF]. This method makes the tissue intensity more uniform in the effort to improve segmentation but the potential interesting differences in white matter intensity caused by biological factors may be inadvertently altered [START_REF] Van Walderveen | Multislice T1 relaxation time measurements in the brain using IR-EPI: reproducibility, normal values, and histogram analysis in patients with multiple sclerosis[END_REF]. So for the preprocessing of the database we added the "-3T" argument in the command line ("recon-all"). Corrected volumes are stored in "nu.mgz" (Figure 53B).

INTENSITY NORMALIZATION

The next step consists in an intensity normalization of the original volume. The results are stored in "T1.mgz" (Figure 53C). Intensities for all voxels are scaled so that the mean intensity of the white matter is 110. by moving each vertex in the tessellation of the inflated surface to the closest point on the sphere based on surface normal vector (Figure 55D). It allows the preservation of the topological structure of the original surface, i.e. the local connectivity (in contrast to the use of a flattened surface) and facilitates the calculation of metric properties, more difficult to compute on less symmetric surfaces such as ellipsoid. This spherical representation is used for the registration procedure developed in the next paragraph.

FreeSurfer provides an automatic parcellation of cortical ribbon in neuroanatomical labels into the individual space. Different atlases are available (Figure 56): Desikan-Killiany atlas with 33 gyral-based regions (lh.aparc.annot, [START_REF] Desikan | An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest[END_REF]), DKT atlas with 31 gyral-based regions (lh.aparc.DKTatlas40.annot, [START_REF] Klein | 101 labeled brain images and a consistent human cortical labeling protocol[END_REF]) and Destrieux atlas with 74 sulcal and gyral regions (lh.aparc.a2009s.annot, [START_REF] Destrieux | Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature[END_REF]). The software also provides more specific parcellations such as the segmentation of hippocampal subfields (Iglesias et al., 2015) or atlases built from intrinsic functional connectivity for the cortex [START_REF] Yeo | The organization of the human cerebral cortex estimated by intrinsic functional connectivity[END_REF], the cerebellum [START_REF] Buckner | The organization of the human cerebellum estimated by intrinsic functional connectivity[END_REF] and the striatum [START_REF] Choi | The organization of the human striatum estimated by intrinsic functional connectivity[END_REF]. It consists in a non-linear mapping of a surface atlas drawn from initial manual segmentation (probabilistic average from many brains) to the target surface [START_REF] Fischl | Automatically Parcellating the Human Cerebral Cortex[END_REF]. registering brains to the template to improve the registration procedure [START_REF] Klein | Evaluation of volume-based and surface-based brain image registration methods[END_REF]. Considering our population is composed of healthy participants, we decided to create a template from 40 subjects of our database with the procedure described in the former paragraph and detailed in the Chapter 1, 2.3.6 Definition of a specific template for between-subject registration and smoothing, p.39.

THE BIL&GIN DATABASE

The BIL&GIN (for Brain Imaging of Lateralization by the Groupe d'Imagerie Fonctionelle) database has been designed for investigating the cognitive, behavioral, genetic, and brain morphological/functional correlates of hemispheric specialization [START_REF] Mazoyer | BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization[END_REF], which is a fundamental characteristic of brain large-scale organization [START_REF] Hervé | Revisiting human hemispheric specialization with neuroimaging[END_REF].

The database contains records from a sample of 453 adults participants enriched in left-handers (45%, N = 205) as compared to the general population.

For each subject, socio-demographic data (sex, age, level of education), behavioral laterality measures and cognitive skills have been recorded.

BEHAVIORAL LATERALITY MEASURES

SELF REPORTED HANDEDNESS

Participants were asked whether they considered themselves as either righthanded, left-handed, or forced left-handed. Among the 453 participants, 248 considered themselves as right-handers (116 men and 132 women) and 199 as lefthanders (104 men and 95 women) and 6 as converted right-handers (1 man, 5 women), the latter being pooled with the other left-handers unless otherwise specified.

MANUAL PREFERENCE STRENGTH

Manual preference strength was evaluated using the Edinburgh inventory score [START_REF] Oldfield | The assessment and analysis of handedness: the Edinburgh inventory[END_REF] with the broom item discarded.

MANUAL SKILL

The finger-tapping test was used for assessing manual skill.

EYE PREFERENCE

Eye sighting dominance (ESD) evaluated by having the participants extending his arms in front of him, forming a frame using the thumb and index finger of both hands, and looking at a distant object through this frame without moving hands, first with both eyes open, then when shutting the left or the right eye. The ESD was that for which the object is perceived at the same place in the frame as with two eyes.

FAMILIAL SINISTRALITY

Positive familial sinistrality was defined as the presence of at least one lefthanders individual among participant's first-degree relatives.

COGNITIVE SKILLS

Participant abilities were also evaluated in the language (10 tests), visuo-spatial (5 tests), and arithmetic domains (4 tests) (see Table 23 for the detail of tests).

STRUCTURAL MRI

The acquisition protocol included a high resolution 3D T1w sequence (3D-FFE-TFE; TR = 20 ms; TE = 4.6 ms; flip angle = 10°; inversion time = 800 ms; turbo field echo factor = 65; sense factor = 2; matrix size = 256 × 256 × 180 mm 3 ; 1mm 3 isotropic voxel size), a T2*-weighted multi-slice fast field echo (T2*-FFE; TR = 3500 ms; TE = 35 ms; flip angle = 90°; sense factor = 2; 70 axial slices; 2 × 2 × 2 mm 3 isotropic voxel size) and a 3D-TSE T2-weighted volume acquisition (TR = Annexes 162 5500 ms; TE = 80 ms; sense factor = 2; FOV = 256 mm; matrix size = 256 x 256 x 81; 1 x 1 x 2 mm voxels).

