Nachiket A Nadkarni

Salma Bougacha

Clément Garin

Marc Dhenain
email: marc.dhenain@cea.fr

Jean-Luc Picq

A 3D population-based brain atlas of the mouse lemur primate with examples of applications in aging studies and comparative anatomy

Keywords: Atlas, Cerebral atrophy, Comparative anatomy, MRI, Mouse lemur, Template. Graphical

The gray mouse lemur (Microcebus murinus) is a small prosimian of growing interest for studies of primate biology and evolution, and notably as a model organism of brain aging. As brain atlases are essential tools for brain investigation, the objective of the current work was to create the first 3D digital atlas of the mouse lemur brain. For this, a template image was constructed from in vivo magnetic resonance imaging (MRI) data of 34 animals. This template was then manually segmented into 40 cortical, 74 subcortical and 6 cerebro-spinal fluid (CSF) regions. Additionally, we generated probability maps of gray matter, white matter and CSF. The template, manual segmentation and probability maps, as well as imaging tools used to create and manipulate the template, can all be freely downloaded. The atlas was first used to automatically assess regional age-associated cerebral atrophy in a cohort of mouse lemurs previously studied by voxel based morphometry (VBM). Results based on the atlas were in good agreement with the VBM ones, showing age-associated atrophy in the same brain regions such as the insular, parietal or occipital cortices as well as the thalamus or hypothalamus. The atlas was also used as a tool for comparative neuroanatomy. To begin with, we compared measurements of brain regions in our MRI data with histology-based measures from a reference article largely used in previous comparative neuroanatomy studies. We found large discrepancies between our MRI-based data and those of the reference histology-based article. Next, regional brain volumes were compared amongst the mouse lemur and several other mammalian species where high quality volumetric MRI brain atlases were available, including rodents (mouse, rat) and primates (marmoset, macaque, and human). Unlike those based on histological atlases, measures from MRI atlases indicated similar cortical to cerebral volume indices in all primates, including in mouse lemurs, and lower values in mice. On the other hand, white matter to cerebral volume index increased from rodents to small primates (mouse lemurs and marmosets) to macaque, reaching their highest values in humans.

Introduction

The gray mouse lemur (Microcebus murinus) is one of the smallest non-human primates (NHPs). Its small size (typical length 12cm, 60-120g weight) and rapid maturity (puberty at 6-8 months) bring rodent-like practicality to primate experimentation. As a result, the mouse lemur is used as an NHP model organism for primate and human biology [START_REF] Ezran | The mouse lemur, a genetic model organism for primate biology, behavior, and health[END_REF]. It has a life span of approximately 12 years, which is short for a primate, and displays age-associated cerebral atrophy that is correlated with cognitive alterations [START_REF] Picq | Age-related cerebral atrophy in nonhuman primates predicts cognitive impairments[END_REF] as well as various neuropathological lesions [START_REF] Kraska | Age associated cerebral atrophy in mouse lemur Primates[END_REF]. As a consequence, it is used as a model of aging and age-related diseases in the brain [START_REF] Languille | The grey mouse lemur: A non-human primate model for ageing studies[END_REF]. In particular it has been used to evaluate how cerebral aging is modulated by various biological factors or diseases, such as chronic caloric restriction [START_REF] Pifferi | Caloric restriction increases lifespan but affects brain integrity in grey mouse lemur primates[END_REF] or diabetes [START_REF] Djelti | Impaired fasting blood glucose is associated to cognitive impairment and cerebral atrophy in middle-aged non-human primates[END_REF].

Mouse lemurs can also be used to shed light on primate brain evolution [START_REF] Montgomery | Reconstructing the ups and downs of primate brain evolution: implications for adaptive hypotheses and Homo floresiensis[END_REF].

Surprisingly, most studies of this [START_REF] Barton | Mosaic evolution of brain structure in mammals[END_REF][START_REF] Finlay | Linked regularities in the development and evolution of mammalian brains[END_REF] rely on the analysis of the same set of volumetric measurements made on a large variety of mammalian species by a single research group using perfused brains processed by histology [START_REF] Stephan | New and revised data on volumes of brain structures in insectivores and primates[END_REF].

Because of the tediousness of the evaluation of brain region volumes by histology, the experiments were not reproduced by other research groups, leaving scientists with a single lone source of data to provide reference measures.

Given the importance of the mouse lemur for biomedical research and as a key species for studying primate brain evolution, it is critical to have a 3D digital brain atlas and associated template (standard image reflecting the population's brain anatomy) for this species. However, today, reference atlases available to study mouse lemurs are based on histological sections [START_REF] Gros | The brain of Microcebus murinus[END_REF][START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF]. Such atlases suffer from distortions caused by histological processing and do not cover the whole brain. Also, they are very unsuited to use with non-invasive imaging data from live individuals. A first MRI-based description of the mouse lemur brain was developed in the 1990s, but it is mainly a partial annotation of MR images of one post mortem brain sample [START_REF] Ghosh | Mouse lemur microscopic MRI brain atlas[END_REF]. More recently, a population image based on 30 mouse lemur brains including probabilistic gray matter (GM), white matter (WM) and cerebro-spinal fluid (CSF) maps was developed, but it did not include annotated labels [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF]. Here we present the first 3D digital brain atlas and associated template of the mouse lemur. We used MR acquisitions from 34 young to middle-aged adult mouse lemurs to create the template: scans were iteratively mutually registered and meaned through linear then increasingly refined non-linear stages, a standard process that does not favor any one individual, but rather produces an unbiased average of the population used to create it [START_REF] Guimond | Automatic computation of average brain models. Medical image computing and computer-assisted interventation[END_REF][START_REF] Guimond | Average brain models: a convergence study[END_REF]. The template was then segmented manually into 120 structures based on a previous histological atlas [START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF] and other previous characterizations of mouse lemur brain anatomy [START_REF] Gros | The brain of Microcebus murinus[END_REF][START_REF] Zilles | A quantitative approach to cytoarchitectonics. V. The areal pattern of the cortex of Microcebus murinus (E. Geoffroy 1828), (Lemuridae, primates)[END_REF]. The template was also used to create probability maps of mouse lemur GM, WM and CSF. The template, atlas and probability maps are available for download in NIfTI-1 format at . The code developed to create and manipulate the https://www.nitrc.org/projects/mouselemuratlas template has been refined into general procedures for registering small mammal brain MR images, available within a python module sammba-mri (SmAll-maMMals BrAin MRI; https://sammba-). mri.github.io Two applications of the atlas are presented in this article. The first is an evaluation of age-related regional cerebral atrophy in a mouse lemur cohort that was previously studied by voxel based morphometry (VBM) [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF]. We show that atlas-based registration detects age-related atrophy in regions very similar to those identified by VBM. The second application is a comparative anatomy study. Initially, we highlight that reference published histological reports of brain region volumes are very different to those found with our atlas. More interestingly, using morphometric analysis and comparison of measures of the ratios between various brain regions, we show that, despite its rodent-like size, the mouse lemur's cortex/cerebrum index does not differ from those of other primates, and that major differences amongst primates concern more the WM/cerebrum indices.

Materials and Methods

Animals

This study was carried out in accordance with the recommendations of the European Communities Council directive (2010/63/EU). The protocol was approved by the local ethics committees CEtEA-CEA DSV IdF (authorizations 201506051 736524 VI (APAFIS#778)). 34 mouse lemurs (22 males and 12 females) were used for template creation. Age range was 15-58 months, mean ± standard deviation 36.8 ± 9.2 months, so all were young to middle-aged adults at scan time [START_REF] Languille | The grey mouse lemur: A non-human primate model for ageing studies[END_REF]. All mouse lemurs were born in a laboratory breeding colony (Brunoy, France, authorization n°E91-114-1), and maintained at steady ambient temperature (24-26°C) and relative humidity (55%). Full demographic information is provided in Table 1 in [START_REF] Nadkarni | Digital templates and brain atlas of the mouse lemur primate. Data Brief[END_REF].

MR acquisition

One T2-weighted in vivo MRI scan was recorded for each animal. After an overnight fast, animals were immobilized for MRI by isoflurane anesthesia (4% induction, 1-1.5% maintenance). Breathing rate was monitored to ensure animal stability until the end of the experiment. Body temperature was maintained by an air-heating system. Images were acquired using a 7 Tesla (T) Agilent system using a four channel phased-array surface coil (Rapid Biomedical, Rimpar, Germany) actively decoupled from the transmitting birdcage probe (Rapid Biomedical, Rimpar, Germany). The sequence was a 2D T2-weighted fast spin echo with a resolution of 230x230x230 µm: TR/TE = 10000/17.4 msec, RARE factor = 4, field of view (FOV) = 29.44 × 29.44 mm with a matrix (Mtx) = 128 × 128, 128 slices, number of averages (NA) = 6, acquisition duration 32 mins.

