Clément Guichet

Élise Roger

Arnaud Attyé

Sophie Achard

Martial Mermillod

Author, CA Monica Baciu
email: monica.baciu@univ-grenoble-alpes.fr

Ca

Dynamics of White Matter Architecture in Lexical Production among Middle-Aged Adults

Keywords: language, middle age, white matter integrity, cognition, LARA

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Population aging has led to an increase in average life expectancy. However, this demographic transition is accompanied by a higher prevalence of neurodegenerative diseases and cognitive decline, leading to an increase in healthcare demand (United Nations, 2023).

Language function, crucial for human communication and cognition [START_REF] Hagoort | The neurobiology of language beyond single-word processing[END_REF][START_REF] Hagoort | The language marker hypothesis[END_REF], undergoes significant and differentiated changes related to individuals age [START_REF] De Zubicaray | The Oxford handbook of neurolinguistics[END_REF]. Indeed, while some aspects of language processes, such as language comprehension (LC), remain relatively stable compared to younger adults, others, such as language production (LP), decline relatively early with age, starting in middle age [START_REF] Oosterhuis | Getting the brain into gear : An online study investigating cognitive reserve and word-finding abilities in healthy ageing[END_REF][START_REF] Verhaegen | Changes in Naming and Semantic Abilities With Aging From 50 to 90 years[END_REF]. The disparity between LP and LC can be attributed to the benefits from rich semantic knowledge accumulated over the lifespan [START_REF] Gollan | Aging deficits in naturalistic speech production and monitoring revealed through reading aloud[END_REF][START_REF] Salthouse | Trajectories of normal cognitive aging[END_REF]. Indeed, this semantic expertise [START_REF] Spreng | The Shifting Architecture of Cognition and Brain Function in Older Adulthood[END_REF] contributes to preserving language comprehension and implementing compensatory mechanisms to mitigate LP decline in older adults [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF]. At the behavioral level, while advanced age is associated with the most significant LP decline (e.g., lower naming accuracy) (Shafto & Tyler, 2014;[START_REF] Verhaegen | Changes in Naming and Semantic Abilities With Aging From 50 to 90 years[END_REF], increased naming latencies in low-frequency words with poorer semantic connections may onset in middle age [START_REF] Benítez-Burraco | Revisiting the hypothesis of language retrogenesis from an evolutionary perspective[END_REF]. Therefore, a comprehensive investigation of midlife is crucial to understanding the aging mechanisms at play and predicting the neurocognitive trajectory in older late adulthood [START_REF] Lachman | Mind the Gap in the Middle : A Call to Study Midlife[END_REF][START_REF] Park | The Middle-Aged Brain[END_REF].

Previous studies have reported a gradual LP decline resulting from the interplay between domain-general and language-specific mechanisms [START_REF] Gertel | Lexical frequency affects functional activation and accuracy in picture naming among older and younger adults[END_REF]Shafto & Tyler, 2014;[START_REF] Steinberg Lowe | Role of cognitive control in resolving two types of conflict during spoken word production[END_REF]. Typically, there is reduced access to and/or retrieval of lexico-semantic representations [START_REF] Baciu | Functional MRI evidence for the decline of word retrieval and generation during normal aging[END_REF][START_REF] Boudiaf | Behavioral evidence for a differential modulation of semantic processing and lexical production by aging : A full linear mixed-effects modeling approach[END_REF] in association with a decline in executive functioning with age [START_REF] Higby | The Role of Executive Functions in Object-and Action-Naming among Older Adults[END_REF], reduced working memory [START_REF] Burke | Aging and Language Production[END_REF] and inhibitory processes [START_REF] Gordon | The ageing neighbourhood : Phonological density in naming[END_REF] explaining the slowdown of information processing and reduced verbal fluency [START_REF] Gordon | Why do older adults have difficulty with semantic fluency?[END_REF][START_REF] Whiteside | Verbal Fluency : Language or Executive Function Measure?[END_REF] within the LP decline context.

The decline in LP varies among older individuals, exhibiting significant variability [START_REF] Gordon | Why do older adults have difficulty with semantic fluency?[END_REF][START_REF] Wen | The effect of ageing on confrontation naming in healthy older adults : A three-level meta-analysis[END_REF] linked to cognitive reserve differences [START_REF] Oosterhuis | Getting the brain into gear : An online study investigating cognitive reserve and word-finding abilities in healthy ageing[END_REF][START_REF] Perneczky | Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI[END_REF]. As highlighted by previous studies [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF][START_REF] Wulff | Using Network Science to Understand the Aging Lexicon : Linking Individuals' Experience, Semantic Networks, and Cognitive Performance[END_REF] this variability depends on various cognitive reserve factors such as education, social, intellectual, physical, and leisure activities [START_REF] Brosnan | Evidence Accumulation Rate Moderates the Relationship between Enriched Environment Exposure and Age-Related Response Speed Declines[END_REF][START_REF] Perneczky | Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI[END_REF]. As previously reported by the STAC (Scaffolding Theory of Aging and Cognition) model [START_REF] Park | The Adaptive Brain : Aging and Neurocognitive Scaffolding[END_REF], scaffolding is a natural process throughout life that entails utilizing and enhancing alternative neural pathways to accomplish specific cognitive tasks. Its effectiveness is enhanced by cognitive engagement, physical exercise, and reduced default network activity. Subsequently, a revised version of this model entitled STAC-r (Reuter-Lorenz & Park, 2014, 2023) has been described as incorporating life-course factors that contribute to either bolstering or depleting neural resources, thereby influencing the developmental trajectory of brain structure, function, and cognitive abilities. The life-course factors also impact individuals' compensatory mechanisms to address cognitive challenges and mitigate the adverse effects of structural and functional decline. Specifically, studies point to midlife lifestyle activities as a key contributor to this idiosyncratic nature of cognitive aging [START_REF] Chan | Lifestyle activities in mid-life contribute to cognitive reserve in late-life, independent of education, occupation, and late-life activities[END_REF][START_REF] Xu | Association of Lifespan Cognitive Reserve Indicator With Dementia Risk in the Presence of Brain Pathologies[END_REF]. The intricate landscape of language aging underscores the need to comprehend behavioral and cognitive changes and the functional and structural network reorganization associated with compensatory mechanisms. This understanding aims to delay, as much as possible, a decline in LP performance and maintain a relatively normal level.

At a functional level, data from resting-state and task-activation fMRI suggest that aging influences activation dynamics within large brain networks, reorganizing them to maintain cognitive performance [START_REF] Deery | The older adult brain is less modular, more integrated, and less efficient at rest : A systematic review of largescale resting-state functional brain networks in aging[END_REF][START_REF] Sun | Functional connectome through the human life span[END_REF]. With aging, cerebral networks exhibit reduced functional specialization, as seen by decreased within-network connectivity [START_REF] Chan | Decreased segregation of brain systems across the healthy adult lifespan[END_REF][START_REF] Edde | Functional brain connectivity changes across the human life span : From fetal development to old age[END_REF][START_REF] Jockwitz | Influence of age and cognitive performance on resting-state brain networks of older adults in a population-based cohort[END_REF]. Simultaneously, increased between-network connectivity may counteract cognitive decline [START_REF] Bertolero | The modular and integrative functional architecture of the human brain[END_REF][START_REF] Cabeza | Maintenance, reserve and compensation : The cognitive neuroscience of healthy ageing[END_REF][START_REF] Meunier | Age-related changes in modular organization of human brain functional networks[END_REF]. Notably, reduced activity within the Default Mode Network (DMN), primarily involved in semantic processes [START_REF] Alves | An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings[END_REF][START_REF] Menon | 20 years of the default mode network : A review and synthesis[END_REF][START_REF] Raichle | A default mode of brain function[END_REF], coupled with enhanced functional integration in control-executive regions play a crucial compensatory role in tasks with significant attentional demands (see the DECHA model; [START_REF] Spreng | The Shifting Architecture of Cognition and Brain Function in Older Adulthood[END_REF] such as LP [START_REF] Roger | Missing links : The functional unification of language and memory (L∪M)[END_REF]. This aligns with studies showing that semantic cognition becomes increasingly reliant on domain-general processes with age to ensure efficient and context-relevant use of semantic representations [START_REF] Hoffman | Age-related changes in the neural networks supporting semantic cognition : A meta-analysis of 47 functional neuroimaging studies[END_REF]Martin, Saur, et al., 2022;[START_REF] Martin | Age-related reorganization of functional network architecture in semantic cognition[END_REF]. For example, [START_REF] Hoyau | Aging modulates fronto-temporal cortical interactions during lexical production. A dynamic causal modeling study[END_REF] found that, compared to younger adults, older adults modulate the top-down connectivity from inferior frontal to medial temporal regions (IFC-MTC) to facilitate semantic access, suggesting a compensatory mechanism to provide the neural resources needed for LP performance. Similarly, [START_REF] Krieger-Redwood | Reduced semantic control in older adults is linked to intrinsic DMN connectivity[END_REF] highlighted that increased within-DMN connectivity between the right anterior temporal lobe (ATL) and medial prefrontal cortex (mPFC) might translate to inefficient semantic retrieval, reflecting older adults' reduced ability to access the semantic store in a goal-directed manner.