DIFFUSION TENSOR MRI

Diffusion-weighted imaging (DWI) data were acquired using a single-shot spinecho echo-planar sequence with 21 non-collinear diffusion gradient directions (b = 1000 s/mm2), the series of 21 directions being acquired twice by reversing the gradients' polarity. Seventy axial slices parallel to the AC-PC plane were acquired from the bottom of the cerebellum to the vertex. Imaging parameters were as follows: TR = 8500 ms, TE = 81 ms, angle = 90°, sense reduction factor = 2.5, FOV 224 mm, acquisition matrix 112 × 112, 2 × 2 × 2 mm 3 isotropic voxel. A second series of 42 volumes was acquired leading to a total DTI acquisition time of 15 min 30 s.

FUNCTIONAL MRI

Functional images were acquired with a T2*-weighted echo-planar sequence (T2*-EPI; 240 volumes; TR = 2 s; TE = 35 ms; flip angle = 80°; 31 axial slices; 3.75 × 3.75 × 3.75 mm 3 isotropic voxel size) covering the same field of view as the T2*-FFE acquisition.

Resting state fMRI Spontaneous brain activity was monitored while the participants performed an 8-minute resting state condition. Participants were instructed to "keep their eyes closed, to relax, to refrain from moving, to stay awake, and to let their thoughts come and go". The acquisition was immediately followed by a debriefing interview allowing assessment of the participant's spontaneous thought content during the resting state-fMRI scanning.

Task-related fMRI

A Functional Battery for Hemispheric Specialization (FunBatHS) exploring hemispheric specialization (HS) for language, motor, visuo-spatial, and numerical activities was implemented in a functional MRI environment and performed in a subsample of 303 subjects (157 left-handers). Acquisition of FunBatHS fMRI data was organized in two sessions made of 4 runs each, one session being devoted to the mapping of language HS, the other to motor, spatial and numerical skills. Both sessions occurred the same day in a randomized order, each lasting about 2 h. Table 24 summarizes the various runs and tasks of the FunBatHS. DNA has been extracted from salivary samples (28 µg on average, N = 297). Whole genome re-sequencing in a subset of 29 subjects (Illumina hiseq 2000, ×20 depth) has recently been achieved, thanks to a specific collaborative agreement. Genotyping and/or sequencing are pending additional funds.

  Groupe d'Imagerie Neurofonctionnelle (GIN) -Equipe 5 IMN, UMR 5293 -Université de Bordeaux -CNRS -CEA, 146 rue Léo Saignat -Case 71, 33076 Bordeaux cedex

Figure 2 -

 2 Figure 2 -Carte moyenne de signal T1w/T2w selon configuration du gyrus de Heschl. Les cartes surfaciques sont affichées sur l'anatomie moyenne de chacune des configurations pour l'hémisphère gauche (A) et l'hémisphère droit (B). De la gauche vers la droite : A. 281 sujets avec un gyrus unique, 98 avec une duplication partielle, 46 avec une duplication complète ; B. 237 sujets avec un gyrus unique, 93 avec une duplication partielle, 48 avec une duplication complète.

Figure 3 -

 3 Figure 3 -Comparaisons de groupes du signal T1/T2. Dans les deux hémisphères, chaque groupe a été comparé aux deux autres et projeté sur la représentation anatomique des deux groupes afin de faciliter les interprétations. Les analyses correspondant à l'hémisphère gauche sont sur la ligne supérieure (A) et sur la ligne inférieure pour l'hémisphère droit (B). De la gauche vers la droite : « gyrus unique -duplication partielle » sur gyrus unique et sur duplication partielle, « gyrus uniqueduplication complète » sur gyrus unique et sur duplication complète et « duplication partielleduplication complète » sur duplication partielle et sur duplication complète. Uniquement les résultats statistiquement significatifs sont montrés avec un seuil de p < 0,01. Lorsqu'une différence est positive est représentée par les couleurs chaudes, et une différence négative par les couleurs froides.

Figure 4 -

 4 Figure 4 -A. Effet de l'âge sur l'index de maturation local pour les 341 jeunes adultes et les 106 adultes d'âge moyen. Le code couleur représente la diminution par an contrôlée par la courbure. B. Carte de différence d'effet de l'âge sur l'index de maturation entre les jeunes adultes et les adultes d'âge moyen. p < 0.05 corrigé FDR avec un seuil différent pour chaque hémisphère (<7.10 -5 pour l'hémisphère gauche et <10 -3 pour le droit). Tous les clusters montrent une perte par an plus importante chez les jeunes que chez les adultes d'âge moyen.

Figure 5 -

 5 Figure 5 -Corrélation entre les asymétries d'épaisseur et d'aire cortical dans les clusters de superposition i.e. qui montrent soit des asymétries concordantes soit des asymétries opposées. Les corrélations positives significatives sont en rouge et négatives en bleu. Les graphiques montrent les corrélations entre les asymétries d'épaisseur et d'aire dans 4 clusters : le gyrus de Heschl (HG), le sillon temporal supérieur (STS), l'insula antérieure et le gyrus fusiforme. Tous les clusters sont affichés sur les "inflatées" de l'hémisphère gauche.

Figure 1 -

 1 Figure 1 -Three-dimensional reconstruction of the lateral (top row) and medial (bottom row) surface of 13-21 week brains to reveal the development of the Sylvian fissure (green arrow), the calcarine fissure (blue arrow), and the parieto-occipital sulcus (red arrow), respectively. Adapted from[START_REF] Huang | Anatomical characterization of human fetal brain development with diffusion tensor magnetic resonance imaging[END_REF]

Figure 2 -

 2 Figure 2 -Simplified drawings of the HG and its duplications adapted from sagittal and axial MRI sections. From left to right: single gyrus, common stem duplication and complete posterior duplication. Yellow area = single HG or first HG; green area = second HG; red line = first transverse sulcus; dark blue line = Heschl's sulcus; light blue line = sulcus intermedius; pink line = second Heschl's sulcus. Adapted from Abdul-Kareem et al. (2008).