Template creation and validation

Raw k-space slice data from the 34 mouse lemurs were zero-filled to 256 × 256 and reconstructed to 3D NIfTI-1 format using custom python code. Images were then up-sampled in the through-slice direction as well to 256 slices, thus giving a final matrix of 256 3 , 115 µm isotropic resolution.

The template generation pipeline is diagrammed in Fig. 1, and has been developed into the function anats_to_common available within the sammba-mri python module (https://sammbamri.github.io/generated/sammba.registration.anats_to_common.html#sammba.registration.anats_t o_common). All steps used tools from freely available AFNI software (https://afni.nimh.nih.gov/ [START_REF] Cox | AFNI: software for analysis and visualization of functional magnetic resonance neuroimages[END_REF]), except for brain extraction, which was done with RATS [START_REF] Oguz | RATS: Rapid Automatic Tissue Segmentation in rodent brain MRI[END_REF][START_REF] Yin | LOGISMOS--layered optimal graph image segmentation of multiple objects and surfaces: cartilage segmentation in the knee joint[END_REF]. Head images were bias corrected (Fig. 1b), brain extracted (Fig. 1c), and individual brain extracted image centers were shifted to the brain center of mass (Fig. 1d). Brains were then all rigid body aligned to a digitized version of a previous histological atlas [START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF] (Fig. 1e) and the transform was then applied to the original heads. The aligned heads were meaned to produce a first brain template (Fig. 1f). The previous rigid body registration step was performed a second time to align the 34 centered brains to the first template leading to a template 2 (Fig. 1g). Then, the 34 centered brains were affine aligned to template 2 leading to a template 3 (Fig. 1h). Finally, four cycles of non-linear registration were executed, the first to affine template 3, the rest to templates of heads from the previous non-linear cycle, including initialization using the concatenated transforms of the previous cycles, and an adjustment after each cycle to correct for systematic biases in the non-linear transforms (Fig. 1i) leading to the final template. Note that non-linear registration used the AFNI tool 3dQwarp, which repeatedly composes incremental warps defined by Hermite cubic basis functions, first over the entire volume, then over steadily shrinking and overlapping patches, with the resulting final warp being a grid representation of a diffeomorphism between source and target images. In the non-linear cycles above, final patch size was relatively large in the first cycle and was reduced substantially with each subsequent cycle. The intermediate and final templates were all means in intensity space of transformed images.

The contrast to noise ratio (CNR) was measured in the template and in raw images by evaluating the difference between the mean intensity of GM (in the caudate nucleus, 1920 voxels, 1.45 mm 3 ) minus mean intensity of WM (splenium of the corpus callosum, 500 voxels, 0.38 mm 3 ) divided by the standard deviation of the intensities in the tympanic bulla (1280 voxels, 0.96mm 3 ). [START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF] (AFNI-3dAllineate) and the 6 degrees of freedom (DOF) transforms were then applied to the centered heads. (e) The aligned heads were averaged to produce a first template and similarly for the aligned brains. (f) The rigid body registration was performed a second time to align the 34 centered heads to the first created template leading to a template 2. (g) Then, the 34 centered brains were affine aligned to brain template 2 and the 12 DOF transforms were applied to the centered heads leading to template 3. (h) Finally, four cycles of nonlinear registration were carried out, the first to affine template 3, then subsequently to match templates of heads from the previous cycle (AFNI-3dQwarp), including initialization by the concatenation of previous transforms, and an adjustment after each cycle to correct for systematic biases in the non-linear transforms . These steps used a weight, created by using a mask of brain template 3 dilated by 5 voxels .

Finally, adopting procedures of template validation from previous studies, landmark distance measures were used to validate the mouse lemur template (Black et al., 2001a;Black et al., 2001b;[START_REF] Ella | Construction of an MRI 3D high resolution sheep brain template[END_REF][START_REF] Hikishima | Population-averaged standard template brain atlas for the common marmoset (Callithrix jacchus)[END_REF][START_REF] Mclaren | A population-average MRI-based atlas collection of the rhesus macaque[END_REF][START_REF] Quallo | Creating a population-averaged standard brain template for Japanese macaques (M. fuscata)[END_REF]. Landmarks were identified at the level of the middle of the anterior (AC) and posterior (PC) commissures in the template, raw images and images normalized to the mouse lemur template (Anatomist freeware; http://brainvisa.info/index_f.html). The 3D Euclidean distances (AC-PC) between each of these landmarks and the equivalent landmarks in the mouse lemur template were calculated.

Segmentation of the MRI-based atlas

The template image was up-sampled to 91 µm isotropic resolution, then segmented manually by a single person (JLP) using ITK-SNAP software (http://www.itksnap.org; [START_REF] Yushkevich | User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability[END_REF]).

Brain structures, except cortical areas, were defined according to the histological atlas of Bons [START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF] on the basis of the contrast in the anatomical images. Each structure was segmented slice by slice along either the coronal, axial or sagittal orientations depending on which orientation offered the best contrast for the structure. The boundaries of each structure were then checked, corrected using all three orientations and continuously updated until, after several iterations in each direction, the three-dimensional representation of the labelled structure was found to be smooth and non-jagged. Due to insufficient contrast within the cortex of the template image, the boundaries of cortical areas were approximated from the histological atlas of [START_REF] Gros | The brain of Microcebus murinus[END_REF], and even then only on coronal slices of the template because this histological atlas only contains some coronal sections and a rough lateral view of the mouse lemur cortex parcellation. After the delineation of the cortical areas on the coronal orientation was completed, the boundaries were carefully adjusted using the axial and sagittal orientations until achieving internal coherence among the three views. The study of the cytoarchitectonic structure of the mouse lemur cortex by Zilles et al. [START_REF] Zilles | A quantitative approach to cytoarchitectonics. V. The areal pattern of the cortex of Microcebus murinus (E. Geoffroy 1828), (Lemuridae, primates)[END_REF] was used to make three small changes to the Le Gros Clark-based cortical parcellation: 1) the more rostral parts of the temporal pole were occupied by the prepyriform and periamygdalar areas instead of area 28 (entorhinal cortex), 2) areas 26 and 29 were merged to form the retrosplenial area, 3) area 22 was identified as the whole auditory cortex corresponding to areas 41, 42 and 22 of Brodmann [START_REF] Brodmann | Brodmann's 'Localisation in the cerebral cortex' {Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Orinzipien dargestellt auf Grund des Zellenbaus}[END_REF](Brodmann, (original in 1909))). In total, 120 regions were drawn.

They included 40 cortical, 74 subcortical and 6 CSF regions. Each structure was outlined bilaterally.

The names of the structures were based on the NeuroName ontology (http://www.braininfo.org; [START_REF] Bowden | NeuroNames: an ontology for the BrainInfo portal to neuroscience on the web[END_REF]). Labels of all brain regions are provided in Table 2 in [START_REF] Nadkarni | Digital templates and brain atlas of the mouse lemur primate. Data Brief[END_REF].

Tissue probability maps

Tissue probability maps were created using SPM8 (Wellcome Trust Institute of Neurology, University College London, UK, www.fil.ion.ucl.ac.uk/spm) with the SPMMouse toolbox (http://spmmouse.org) for animal brain morphometry as previously described [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF][START_REF] Sawiak | Voxel-based morphometry with templates and validation in a mouse model of Huntington's disease[END_REF].

Briefly, MR images from the 34 animals involved in the study were registered to a previously published SPM template of the mouse lemur brain [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF]. Affine registration adjusted the images to control for different head positions and scanner geometry as well as overall brain size.