At a structural or neuroanatomical level, our understanding of the white matter integrity that accompanies these midlife functional changes remains largely unexplored, despite recent research highlighting white matter degradation as an explanation for the onset of LP deficits [START_REF] Kljajevic | Dorsal White Matter Integrity and Name Retrieval in Midlife[END_REF][START_REF] Sánchez | White matter brain structure predicts language performance and learning success[END_REF][START_REF] Troutman | Cerebral White Matter Mediation of Age-Related Differences in Picture Naming Across Adulthood[END_REF][START_REF] Yeske | Differences in Diffusion Tensor Imaging White Matter Integrity Related to Verbal Fluency Between Young and Old Adults[END_REF]. Within the language network [START_REF] Shekari | A narrative review of the anatomy and function of the white matter tracts in language production and comprehension[END_REF], microstructural integrity assessed via diffusion tensor-based metrics (e.g., fractional anisotropy, radial diffusivity) is associated with higher-order aspects of naming, such as lexico-semantic selection, notably along the left superior fasciculus (SLF III; [START_REF] Troutman | White matter disconnection is related to age-related phonological deficits[END_REF] and inferior longitudinal fasciculus (ILF; [START_REF] Kantarci | Diffusion tensor imaging and cognitive function in older adults with no dementia[END_REF][START_REF] Stamatakis | White Matter Changes and Word Finding Failures with Increasing Age[END_REF][START_REF] Troutman | White matter disconnection is related to age-related phonological deficits[END_REF].

Moreover, the frontal aslant tract (FAT; [START_REF] Rizio | Language, aging, and cognition : Frontal aslant tract and superior longitudinal fasciculus contribute toward working memory performance in older adults[END_REF][START_REF] Troutman | White matter disconnection is related to age-related phonological deficits[END_REF], which connects the IFG to the premotor cortex (SMA and pre-SMA), is relevant for the sensorimotor aspects of fluency and speech-to-motor planning, with its anterior terminations associated with working memory [START_REF] Varriano | Distinct Components in the Right Extended Frontal Aslant Tract Mediate Language and Working Memory Performance : A Tractography-Informed VBM Study[END_REF]. This is in line with a recent study suggesting that converging locations between the left frontal aslant tract (FAT), frontostriatal tract (ST-FO; [START_REF] Stamatakis | White Matter Changes and Word Finding Failures with Increasing Age[END_REF], and left SLF I are essential for efficient verbal working memory [START_REF] Ribeiro | White matter tracts and executive functions : A review of causal and correlation evidence[END_REF]. In addition, the middle longitudinal fasciculus (MLF) can also support the executive functions and working memory aspects of LP [START_REF] Rizio | Language, aging, and cognition : Frontal aslant tract and superior longitudinal fasciculus contribute toward working memory performance in older adults[END_REF][START_REF] Troutman | White matter disconnection is related to age-related phonological deficits[END_REF]. Correspondingly, these studies align with recent findings [START_REF] Roger | Unraveling the functional attributes of the language connectome : Crucial subnetworks, flexibility and variability[END_REF] on the left arcuate fascicle (AF), SLF III, ILF, and thalamic-premotor projections, which overlap spatially with language networks. In addition, spatial concordance was found between the left SLF II/left cingulum bundle (CG) and control-executive subnetwork, as well as between the fornix/hippocampal formation and the abstract-knowledge (DMN-related) subnetwork (see in detail Roger et al., 2022).

Based on behavioral and neurofunctional results, a recent study reported a comprehensive overview of various compensatory mechanisms for LP with aging (LARA model, Lexical Access and Retrieval in Aging, [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF]. This model describes two dimensions, LA (Lifespan Aging, uniform aging; natural effect of age) and RA (Reserve Aging, idiosyncratic aging; effect of cognitive reserve), according to two dimensions: Language-Specific (LS, specific to LA dimension) and Domain-General (DG, specific to RA dimension). Despite being grounded in experimental findings, the LARA model remains predominantly descriptive, and the brain structure dynamics that fit these dimensions are not included.

In the current study, our primary objective is to evaluate white matter changes supporting LP decline that emerges in midlife [START_REF] Fargier | Referential and inferential production across the lifespan : Different patterns and different predictive cognitive factors[END_REF][START_REF] Oosterhuis | Getting the brain into gear : An online study investigating cognitive reserve and word-finding abilities in healthy ageing[END_REF]. We anticipate decreased white matter integrity across the brain, especially along the dorsal and frontostriatal pathways, correlating with neurocognitive changes linked to age-related LP decline. Furthermore, we expect nonlinear microstructural changes that reflect accelerated cognitive decline in older adults. In line with the LARA model [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF], we further hypothesize that these white matter changes will align with two dimensions: (1) Lifespan Aging/Language-Specific LA/LS, involving semantic-related mechanisms with enhanced diffusivity along lateral pathways to enhance lexico-semantic representations, and along ventral mesial pathways to strengthen lexico-semantic memory retrieval. In line with [START_REF] Hoyau | Aging modulates fronto-temporal cortical interactions during lexical production. A dynamic causal modeling study[END_REF], this dimension could represent a compensatory mechanism that onsets in midlife to maintain LP performance, and (2) Reserve Aging/Domain-General RA/DG, representing the decline of domain-general mechanisms associated with reduced diffusivity within prefrontal regions, potentially involving SLF II and CG bundles. In line with [START_REF] Krieger-Redwood | Reduced semantic control in older adults is linked to intrinsic DMN connectivity[END_REF], this could challenge efficient and goal-directed access to the semantic store, compromising LP performance in older adults.

Material and Methods

Using state-of-the-art tractography techniques, we analyzed diffusion-weighted imaging and lexical production (LP)-related neuropsychological data of 155 healthy middle-aged adults (aged 45-60) from the CamCAN cohort [START_REF] Shafto | The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study protocol : A cross-sectional, lifespan, multidisciplinary examination of healthy cognitive ageing[END_REF]. Figure 1 outlines the study workflow. After preprocessing diffusion-weighted imaging (DWI) data, we investigated the relationship between middle age and structural integrity by generating a track-weighted fractional anisotropy image (TW-FA) for each subject [START_REF] Calamante | Track-weighted imaging methods : Extracting information from a streamlines tractogram[END_REF]. Subsequently, using Non-Negative Matrix Factorization (NMF), we reduced the dimensionality of these TW-FA images to identify sets of networks consisting of structurally covarying voxels. We then assessed the impact of age on the average microstructural integrity of each NMF network by using generalized additive models. Finally, we applied Partial Least Squares (PLS) correlation analysis at the voxel and network levels to examine how localized and distributed microstructural integrity changes covary with LP performance during middle age. To enhance the theoretical relevance of our study, a preliminary lifespan analysis (not depicted in Figure 1)) was conducted to specify the most critical age window for cognitive aging. This age window guided the main statistical analyses described earlier (please refer to section 2.3.1).

Figure 1: Workflow of the study. For multilevel PLS analysis, only one covariance matrix (R) is depicted for visual clarity; however, it is important to emphasize that a separate PLS model was executed using either voxellevel TW-FA values or network-level values derived from NMF (H values), resulting in two distinct covariance matrices.

Data and MRI acquisition

Participants

We selected 155 healthy adults (76 females and 79 males) aged-45-60 at the time of MRI acquisition based on our preliminary analysis (refer to Section 2.3.1). These individuals were chosen from the Cambridge Center for Ageing and Neuroscience project dataset [START_REF] Shafto | The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study protocol : A cross-sectional, lifespan, multidisciplinary examination of healthy cognitive ageing[END_REF]. The East of England Cambridge Central Research Ethics Committee approved the CamCAN study. Please refer to [START_REF] Taylor | The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository : Structural and functional MRI, MEG, and cognitive data from a crosssectional adult lifespan sample[END_REF] for further recruitment information.

There was no significant difference in mean age at the time of MRI acquisition (p FDR = .52) or handedness (p FDR = .49), but middle-aged females tend to have better overall cognition (MMSE; t = 2.7, p FDR = .017) across genders, and middle-aged males tend to have a higher total intracranial volume (t = -9.9, p FDR < .001) (Figure A.1, Appendix A).

Cognitive data

To assess lexical production (LP)-related performance, we selected eight neuropsychological tests that showed either: (i) a direct relationship with lexical production (LP) (e.g., Verbal Fluency, Naming, and Tip-of-the-Tongue tests) or (ii) an indirect relationship via the domaingeneral (DG) and language-specific (LS) mechanisms posited by the LARA model [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF]. Table 1 shows the main cognitive processes associated with each test. Middle-aged females show better performances in Naming (t = 2.8, p FDR = .04) and Story recall tasks (t = 2.3, p FDR = .05). Specifically, the gap in sentence comprehension performances in favor of women grows as age increases (t = 2.18; p = .03) (see Table A.2, Appendix A for the results).

Diffusion MRI

Multi-shell diffusion-weighted imaging (DWI) data were acquired using a twice-refocused spin echo sequence. The acquisition parameters were as follows: 66 axial slices, TR/TE = 9100/104 ms, 2 mm isotropic voxels, 30 directions (b-values: 1000 and 2000 s/mm2), and three b0 images with an acquisition time of ~10 min. Details can be found in the study by [START_REF] Taylor | The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository : Structural and functional MRI, MEG, and cognitive data from a crosssectional adult lifespan sample[END_REF]. All DWI data were preprocessed using MRtrix3 [START_REF] Tournier | MRtrix3 : A fast, flexible and open software framework for medical image processing and visualisation[END_REF] (version 3.0.4; https://www.mrtrix.org/).