Figure 3 -

 3 Figure 3 -Myeloarchitectonic map of the supratemporal plane of the human cortex based on data from the Vogt-Vogt school. Adapted from Nieuwenhuys et al. (2015). B. Map of subcortical myelination during development by Flechsig. Darkly shaded regions myelinate first, then intermediate shaded regions myelinate, and finally, unshaded regions myelinate last. The order of myelination is given by the numbers.

Figure 5 -

 5 Figure 5 -Regions of high R1 on the superior temporal lobe. Each panel shows either the right (top) or left(bottom) superior temporal lobe of a given subject. High R1 regions are white if they overlap first HG and shaded (with diagonal lines) if they did not. A dashed line separates 3 hemispheres in which pattern of high R1 may be lass accurate because of lower grey/white matter contrast. Adapted from[START_REF] Sigalovsky | Mapping an intrinsic MR property of gray matter in auditory cortex of living humans: a possible marker for primary cortex and hemispheric differences[END_REF]

Figure 7 -

 7 Figure 7 -An example of manual corrections applied in case of wrong estimation of pial and/or white cortical surfaces.In this individual, the FreeSurfer software did not correctly estimate both white and pial surfaces in the upper part of the temporal pole. Manually adding checkpoints to the white matter surface results in better surface estimation after a second extraction process (yellow line, white surface; red line, pial surface; green dots, checkpoints).

Figure 12 -

 12 Figure 12 -Variability maps of the curvature (CURV) parameter in the left (A) and right (B) hemispheres. The colour scale represents the variance of the CURV parameters computed for each HG gyrification pattern in each hemisphere. The zoomed part is centred in the temporal transverse region where the HG duplication is located.

Figure 13 -

 13 Figure 13 -T1w/T2w average maps by HG configuration. Surface-based maps are displayed on the average anatomical surface of the same configuration in the left (A) and in the right hemisphere (B).From left to right: 281 single HG,98 CSD, 46 CPD, 237 single HG, 93 CSD and 95 CPD.

Figure 15 -

 15 Figure 15 -Comparison of groups varying in gyrification pattern obtained using the default FSaverage SBM template. a. Significant variations in cortical thickness. b. Significant variations in cortical surface area, the lateral view of the right temporal lobe is provided to illustrate the increase in cortical surface area located in the mid-part of the STS in the "CSDsingle HG" comparison. Significant variations are superimposed on the mean patch of each corresponding group (48 left CPD, 96 right CPD, for the "CPD -single HG" and "CPD -CSD" contrasts, 98 left CSD and 95 right CSD while for the "CSD -single HG" contrast, the lateral view is displayed on temporal lobe patch of the right CSD group (CSA: cortical surface area; CT: cortical thickness; CPD: common posterior duplication; CSD: common stem duplication; HG: Heschl's gyrus; p < 0.05 FDR corrected for multiple comparison; cluster extension threshold: 20 mm 2 ; hot color indicates a positive variation; cold color indicates a negative variation; light grey: gyrus; dark grey: sulci).

Figure 16 -

 16 Figure 16 -Projection of the significant surface-based clusters (Figure 14) in the average volume for each contrast and anatomical variable.In yellow: positive differences, in blue: negative differences.

Figure 17 -

 17 Figure17-Group comparisons of T1w/T2w signal. In both hemispheres, each group was compared to the two others, then projected onto the anatomical surfaces of the two groups being compared. In the top row (left hemisphere) and the bottom row (right hemisphere), from left to right: single -CPD on single and CPD, single -CSD on single and CSD, CSD -CPD on CSD and CPD. Only the statistically significant results are shown, with a threshold of p < 0.01; when a difference is positive, the colour scale is "hot" (yellow corresponding to the most significant vertices) and when the difference is negative, the colour scale is "cold" (with green corresponding to the most significant vertices).

Figure 19 -

 19 Figure 19 -Developmental timeline for gyrification. Adapted and modified from White et al. 2010.

Figure 20 -

 20 Figure 20 -Comparison of evolutionary and postnatal cortical surface expansion. A. Map of regional evolutionary cortical expansion between an adult macaque and the average human adult PALS-B12 atlas. Evolution expansion scale indicates how many times larger the surface area is in humans relative to the corresponding area in the macaque. B. Map of human postnatal cortical expansion. The development scale corresponds to the "absolute expansion" indicating how manytimes larger the surface area of a given region is in adulthood relative to that region area at term.

Figure 21 -

 21 Figure 21 -A. Scatterplots of age-brain structures relationships. Thickness of the cerebral cortex on the left and cerebral white matter (WM) volume on the right corrected for the influence of sample and intracranial volume (z scores). N = 1100. Adapted from Fjell et al. 2013. B. Geometrical relationship between cortical thickness, surface area and grey matter volume. Adapted from Winkler et al. 2010.

  [18-59y]: decrease of CT in frontal and parietal lobe (high postnatal expansion areas)[60-96y]: decrease of CT in occipital lobe and low postnatal expansion areas Raznahan et al. 2011 of most cortical regions except in bilateral anterior-medial temporal and right -related thinning in superior frontal gyrus, paracentral gyrus and pars opercularis and pars triangularis of inferior frontal gyrus Brown et al. (Cross-sectional) 202 [4-20] Decrease throughout the cortex with the most thinning rate in the medial and polar occipital, prefrontal and parietal region Van Soelen et al. in posterior cingulate, inferior and superior frontal on the right and in postcentral, paracentral and cingulate on the left Increase of CT in right superior frontal and left postcentral Fjell et al. between age and CT in posterior and superior frontal, temporal and orbitofrontal regions Quadratic model in lateral and medial prefrontal, parieto-temporo-occipital junction and medially around the precuneus No effect of age in occipital and temporal pole McKay et al. laterally in temporal and superior and caudal middle frontal & medially in posterior cingulate, precuneus and orbitofrontal Amlien et 83y]: widespread negative quadratic effect, stronger in frontal, parietal and temporal association areas and weaker in primary sensory areas [8-19y]: positive linear correlation stronger in posterior frontal, parietal and temporal cortices Superior frontal, inferior parietal and temporal showed earliest signs of transition between development and aging-related decline, and primary sensory areas did not show decline Shafee et al. (Cross-sectional) 1555 [18-35]