Then unified segmentation iteratively warped the data whilst correcting for signal inhomogeneity due to the receiver coil. The images of the rigidly-aligned brains of each animal were then segmented using a k-means algorithm [START_REF] Mackay | Information theory, inference and learning algorithms[END_REF] with 4 segments: background, GM, WM, and CSF. These maps were then averaged across individuals separately for each tissue type to produce mean GM, WM and CSF tissue probability maps. These maps were manually edited, particularly around the edges of the brain where partial volume effects lead to mislabeling of CSF as GM or WM voxels. The templates were also masked using masks derived from the segmented atlas, to conserve only brain and CSF structures. brains came from an in-house mouse lemur brain collection. The brains were extracted and formalin-fixed for at least 6 months after the death of the animals. They were then stained by a oneweek soaking in a solution of Gadolinium (Dotarem, Guerbet, France) in PBS at 2.5 mmol/l. This protocol enhances the signal-and contrast-to-noise ratios on MR images of fixed brains [START_REF] Bertrand | Micro-MRI study of cerebral aging: Detection of hippocampal subfield reorganization, microhemorrhages, and amyloid plaques in mouse lemur primates[END_REF].

Evaluations and applications

Quality of registration to other images

Evaluation of cerebral atrophy

The MRI brain atlas was then used to measure the volumes of individuals' brain structures and evaluate age-related cerebral atrophy in a cohort of 30 mouse lemurs that had previously been evaluated by voxel-based morphometry [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF]. Animals from this cohort had ages ranging from 1.9 to 11.3 years old (7 "young" animals (2.2 ± 0.2 years), 11 "middle-aged" (4.8 ± 1.0 years) and 12 "old" (8.3 ± 1.7 years) animals). Compared to those used for atlas creation, images for these animals were recorded by MRI at a different field strength (4.7 T) with a 3D inversion-recovery fast spin-echo sequence using the same parameters as described in the previous section though without zero-filling [START_REF] Dhenain | Regional atrophy in the brain of lissencephalic mouse lemur primates: measurement by automatic histogram-based segmentation of MR images[END_REF][START_REF] Kraska | Age associated cerebral atrophy in mouse lemur Primates[END_REF].

A study template representative of the 30 animals was created by registering individuals' images using the same procedure described earlier for template creation. The study template was then nonlinearly registered to the earlier-created mouse lemur template. The mouse lemur atlas was then transformed to each individual's original image by applying the concatenated inverted studytemplate-to-mouse-lemur-template and animal-to-study template transforms. CSF accumulations and infiltrations were identified by simple thresholding and used to correct the animal-specific atlases, which were then used to measure the volumes of different brain structures. These volumes were analyzed by linear regression in R (function lm, https://www.R-project.org) using the following model:

V ij = β 0 + β 1j age i + β 2j IV i + ε ij
where the dependent variable V ij is the estimated volume (in mm 3 ) of region j for animal i, the independent variables being age i the age (in years) and IV i the intracranial volume (total volume of the individually-transformed mouse lemur atlas, which marks brain plus surrounding CSF, so total intracranial volume, in mm 3 ) of animal i, and ε ij is the error term.

Comparative anatomy

Cerebral anatomy in the mouse lemur was compared to that of other mammals using available downloadable 3D digital MRI-based brain atlases of the mouse [START_REF] Dorr | High resolution threedimensional brain atlas using an average magnetic resonance image of 40 adult C57Bl/6J mice[END_REF], rat [START_REF] Papp | Waxholm Space atlas of the Sprague Dawley rat brain[END_REF], marmoset [START_REF] Woodward | The Brain/MINDS 3D digital marmoset brain atlas[END_REF], macaque [START_REF] Reveley | Three-Dimensional Digital Template Atlas of the Macaque Brain[END_REF], and compared to human data from MRI-based morphometric analysis [START_REF] Filipek | The young adult human brain: an MRI-based morphometric analysis[END_REF]. The volumes of the hippocampal formation, striatum (caudate nucleus + putamen), cortex and cerebral WM (see list of structures in Table 1) were measured and expressed as a proportion of total cerebrum (cortical GM + central GM + cerebral WM, see Suppl. Table 2).

Results

Mouse lemur template and probability maps

An MRI template of mouse lemur brains was generated from 34 animals aged 15-60 months old scanned at 7 T using a T2-weighted sequence with a final isotropic resolution of 115 µm (Fig. 2A,C, E,Fig 3A). The orientation of the template roughly corresponded to that of the reference Bons atlas [START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF]. The image grid mid-plane coincided with the anatomical midsagittal plane, and the image grid horizontal plane passed through the centers of the AC and PC, corresponding to a standard anatomical coordinate system similar to Talairach space [START_REF] Talairach | Co-planar stereotaxic atlas of the human brain[END_REF].

This template was used to create tissue probability maps for GM, WM and CSF (See Fig. 2 The usability of an atlas for imaging studies relies on the accuracy of registration to its template.

Here, we tested the performance of our MRI-based atlas on non-linear registration with imaging data obtained from in vivo T2-weighted MRI at different field strengths (4.7 T (Fig. 3E,F) and 11.7 T (Fig. 3G,H)), as well as with ex vivo MRI recorded at 7 T (Fig 3D). Visual inspection of the registered images suggested good accuracy of registration to the template (Fig. 3A).

Figure 3. Registration of various in vivo and ex vivo MR images to the mouse lemur template. A-B. Coronal section of the mouse lemur MRI template (level of the anterior commissure, A) and associated section in the atlas (B). C displays an MR image from one of the 34 animals used to create this template. D displays 7 T gradient echo T2*-weighted, gadolinium stained images from an ex vivo brain registered on the template. E-F highlight 4.7 T fast-spin echo T2

-weighted MR images from 1.9 year-old (E) and 10.9 year-old (F) animals, registered on the template. G-H display 11.7 T-T2weighted multi-slice multi-echo MR images from 2.3 year-old (G) and 10.4 year-old (H) animals, registered on the template. Scale bar: 5 mm.

Mouse lemur atlas

The template was manually labelled (https://www.nitrc.org/projects/mouselemuratlas). A twodimensional representation of the atlas in three orientations is shown in Fig. 2B, D, F and 3B; a three-dimensional representation from the superior lateral view is shown in Fig. 2G. 74 subcortical structures could be identified (See Table 2 in [START_REF] Nadkarni | Digital templates and brain atlas of the mouse lemur primate. Data Brief[END_REF]. 40 cortical structures were outlined by interpreting borders defined in the Le Gros Clark atlas (Le Gros [START_REF] Gros | The brain of Microcebus murinus[END_REF] with some adjustments on the basis of updates in more recent atlases [START_REF] Zilles | A quantitative approach to cytoarchitectonics. V. The areal pattern of the cortex of Microcebus murinus (E. Geoffroy 1828), (Lemuridae, primates)[END_REF]

Application to evaluating regional atrophy from atlas-based defined regions

We assessed atrophied brain regions in a cohort of 30 mouse lemurs aged from 1.9 to 11.3 years old that had previously been evaluated with other methods such as voxel-based analysis [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF]. Regions presenting with a significant atrophy are presented in Fig. 4 and Table 2. Nearly all of the changes were symmetric with both sides of the brain affected. Most cortical regions displayed some atrophy with age, with the most prominent including the insular (areas 13-16, Fig. 4C), frontal (area 6), parietal (areas 5 (Fig. 4D) and 7), occipital (areas 17, 18), inferior temporal (areas 21, 28)

and cingulate cortices (areas 23, 24, 25) (Table 2). With the exception of the visual cortex, the primary motor and sensory cortices were spared. Subcortical regions such as the thalamus (Fig. 4E), hypothalamus, caudate nucleus, and central gray of the midbrain were also particularly affected by aging. Interestingly, with some minor exceptions, the regions that were reported atrophied here are the same as those declared atrophied in a previous article focusing on this cohort (Table 2, [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF]). These data confirm that in mouse lemurs 1) the cortex as a whole is more vulnerable to age-related atrophy than subcortical regions, 2) the magnitude of age-related cortical shrinkage varies greatly among cortical regions, 3) atrophy of association cortices is prominent whereas motor and primary sensory (except the visual area) cortices are relatively spared, 4) multimodal association cortices such as areas 13-16 and the cingulate cortex -which are viewed as equivalent of prefrontal regions subserving executive functions (Le Gros Clark, 1931)-are also especially vulnerable to aging. 2. Brain structures presenting with age-related atrophy. Analysis was carried out as detailed in Section 2.6.2. Slope is the co-efficient estimated for the parameter age (β 1j effectively in mm 3 per year) and p-value is its associated p-value (p-value for the hypothesis test H o : β 1j = 0 versus H1: β 1j ≠0, reflecting the significance of the regression coefficient associated to the age). NS: p > 0.05. 30 animals were used for this study Animals' age range was 1.9 to 11.3 years old.