LARA mechanisms

Direct

  

Proverb [START_REF] Huppert | Dementia and normal aging[END_REF]  

Sentence Comprehension [START_REF] Rodd | The functional organisation of the fronto-temporal language system : Evidence from syntactic and semantic ambiguity[END_REF]  

Story Recall [START_REF] Tulsky | The Wechsler Memory Scale, Third Edition[END_REF]  Tip-of-the-Tongue (R. [START_REF] Brown | The "tip of the tongue" phenomenon[END_REF]  

Verbal Fluency [START_REF] Lezak | Neuropsychological assessment[END_REF]   

MRI data processing

Diffusion MRI

Preprocessing includes denoising [START_REF] Veraart | Denoising of diffusion MRI using random matrix theory[END_REF], Gibbs artifact removal [START_REF] Tustison | N4ITK : Improved N3 Bias Correction[END_REF], eddy current and motion correction with FSL [START_REF] Andersson | How to correct susceptibility distortions in spin-echo echo-planar images : Application to diffusion tensor imaging[END_REF], and bias correction with ANTs N4. DWI images were then upsampled to a voxel size of 1.5 mm 3 using cubic B-spline interpolation [START_REF] Raffelt | Reorientation of fiber orientation distributions using apodized point spread functions[END_REF]. Following these preprocessing steps, fiber orientation distributions (FOD) were computed using the multi-shell 3-tissue Constrained Spherical Deconvolution model (MSMT CSD; [START_REF] Dhollander | Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image[END_REF][START_REF] Jeurissen | Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data[END_REF][START_REF] Tournier | Robust determination of the fibre orientation distribution in diffusion MRI : Non-negativity constrained super-resolved spherical deconvolution[END_REF] with group-averaged response functions calculated before upsampling.

Finally, a joint bias field correction and intensity normalization were applied to the resulting FOD images.

Track-Weighted Imaging

We quantified structural integrity at each voxel location using Track-Weighted Imaging (TWI). Compared to conventional tensor-based metric, TWI enhances the sensitivity to microstructural changes and the representation of crossing fiber configurations [START_REF] Calamante | Track-weighted imaging methods : Extracting information from a streamlines tractogram[END_REF][START_REF] Calamante | A generalised framework for super-resolution track-weighted imaging[END_REF]. The TW images were generated in four steps. (1) Whole-brain tractography (iFOD2; 10 million streamlines, max. length = 250 mm, cutoff = 0.06, backtrack option) to obtain subject-specific tractograms while reducing reconstruction biases (SIFT2; [START_REF] Smith | SIFT2 : Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography[END_REF]; (2) Generation of a study FOD template to ensure compatibility of tracks' length and spatial location between participants [START_REF] Willats | Quantification of track-weighted imaging (TWI) : Characterisation of within-subject reproducibility and between-subject variability[END_REF]. The template was based on normalized WM FOD images [START_REF] Raffelt | Symmetric diffeomorphic registration of fibre orientation distributions[END_REF] from a subset of 35 participants, controlling for age (mean and standard deviation within 1%) and gender. Spatial correspondence across participants was achieved through FOD-guided nonlinear registration [START_REF] Raffelt | Symmetric diffeomorphic registration of fibre orientation distributions[END_REF][START_REF] Raffelt | Reorientation of fiber orientation distributions using apodized point spread functions[END_REF], producing a transformation image used to warp the tractograms to template space;

(3) generation of subject-specific Fractional Anisotropy (FA) images using iterative least-squares [START_REF] Basser | MR diffusion tensor spectroscopy and imaging[END_REF][START_REF] Veraart | Weighted linear least squares estimation of diffusion MRI parameters : Strengths, limitations, and pitfalls[END_REF], and registered to the template space with the FOD-computed transformation images; (4) Generation of Track-Weighted FA images (TW-FA) by counting the number of tracks traversing a given voxel and weighting this count by the integrity (FA) of each track. We used a Gaussian neighborhood weighting of 25 mm (FWHM) to assess the short-to-mid-range variations in track structural integrity [START_REF] Willats | Quantification of track-weighted imaging (TWI) : Characterisation of within-subject reproducibility and between-subject variability[END_REF].

Statistical analysis

Statistical analysis was conducted in MATLAB (R2020b) and R (4.2.1). We controlled for handedness, gender, MMSE scores, and total intracranial volume in all the models [START_REF] Eikenes | Both brain size and biological sex contribute to variation in white matter microstructure in middle-aged healthy adults[END_REF].

Preliminary analysis

To increase the theoretical relevance of our study, we determined the most relevant age window for cognitive aging with the hypothesis that middle age is a critical period.

Method. We modeled the trajectory of each cognitive score across the lifespan (18-88 years; 628 participants) using generalized additive models (GAM; [START_REF] Wood | Generalized Additive Models (0 éd[END_REF][START_REF] Wood | Generalized Additive Models : An Introduction with R (2 e éd[END_REF]. We then calculated the curvature of each trajectory at each age point, selected the significant values aged adults between the ages of 45 and 60 to target the period of transition associated with the onset of LP-related decline. Specifically, we chose at interval of 15 years that could equally be divided into 3 age groups for later statistical analysis (more details in section 2.3.3).

Neuroanatomical level : Dimensionality Reduction

We explored the relationship between middle age and microstructural alterations in two steps.

First, dimensionality reduction was used to identify a low-dimensional number of white matter networks. We then examined the effects of age on each network's average microstructural integrity. All analyses were performed within a group mask to mitigate the spatial bias due to inter-individual variability and potential shortcomings of registration.

Voxels with null TW-FA values across more than 5% of the participants were not included in the mask.

NMF network segmentation. We employed non-negative matrix factorization with an orthogonality constraint (https://github.com/asotiras/brainparts) to segment whole-brain white matter into networks. NMF is a dimensionality reduction technique widely used in neuroimaging to decompose high-dimensional datasets (e.g., voxel-level data) into meaningful networks [START_REF] Sotiras | Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization[END_REF]. The orthogonality constraint ensured that networks were spatially non-overlapping. That is, each network comprised of a unique set of structurally covarying voxels, indicating that the microstructural integrity changes (TW-FA) along these voxels covary across participants (i.e., either strongly correlated or anticorrelated). Given its recent application in investigating age-related [START_REF] Bagautdinova | Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth[END_REF][START_REF] Lynch | Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI[END_REF][START_REF] Sotiras | Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization[END_REF] and biological processes captured by microstructural changes [START_REF] Patel | Investigating individual variability in microstructural-functional coupling in the human cortex[END_REF][START_REF] Robert | Analyses of microstructural variation in the human striatum using non-negative matrix factorization[END_REF], and given that TW-FA values are non-negative, we considered NMF as an appropriate approach for our research question.

NMF implementation. NMF decomposes the matrix containing all TW-FA images (A) into two matrices: voxel matrix W (voxels × k) and subject matrix H (k × participants). The optimal number of networks k was determined using the procedure described by Network interpretation and composition. To accurately identify the brain pathways involved in each network, we automatically segmented 72 major bundles from the study template SH peaks using TractSeg [START_REF] Wasserthal | TractSeg-Fast and accurate white matter tract segmentation[END_REF] and combined two metrics based on volumetric information (i.e., network and bundle-focused spatial overlap) with one metric based on fiber-connectivity information [START_REF] Bullock | A taxonomy of the brain's white matter : Twenty-one major tracts for the 21st century[END_REF]. We considered brain pathways with a compositive score above or close to 1 as having a significant contribution. Further details are provided in supplementary material (Appendix A).

Age trajectory with GAM. To examine the effect of age, we fitted one GAM model for each network, with subject-level weightings (H values) as the dependent variable. These weightings reflect the average TW-FA values of each subject within a specific network.

GAMs were fitted using restricted maximum likelihood (REML) for an unbiased estimate of fixed effects, a 3-knot spline to address overfitting concerns, and FDR-corrected (q < 0.05).

Neurocognitive level: Partial Least Squares

To examine the many-to-many relationships between age-related white matter integrity changes and LP performance, we employed a Partial Least Squares (PLS) correlation analysis using the toolbox myPLS (https://github.com/MIPLabCH/myPLS). PLS is a data-driven multivariate statistical technique that seeks to optimize the covariance between two datasets [START_REF] Krishnan | Partial Least Squares (PLS) methods for neuroimaging : A tutorial and review[END_REF]. In this study, PLS generates latent components that describe agerelated patterns of covariance (i.e., coordinated changes with age) between Track-Weighted FA (TW-FA) values and cognitive scores related to lexical production (LP).

Multilevel PLS. While previous studies have used network-level NMF loadings in the PLS model (e.g., [START_REF] Patel | Investigating individual variability in microstructural-functional coupling in the human cortex[END_REF][START_REF] Robert | Analyses of microstructural variation in the human striatum using non-negative matrix factorization[END_REF], we reasoned that this may compromise the identification of more localized age effects at the voxel-level that would not have been captured using NMF as they may only appear when jointly considering white matter and cognitive performance changes. For this reason, we ran two models: network-level and voxellevel PLS. This multilevel approach allowed us to examine whether distributed (networklevel) and localized (voxel-level) alterations are differently related to LP performance in middle age.

PLS setup. We organized the data into a structural (X) and cognitive (Y) matrix to set up the PLS. For X, TW-FA loadings (for voxel-level PLS) or NMF loadings (for network-level PLS;

H values) were vectorized, stacked, and z-scored across participants so that each row encoded the values of one subject. For Y, cognitive scores were first quantile-normalized to improve Gaussianity (Pur et al., 2022) and then z-scored before prepending two age-related contrast variables and their respective interaction with the cognitive variables. The contrasts were set between three age groups: (contrast #1) 56-60 > 45-50 + 51-55, (contrast #2) 51-55 > 45-50.

These contrasts ensured that nonlinear relationships with age were accounted for while remaining consistent with the parameter chosen previously for GAM modeling (i.e., 3-knot spline; see section 2.4.1). In this way, PLS allowed us to disentangle the common and differing covariance effects across age groups without disregarding absolute differences in either dataset [START_REF] Zöller | Disentangling resting-state BOLD variability and PCC functional connectivity in 22q11.2 deletion syndrome[END_REF].