Figure 22 -

 22 Figure 22 -A. Single-subject non-smoothed map of cortical thickness. B. Single-subject nonsmoothed map of intracortical T1w/T2w ratio estimated myelination. Anatomical contrasts are projected on the individual reconstructed pial (left) and white inflated (right) surfaces of both hemispheres. C. Correlation map of intracortical T1w/T2w ratio and cortical thickness at each vertex while controlling for curvature. Only correlation coefficients surviving FDR with q = 0.05 are shown. Both positive (hot colours) and negative (cold colours) correlations are displayed on the reconstructed pial (left) and white inflated (right) surfaces of both hemispheres of 40-average space.

Figure 23 -

 23 Figure 23 -Average map of cortical thickness. The values obtained from the computation of 447 subjects are projected on the reconstructed pial (left) and white inflated (right) surfaces of both hemispheres of 40-average space.

Figure 24 -

 24 Figure 24 -Average map of intracortical T1w/T2w ratio. The values obtained from the computation of 447 subjects are projected on the reconstructed pial (left) and white inflated (right) surfaces of both hemispheres of 40-average space.

Figure 25 -

 25 Figure 25 -Variability map of sulcal depth. The values obtained from the computation of 447 subjects are projected on the reconstructed pial (left) and white inflated (right) surfaces of both hemispheres of 40-average space.

Figure

  Figure 29 -A. Vertex-wise analysis of age effect on local brain maturation index for the 341 young adults and the 106 middle-aged. Colour coding represents the loss per year covaried by the curvature. B. Map of difference of age effect on local brain maturation index between young and middle-aged adults. p < 0.05 corrected for FDR with a differentthreshold for each hemisphere (<7.10 -5 for the left hemisphere and <10-3 for the right one). All the clusters showed an loss per year stronger for young adults than middle-aged. Light grey for gyri and dark grey for sulci.

Figure 30 -

 30 Figure 30 -Vertex displacement asymmetry (on the left) and coordinate difference map based on the distance from each right hemisphere node to the corresponding node in the mirror-flipped left hemisphere surface (on the right). Adapted from Lyttelton et al. 2009 and Van Essen et al. 2012.

Figure 31 -

 31 Figure 31 -A. Upper surface of human temporal lobes exposed by a cut on each side in the plane of the Sylvian Fissure. SI = sulcus intermedius de Beck, SH = sulcus of Heschl, TG = transverse gyrus, PT = planum temporale, PM = posterior margin of the PT, y = end of the Sylvian Fissure. Adapted from Geschwind and Levitsky 1968. B. Leftward (from red to yellow) and rightward (from blue to green) asymmetries in a sample of 56 right-handed subjects.Adapted from[START_REF] Hervé | Handedness and cerebral anatomical asymmetries in young adult males[END_REF]

Figure 32 -

 32 Figure 32 -Significant interhemispheric folding asymmetries at gestational age of the fetal brain surface. GW = gestational week. Adapted from Habas et al. 2012.

Figure 36 -

 36 Figure 36 -A. Surface area asymmetry effect map. Adapted from Lyttelton et al. 2009. B. Cortical thickness asymmetry effect map. Adapted from Zhou et al. 2013.

Figure 37 -

 37 Figure 37 -Histogram distribution of hemispheric functional lateralization index (HFLI) in right-and left-handers. Solid line is fit of these distributions by models of mixture of 4 Gaussian distributions.

Figure 38 -

 38 Figure 38 -Inter-hemispheric surface-based registration for vertex-wise asymmetrical analysis. Left part of panel A illustrated left (respectively right) mean surface rendering and mean spherical projection of the 40 subjects used for computing the symmetrical template before the symmetrization process. Red (respectively Yellow) coloured areas in the spherical projection correspond to sulci in the left (respectively right) hemispheres. Right part of panel A illustrates the sulci misalignment between hemispheres before symmetrization. Panel B shows the same features after symmetrization illustrating that left and right homotopic sulci are quite perfectly aligned and that the cortical asymmetry analysis is not bias due to sulci shape and position differences between hemispheres. LH: left hemisphere, RH: right hemisphere, STS: superior temporal sulcus.

Figure 39 -

 39 Figure 39 -Regression plot of the hemispheric asymmetries index. Left: CT versus CSA, middle: CT versus CV and right: CSA versus CV.

Figure 41 -

 41 Figure 41 -Vertex-wise analysis of anatomical asymmetries for CV (panel A) and SULC (panel B). The cortical asymmetries are displayed on inflated view of the symmetrical template.Light grey corresponds to gyri. Statistical threshold was set to 0.05 FDR corrected for multiple comparisons. Leftward asymmetries are displayed on the left hemisphere and rightward asymmetries on the right hemisphere. LH: left hemisphere, RH: right hemisphere.

Figure 42 -

 42 Figure 42 -A. Effect of handedness on SULC asymmetries. Results are displayed on the left hemisphere pial surface of the symmetrical template. Light grey corresponds to gyri. Statistical threshold was set to 0.05 FDR corrected for multiple comparisons. B. Plot of SULC asymmetry for right and left-handers in the left precentral (Rolando genu) cluster of SULC asymmetry.

Figure 43 -

 43 Figure 43 -Effect of brain volume on CSA asymmetries. Results are displayed on the pial left hemisphere pial surface of the symmetrical template. Light grey corresponds to gyri. Statistical threshold was set to 0.05 FDR corrected for multiple comparisons. The graphs showed the actual association between CSA asymmetry and brain volume in three clusters: posterior Sylvian fissure, anterior part of middle temporal gyrus and marginal part of the cingulate sulcus.