Figure 4. Age-related evolution of cerebral atrophy in various brain regions. (A). Dorsal (left), ventral (middle) and lateral (right) views of the cortex showing regions presenting with a significant age-related atrophy (colored labels) and spared cortical areas (white). (B) Dorsal (left), ventral (middle) and lateral (right) views of atrophied subcortical brain structures. (C-E) Age-related evolution of the volume of area 13-16 (insular cortex, C), area 5 (D) and thalamus (E). Statistical modeling was performed as described in Section 2.6.2, with numerical results given in

Application to comparative neuroanatomy

Most studies on brain evolution rely on the analysis of the same set of volumetric measurements made on a large variety of mammalian species by a single research group using histology-based measures [START_REF] Stephan | New and revised data on volumes of brain structures in insectivores and primates[END_REF]. Our 3D MRI-based brain atlas offered the opportunity to compare the volumes of brain regions assessed in this histology-based reference article to in vivo MRI-based data. This revealed large discrepancies between the two methods (Suppl. Table 1). For example, the size of the hippocampus is overestimated by about 38% with histology-based measures whereas the size of the pallidum is under-estimated by about 38%. For the whole cortex, it is difficult to compare cortical prominence between the two methods since the histology-based dataset has the limitation of including the underlying WM and corpus callosum within the volume of the neocortex.

In addition to measures of volumes within a single species, digital atlases offer new opportunities to compare cerebral volumes across different species (Suppl. Table 2). As a proof of principle, we found that, in our population of adult mouse lemurs, the cortex contributes 54% of cerebral volume (Fig. 5). This value is close to that given by Filipek and al. for the human brain [START_REF] Filipek | The young adult human brain: an MRI-based morphometric analysis[END_REF]. By using freely downloadable 3D MRI-based brain atlases of the mouse [START_REF] Dorr | High resolution threedimensional brain atlas using an average magnetic resonance image of 40 adult C57Bl/6J mice[END_REF], rat [START_REF] Papp | Waxholm Space atlas of the Sprague Dawley rat brain[END_REF], marmoset [START_REF] Woodward | The Brain/MINDS 3D digital marmoset brain atlas[END_REF], and macaque [START_REF] Reveley | Three-Dimensional Digital Template Atlas of the Macaque Brain[END_REF], it can be determined that the cortex is around 56±3% of cerebral volume in the four primate species as in the rat but only 51% in the mouse (Fig. 5, Suppl. Table 2). These trends are especially marked in the human brain, in particular the large volume of WM. In addition to measures of brain volumes, another advantage of 3D digital brain atlases is that they allow an easy visualization of the 3D shape of each brain structure. As an illustration, Fig. 6A shows that the shape of the striatum is very different between rodents and primates. Also, within the primate group, it is very similar between the mouse lemur and the marmoset. In particular it can be noted that the putamen is flat and bent in these two primate species whereas it is rounded and domed in the macaque as well as in human. Likewise, it can be seen in Fig. 6B that the hippocampus is much thinner with a dorsal part that is much less developed in the macaque than in the mouse lemur, the shape being intermediate in the marmoset.

Figure 6. 3D shape comparison of the striatum and hippocampal formation in rodent and primate species.

A: 3D visualizations of the striatum in mouse, rat, mouse lemur, marmoset and macaque as seen from a left anterior-superior view (green: caudate in primates, striatum in rodents, brown: putamen). B: 3D visualizations of the C-shaped hippocampal formation in mouse, rat, mouse lemur, marmoset and macaque as seen from a right anterior-superior view.

Discussion

Mouse lemurs are generating more and more interest as models of neurodegenerative disease and references for comparative anatomy. The use of these animals in biological research depends on the development of tools for high throughput and automatic analysis as well as for standardization. We presented here one such tool: the first 3D digital brain atlas of the mouse lemur primate, consisting of an MRI template and labels for the whole brain. We also presented two potential applications of this atlas to assess age-related cerebral atrophy and for comparative neuroanatomy.

Compared to previous traditional 2D histology-based atlases of the mouse lemur brain, our MRIbased atlas has three main advantages: 1) a high resolution MRI template is provided for accurate registration to different imaging modalities and we showed that it can be used to register images recorded in various conditions (MRI recorded on 3 different scanners, from 4.7 to 11.7 T, in vivo and ex vivo), 2) brain regions are directly delineated onto 3D MR images, 3) all the voxels from the brain were labeled, including WM areas, subcortical nuclei and cortical regions.

In other species, including primates, several atlases have been based on ex vivo samples. Here, we developed an atlas based on in vivo images that do not suffer from the deformation of post mortem tissue processing. We also averaged data from several animals to reduce bias linked to individual differences.

Accuracy of cerebral label attribution

After the seminal work of Brodmann [START_REF] Brodmann | Brodmann's 'Localisation in the cerebral cortex' {Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Orinzipien dargestellt auf Grund des Zellenbaus}[END_REF](Brodmann, (original in 1909))), cytoarchitectural and other histology-based labeling techniques were the standard methods used for brain parcellation. This strategy was used to annotate cortical region atlases [START_REF] Gros | The brain of Microcebus murinus[END_REF][START_REF] Zilles | A quantitative approach to cytoarchitectonics. V. The areal pattern of the cortex of Microcebus murinus (E. Geoffroy 1828), (Lemuridae, primates)[END_REF] and non-cortical structures [START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF] in mouse lemurs. For our atlas, delineation of WM and subcortical structures was relatively accurate because of the strong contrast in the brain template.

Delineation of cortical regions, however, was mainly based on the transfer of structures found in histological atlases [START_REF] Gros | The brain of Microcebus murinus[END_REF][START_REF] Zilles | A quantitative approach to cytoarchitectonics. V. The areal pattern of the cortex of Microcebus murinus (E. Geoffroy 1828), (Lemuridae, primates)[END_REF]. New techniques of brain parcellation such as registration of MRI to 3D histological sections or measures of anatomical or functional connectivity [START_REF] Glasser | A multi-modal parcellation of human cerebral cortex[END_REF] will allow future refinements of atlas labels.

Application of the mouse lemur atlas to automatically annotate brain regions

Previous studies of cerebral atrophy in mouse lemurs were based on time-consuming manual segmentations [START_REF] Kraska | Age associated cerebral atrophy in mouse lemur Primates[END_REF] or on VBM that can highlight atrophied structures, but that does not provide individual measures of the volume of atrophied structures [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF]. Here we showed that using atlas-based registration, individual scans can be annotated automatically, eliminating the time consuming step of manual tissue segmentation, and enabling rapid and objective quantification of individual subjects' brain region volumes. Using this method, a reanalysis of past data processed by VBM [START_REF] Sawiak | Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate[END_REF] produced similar results. The interest of this method is that, unlike VBM measures of atrophy, it provided individual measures of the volumes of each brain region and allowed a quantitative assessment of the atrophy. Caution should, however, be recommended after automatic annotation of brain regions, and in particular for small regions or for regions close to CSF, and it is always recommended to perform a visual assessment of the quality of the annotation.

Application of the mouse lemur atlas for comparative neuroanatomy

Comparative anatomy should be performed on reliable measures of brain structures to provide reliable interpretations. One of the obstacles when evaluating many different rare animals is to have access to anatomical data that are often difficult to record. For this reason, many studies [START_REF] Barton | Mosaic evolution of brain structure in mammals[END_REF][START_REF] Finlay | Linked regularities in the development and evolution of mammalian brains[END_REF] have used measures from a histological study published in the 1980s [START_REF] Stephan | New and revised data on volumes of brain structures in insectivores and primates[END_REF]. The study was based on perfused brains, extracted out of the skull, embedded in paraffin and sectioned serially. The borders of brain structures were delineated from the stained histological sections. Calculations were performed to take into account distances between the sections and corrections applied for shrinkage resulting from fixation and embedding. Although it has been acknowledged that the different components of the brain may have sustained different degrees of shrinkage, these differences were considered negligible and not accounted for. We found substantial differences between the measures we made and the data reported in this reference article. One likely explanation is the post mortem artefacts associated with brain sampling and shrinkage resulting from fixation and embedding during histological preparation. An additional explanation may be differences in delineation of brain structures. It is impossible to evaluate how delineation was done in the reference article as technologies at the time did not allow digitization of large datasets. Delineation of an MRI template is expected to be less accurate than that of histological sections, but one of the advantages of MRI-based digital atlases is that the whole set of data is publicly available and can thus be corrected by other researchers.