PLS implementation and interpretation. To start the PLS, the structural matrix (X) was crosscorrelated with the cognitive matrix (Y), resulting in a covariance matrix (R). Singular value decomposition (SVD) was applied to decompose R, yielding a set of singular value (S), structural (U), and cognitive (V) saliences. The significance of S was assessed using 10,000 permutations and the robustness of salience (U and V) with 1000 bootstrap resamples. S contains singular values that represent the amount of information shared between the two datasets for each latent component (LC). U and V contain salience weights representing the contribution of each voxel or cognitive variable to the pattern of covariance captured by each LC. For each LC, we obtained two latent variables, one structural (LV struct ) and one cognitive (LV cog ), by projecting the saliences back onto the corresponding z-scored dataset (i.e., LV struct = U X and LV cog = V T Y). To assess the robustness of structure and cognitive saliences, we report bootstrap sampling ratios (BSR), calculated as the salience weight over its bootstrapped standard deviation. A high BSR (± 2.58) indicates a robust contribution within a 99% confidence interval [START_REF] Krishnan | Partial Least Squares (PLS) methods for neuroimaging : A tutorial and review[END_REF].

Results

Neuroanatomical level

We applied non-negative matrix factorization (NMF) to identify patterns of white matter microstructural integrity (WMI) changes in middle-aged adults. We identified a total of 16 white matter networks. Six white matter networks showed significant modifications with age, indicating a broad structural reorganization between 45 and 60.

The average WMI of 4 of these 6 networks decreased nonlinearly with age, confirming that middle age is a transition period at the structural level. Specifically, we observed the largest decrease in WMI beyond age 53, compromising widely distributed brain pathways. Figure 2 and the following white matter network presentation are organized based on the extent of change with age, ranging from the most to least significant.

Neurocognitive level

To evaluate the white matter changes supporting the emergence of LP difficulties in middle age, we performed two partial least squares (PLS) analyses: one at the network level to examine the effect of distributed alterations (i.e., network-level PLS) and one at the voxel level to examine the effect of localized alterations (i.e., voxel-level PLS).

In line with our hypothesis, multilevel PLS found two latent components consistent with a domain-general (LC1) and language-specific mechanism (LC2) (Figure 3A). LC1 was significant at both levels of analysis (51.73/19.57% of the total shared variance; singular value = 228.4/9581.1; p Bonferroni = .001/p Bonferroni = .002), and LC2 remained significant only at the voxel level after Bonferroni correction (13.76%; 8033.3; p Bonferroni = .002). The subsections below describe the cognitive and microstructural changes of each component and how their joint dynamic may suggest a relationship between middle-aged LP and the control of semantic representations (interplay LC1-LC2). Cluster analysis was performed using the MATLAB bwconncomp function. Voxels were considered part of the same cluster if they were both salient and connected in one of these directions (in/out, left/right, up/down; 3D connectivity set to 6). Abbreviations: bootstrap sampling ratio (BSR), white matter (WM).

Latent component 1: Domain-general mechanism

The first latent component (LC1) aligned with our previous finding, suggesting that the magnitude of distributed and localized microstructural integrity alterations increases significantly in late middle-aged individuals (BSR 56-60>45-55 = -9.66 for network-PLS/-19.2 for voxel-PLS) and correlated with an acceleration in cognitive decline (correlation between LVs:

.42/.55).

Voxel-level PLS. At the cognitive level, individuals aged 56-60 versus younger adults (contrast 56-60>45-55), had lower performances in tasks related to executive functioning (see Section 2.1.2): multitasking (BSR = -6.59), fluid intelligence (-6.28), directly correlating with direct LP difficulties (naming = -6.22). More marginally, we also found a decline in sentence comprehension (-4.34) and proverb comprehension (-3.32). In comparison, individuals aged 51-55 versus younger middle-aged adults (contrast 51-55>45-50) exhibited a tendency for long-term memory (-2.73) and verbal fluency difficulties (2.69) (Figure 3B).

At the structural level, late middle-aged individuals showed a significant bilateral reduction in microstructural integrity in three localized clusters of white matter accounting for 84.39% of all alterations: Cluster I (37.65%) and Cluster II (35.91%) primarily engaged either left or right, subcortico-frontal and dorsal pathways; Cluster III engaged the cerebellar white matter (10.82%) (see Table 2 & Figure 3C).

Network-level PLS. In line with these results, we found corresponding distributed alterations in all 6 age-related networks (Net 16: -7.21; Net 11: -6.25; Net 5: -6.18; Net 4: -3.73; Net 7: -3.55; Net 14: -3.15; Figure 4B). Specifically, Net 16 (left fronto-parieto-pontine), 11

(thalamo-frontal) and 7 (visual-occipital) robustly underpinned the onset of multitasking difficulties in late middle-age (BSR = -3.2). Net 5 (bilateral association) additionally covaried with verbal fluency abilities and modulation of Net 14 (cerebellar) seemed to underpin a wider range of LP-related tasks except for multitasking (Figure 4A). Displayed on the study template is the average TW-FA image. Abbreviations: bootstrap sampling ratio (BSR).

Latent component 2: Semantic mechanism

The second latent component (LC2) differed markedly from LC1, revealing an intriguing agerelated trajectory stabilizing around aged 51-55 (BSR 51-55>45-50 = 12.41).

Voxel-level PLS. At the cognitive level, individuals aged 51-55 compared to early middleaged adults showed sign of increased semantic knowledge (proverb = 14.76; sentence comprehension = 12.41), translating to better naming (10.02) and long-term memory performances (4.99), and this increase was proportional to the decline in fluid intelligence (-3.88). Interestingly, despite similar activation of semantic representations, late middle-aged adults exhibited significant multitasking (-6.7), naming (-4.56), and semantic abstraction difficulties (-4.18), suggesting that the onset of cognitive control challenges reported in LC1 could regulate the access to semantic representations (Figure 3B).

At the structural level, this pattern of cognitive changes covaried with an increase in microstructural integrity in two clusters of white matter accounting for 81.73% of all modifications: Cluster I (56.5%) and Cluster II (35.23%) primarily engage either left or right thalamo-and striato-sensory pathways (see Table 3 & Figure 3C).

Joint dynamic of LC1 and LC2: Cognitive control over semantic representations

Having established the two structure-cognition patterns of covariance in middle age, we sought to gain additional insight by considering their joint dynamic. Doing so points to an interesting dynamic characterized by divergent middle-aged trajectories: executive functions tend to decline but semantic knowledge accrues. Moreover, these trajectories intersect around age 53-54 (Figure 5), which concurs with the inflection point for accelerated LP-related decline and microstructural integrity damage respectively reported in the preliminary (Section 1.3.1) and neuroanatomical analysis section (Section 2.1).

Discussion

This study evaluated white matter changes supporting lexical production (LP) decline that emerges in middle age. Indeed, healthy aging is associated with a gradual decline in LP, beginning in middle age and manifesting in increased naming latencies. To delay the onset of LP decline as much as possible, middle-aged adults may rely on compensatory mechanisms, as proposed by the LARA model (Lexical Access and Retrieval in Aging; [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF].

However, our knowledge of the white matter changes supporting these mechanisms remains incomplete. Therefore, in this study, we employed advanced machine learning approaches on diffusion-weighted imaging and neuropsychological data from a sample of 155 middle-aged adults to (i) identify the brain pathways undergoing age-related microstructural changes and

(ii) explore how LP performance is related to structural brain reorganization as individuals age.

Consequently, our main findings can be presented at two levels: (a) At a neuroanatomical level, middle age compromises the microstructural integrity of distinct white matter networks, revealing novel associations between brain pathways. (b) At a neurocognitive level, we reaffirm that middle age is a critical period for language processing. Indeed, while early middle-aged adults may rely on significant semantic access to maintain LP performance, our study suggests that late middle-aged adults may fail to exert cognitive control over these semantic representations, eventually leading to word-finding difficulties. The present study furthers our comprehension of middle-aged brain structure changes and sheds light on the neurocognitive transition leading to the onset of LP decline in middle age. We will discuss our neuroanatomical findings and the neurocognitive changes related to LP in middle-aged adults.