Figure 44 -

 44 Figure 44 -Concordant and opposite clusters of overlap between CT and CSA asymmetries. All clusters were displayed on the inflated external and internal views of the left hemisphere. Light grey corresponds to gyri. STS: superior temporal sulcus.

Figure 46 -

 46 Figure46 -A. Concordant (panel A) and opposite (panel B) sites of overlap between CV and CT or CSA asymmetries. Left part of panel A and B displayed overlap between CV and CT asymmetries and right part of panel A and B, overlap between CV and CSA. Left hemisphere of panelA illustrates the concordant sites of overlapping between leftward CV and leftward CT (or CSA) asymmetries, while right hemisphere of panel A illustrates the concordant sites of overlapping between rightward CV and rightward CT (CSA) asymmetries. Left hemisphere of panel B illustrated the opposite sites of overlapping between leftward CV and rightward CT asymmetries or between leftward CSA and rightward CV asymmetries, while right hemisphere of panel B illustrated the opposite sites of overlapping between rightward CV and leftward CT asymmetries or rightward CSA and leftward CV asymmetries.

Figure 47 -

 47 Figure 47 -Cortical brain regions from automatic parcellation (Destrieux's atlas) of significant CT asymmetry from non-flipped (A) and flipped (B) images. Yellow colour indicates leftward asymmetries and blue colour, rightward asymmetries considering a Bonferroni correction. C. Reliability of the asymmetry profile from the automatic parcellation of both datasets. "Reliable" asymmetries i.e. that changed their direction with the flipping of the images are in green and the "non-reliable" asymmetries that maintains their status of asymmetry despite the flipping of the images are in red.

Figure 48 -

 48 Figure 48 -Cortical brain regions from automatic parcellation (Destrieux's atlas) of significant CSA asymmetry from non-flipped (A) and flipped (B) images. Yellow colour indicates leftward asymmetries and blue colour, rightward asymmetries considering a Bonferroni correction. C. Reliability of the asymmetry profile from the automatic parcellation of both datasets. "Reliable" asymmetries i.e. that changed their direction with the flipping of the images are in green and the "non-reliable" asymmetries that maintains their status of asymmetry despite the flipping of the images are in red.

Figure 49 -

 49 Figure 49 -Vertex-wise analysis of CT asymmetries with non-flipped (A) and flipped (B) images from 453 participants. The p-value for each vertex is displayed on inflated view of the symmetrical template with a threshold of 10 -3 . Leftward asymmetries are in hot colours and rightward asymmetries in cold colours. C. Vertex-wise overlap between asymmetries from non-flipped and flipped data showing reliable (in green) and non-reliable (in red) asymmetries.

Figure 50 -

 50 Figure 50 -Vertex-wise analysis of CSA asymmetries with non-flipped (A) and flipped (B) images from 453 participants. The p-value for each vertex is displayed on inflated view of the symmetrical template with a threshold of 10-3. Leftward asymmetries are in hot colours and rightward asymmetries in cold colours. C. Vertex-wise overlap between asymmetries from non-flipped and flipped data showing reliable (in green) and non-reliable (in red) asymmetries.

Figure 51 -

 51 Figure 51 -A. PT activation for sensory-motor contrast in yellow (a) and spatial hearing contrast in red (b). B. Projections of fiber tracts from the sensory-motor regions of the posterior planum temporale are in yellow, from the spatial hearing seed in red and the overlap is in blue. DTI data are rendered in 3D and superimposed on a 2D sagittal slice of the left hemisphere from the standard 1 mm FMRIB58 FA template in MNI space. Adapted from[START_REF] Isenberg | Functionally distinct regions for spatial processing and sensory motor integration in the planum temporale[END_REF]

Figure 55 -

 55 Figure 55 -Different representations of individual cortical surfaces. Red and green regions represent sulci and gyri, respectively.

Figure 56 -

 56 Figure 56 -Automatic cortical parcellation of one individual left hemisphere from three different surface-based atlases. The top row illustrates the pial views and the bottom row, the inflated views.

  presentation of scramble drawing + word list Read word list (seasons, days of the weeks, months of the year) Cross change detection Semantic decision Written words pair Judge whether both words relate to man-made items Cross change detection Rhyming Written pseudo-words pair Judge whether both pseudo-words rhyme Cross change detection Right and left finger tapping Arrow to indicate side of tapping Tap left (or right) finger at internally guided rhythm (

Table 1 -Meta-analysis of reports on HG structure changes related to phonology, music, sound processing, or pathology.

 1

Table 3 -Local variations of Cortical Surface Area (CSA) detected in "CPD-single HG", "CSD-single HG" and "CPD-CSD" contrasts.

 3

Table 4 -Main findings of quantitative MRI studies of age effect on CT and T1/T2 ratio through the lifespan. CT: Cortical Thickness. AGE-RELATED MODIFICATIONS OF CORTICAL THICKNESS

 4 Thinning in primary sensory, primary somatosensory, motor and association areas, more significant in inferior prefrontal, precentral and supramarginal and preservation of temporal cortex Thickening in anterior cingulate and medial orbitofrontal/subcallosal cortex

	Salat et al. 2004	106
	(Cross-sectional)	[18-93]
	Sowell et al.	45	Thinning in right frontal and bilateral parieto-occipital regions
	(Longitudinal)	[5-11]	Thickening in bilateral perisylvian cortex
	Shaw et al. 2008	375	Widespread cubic developmental trajectory, quadratic model in insula and anterior
	(Longitudinal)	[3-33]	cingulate cortex and negative linear relationship in posterior orbitofrontal, frontal
			operculum, medial temporal cortex, subgenual cingulate areas and medial
			occipitotemporal cortex
			Peak of CT between 7 and 11y
	Fjell et al. 2009	883	Thinning stronger in prefrontal cortex and superior temporal gyrus
	(Cross-sectional)	[18-94]
	Tamnes et al. 2010	168	CT decreased non linearly and stronger effect in parietal lobe, superior frontal and
	(Cross-sectional)	[8-30]	cingulate
	Westlye et al. 2010	429	Thinning most significant and widespread in the youngest group [8-30y] vs. adults
	(Cross-sectional)	[8-85]	[31-57y]
			Decelerating thinning from late 20s to the early 40s in some regions
	McGinnis et al.	316
	2011	[18-96]
	(Cross-sectional)

Table 5 -Sample characteristics of the young and middle-aged adults groups.