Published datasets suggest that the ratio of the cortical to cerebral volume is highly different between humans (92%) and mouse lemurs (61%) [START_REF] Stephan | New and revised data on volumes of brain structures in insectivores and primates[END_REF]. Also, they report intermediate values for the marmoset, macaque and chimpanzee (76%, 85%, and 89%, respectively). These reference data support the theory of the corticalization of the human brain. Unexpectedly, our own analyses based on MRI-based atlases show similar cortical indices (56±3%) in four primates (mouse lemurs, marmosets, macaques and humans) while lower values were found in mice. Our results are not consistent with a corticalization theory of brain evolution. This is a good demonstration of the interest in revisiting previous comparative anatomy studies but using MRIbased atlases. Also, contrary to some previous assertions (see [START_REF] Passingham | Primate specialization in brain and intelligence[END_REF] for example), we showed that mouse lemurs do not differ from other primates in the proportion of their cortex and must not be considered, in this respect, as "lower primates". Major differences between primates were found for the WM/cerebrum indices. These are bigger in macaques and humans, suggesting that WM increase, a marker for reinforced intracerebral connectivity, is a critical event for primate brain evolution, as already proposed by several authors [START_REF] Schenker | Neural connectivity and cortical substrates of cognition in hominoids[END_REF][START_REF] Schoenemann | Prefrontal white matter volume is disproportionately larger in humans than in other primates[END_REF]. Hippocampus/cerebrum indices also decreased for the different primates. Our atlas of the mouse lemur is thus a key tool for future collaborative studies of primate brain evolution.

Conclusion

We constructed the first 3D digital atlas of the mouse lemur brain. It consists of a template constructed from in vivo MRI of 34 animals and labelled maps including all brain regions. It is freely distributed at https://www.nitrc.org/projects/mouselemuratlas and also includes GM, WM and CSF probability maps. The imaging tools used to create and manipulate the template are also available (https://sammba-mri.github.io). The labelled atlas itself has room for improvement. For example, future cortex parcellation could be based on the registration of our atlas to histological data. Newer brain imaging modalities such as structural or functional connectivity could also be included in future versions to improve understanding of primate brains. This atlas is an important tool for current and future automatic evaluation of pathologies in mouse lemur brains and for comparative anatomy.

Figure 1 .

 1 Figure 1. Template generation pipeline. T2-weighted MRI scans of the brain were collected from 34 mouse lemurs. (a) Head images were bias corrected (AFNI-3dUnifize), (b) brain extracted (RATS), and (c) each individual head (and brain extracted images) center was shifted to the brain center of mass (AFNI-3dCM). (d) Brains were then all rigid body aligned to a digitized version of a previous histological template[START_REF] Bons | A stereotaxic atlas of the grey lesser mouse lemur brain (Microcebus murinus)[END_REF] (AFNI-3dAllineate) and the 6 degrees of freedom (DOF) transforms were then applied to the centered heads. (e) The aligned heads were averaged to produce a first template and similarly for the aligned brains. (f) The rigid body registration was performed a second time to align the 34 centered heads to the first created template leading to a template 2. (g) Then, the 34 centered brains were affine aligned to brain template 2 and the 12 DOF

  .io/generated/sammba.registration.anats_to_template.html#sammba.registration.anats_ to_template), our MRI atlas was non-linearly registered to different MR images, including in vivo MRI recorded at different field strengths (4.7 and 11.7 T), and ex vivo high-resolution gadolinium-stained MRI. These images were collected from mouse lemurs unrelated to the atlas. Images at 4.7 T were recorded according to previously published protocols on a Bruker Biospec 47/30 system by using a surface coil (diameter = 30 mm) actively decoupled from the transmitting birdcage probe (Bruker GmbH) and a three-dimensional inversion-recovery fast spin-echo sequence of 234x234x234 µm nominal resolution (TR/TE = 2500/6 msec, TEw = 45 msec, TI = 200 msec, RARE factor = 16, Mtx = 128 x 128 x 128, NA = 1). MR images were zero-filled to reach an apparent resolution of 117x117x117 µm. Images at 11.7 T were recorded on a Bruker Biospec 117/16 system (Bruker, Ettlingen, Germany) using a two-dimensional multi-slice multi-echo sequence of 200x200x200 µm nominal resolution (TR/TE = 5000/5 msec, TEw = 17.5 msec, 6 echos, Mtx = 160 x 160, 75 slices, NA = 1). For each field, we present images from young non-atrophied animals (1.9 and 2.4 years at 4.7 and 11.7 T, respectively) and old atrophied animals (10.9 and 10.4 years at 4.7 and 11.7 T, respectively). Ex vivo gadolinium-stained MRI were recorded on a 7 T clinical magnet (Siemens, Syngo MR VB15) using a 2D gradient echo T2*-weighted sequence with a spatial resolution of 31 x 31 x 120 µm (TR/TE = 200/20.8 msec, flip angle = 80°, Mtx = 768 x 648, 144 slices, NA = 1). Animal

  in[START_REF] Nadkarni | Digital templates and brain atlas of the mouse lemur primate. Data Brief[END_REF]. The template and tissue probability maps are available from https://www.nitrc.org/projects/mouselemuratlas. Contrast to noise in the template reached 58 between GM and WM. The quality of the template was improved as compared to individual images that had a GM/WM CNR of 13.2±2.6 (See Fig.2in[START_REF] Nadkarni | Digital templates and brain atlas of the mouse lemur primate. Data Brief[END_REF]. The Euclidian AC-PC distance was 4740 µm in the template and in each of the individual images registered to the template. It was 4678±163 µm in the original images, which represents a 1.3% difference between raw and template images.

Figure 2 .

 2 Figure 2. Labeling of the mouse lemur atlas. Brain structure delineations are shown in coronal, sagittal and axial views (B, D, F) together with corresponding template images (A, C, E). Panel G displays a three-dimensional representation of the atlas from a superior lateral view. Scale bars equal 1 cm. For clarity, the label marking surrounding CSF is not displayed.

Figure 5 .

 5 Figure 5. Volume fractions of hippocampus, cortex, WM and striatum plotted against total cerebrum volume in mouse, rat, mouse lemur, marmoset, macaque and human.

Fig. 5

 5 Fig. 5 also shows that overall, the mouse lemur brain is very close to that of the marmoset in terms of relative volumes of brain components and that primate brains differ from those of rodents in the relatively smaller volumes of the hippocampus and striatum, and relatively larger volumes of WM.

Table 1 . List of brain structures and volumes (mm 3 , mean ± standard deviation) determined by transformation of atlas labels back to individual mouse lemurs

 1 . The volumes of each structure and their variation across the 34 animals used for template creation, including measures of cerebral asymmetry and sex difference, are shown in Table1.