From a neuroanatomical standpoint, our results reveal that large-distributed WM pathways undergo coordinated microstructural changes with age. This suggests that short-to-mid-range (i.e., ~25 mm length) microstructural alterations along known brain pathways can be grouped and analyzed within WM networks. Crucially, this network-level approach complements the conventional view that the age-related loss of integrity takes place along dorsoventral [START_REF] Boban | Gradient Patterns of Age-Related Diffusivity Changes in Cerebral White Matter[END_REF][START_REF] Zahr | Problem solving, working memory, and motor correlates of association and commissural fiber bundles in normal aging : A quantitative fiber tracking study[END_REF] and antero-posterior gradients [START_REF] Bennett | Age-related differences in multiple measures of white matter integrity : A diffusion tensor imaging study of healthy aging[END_REF][START_REF] Boban | Gradient Patterns of Age-Related Diffusivity Changes in Cerebral White Matter[END_REF]. Indeed, our results reveal that the SLF (II/III) and thalamo-frontal pathways, often attributed with the largest age-related changes [START_REF] Bonifazi | Structure-function multi-scale connectomics reveals a major role of the fronto-striato-thalamic circuit in brain aging[END_REF][START_REF] Hughes | Regional changes in thalamic shape and volume with increasing age[END_REF][START_REF] Troutman | Cerebral White Matter Mediation of Age-Related Differences in Picture Naming Across Adulthood[END_REF], are part of heterogeneous WM networks bind together by callosal fibers: the posterior midbody (CC6) binds association pathways (SLF II and SLFIII/MLF; Net 5), and the rostrum and genu (CC1/2) bind anterior cortico-subcortical pathways (e.g., ATR, T PREF, FPT; Net 11). Temporally, the WM networks most affected by age (i.e., Net 16, 5, 11, 4) showed the largest microstructural alterations occurring from age 53 onwards. This aligns with previous studies concluding that discontinuities (i.e., nonlinear trajectory) in brain structure are likely to onset at middle age [START_REF] Beck | White matter microstructure across the adult lifespan : A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction[END_REF][START_REF] Park | The Middle-Aged Brain[END_REF] and further reinforces the idea that midlife is a critical period of major brain structural reorganization in line with reports on brain function and language performance [START_REF] Deery | The older adult brain is less modular, more integrated, and less efficient at rest : A systematic review of largescale resting-state functional brain networks in aging[END_REF][START_REF] Hennessee | Relationship of prefrontal brain lateralization to optimal cognitive function differs with age[END_REF][START_REF] Park | The Middle-Aged Brain[END_REF][START_REF] Roger | When Age Tips the Balance : A Dual Mechanism Affecting Hemispheric Specialization for Language[END_REF]Shafto & Tyler, 2014). Overall, our study supports the current evidence that dorso-ventral association (SLF II/III, MLF) and anterior cortico-subcortical pathways suffer the largest age-related microstructural alterations [START_REF] Gunning-Dixon | Aging of cerebral white matter : A review of MRI findings[END_REF][START_REF] Park | The Middle-Aged Brain[END_REF][START_REF] Yeatman | Lifespan maturation and degeneration of human brain white matter[END_REF]. Specifically, the reduction of TW-FA in the anterior corpus callosum (CC1/2) and deep (pre-)frontal regions suggests that fibers of the forceps minor could be preferentially affected [START_REF] Hsu | Gender differences and age-related white matter changes of the human brain : A diffusion tensor imaging study[END_REF][START_REF] Kelley | Age-related differences in white matter : Understanding tensor-based results using fixel-based analysis[END_REF], along with critical age-related modulation of the integrity of frontolimbic, and fronto-parieto-pontine fibers (i.e., FPT, POPT). Nonetheless, we also note that more posterior brain pathways do not show evidence for such disruptions. That is, cerebellar (Net 14) and visual-occipital (Net 7) pathways tend to exhibit a weaker and continuous (i.e., linear) loss in microstructural integrity as individuals age.

From a methodological standpoint, our results advocate for a network-level approach to complement anatomically defined bundle atlases [START_REF] Bullock | Associative white matter connecting the dorsal and ventral posterior human cortex[END_REF][START_REF] Bullock | A taxonomy of the brain's white matter : Twenty-one major tracts for the 21st century[END_REF]Catani & Thiebaut De Schotten, 2008;[START_REF] Mori | Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template[END_REF][START_REF] Rojkova | Atlasing the frontal lobe connections and their variability due to age and education : A spherical deconvolution tractography study[END_REF][START_REF] Wasserthal | TractSeg-Fast and accurate white matter tract segmentation[END_REF], leading to novel associations between brain pathways free from explicit spatial constraints [START_REF] Bagautdinova | Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth[END_REF]. Ultimately, this emphasizes the need to apply advanced data-driven tools (i.e., dimensionality reduction via NMF; [START_REF] Sotiras | Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization[END_REF] to capture the complexity of WM changes. This opens new research avenues for building complex yet highly interpretable models to explore how brain structure constrains brain function, for example projecting the functional signals onto white matter pathways of interest (see the functionnectome by [START_REF] Nozais | Functionnectome as a framework to analyse the contribution of brain circuits to fMRI[END_REF][START_REF] Nozais | Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain[END_REF] and, more broadly, assess the coupling between microstructure and brain function (e.g., [START_REF] Patel | Investigating individual variability in microstructural-functional coupling in the human cortex[END_REF] (see also [START_REF] Calhoun | Multimodal fusion of brain imaging data : A key to finding the missing link(s) in complex mental illness[END_REF] for a review on data fusion methods).

From a neurocognitive standpoint, our analyses offer new insights into the brain structure dynamics involved in maintaining lexical production (LP) performance in middle age. In line with our hypothesis, two latent components, LC1 and LC2, were identified, corresponding to the Domain-General (DG) & Language-Specific (LS) mechanisms posited in the LARA model (Lexical Access and Retrieval in Aging; [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF].

On one hand, LC1 indicated a decline in DG processes in late middle-age, such as multitasking and fluid intelligence, coinciding with the onset of LP difficulties, particularly in naming. This aligns with evidence linking the speed of lexical retrieval and the generation of lexical predictions to fluid processing abilities [START_REF] Brothers | Goals and strategies influence lexical prediction during sentence comprehension[END_REF][START_REF] Strijkers | Early Goal-Directed Top-Down Influences in the Production of Speech[END_REF].

Specifically, this suggests that LP demands substantial cognitive effort, as older adults' [START_REF] Hafkemeijer | Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults[END_REF][START_REF] Roger | Unraveling the functional attributes of the language connectome : Crucial subnetworks, flexibility and variability[END_REF], with the cingulum bundle being closely linked with inhibition tasks [START_REF] Ribeiro | White matter tracts and executive functions : A review of causal and correlation evidence[END_REF]; (ii) the anterior cortico-subcortical pathways (Net 11), especially right striato-prefrontal pathways [START_REF] Buckner | Memory and Executive Function in Aging and AD[END_REF][START_REF] Webb | Frontostriatal white matter connectivity : Age differences and associations with cognition and BOLD modulation[END_REF] and the right anterior thalamic radiations for response inhibition [START_REF] Ribeiro | White matter tracts and executive functions : A review of causal and correlation evidence[END_REF]; (iii) the SLF II and MLF for mental flexibility (Net 5) [START_REF] Ribeiro | White matter tracts and executive functions : A review of causal and correlation evidence[END_REF][START_REF] Rizio | Language, aging, and cognition : Frontal aslant tract and superior longitudinal fasciculus contribute toward working memory performance in older adults[END_REF][START_REF] Troutman | White matter disconnection is related to age-related phonological deficits[END_REF]. The link between DG and LP is further evidenced by a recent longitudinal study showing that the inability of structural brain networks to facilitate effortful brain state transitions is primarily associated with a deficit in executive functions [START_REF] Tang | Longitudinal association of executive function and structural network controllability in the aging brain[END_REF]. Of note, LC1 was also associated with minor sentence comprehension difficulties in late middle age. This could further underscore the high cognitive demands of LP, considering that lexical prediction is influenced by topdown comprehension strategies [START_REF] Brothers | Goals and strategies influence lexical prediction during sentence comprehension[END_REF].

On the other hand, LC2 revealed enhanced sentence comprehension, semantic abstraction, and long-term memory processes up until age 53-54. Interestingly, these changes were proportional to both (a) the increase in naming performances and (b) the decline in fluid abilities faced in early middle age. Given the constraint that fluid processing places on LP, this suggests that such an increase in semantic representations could provide the basis of a compensatory "semantic strategy" to maintain LP performance despite a decline in fluid-related abilities (e.g., problem-solving, learning). This is consistent with the idea that older adults may compensate for age-related decline in "control over LP" with higher vocabulary knowledge [START_REF] Gollan | Aging deficits in naturalistic speech production and monitoring revealed through reading aloud[END_REF]. This also confirms that semantic knowledge accumulated over the lifespan [START_REF] Salthouse | Trajectories of normal cognitive aging[END_REF][START_REF] Spreng | The Shifting Architecture of Cognition and Brain Function in Older Adulthood[END_REF]) is a viable alternative to meet reduced fluid processing with increased associative processing, thus lowering the control demands during LP [START_REF] Spreng | From exploration to exploitation : A shifting mental mode in late life development[END_REF]. Structurally, this tendency towards an increasingly "semanticized" cognition [START_REF] Spreng | Semanticized autobiographical memory and the defaultexecutive coupling hypothesis of aging[END_REF] 5). This supports the idea that semantic cognition depends on both representational and control neural systems [START_REF] Hoffman | What determines cognitive estimation ability? Changing contributions of semantic and executive domains as a function of age[END_REF][START_REF] Wu | Age differences in the neural processing of semantics, within and beyond the core semantic network[END_REF], with semantic control regulating access to semantic representations [START_REF] Branzi | Semantic-specific and domain-general mechanisms for integration and update of contextual information[END_REF][START_REF] Ralph | The neural and computational bases of semantic cognition[END_REF].

Taken together, our investigation provides empirical evidence in favor of the LARA model [START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF] by suggesting that the interplay between domain-general (DG) and language-specific (LS) mechanism is crucial to understanding the onset of word-finding difficulties in the middle age. Importantly, this reaffirms that LP is a highly integrative cognitive function and the product of intra-(LS) and extra-(DG) linguistic processes [START_REF] Hagoort | The neurobiology of language beyond single-word processing[END_REF][START_REF] Hertrich | The Margins of the Language Network in the Brain[END_REF][START_REF] Roger | Missing links : The functional unification of language and memory (L∪M)[END_REF]. While middle-aged adults may adopt a compensatory "semantic strategy" to delay the onset of word-finding difficulties, this strategy may be compromised in late middle age when the ability to exert cognitive control over semantic representations is challenged, translating into a poorer filtering of irrelevant semantic associations (i.e., reduced semantic selection; [START_REF] Badre | Left ventrolateral prefrontal cortex and the cognitive control of memory[END_REF][START_REF] Barba | Confabulation in healthy aging is related to interference of overlearned, semantically similar information on episodic memory recall[END_REF][START_REF] Jefferies | The neural basis of semantic cognition : Converging evidence from neuropsychology, neuroimaging and TMS[END_REF].