 5

		YOUNG	MIDDLE-AGED	P-VALUE
	N	341	106
	Age (years)	23.2 ± 2.8	38.1 ± 7.7	< 0.0001
	Educational level (years)	15.2 ± 2.0	15.0 ± 3.7	0.40
	Sex (% of women)	52.8	46.2	0.24
	Manual preference	51.9	62.2	0.06

Table 6 -Clusters of difference of age effect on cortical thickness between young and middle-aged adults displayed in the Figure 27.

 6

	x, y, z : Talairach coordinates for vertex with

Table 7 -Clusters of difference of age effect on T1w/T2w ratio between young and middle-aged adults displayed in Figure 28.

 7

	x, y, z : Talairach coordinates for vertex with the

Table 8 -Clusters of difference of age effect on the brain maturation index between young and middle-aged adults displayed in .

 8

	x, y, z : Talairach coordinates for vertex with the

Anatomical localization of maximum vertex

		Size (mm2)	p max	x	y	z
	Leftward asymmetries
	Inferior temporal gyrus	22174	3.10 -29	-54 -52	-13
	Insula	2687	4.10 -23	-33 9	-11
	Postcentral gyrus	356	4.10 -8	-41 -16	22
	Superior occipital gyrus	298	10 -7	-15	-95	23
	Cuneus	174	10 -4	-2	-82	15
	Inferior part of precentral gyrus	170	7.10 -4	-56 7	29
	Parieto-occipital sulcus	167	5.10 -3	-19 -67	19
	Rightward asymmetries
	Medial part of superior frontal gyrus	23233	2.10 -42	13	42	9
	Lingual gyrus	5592	10 -28	19	-59	3
	Superior temporal gyrus	3363	3.10 -19	59	-22	7
	Pars triangularis	714	3.10 -10	37	31	3
	Posterior part of insula	242	2.10 -9	35	-19	6
	Entorhinal gyrus	149	10 -5	29	-14	-27

Table 10 -Clusters of CT (cortical thickness) asymmetries. x

 10 , y, z: Talairach coordinates for vertex with the maximum p-value (p max). Cluster extension threshold of 100 mm 2 .

	Anatomical localization of maximum vertex	Size (mm2)	p max	x	y	z
	Leftward asymmetries
	Supramarginal gyrus	9859	10 -50	-50	-31	29
	Anterior part of superior temporal gyrus	6294	4.10 -32	-44	4	-21
	Anterior segment of the circular sulcus of the insula	2629	2.10 -31	-30	19	11
	Inferior temporal gyrus	2948	10 -12	-54	-46	-15
	Precuneus	1727	7.10 -6	-15	-46	34
	Intraparietal sulcus	181	9.10 -4	-27	-48	47
	Intraparietal sulcus	185	10 -3	-33	-65	36
	Caudal part of middle frontal gyrus	338	3.10 -3	-41	20	44
	Rightward asymmetries
	Posterior insula	835	7.10 -37	35	-19	9
	Precuneus	9660	6.10 -36	23	-57	21
	Medial part of orbitofrontal gyrus	14345	10 -29	10	44	-13
	Superior temporal gyrus	5272	4.10 -22	63	-6	0
	Paracentral lobule	1904	3.10 -14	13	-39	72
	Inferior part of precentral gyrus	566	5.10 -9	61	0	14
	Angular gyrus	192	10 -3	38	-61	45
	Mid part of precentral gyrus	182	7.10 -3	41	-7	56

Table 12 -Clusters of CV (cortical volume) asymmetries. x

 12 , y, z: Talairach coordinates for vertex with the maximum p-value (p max). Cluster extension threshold of 100 mm 2 .

Table 13 -Clusters of SULC (sulcal depth) asymmetries. x

 13 , y, z: Talairach coordinates for vertex with the maximum p-value (p max). Cluster extension threshold of 100 mm 2 .

Table 14 -Clusters of brain volume effect on CSA asymmetries

 14 . x, y, z: Talairach coordinates for vertex with the maximum p-value (p max). Cluster extension threshold of 100 mm 2 .

	Chapter 3

Chapter 3 111 3 .3.4 RELATIONSHIPS BETWEEN CT AND CSA ASYMMETRIES IN CLUSTERS OF CONCORDANT AND OPPOSITE DIRECTIONAL ASYMMETRIES