	Region	Structure	All animals (n=34)	Male (n=22)	Females (n=12)
			Left	Right	Left	Right	Left	Right
		cerebral cortex 1-3	18.9±1.8 18.8±1.9 19.2±1.8 19.0±1.9 18.4±1.5 18.4±2.1
		cerebral cortex 4	26±2.7	27.0±3 26.1±2.8 27.0±3.4 25.7±2.5 26.9±2.1
		cerebral cortex 5	23.8±3.6 24.9±2.9 24.5±3.5 25.3±2.9 22.3±3.7 23.9±2.8
		cerebral cortex 6	34.5±3	35.9±3 34.7±3.2 34.2±2.6 36.0±3.1 35.5±2.8
		cerebral cortex 7	5.8±1.1	5.7±1	6.1±1.1 5.9±1.1	5.2±1.1	5.3±0.8
		cerebral cortex 8	7.9±0.9 7.8±0.9 8.0±0.9 7.8±0.9	7.8±1	7.7±1
		cerebral cortex 13-16	10.9±1.2 9.9±1.1 11.0±1.2 10.1±1.2 10.9±1.1	9.7±0.8
		cerebral cortex 17	46.2±5 47.1±5.1 46.6±5.3 47.7±5 45.5±4.6 46.0±5.5
		cerebral cortex 18	17.9±2.8 18.6±3.2 18.2±2.9 18.6±3.3 17.3±2.3 18.6±3.2
		cerebral cortex 20	2.6±0.6 2.6±0.5 2.5±0.4 2.5±0.4	2.9±0.9	2.9±0.5
	Cortical gray	cerebral cortex 21 cerebral cortex 22 (40-42) 32.8±3.7 34.5±3.6 33.1±3.5 34.5±3.9 32.2±4.3 34.5±3.2 28.8±3.4 28.1±2.9 28.5±2.8 27.9±2.6 29.5±4.5 28.5±3.5
		cerebral cortex 23	7.8±1.1 7.7±0.9 7.7±0.7 7.6±0.9	8.0±1.7	7.8±1.1
		cerebral cortex 24	6.9±0.9 6.4±0.9	6.9±1	6.4±0.9	6.8±0.7	6.5±0.7
		cerebral cortex 25	0.8±0.3 0.8±0.2 0.8±0.3 0.8±0.2	0.7±0.2	0.8±0.2
		cerebral cortex 26-29	8.7±1.2 8.9±1.2 8.8±1.3 9.1±1.3	8.4±0.8	8.6±0.9
		cerebral cortex 27	2.1±0.5 2.0±0.4 2.1±0.4 2.0±0.4	2.2±0.6	1.9±0.4
		cerebral cortex 28	19.1±2.1 18.5±1.8 19.4±2 18.8±1.7 18.4±2.1	17.8±2
		cerebral cortex 30	2.5±0.5 2.4±0.4 2.5±0.5 2.4±0.4	2.5±0.6	2.3±0.5
		cerebral cortex
		prepyriform and	6.3±0.7 5.7±0.6 6.3±0.5 5.8±0.6	6.2±0.9	5.5±0.9
		periamygdalar
		Amygdala	12.6±1.1 13.5±1.2 12.7±1.1 13.6±1.2 12.5±1.1 13.2±1.1
		basal forebrain	3.6±0.6 3.7±0.6 3.6±0.5 3.7±0.6	3.5±0.6	3.6±0.6
		basal forebrain nucleus	0.3±0.1 0.3±0.1 0.3±0.1 0.3±0.1	0.2±0.1	0.3±0.2
	Central	caudate nucleus	18.1±1.8 18.3±1.8 18.4±1.5 18.6±1.5 17.5±2.1 17.6±2.3
	gray	claustrum	5.0±0.5 4.4±0.6 5.0±0.5 4.5±0.6	4.8±0.5	4.2±0.5
		globus pallidus	8.9±1.1 8.4±2.2 9.3±0.9 8.8±0.9	8.2±1.2	7.5±1.1
		habenula	0.5±0.2 0.5±0.1 0.5±0.2 0.5±0.1	0.5±0.2	0.5±0.1
		hippocampal formation	36.6±3.3 36.1±3.4 36.7±3.2 35.9±3.3 36.4±3.7 36.6±3.7

. Animals' age range was 15-58 months. Sex, age and identifier of individual animals is given in Suppl. Table 1.

Table 2 .

 2

	name of	slope	p-value	Structures detected as atrophied by
	structure			VBM analysis in (Sawiak et al., 2014)
	Insular cortex (13-16)	-1.01	0.000039	+
	Frontal cortex
	Area 6	-1.36	0.0019	+
	Parietal cortex
	Area 5	-2.22	0.00000027	+
	Area 7	-0.70	0.000000016	+
	Occipital cortex
	Area 17	-3.55	0.00000370	+
	Area 18	-0.69	0.011	+
	Retrosplenial cortex	-0.63	0.000013	+
	Cingulate cortex
	Area 23 left	-0.24	0.0086	+
	Area 24	-0.27	0.00058	+
	Area 25	-0.10	0.00014	+
	Temporal cortex
	Area 21	-1.20	0.0030	+
	Area 28	-0.75	0.015	-
	Area 20	NA	NS	+
	Area 22	NA	NS	+
	Total cortex	-14.46	0.00000030	NA
	Thalamus	-2.50	0.000072	+
	Hypothalamus	-0.90	0.00000001	+
	Caudate	-0.75	0.0016	+
	Central gray of the midbrain	-0.48	0.00000052	+
	Putamen	-0.30	0.057	+
	Septum right	-0.20	0.020	+
	Cerebellum right	-1.53	0.035	-
	Table

Annotations: ca = caudate nucleus, ce = cerebellum, g = central gray of the midbrain, h = hypothalamus, Prp-pa = prepyriform and periamygdalar area, t = thalamus.

Acknowledgements

We thank the France-Alzheimer Association, Plan Alzheimer Foundation and the French Public Investment Bank's "ROMANE" program for funding this study.

Supplementary Table 1. Comparison of the volumes (mm 3 ) of various cerebral structures according to our 3D atlas and that of the reference histological evaluation

 [START_REF] Stephan | New and revised data on volumes of brain structures in insectivores and primates[END_REF]


Mathieu Rospabé

Georges Ceuleneer

Mathieu Benoit

Bénédicte Abily

Patrick Pinet

Origin of the dunitic mantle-crust transition zone in the Oman ophiolite: The interplay between percolating magmas and high-temperature hydrous fluids

Determining which petrological processes build the mantle-crust dunitic transition zone (DTZ) in oceanic spreading settings has a direct impact on our understanding of thermal and chemical transfers on Earth. We report on understated but widespread mineral assemblages present in the DTZ at the top of a mantle diapir (Oman ophiolite), including pargasite, grossular, and pyroxenes of peculiar composition. These minerals are present interstitially between olivines and as inclusions in the disseminated chromite grains, indicating that they are early, high-temperature features. They call for hybridization between the mid-oceanic ridge basalt melts that fed the crustal section and supercritical water saturated with silica. Our synoptic survey (~300 samples collected along 12 cross sections) demonstrates that the DTZ was pervasively infiltrated by such hybrid melts and that the abundance of their crystallization products increases upsection,

INTRODUCTION

In ophiolites, and especially in Oman, the contact between the mantle peridotites and the lower crust is underlined by a horizon as much as several hundred meters thick made essentially of dunite (>95% olivine + minor chromite). The origin of this dunitic transition zone (DTZ) was questioned in the pioneering studies of [START_REF] Moores | The Troodos massif, Cyprus and other ophiolites as oceanic crust-Evaluation and implications[END_REF] and [START_REF] Greenbaum | Magmatic processes at ocean ridges: Evidence from Troodos massif[END_REF] and is still debated. The DTZ has been viewed as the shallowest part of the mantle, i.e., a residue of reaction melting between host harzburgite and a percolating melt becoming undersaturated in silica relative to orthopyroxene (Opx) at low pressure (e.g., [START_REF] Moores | The Troodos massif, Cyprus and other ophiolites as oceanic crust-Evaluation and implications[END_REF][START_REF] Dick | Evidence of partial melting in the Josephine Peridotite[END_REF][START_REF] Rabinowicz | Melt segregation and flow in mantle diapirs below spreading centers: evidence from the Oman ophiolite[END_REF], or as the deepest part of the crust, i.e., cumulates from Mg-rich melts (e.g., [START_REF] Greenbaum | Magmatic processes at ocean ridges: Evidence from Troodos massif[END_REF][START_REF] Elthon | High magnesia liquids as the parental magma for ocean floor basalts[END_REF]. We have shown that the two options are not mutually exclusive and that the DTZ can include both residual and cumulative horizons [START_REF] Abily | The dunitic mantle-crust transition zone in the Oman ophiolite: Residue of melt-rock interaction, cumulates from high-MgO melts, or both?[END_REF].

We have performed a systematic sampling of the DTZ in the Maqsad area and, based on our sampling collection (>300 sampling sites), we realized that the DTZ exposes an unexpected abundance of discreet mineral assemblages of enigmatic origin (partly igneous, partly hydrous). The distribution of these mineral assemblages is not random, but vertical within the DTZ. We propose that they are a clue to understand the petrological processes involved in the formation of the DTZ.

GEOLOGICAL SETTING AND FIELD OCCURENCE

DOI:10.1130/G38778.1 The upper Cretaceous Oman ophiolite issued from the Tethys Ocean.

It is made of two contrasting magma series: one is a mid-oceanic ridge basalt (MORB) type and the other has a depleted andesitic affinity attributed to subduction and/or thrusting or to hydrated remelting of the shallow lithosphere during spreading (e.g., [START_REF] Pearce | The Oman ophiolite as a Cretaceous arc-basin complex: Evidence and implications[END_REF][START_REF] Benoit | The remelting of hydrothermally altered peridotite at mid-ocean ridges by intruding mantle diapirs[END_REF][START_REF] Python | Nature and distribution of dykes and related melt migration structures in the mantle section of the Oman ophiolite: Geochemistry[END_REF][START_REF] Yamasaki | Geochemical evidence in clinopyroxenes from gabbroic sequence for two distinct magmatisms in the Oman ophiolite[END_REF][START_REF] Macleod | Moist MORB" axial magmatism in the Oman ophiolite: The evidence against a mid-ocean ridge origin[END_REF].