Taking a broader perspective, this transition in midlife echoes recent proposals advocating for a learning-to-prediction shift (R. M. [START_REF] Brown | Prediction in the Aging Brain : Merging Cognitive, Neurological, and Evolutionary Perspectives[END_REF] from an explorative to an exploitative cognitive mode [START_REF] Hills | Exploration versus exploitation in space, mind, and society[END_REF]; see Spreng & Turner, 2021 for a review), ultimately disproving that cognitive aging is solely synonymous with cognitive decline [START_REF] Spreng | The Shifting Architecture of Cognition and Brain Function in Older Adulthood[END_REF]. Indeed, exploiting accumulated semantic knowledge resources can be viewed as a predictive process, providing sufficient flexibility for comparing sensory inputs against long-term memory traces when given ambiguous, noisy, or incomplete lexical information [START_REF] Bar | The proactive brain : Using analogies and associations to generate predictions[END_REF][START_REF] Bubic | Prediction, cognition and the brain[END_REF]. In the context of LP, this signifies that middle-aged adults are better equipped to produce utterances elicited by semantic and/or episodic associations (i.e., inferential naming) compared to a typical picture naming task (i.e., referential naming) [START_REF] Fargier | Referential and inferential production across the lifespan : Different patterns and different predictive cognitive factors[END_REF]. In the context of semantic processing, this is consistent with studies reporting that older adults make less use of contextual information as noted by [START_REF] Jongman | Age-related changes in the structure and dynamics of the semantic network[END_REF].

Limitations and Perspectives. We mention that we did not explicitly model cognitive reserve factors despite their key role in capturing the inter-individual variability in language processing [START_REF] Chan | Lifestyle activities in mid-life contribute to cognitive reserve in late-life, independent of education, occupation, and late-life activities[END_REF][START_REF] Oosterhuis | Getting the brain into gear : An online study investigating cognitive reserve and word-finding abilities in healthy ageing[END_REF] As methodological limitations of our study, we mention that relaxing the orthogonality constraint when performing NMF (Non-Negative Matrix Factorization; see Section 2.3) would be interesting to identify white matter regions overlapping with more than one WM network [START_REF] Patel | Inter-and intra-individual variation in brain structural-cognition relationships in aging[END_REF][START_REF] Patel | Investigating individual variability in microstructural-functional coupling in the human cortex[END_REF]. This is particularly relevant at crossing fiber locations, considering that fiber from different bundle types may cross the same white matter area with a different orientation, thus not necessarily sharing the same component from the NMF solution. Additionally, we acknowledge that the voxel-wise analyses conducted in this study are insufficient for distinguishing fiber differences in white matter alterations in crossing fiber locations. Further analysis showed that cognitive control decline in our voxel-level PLS model was partially associated with a putative integrity increase from the corpus callosum's splenium extending to the right TPJ (see bottleneck region of crossing fibers along an anterior-posterior axis [START_REF] Schilling | Prevalence of white matter pathways coming into a single white matter voxel orientation : The bottleneck issue in tractography[END_REF].

This suggests that this localized increase may be deceitful and instead reflect fiber-specific degeneration [START_REF] Han | Fiber-specific age-related differences in the white matter of healthy adults uncovered by fixel-based analysis[END_REF]. Considering that age-related differences have also been reported in crossing fibers in addition to individual fiber segments [START_REF] Kelley | Age-related differences in white matter : Understanding tensor-based results using fixel-based analysis[END_REF], fixelbased analysis (FBA) would have been more accurate [START_REF] Dhollander | Fixel-based Analysis of Diffusion MRI : Methods, Applications, Challenges and Opportunities[END_REF]. However, we preferred not to perform FBA in this study, considering that the b-values (1000 and 2000 s/mm²) in this study are insufficient to attenuate the extra-axonal water signal, meaning that signals from the extra-cellular space outside the axons would contribute to a biased apparent fiber density, rendering "biological interpretation challenging and fundamentally limited" (p.9, [START_REF] Dhollander | Fixel-based Analysis of Diffusion MRI : Methods, Applications, Challenges and Opportunities[END_REF]. Additionally, to our knowledge, MRtrix3 (version 3.0.4; [START_REF] Tournier | MRtrix3 : A fast, flexible and open software framework for medical image processing and visualisation[END_REF], does not yet offer users a weighted variant of the streamline-to-voxel algorithm. This means that track-weighted-FA images could not be weighted by the length of the streamline traversing the voxel, resulting in a less accurate contrast.

Finally, out-of-sample replication using larger, independent, and longitudinal databases would also enhance the reliability of our results in light of recent reports showing that cross-sectional studies may largely be underpowered for brain-behavior associations [START_REF] Gratton | Brain-behavior correlations : Two paths toward reliability[END_REF][START_REF] Marek | Reproducible brain-wide association studies require thousands of individuals[END_REF]. Additional investigations using a multiple DTI metric (e.g., AD, RD)

would also give us a better outlook on age-related biological changes such as demyelination, axonal damage, as well as mild or chronic microstructural alterations [START_REF] Molloy | Alterations in Diffusion Measures of White Matter Integrity Associated with Healthy Aging[END_REF], leveraging sophisticated machine learning techniques (e.g., [START_REF] Mishra | Swiss knife partial least squares (SKPLS) : One tool for modelling single block, multiblock, multiway, multiway multiblock including multi-responses and meta information under the ROSA framework[END_REF]

Conclusion

In this study, we aimed to disentangle the WM changes related to lexical production (LP) difficulties, typically beginning in middle age. Our findings underscore that midlife is a pivotal period characterized by a discontinuity in brain structure within distributed networks mainly comprised of dorsal, ventral, and anterior cortico-subcortical pathways. Importantly, this discontinuity signals a neurocognitive transition around age 53-54, marking the onset of LP decline. While middle-aged adults may initially adopt a "semantic strategy" to compensate for the initial LP challenges, this strategy may be compromised as late middle-aged adults (age 55-60) lose the ability to exert cognitive control over semantic representations. Taken together, our study (i) emphasizes the importance of considering the interplay between domain-general and language-specific processes when studying the cerebral substrates of lexical production and (ii) reaffirms that sophisticated statistical analysis techniques studies applied to the middle-aged population is a promising avenue for identifying predictive biomarkers of neurodegenerative pathologies.

  (i.e., confidence intervals do not contain 0), and averaged them across the seven cognitive scores. The inflection point of cognitive aging corresponds to the point at which the curvature crosses zero (i.e., changes its sign). Computational details are available in supplementary material (Appendix A). Results. Age 53-54 is the average inflection point for LP-related performance This confirms that middle age is a critical period for cognitive aging and indicates a sudden acceleration in cognitive decline around this age, specifically driven by a drop in executive function performances (i.e., fluid intelligence via the Cattell task). After visually inspecting Figure A.3 (please refer to Appendix A), we selected a sample of middle-

  [START_REF] Bagautdinova | Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth[END_REF]: We performed NMF 10 times, incrementing the number of networks at each iteration (i) from k=2 two k=20 by steps of 2. The reconstruction error (RE), calculated as the Frobenius norm of the difference between the input and reconstructed matrix (Eq.2), guides the selection of the optimal k. The gradient of this error (GradientRE), representing the difference between reconstruction errors of two successive iterations (Eq.3), helped identify the point after which decomposing A into more networks yielded diminishing returns on model fit(Figure A.4, Appendix A).

Figure 2 :

 2 Figure2: Age-related white matter networks. Age trajectory: Plots display the significant relationships between TW-FA (track-weighted microstructural integrity) and age quantified by generalized additive models. Bars above the x-axis represent the derivative of the fitted GAM smooth function and correspond to age windows of significant changes. The color of this bar indicates the magnitude of the TW-FA change with age: orange when increasing (i.e., positive derivative), purple when decreasing (i.e., negative derivative), and white when no significant change was found. A derivative was considered significant when its confidence interval did not contain zero. The networks are sorted from the one showing the strongest (top left) to the one showing the weakest age-related effect (bottom right). Word cloud: Depicts the major brain pathways a given network engages (see Appendix A for details on calculations). Tract names correspond to the TractSeg nomenclature (https://github.com/MIC-DKFZ/TractSeg). Brain illustration. Depicts the bundle fibers (min. length 25 mm) crossing one or many of the voxel clusters associated with a given network. Fiber orientations: red (left-right), green (anterior-posterior), and blue (superior-inferior). Displayed on a mesh of the average TW-FA image using the Surf Ice software (https://www.nitrc.org/projects/surfice/). Abbreviations: L (left), R (right), Ant (anterior), Post (posterior), Sup (superior), Inf (inferior).In the discussion section, we discuss extensively how the following Net 16, 5, and 11 may

Figure 3 :

 3 Figure 3: Results from voxel-level PLS analyses. (A) Depicts the 2D latent space across middle-aged groups. For each latent component (LC1 and LC2), latent cognitive and structural scores were combined with a PCA for visualization. See Figure B.3, Appendix B for the detail on each component and Figure B.1-2, Appendix B for diagnostic plots (B) Cognitive saliences. Only the variables with a robust contribution to the latent component are reported (i.e., bootstrap sampling ratio ± 2.58). Bars extend to the corresponding salience weight (U), and error bars indicate the bootstrapped standard deviation. (C) Brain saliences. Blue/green indicates a decrease in white matter microstructural integrity, and red/yellow indicates an increase. Please see Figure B.4, Appendix B for the raw brain saliences. Displayed on the study template is the average TW-FA image.Cluster analysis was performed using the MATLAB bwconncomp function. Voxels were considered part of the same cluster if they were both salient and connected in one of these directions (in/out, left/right, up/down; 3D connectivity set to 6). Abbreviations: bootstrap sampling ratio (BSR), white matter (WM).