 33

	Anatomical localization	Size (mm2)	p-value	t ratio	R 2
	Leftward CT and leftward CSA
	Postcentral and supramarginal gyrus	4656	0.0374	2.09	0.017
	Temporal pole	1408	0.6735	0.42	0.001
	Posterior part of fusiform gyrus	991	0.0004	-3.61	0.050
	Parahippocampal gyrus	875	0.4705	0.72	0.002
	Anterior part of inferior temporal gyrus	185	0.0610	1.88	0.014
	Anterior insula	183	0.0367	-2.10	0.017
	Rightward CT and rightward CSA
	Orbito-frontal gyrus	5738	0.2454	-1.16	0.005
	Pericalcarine cortex	2955	0.8935	0.13	0
	Cingulate cortex	1572	<10 -4	4.34	0.071
	Middle part of superior temporal sulcus	944	0.0064	2.75	0.030
	Paracentral lobule	513	0.9365	-0.08	0
	Precuneus	243	0.9170	-0.10	0
	Posterior insula	219	0.4013	0.84	0.003
	Leftward CT and rightward CSA
	Angular gyrus	3962	0.0610	-1.88	0.014
	Parieto-occipital sulcus	431	0.9669	-0.04	0
	Superior occipital gyrus	261	0.5462	-0.60	0.001
	Central insula	249	0.0001	-3.87	0.057
	Rightward CT and leftward CSA
	Superior frontal gyrus	1215	<10 -4	-4.24	0.068
	Occipital pole	624	0.5932	-0.53	0.001
	Anterior part of circular sulcus of insula	548	<10 -4	-4.09	0.063
	Caudal part of middle frontal gyrus	484	0.0006	-3.47	0.046
	Middle part of inferior temporal gyrus	425	0.2091	-1.26	0.006
	Subparietal sulcus	411	0.0005	-3.53	0.048
	Precuneus	406	0.0188	-2.36	0.022
	Heschl's gyrus	396	<10 -4	-5.39	0.113
	Rostral part of anterior cingulate cortex	333	0.6291	0.48	0.001
	Anterior part of superior temporal gyrus	323	0.6864	-0.40	0.001

Table 15 -Clusters of overlap between concordant and opposite clusters of CT and CSA asymmetries.

 15 Cluster extension threshold of 150 mm 2 . The p-value and t-ratio are associated to the linear regression between CT and CSA correlation for each cluster of overlap. Significant p-value are in bold. When R 2 was o0.001, the value of 0 was reported in the table.

Table 20 -CT Laterality index (LI) of each brain cortical region computed in non-flipped and flipped data.

 20 Leftward asymmetries are in yellow and rightward asymmetries in blue. The more right column corresponds to the p-value of the paired Student's t-test between LI in non-flipped and flipped data, in bold significant reliable asymmetries.

Table 21 -CSA Laterality index (LI) of each brain cortical region computed in non-flipped and flipped data.

 21 Leftward asymmetries are in yellow and rightward asymmetries in blue. The more right column corresponds to the p-value of the paired Student's t-test between LI in non-flipped and flipped data, in bold significant reliable asymmetries.

Table 23 -Battery of cognitive tests performed by the participants of the BIL&GIN.

 23 Auditory verbal learning test: mean number of recalled words across 5 repeated lists 450 Auditory phonological learning test: mean number of recalled pseudo-words across 5 repeated lists

	Cognitive battery

Table 24 -Description of the functional battery of task performed by the subjects during the two FMRI sessions.

 24

The frontal lobe exhibited rightward asymmetries located in the inferior part of the precentral gyrus and the Rolandic operculum, in the most anterior part of the medial superior frontal gyrus and in the gyrus rectus. There was also a rightward asymmetry in the cingulate cortex extending to the paracentral lobule and in the posterior half of the insula. The strongest rightward asymmetry was located in the angular gyrus and extended anteriorly towards the posterior halves of the STS and of the middle temporal gyrus. This large cluster of rightward CSA asymmetry extended posteriorly in the medial part of the occipital lobe, including the calcarine fissure, the lingual gyrus, the cuneus and the parieto-occipital sulcus.

CORTICAL VOLUME ASYMMETRIES

We observed that the CV of the medial part of the frontal lobe, including its orbital part and extending to the cingulate gyrus, was rightward asymmetrical with the exception of the caudal part of the medial superior frontal gyrus, a cluster in the depth of the inferior frontal sulcus and in a cluster within the middle frontal gyrus, which showed leftward volume asymmetry (Figure 41A, Table 12). The pars orbitalis of the IFG and the anterior half of the insula presented leftward volume asymmetry. The entire postcentral gyrus extending to the supramarginal and the PT, the temporal pole and the fusiform gyrus were also leftward asymmetrical for CV. Some rightward CV asymmetries were seen in the posterior half of the insula and all along the STS and covering the angular gyrus. Finally, the CV of the medial view of the occipital lobe was strongly rightward asymmetrical.

RELATIONSHIPS BETWEEN CV ASYMMETRIES AND CT AND CSA

The overlaps and tables of associated clusters are provided in the Figure 46 and Table 16, Table 17, Table 18, & Table 19. All clusters of concordant overlap between CV and CT asymmetries, as well as clusters of concordant overlap between CV and CSA, showed highly significant positive correlations between pairwise asymmetries. CV asymmetries exhibited stronger correlations with CSA (R 2 range [0.46-0.92]) than with CT measurements (R 2 range [0.09-0.52]), suggesting that unlike total CV AI, regional CV asymmetries are more driven by CSA asymmetries than by CT asymmetries.

Anatomical localization

Size

. The p-value and t-ratio are associated to the linear regression between CV and CT correlation for each cluster of overlap. Significant p-value are in bold.

Table 19 -Clusters of overlap between opposite CV and CT asymmetries. Cluster extension threshold of 150 mm 2 . The p-value and t-ratio are associated to the linear regression between CV and CT correlation for each cluster of overlap. Significant p-value are in bold.

investigate such relationship in the entire frontal lobe where Chiarello et al. reported numerous negative correlations between CT and CSA asymmetries.

By investigating the mechanisms underlying the correlations between CT and CSA asymmetries, we found that approximately 40% of these were driven by differences in the slope characterizing the linear correlations between CT and CSA in each hemisphere (Table 22). This latter finding supports the hypothesis that CT and CSA intra-hemispheric relationships, considered as resulting from the expansion of the underlying white matter bundles during the development of cortical folding [START_REF] Hogstrom | The structure of the cerebral cortex across adult life: age-related patterns of surface area, thickness, and gyrification[END_REF][START_REF] Van Essen | A tension-based theory of morphogenesis and compact wiring in the central nervous system[END_REF], are supporting some of the associations between the asymmetries of CT and CSA. The identification of regional relationships between CT and CSA asymmetries extends our knowledge on the organization of grey matter cortical asymmetries in healthy adults and call for complementary analysis for a full understanding of the complex mechanisms underlying these relationships.