The Maqsad area (Sumail massif), the focus of our study (Fig. 1), exposes a former asthenospheric diapir that contributed a large amount of melt into the crust [START_REF] Rabinowicz | Melt segregation and flow in mantle diapirs below spreading centers: evidence from the Oman ophiolite[END_REF]. It fed a ridge segment extending to the northwest and southeast of the diapir for a distance of ~80 km [START_REF] Python | Nature and distribution of dykes and related melt migration structures in the mantle section of the Oman ophiolite: Geochemistry[END_REF]. It evolved in a MORB igneous environment [START_REF] Ceuleneer | Thermal structure of a fossil mantle diapir inferred from the distribution of mafic cumulates[END_REF][START_REF] Benoit | Trace element and isotopic characterization of mafic cumulates in a fossil mantle diapir (Oman ophiolite[END_REF][START_REF] Korenaga | Origin of gabbro sills in the Moho transition zone of the Oman ophiolite: Implications for magma transport in the oceanic lower crust[END_REF].

A few faults parallel to the paleo-ridge direction (northwest-southeast) affect the DTZ. They consist of breccia with serpentine and carbonate matrix, frequently intruded by gabbroic dikes altered in greenschist facies conditions. They are zones of intense fluid circulation that underwent moderate normal fault movement. Away from them, dunite is weakly serpentinized (<20%); this has preserved its high-temperature mineral assemblages. Above the Maqsad diapir the DTZ was not transposed off axis by mantle corner flow, and the massif as a whole was not affected by late tectonic events [START_REF] Ceuleneer | Mantle flow patterns at an oceanic spreading centre: The Oman peridotites record[END_REF].

PETROLOGY AND MINERAL CHEMISTRY

We sampled the Maqsad DTZ with a vertical step of 10-20 m along 12 cross sections extending from the mantle harzburgites to the layered cumulates (Fig. 1C). All Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38778.1 Page 4 of 16 samples (~300) as well as ~400 silicate inclusions enclosed in chromite grains were analyzed with the electron microprobe.

The Maqsad DTZ, 200-350 m thick, is made of alternating metric to decametric horizons of pure dunites and dunites containing variable amounts of interstitial clinopyroxene (Cpx) and plagioclase (Fig. 2). The abundance of these interstitial minerals, witnesses of melt percolation, and the degree of differentiation increase upward in most sections, e.g., lower Mg# (100 × Mg/[Mg + Fe Total ]) in olivine and Cpx, lower NiO in olivine, and higher TiO 2 in chromite.

In addition to large (millimeter to centimeter) interstitial and poikilitic Cpx compositions (Cr, Al, and Ti rich) consistent with an igneous origin, tiny (tens to hundreds of microns) Cpx crystals underline olivine grain rims (Fig. 3A).

They display high Mg# (93 < Mg# < 99) and CaO (>25 wt%) and low Al 2 O 3 , Cr 2 O 3 , and TiO 2 contents (see the GSA Data Repository 1 ). These compositions are spread between two end members, the igneous Cpx and the diopsides found in hydrothermal diopsidite veins [START_REF] Python | Diopsidites and rodingites: Serpentinisation and Ca-metasomatism in the Oman Ophiolite mantle[END_REF] (Fig. 4A). They are observed in two-thirds of the samples, distributed across the DTZ and particularly abundant at the top of the diapir. Inclusions of Cpx in chromite exhibit the same range of compositions.

Among the other exotic [[SU: should not be in quotes. "exotic" has specific geological meaning (i.e., foreign or introduced); is meaning here "unusual" or similar?]] interstitial phases, we observed grossular garnet (37 samples; Fig. 3B), amphibole (pargasites and magnesio-hornblendes) (41 samples; Fig. 3C), and enstatite (Opx, 19 samples; Fig. 3D). Almost all occurrences of amphibole and garnet are in the upper half of the DTZ (>~150 m above its base), and Opx is restricted to its upper part Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38778.1 Page 5 of 16 (>~250 m) (Fig. 2). The vertical distribution of each mineral phase in inclusions in chromite grains perfectly mimics their distribution in the olivine matrix.

Interstitial calcic amphiboles (Fig. 3C) have a lower TiO 2 content (mostly <0.2 wt%) than those in inclusions in chromite (0.2-0.9 wt%) (Fig. 4B). This can be attributed to chemical exchange with the host chromites. All amphiboles (both interstitial and enclosed in chromite) display a common evolution of (Na + K) A element concentration from 0.4 to 1. DTZ Opx forms oikocrysts with lobate contacts with olivine, in obvious contrast to their porphyroclastic texture in mantle harzburgite (Fig. 3D). The composition of the two kinds of Opx is also contrasted (Fig. 4C): DTZ Opx (both oikocrysts and inclusions in chromite) have a much higher TiO 2 content for similar Mg#, reaching 0.37 wt% (average = 0.2 wt%). Among the ~400 analyzed inclusions in chromite (Figs. 3E, 3F), 40% = amphibole (mostly pargasite), 39% = igneous Cpx, 7% = hybrid diopside, 7% = olivine, 3% = mica (Na-rich aspidolite and K-rich phlogopite), 3% = Opx, and 1% = plagioclase and garnet.

INVOLVMENT OF A HYDROUS MELT IN THE GENESIS OF THE DTZ

Variations in the distribution of the interstitial minerals evoke crystallization from a percolating melt in response to compaction [START_REF] Rabinowicz | Melt segregation and flow in mantle diapirs below spreading centers: evidence from the Oman ophiolite[END_REF]. In previous studies, the origin of the DTZ has been discussed in a dry igneous system. Interstitial, igneous, Ti-rich Cpx indicates that a MORB melt percolated through the Maqsad DTZ [START_REF] Abily | The dunitic mantle-crust transition zone in the Oman ophiolite: Residue of melt-rock interaction, cumulates from high-MgO melts, or both?[END_REF]this study). This is also evidenced by the composition of the feeding melt channels entrapped in the underlying mantle harzburgite [START_REF] Kelemen | Extraction of mid-ocean-ridge basalt from the upwelling mantle by focused flow of melt in dunite channels[END_REF][START_REF] Ceuleneer | Thermal structure of a fossil mantle diapir inferred from the distribution of mafic cumulates[END_REF][START_REF] Benoit | Trace element and isotopic characterization of mafic cumulates in a fossil mantle diapir (Oman ophiolite[END_REF] and by the composition of the troctolitic-gabbroic sills inside the DTZ [START_REF] Korenaga | Origin of gabbro sills in the Moho transition zone of the Oman ophiolite: Implications for magma transport in the oceanic lower crust[END_REF]. However, the Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38778.1

Page 6 of 16 nature and abundance of the exotic minerals call for pervasive percolation of another water-and silica-rich melt throughout the DTZ that occurred early, as demonstrated by the entrapment of these minerals in the chromite grains. This leads us to formulate the hypothesis that the hydrous melt percolation did not occur after dunite formation, but that it contributed to the process that built the DTZ.

The possibility of a hydrous origin of dunites at a temperature significantly lower than the liquidus of dry basaltic melts was stressed in the seminal work of [START_REF] Bowen | The system MgO-SiO 2 -H 2 O[END_REF]. Addition of water to the system triggers the incongruent melting of enstatite into olivine and silica melt. Dunite will form, and excess silica produced by this reaction is exported from the system. Opx will eventually crystallize where this silicaenriched melt accumulates and cools. The absence of Opx in the lower part of the DTZ and its crystallization at its top is elegantly accounted for in this frame.

ORIGIN OF WATER

A water-saturated melt can have different origins: (1) a mantle source hydrated in a subduction setting (e.g., [START_REF] Macleod | Moist MORB" axial magmatism in the Oman ophiolite: The evidence against a mid-ocean ridge origin[END_REF], (2) a shallow lithospheric source hydrated by hydrothermal fluids and undergoing remelting in response to the rise of a mantle diapir [START_REF] Benoit | The remelting of hydrothermally altered peridotite at mid-ocean ridges by intruding mantle diapirs[END_REF], (3) an extreme degree of fractional crystallization of a dry (actually water poor) MORB, and (4) hybridization of a MORB with hydrothermal fluids.