Figure B. 5 ,

 5 Figure B.5, Appendix B). This is in line with high residual variability found along the latent

Figure 4 :

 4 Figure 4: Results from network-level PLS. (A) Covariance matrix. (B) Brain structural saliences. Displayed on the study template is the average TW-FA image. Abbreviations: bootstrap sampling ratio (BSR).

Figure 5 .

 5 Figure 5. Compensatory dynamic of lexical production difficulties in midlife. Each component's latest cognitive and structural variables were combined with a PCA for visualization. Bars above the x-axis represent the second-order derivative of the fitted GAM smooth function in red. A blue hue indicates a period of transition during middle age. A derivative was considered significant when its confidence interval did not contain zero.

  Figure B.4, Appendix B). Specifically, the bundles converging to the right TPJ (see Figure B.7, Appendix B) have been reported to form a

Table 1 .

 1 Presentation of the eight neuropsychological tests considered in this study and associated cognitive processes. A detailed description can be found in Table A.1, Appendix A, and the effect of age on cognitive performances is illustrated in Figure A.2, Appendix A.

Table 2 .

 2 Brain pathways contributing to LC1. Numerical values are a z-scored composite metric based on volumetric and connectivity-based overlap with the robust brain saliences (please refer to Appendix A for details). A score above 1 shows a significant contribution. Pathways highlighted in bold font show the highest contribution. Tract names correspond to the TractSeg nomenclature (https://github.com/MIC-DKFZ/TractSeg).

	Brain pathways	Cluster I	Cluster II	Cluster III
	FPT	1.93	1.44	/
	T PREF/ST PREF	2.04/1.81	1.72/1.83	/
	ATR	1.5	1.53	/
	SLF I/II/III	1.26/1.31/-	1.08/1.31/1.16	/
	CC/CC 2	1.72/1.19	1.8/1.23	/
	IFO/CG/AF	/	1.19/1.18/1.17	/
	T PREM/PREC	1.09/1	/	/
	ST PREM/PREC/POSTC	-/1.04/0.94	1.11/1.14/0.98	/
	MCP	/		4.66
	ICP	/		3.9 bilat.
	SCP	/		left: 2.26 & right: 2.33

Moreover, we found a robust contribution from networks not previously associated with age (primarily Net 8, Net 9, and Net 15 covarying with multitasking and long-term memory; see

Table 3 . Brain pathways most contributing to LC2.

 3 Numerical values are a z-scored composite metric based on volumetric and connectivity-based overlap with the robust brain saliences (please refer to Appendix A for

	Brain pathways	Cluster I	Cluster II
	STR	2.22	2.54
	T PREC/ST PREC	2.05/1.78	2.09/1.71
	T POSTC/ST POSTC	1.88/1.6	2.12/1.74
	FPT	1.71	/
	POPT	1.78	2
	CST	1.82	1.62
	T PREF/PREM	1.32/1.3	/
	T PAR/ST PAR	1.54/1.28	2.11/1.88
	SLF II	1.01	1.18

details). A score above 1 shows a significant contribution. Pathways highlighted in bold font show the highest contribution. Tract names correspond to the TractSeg nomenclature (https://github.com/MIC-DKFZ/TractSeg).

  is associated with enhanced microstructural integrity in a left-dominant cortico-subcortical network (e.g., STR, T/ST PREC, T/ST POSTC), aligning with the idea that thalamocortical pathways are crucial for stable semantic representations at the semantic-lexical interface[START_REF] Crosson | The Role of Cortico-Thalamo-Cortical Circuits in Language : Recurrent Circuits Revisited[END_REF].Critically, our investigation sheds light on the interplay between DG and LS during middle age, suggesting that sufficient cognitive control is key to the compensatory "semantic strategy". Indeed, in late middle age, LP decline co-occurs with significant DG deficits and increased semantic abstraction difficulties in LS. Yet, the brain structural changes of LS in late middle-aged adults remain comparable with that of younger adults (age 51-55), indicating late middle-aged difficulties are not underpinned by reduced semantic knowledge. Said differently, a richer repertoire of stored semantic resources in middle age, as captured by LS, appears to be a necessary but insufficient condition to maintain LP performance in late middle age. Instead, we argue that the compensatory dynamic of middle-aged LP is driven by the ability to use flexibly and abstract this semantic knowledge, that is the DG-LS interplay (as depicted in red in Figure

  see also the dynamic framework proposed by the STAC-R model[START_REF] Reuter-Lorenz | Cognitive aging and the life course : A new look at the Scaffolding Theory[END_REF]. Relatedly, in our PLS model (please refer to Figure3A), the residual variability highlights that age-invariant factors (e.g., lifestyle, leisure activities, socio-demographics) could affect LP performance (see also[START_REF] Gallo | Cognitive Trajectories and Dementia Risk : A Comparison of Two Cognitive Reserve Measures[END_REF] for the association between residual-based measures and cognitive trajectories in late life). Indeed, we observed that the DG component (LC1) was also driven by brain structure changes in white matter networks, showing no significant association with age alone. This further ties in with our hypothesis, stating that DG processes are associated with reserve aging, potentially indexing the age-invariant search and retrieval of less salient semantic knowledge[START_REF] Hoffman | An individual differences approach to semantic cognition : Divergent effects of age on representation, retrieval and selection[END_REF]. Future research should investigate how cognitive reserve factors modulate the reported modified white matter networks, by considering universal and idiosyncratic mechanisms[START_REF] Baciu | Strategies and cognitive reserve to preserve lexical production in aging[END_REF]. Appendix B for details). This could indicate that all other things being equal, women may more readily manipulate and generalize stored semantic knowledge, contributing to further delay of the onset of word-finding difficulties. Another question remains to understand how this compensatory dynamic pattern translates to pathological aging. For example, one could hypothesize that individuals with neurocognitive disorders would show noticeably limited increases in semantic representations with age or that the ability to access stored semantic knowledge flexibly is compromised early on, resulting in heightened LP deficits. In sum, this perspective offers a promising avenue for establishing whether and how these midlife compensatory mechanisms could capture early signs/trends of neurodegenerative pathology (i.e., neurocognitive biomarkers), paving the way for targeted and anticipated cognitive rehabilitation.

	Similarly, while we controlled for gender differences, our findings would certainly benefit
	from directly investigating the effect of this variable, especially given that middle-aged
	women tend to preserve semantic access longer than men as age increases (i.e., higher
	sentence comprehension performances in late middle age, see Section 2.1.1). In line with this,
	supplementary analysis suggests that men's ability to exploit stored semantic resources (LS
	mechanism) is delayed compared to women. Accordingly, the neurocognitive transition
	signaling the onset of LP difficulties (i.e., DG-LS interplay) is likely to occur earlier (age 52
	vs. 54) (please see Figure B.6,

Acknowledgments

This work has been supported by the ANR project ANR-15-IDEX-02. This project has received financial support from the CNRS through the MITI interdisciplinary programs. The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) research was supported by the Biotechnology and Biological Sciences Research Council (grant number BB/H008217/1).

Data and code availability statement

Code is available at https://github.com/LPNC-LANG/MiddleAge_LARA2024.

Supplementary files for MRI data processing and visualization can be found at https://zenodo.org/doi/10.5281/zenodo.10423906.

Conflict of interest statement

Authors declare no conflict of interest.

Supplementary materials

Appendix A. Supplementary material and methods.

Appendix B. Supplementary results.


Martin Mulsow

Savoirs

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Compte-rendu de Martin Mulsow, Savoirs précaires. Pour une autre histoire des idées à l'époque moderne, trad. par L. Cantagrel et L. Windels, Paris, Éd. de la Maison des sciences de l'homme, [2012] 2018, VIII-429 p.

Annales. Histoire, Sciences Sociales 78, no. 3 (2023), 592-4.

La précarité a toujours affecté la fabrique des savoirs, comme le rappelle Martin Mulsow dans ce beau livre : fragilité des supports, défaveur de certains champs et de certaines approches, incertitude et instabilité des carrières. Dix ans après la parution de la version allemande, cet ouvrage reste d'actualité. Actualité politique, puisqu'il pose des questions au XVIII e siècle allemand (par exemple, comment la menace de précarité a-t-elle façonné les oeuvres et leur transmission ?) qui résonnent avec force dans notre présent. Pensons au mouvement #IchBinHanna de 2021, qui mit la question de la précarité universitaire au coeur du débat public en Allemagne, un pays où deux-tiers des emplois scientifiques sont temporaires et généralement limités à un total de six ans après le doctorat. Actualité scientifique, également, puisque les propositions de Mulsow restent novatrices dans le champ de l'histoire des idées et Mais la transmission de ces savoirs resta toujours précaire. Si leur passage de père en fils pourrait sembler le plus sûr dans un premier temps, M. Mulsow montre qu'il en était loin d'être ainsi. L'héritage intellectuel d'un aïeul pesait lourd sur les épaules de plus d'un lettré. La bibliothèque du pasteur hambourgeois Abraham Hinckelmann regorgeait de manuscrits kabbalistiques (qu'il finit par vendre) d'un grand-père dont la pensée l'embarrassait grandement dans un contexte de forte tension religieuse. Les circulations physiques des manuscrits ne fut pas moins difficile. C'est ce que le polymathe Christoph August Heumann, de Göttingen, apprit à ses dépens lorsque les milliers de pages de ses précieux cahiers de lecture, qu'il avait prêté à son jeune collègue Johann Jakob Brucker, s'égarèrent mystérieusement au cours de leur renvoi, peut-être par oeuvre d'un de ses plus farouches ennemis. Au-delà de l'anecdote, cet incident nous rappelle l'importance des bibliothèques manuscrites privées et d'une histoire des idées qui ne se limite pas aux ouvrages imprimés.