ANATOMICAL ASYMMETRIES OF THE PERISYLVIAN CORTEX AND THE STS

To our knowledge, the only previous map of sulcal depth asymmetries for an adult population was provided by Hill et al. who showed two significant sulcal depth asymmetries located along the STS and at the level of the perisylvian cortex centred on the PT based on landmark surface-based registration (Hill et al., 2010a;Van Essen et al., 2012). In the present work, we did not observe such a strong sylvian fissure leftward asymmetry. This apparent discrepancy might be related to the optimal sulcal alignment we obtained between the left and right Sylvian fissures, which are known

SKULL STRIPPING

The following skull stripping step consists in removing brain tissue from nonbrain tissue such as the skull, eyeballs, meninges and skin. In FreeSurfer a watershed algorithm combined with a deformable model is used to peel the skull. The obtained volumes are saved in "brainmask.mgz" (Figure 53D).

AUTOMATED LABELING OF NEUROANATOMICAL STRUCTURES IN THE VOLUME

In this edited brain mask, each voxel from the MRI volume is associated to a neuroanatomical label based on probabilistic information automatically estimated from a manually labelled training set [START_REF] Fischl | Whole Brain Segmentation: Neurotechnique Automated Labeling of Neuroanatomical Structures in the human Brain[END_REF]. This segmentation procedure assigns one of 44 labels to each voxel, i.e. left and right caudate, putamen, pallidum, thalamus, hippocampus, amygdala, accumbens nucleus, ventral diencephalon (group of structures that cannot be distinguished from each other with standard MRI images), white matter, cortical grey matter, cerebellar white matter, cerebellar grey matter, lateral ventricles, inferior lateral ventricles, vessels, choroid plexus, and some non-bilateral regions with third ventricle, fourth ventricle, "sulcal" cerebrospinal fluid, optic chiasma, 5 subregions of corpus callosum, white "hypointensities" (in the T1w volume) and the brainstem (stored in "aseg.mgz", Figure 54A). Local spatial relationships between labelled structures have been encoded by modelling the labelled image using Markov random fields. With this approach, the probability of a label at a given voxel is computed not just in terms of the intensities and prior probabilities at that voxel, but also as a function of the labels in a neighbourhood around the voxel in question.

SURFACE RECONSTRUCTION, INFLATION AND AUTOMATIC PARCELLATION OF CEREBRAL CORTEX

After the segmentation is complete, the software generates a single connected mass representing the white matter structure of each hemisphere ("fill.mgz", Figure 54B) using a connected components procedure [START_REF] Dale | Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction[END_REF]. Once the two white matter volumes have been generated, a surface tessellation is constructed for each hemisphere. Two triangles are used to represent each face separating voxels classified as a white matter and the results are saved in the surface files "lh.orig" and "rh.orig" (Figure 54B). Then, the initial tessellation is smoothed using a deformable surface algorithm guided by local MRI intensity values, leading to the estimation of grey/white interface or white surface, stored in "lh.white" and "rh.white" files (Figure 54C and Figure 55B). These surfaces were deformed outward to find the pial surface, necessitating the implementation of an algorithm to prevent selfintersections from occurring in the surface and to correct topological defects (i.e. a bridge across the banks of a sulcus and a hole in the wall of a gyrus). The obtained surfaces are stored in lh.pial and rh.pial files (Figure 54C and Figure 55A).

The surface of the human cerebral cortex is a highly folded sheet with the majority of its surface area buried within folds (between 60 and 70%). To visualize inside sulci, white surfaces are inflated, rendering the interior of sulci visible, as well as making the surface-based distance between regions more apparent to visual inspection ("lh.inflated" and "rh.inflated" files, Figure 55C). This inflation functional is integrated until the normalized average distance of the neighbours of each vertex from its tangent plane is below a prespecified threshold (Fischl et al., 1999a). Identifying corresponding points on different cortical surfaces requires the establishment of a uniform surface-based coordinate system. In order to establish this system, the reconstructed cortical surfaces are then transformed into a sphere

Figure 54 -Automated labelling of the volume (A) and surfaces reconstructions (B and C).

The "white" surface corresponding to the grey/white interface is in yellow and the 'pial" surface corresponding to the external surface of the brain is in red.

SURFACE-BASED REGISTRATION

In order to compare anatomical features across subjects, it is necessary to establish a mapping that specifies a unique correspondence between each location in one brain and the corresponding location in another. It consists in bringing the two brains into a registration template. The curvature pattern, i.e. sulcal and gyral folding, is used to drive the intersubject aliment of the cortical surfaces.

The reconstructed surface of each individual subject is first mapped onto a sphere, using a maximally isometric transformation. The surfaces are then morphed into register with an average surface, guided by a combination of folding alignment and isometry preserving forces (Fischl et al., 1999b) (Figure 57).

CREATING A SURFACE-BASED REGISTRATION TEMPLATE

FreeSurfer developed a surface atlas for the morphometric study of Alzheimer's disease. It is a generalized atlas generated from 40 subjects with wide range of age (from 18 to 87 years old) and clinical status. After cortical surfaces are generated from MRI scans of training subjects, all surface are mapped onto spheres. The spherical maps are aligned with each other by FreeSurfer's multi-scale surface registration. The alignment is performed by choosing one subject as the target surface and registering the rest of surface to the target surface. An atlas was thus generated on a sphere by averaging scalar values representing fold patterns across 40 subjects. Then, the training subjects were registered to the average atlas again and the scalar values on the atlas were updated. The process continues until the atlas converged.

By comparing and evaluating surface-based brain image registration methods, Klein et al. advise to construct a custom template from a limited sample from the same or a similar representative population, using the same algorithm used for