In the first two hypotheses, the mantle source is depleted in incompatible elements, including Ti. Primitive cumulates rich in Opx are widespread in the ophiolite but crystallized from highly depleted melts [START_REF] Benoit | The remelting of hydrothermally altered peridotite at mid-ocean ridges by intruding mantle diapirs[END_REF][START_REF] Python | Nature and distribution of dykes and related melt migration structures in the mantle section of the Oman ophiolite: Geochemistry[END_REF][START_REF] Akizawa | Petrologic profile of peridotite layers under a possible Moho in the northern Oman ophiolite: An example from Wadi Fizh[END_REF]. High Mg# in interstitial Opx in dunite seems to Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38778.1 Page 7 of 16 contradict MORB involvement (e.g., [START_REF] Wang | Formation of orthopyroxenite by reaction between peridotite and hydrous basaltic melt: An experimental study[END_REF] but not the high Ti content.

Moreover, the successive occurrences of garnet, amphibole, and then Opx upsection (Fig. 2) are not in accordance with a deep-water source, which should have delivered hydrated melt across the DTZ. The third hypothesis is difficult to reconcile with the high Mg# of Opx and the abundance of amphibole: even if we consider that the Mg# is partly buffered by high-forsterite olivine, the degree of fractional crystallization necessary to reach water saturation should be far too high [START_REF] Gillis | Metasomatism of oceanic gabbros by late stage melts and hydrothermal fluids: Evidence from the rare earth element composition of amphiboles: Geochemistry[END_REF]. This led us to explore the fourth hypothesis. The percolation of high-temperature hydrothermal fluids in the Oman lower oceanic crust is well documented (e.g., [START_REF] Coogan | Contaminating the lower crust in the Oman ophiolite[END_REF][START_REF] Bosch | Deep and high-temperature hydrothermal circulation in the Oman ophiolite-Petrological and isotopic evidence[END_REF][START_REF] Akizawa | Crustal diopsidites from the northern Oman ophiolite: Evidence for hydrothermal circulation through suboceanic Moho[END_REF][START_REF] Koepke | Partial melting of oceanic gabbro triggered by migrating water-rich fluids: A prime example from the Oman Ophiolite[END_REF]. The distribution of hydrous minerals in the DTZ is consistent with the involvement of hydrothermal water.

The fact that Cpx composition spreads between igneous and hydrothermal end members (Fig. 4A) is strong evidence for hybridization. We propose that the hybrid melt is a blend between supercritical hydrothermal fluids rich in silica, i.e., trondhjemitic melt issued from hydrous melting of the country rocks [START_REF] Amri | Tectonic setting for the genesis of oceanic plagiogranites: Evidence from a paleo-spreading structure in the Oman ophiolite[END_REF], and variably evolved MORB.

Synmagmatic faults are present at the base of the Maqsad lower crust and were main avenues for seawater penetration down to the Moho [START_REF] Abily | Synmagmatic normal faulting in the lower oceanic crust: Evidence from the Oman ophiolite[END_REF]. The brittle features affecting the DTZ may be the late expressions of faults that were active earlier.

They mainly affect the top of the DTZ and are, with the hydrous mineral distribution (Fig. 2), consistent with a water supply from above. The presence of Opx and amphibole in layered gabbroic cumulates in present-day oceanic lower crust was also explained by the involvement of hydrothermal fluids [START_REF] Gillis | Metasomatism of oceanic gabbros by late stage melts and hydrothermal fluids: Evidence from the rare earth element composition of amphiboles: Geochemistry[END_REF] and by the extraction Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38778.1 Page 8 of 16 from the mantle of heterogeneous batches of slightly evolved and unmixed melt [START_REF] Gillis | Primitive layered gabbros from fast-spreading lower oceanic crust[END_REF].

THERMAL AND CHEMICAL GEODYNAMIC IMPLICATIONS

Interstitial hydrous minerals described in this study crystallized early, as shown by similar phases enclosed in chromite grains. Purely hydrothermal alteration followed the magmatic activity, as indicated by Cpx and amphibole alteration products (Fig. 4B) and the presence of hydrogrossular and serpentine (see also [START_REF] Gregory | An oxygen isotope profile in a section of Cretaceous oceanic crust, Samail Ophiolite, Oman: Evidence for  18 O buffering of the oceans by deep (>5 km) seawater-hydrothermal circulation at mid-ocean ridges[END_REF], but obviously did not totally overprint the high-temperature features. This suggests a high cooling rate of the DTZ, consistent with previous geothermometric studies of the base of the Oman lower crust [START_REF] Vantongeren | Cooling rates in the lower crust of the Oman ophiolite: Ca in olivine, revisited[END_REF] and uppermost mantle section [START_REF] Dygert | Temperatures and cooling rates recorded in REE in coexisting pyroxenes in ophiolitic and abyssal peridotites[END_REF].

Below a 5-6-km-thick crust, the stability field for Opx and amphibole after fractionation from a primitive (virtually dry) to a highly evolved (water-saturated) MORB may imply temperature decrease to ~950 °C (pressure of 0.2 GPa) [START_REF] Berndt | An experimental investigation of the influence of water and oxygen fugacity on differentiation of MORB at 200 MPa[END_REF]. High-temperature conditions of crystallization of diopside from hybrid melts are supported both by their entrapment in chromite and their coexistence with igneous Cpx.

Regarding the composition range pointing toward igneous Cpx, the crystallization temperature of diopside seems to be higher than the 600-800 °C previously estimated for a pure hydrothermal frame [START_REF] Python | Oman diopsidites: A new lithology diagnostic of very high temperature hydrothermal circulation in mantle peridotite below oceanic spreading centres[END_REF][START_REF] Arai | Precipitation and dissolution of chromite by hydrothermal solutions in the Oman ophiolite: New behavior of Cr and chromite[END_REF]. Although the garnet stability field is variable (300-800 °C) (e.g., [START_REF] Bach | The petrology of seafloor rodingites: Insights from geochemical reaction path modeling[END_REF][START_REF] Newton | Solubility of grossular, Ca 3 Al 2 Si 3 O 12 , in H 2 O-NaCl solutions at 800° C and 10kbar, and the stability of garnet in the system CaSiO 3 -Al 2 O 3 -H 2 O-NaCl[END_REF], inclusions of andradite and grossular in chromites show that they also fractionated at a high temperature. Considering that a dry MORB injected at Moho level during the rise of the Maqsad diapir reached 1230 °C [START_REF] Ceuleneer | Thermal structure of a fossil mantle diapir inferred from the distribution of mafic cumulates[END_REF], the Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38778.1 Page 9 of 16 mineralogical distribution through the DTZ (Fig. 2) points toward a thermal gradient of about few hundreds degrees in only few hundred meters, making the Moho a clear rheological transition between the hot ductile mantle above the diapir and the lower crust.

CONCLUSIONS

We propose that the formation of the DTZ bears witness to transient processes attributable to the meeting, at Moho level, of an ascending front of mantle partial melts and a descending front of hydrothermal fluids. This specific context triggers the formation of hybrid melts out of equilibrium with their country rocks, which contribute to deeply modify the mineralogical and geochemical composition of the shallow mantle and deep crust. Furthermore, hydrous melts are well known to be particularly efficient in mobilizing metals, such as Cr, in the formation of chromitite ore bodies [START_REF] Borisova | A new view on the petrogenesis of the Oman ophiolite chromitites from microanalyses of chromite-hosted inclusions[END_REF]. Our results suggest that the DTZ is among the most reactive interfaces on Earth.

Its formation may be a major factor in the global chemical transfer and redistribution between the mantle, the crust, and the ocean, and can condition the cycle of carbon, halogens, and gases such as hydrogen and methane.

Our views, although challenging, do not fully contradict previous models for the genesis of the DTZ, but reconcile different pieces of evidence in a more general scenario. , is available online at http://www.geosociety.org/datarepository/2017/ or on request from editing@geosociety.org.

FIGURE CAPTIONS

Figure 1 .

 1 Figure 1. A: Location of the Oman ophiolite. B: Geological map of the southeast massifs

Figure 2 .Figure 3 .

 23 Figure 2. Synthetic lithological log showing the vertical distribution of the mineral

Figure 4 .

 4 Figure 4. Major element compositions of clinopyroxene (cpx), amphibole (amph), and

ACKNOWLEDGMENTS

We thank S. Gouy, J. Langlade, and P. de Parseval for help in microprobe data acquisition. Financial support was provided by the Centre National de la Recherche Scientifique-Institut National des Sciences de l'Univers. Constructive reviews by N.

Dygert and N. Akizawa helped to improve our paper.