  de l'érudition : pour preuve la traduction américaine du livre qui vient de paraître en 2022 1 . Il sera question ici de l'édition française de 2018, publiée dans la « Bibliothèque allemande » des Éditions de la MSH, une collection précisément dédiée à faire connaître des travaux allemands en France. On ne peut que s'en réjouir. M. Mulsow, titulaire de la chaire « Cultures savantes dans l'Europe moderne » à l'université d'Erfurt et directeur du centre de recherche sur l'histoire des savoirs des temps modernes à Gotha, est un historien des idées renommé et un des grands spécialistes des Lumières allemandes. Son oeuvre, foisonnante et influente, était pourtant peu connue du public francophone avant cette traduction, si ce n'est par un article de 2009 dans les Annales sur les « constellations philosophiques » 2 . Savoirs précaires synthétise bien la démarche que M. Mulsow a privilégié dans l'ensemble de ses travaux. Les objets traités sont d'une multiplicité frappante (livres et bibliothèques, manuscrits et peintures, gestes et « vertus », personae et communautés, transferts intergénérationnels et communications postales, l'Orient et la magie), comme le sont les approches utilisées pour les étudier (des études visuelles à l'histoire des sciences, de l'histoire de l'information à la sociologie du travail). Le tout est mobilisé pour mieux étudier un sujet sur lequel Mulsow est un expert reconnu : le Frühaufklärung ou pré-Lumières allemandes des années 1680-1720 et les courants libertins, clandestins et radicaux qui leur étaient associés, avec des incursions occasionnelles dans la Venise du premier XVII e siècle et le Paris de Louis XIV. La question qui guide l'ouvrage est elle aussi l'une de celles posées par l'auteur dans un grand nombre de ses travaux : qu'est-ce que les apports historiographiques hors de l'histoire des idées (tournant matériel, études visuelles, histoire culturelle) imposent à celle-ci en termes d'approche ? M. Mulsow explore cette question à partir de la notion de précarité. Du moment où l'on passe par « les pratiques des acteurs concernés », l'histoire des idées « ne peut pas faire l'économie de[s] contingences » qui façonnent leur fabrique et leur transmission (p. 14). Envisagés de ce point de vue, les savoirs -et surtout ceux en lien avec les courants radicaux qui sont au coeur du livre -apparaissent hantés par des aléas qu'il est impossible de concilier avec tout récit triomphaliste : les manuscrits brûlent ou s'égarent en route ; les carrières savantes se défont avec la perte d'un protecteur ou face aux concurrences universitaires ; la préservation de certaines oeuvres devient d'autant plus incertaine que leurs auteurs ne peuvent les diffuser de leur vivant que de manière clandestine. Le livre se déploie en quatorze chapitres issus de communications que l'auteur a faites pendant sept ans. Bien que la cohérence du volume se dilue dans la grande diversité thématique des parties et le fil conducteur de la précarité devient parfois anecdotique, chaque chapitre est une perle d'érudition et de créativité. Deux thèmes transversaux semblent émerger dans l'ensemble : la précarité des savants et de certains savoirs, d'une part ; et la précarité matérielle des supports et des transmissions, de l'autre. La précarité sociale était criante chez les lettrés dont la proximité avec les idées clandestines rendait la carrière, et parfois la vie, incertaines. Theodor Ludwig Lau, étudiant de Christian Thomasius, se coupe les veines du poignet face aux persécutions et à l'impossibilité de faire publier ses travaux ; Peter Friedrich Arpe, quant à lui, survit comme précepteur et grâce à de petites postes à l'Université qui restèrent toujours temporaires. Face à une histoire intellectuelle qui continue souvent à glorifier les grands noms et leurs oeuvres, M. Mulsow met à profit son incontestable maîtrise de fonds archivistiques épars, peu connus et difficiles, pour aborder ce qu'il identifie comme des « figures de deuxième voire de troisième rang » (p. 20, 304). Il le fait à partir de ce qu'il appelle le « précariat savant », en écho au « prolétariat littéraire » de Robert Darnton 3 . Mais le but de M. Mulsow est avant d'éviter toute réification des positions sociales et philosophiques. Certains savants se dédoublèrent entre une persona publique et une autre privée : soit en diffusant leurs travaux radicaux sous couvert d'anonymat ou sous pseudonyme, par peur à tomber dans la précarité ; soit, pour ceux qui menaient des existences déjà bien fragiles, comme Lau, en présentant leurs prises de position publiques hétérodoxes comme de simples exercices de pensée qui ne s'opposaient pas à une persona privée de bon chrétien et citoyen loyal. En fait, ces penseurs n'étaient souvent pas des fervents défenseurs d'idées fixes, comme l'opposition entre Lumières radicales et modérées le suggérerait, mais des partisans d'une pluralité idéologique à outrance. Avec le clivage entre précariat et bourgeoisie savants, M. Mulsow ne vise pas tant des inégalités de classe ou de statut social, ou des prises de position philosophiques inébranlables, que des réalités plus complexes et changeantes qui furent à la fois sociales et intellectuelles. Ces savoirs proscrits et clandestins étaient eux-mêmes précaires du fait de l'incertitude des conditions matérielles de leur production et de leur transmission, un aspect qui est sans doute l'un des plus fascinants de l'ouvrage. Ce que M. Mulsow nous montre en fin de compte est que la consécration savante des individus et des oeuvres a largement été une affaire d'opportunité matérielle. La survie des oeuvres, pour la plupart manuscrites ou imprimés à très peu d'exemplaires, fut une obsession particulièrement pressante pour les auteurs clandestins. « Comment des oeuvres peuvent-elles être cachées et sauvées à la fois ? » (p. 37). Ayant largement échoué à se faire imprimer, Lau composa à la fin de sa vie une liste de ses travaux pour essayer d'en rendre au moins l'existence publique ; une bonne partie d'entre eux furent d'ailleurs perdus lorsqu'on mit feu à sa maison à deux reprises. Face au morcellement des milieux clandestins, la transmission des savoirs interdits passait souvent par les collections : collections physiques de clandestina ou d'écrits réprimés, tout d'abord, qui offraient dans le même temps de rares espaces de sociabilité radicale ; collections sur papier, également, sous forme de bibliographies. Les deux étaient souvent liées : Johann Heinrich Heubel put projeter une Bibliotheca Vulcani d'ouvrages brûlés, restée manuscrite, grâce à ses voyages diplomatiques dans des villes où ces collections et cercles clandestins existaient.

  Il pointe aussi vers la capacité de M. Mulsow à utiliser des matériaux d'une grande diversité. À son étude pointue des textes imprimés viennent s'ajouter l'analyse d'annotations manuscrites marginales (par exemple, celles d'Arpe sur une copie de sa propre Apologia pro Vanino en vue d'une édition augmentée), de cahiers de lecture (ceux, très nombreux, que Johann Christoph Wolf compila d'une écriture microscopique au sujet de savoirs orientaux) et d'images (les représentations emblématiques de la vérité par Pietro della Vecchia). Les images ont une place centrale dans sa démarche. L'analyse palpitante du Portrait d'un jeune homme de della Vecchia, qu'il relie à la circulation des travaux du mathématicien Erhard Weigel en Italie du Nord à partir d'une feuille volante peinte sur le tableau, est représentative d'une méthode d'historien-détective qui procède « d'énigme en énigme » (p. 197). Là où les traces manquent, l'auteur tire des hypothèses, mais toujours avec une importante prise en compte des contextes. De tout cela, « en résulte-t-il une autre histoire des idées à l'époque moderne » (p. 304), comme M. Mulsow se le demande lui-même en conclusion ? Le sentiment de nouveauté est certainement accru par la manière vertigineuse qu'a l'auteur de mobiliser des notions endogènes à l'histoire (« niches », « charge subversive inférentielle », « nivellement », « philosophie sublimée », « épistémologie des vertus », « microgrammes »). Et presque chaque chapitre offre en effet une proposition programmatique forte : M. Mulsow compare de ce fait le livre à un film à sketches, un mosaïque « de petites histoires qui restent à écrire » (p. 305). Mais, si l'on considère l'historiographie française au moins, où l'histoire culturelle (le champ avec lequel l'auteur fait le plus dialoguer son histoire des idées) est prévalente depuis des décennies, il n'est pas si évident que toutes ces histoires restent véritablement à écrire : les travaux sur l'histoire de la numismatique ou de la lecture la plume à la main y étaient déjà importants avant même la publication de la version allemande. Il n'en demeure pas moins que M. Mulsow déploie un degré d'érudition, de solidité analytique et de créativité difficiles à égaler. Au public francophone, son livre offre non seulement le panorama d'un milieu intellectuel dont il est encore peu familier -celui de l'Allemagne du Nord au tournant de 1700 -, mais aussi une source d'inspiration méthodologique. José Beltrán jose.beltran@cnrs.fr 1 Martin MULSOW, Knowledge Lost: A New View of Early Modern Intellectual History, trad. par H. C. E. Midelfort Princeton, Princeton University Press, 2022. 2 Id., « Qu'est-ce qu'une constellation philosophique ? Propositions pour une analyse des réseaux intellectuels », nº spécial « Histoire et philosophie », Annales HSS, 64-1, 2009, p. 81-109. 3 Robert DARNTON, The Literary Underground of the Old Regime, Cambridge, Harvard University Press, 1982.