A framework to improve the alignment of individual cytoarchitectonic maps of the Julich-Brain atlas using cortical folding landmarks.

The segregation of the cortical mantle into cytoarchitectonic areas provides a structural basis for the specialization of different brain regions. In vivo neuroimaging experiments can be linked to this postmortem cytoarchitectonic parcellation via Julich-Brain. This atlas embeds probabilistic maps that account for inter-individual variability in the localization of cytoarchitectonic areas in the reference spaces targeted by spatial normalization. We built a framework to improve the alignment of architectural areas across brains using cortical folding landmarks. This framework, initially designed for in vivo imaging, was adapted to postmortem histological data. We applied this to the first 14 brains used to establish the Julich-Brain atlas to infer a refined atlas with more focal probabilistic maps. The improvement achieved is significant in the primary regions and some of the associative areas. This framework also provides a tool for exploring the relationship between cortical folding patterns and cytoarchitectonic areas in different cortical regions to establish new landmarks in the remainder of the cortex.

What do brain endocasts tell us? A comparative analysis of the accuracy of sulcal identification by experts and perspectives in palaeoanthropology.

Palaeoneurology is a complex field as the object of study, the brain, does not fossilize. Studies rely therefore on the (brain) endocranial cast (often named endocast), the only available and reliable proxy for brain shape, size and details of surface. However, researchers debate whether or not specific marks found on endocasts correspond reliably to particular sulci and/or gyri of the brain that were imprinted in the braincase. The aim of this study is to measure the accuracy of sulcal identification through an experiment that reproduces the conditions that palaeoneurologists face when working with hominin endocasts. We asked 14 experts to manually identify well-known foldings in a proxy endocast that was obtained from an MRI of an actual in vivo Homo sapiens head. We observe clear differences in the results when comparing the non-corrected labels (the original labels proposed by each expert) with the corrected labels. This result illustrates that trying to reconstruct a sulcus following the very general known shape/position in the literature or from a mean specimen may induce a bias when looking at an endocast and trying to follow the marks observed there. We also observe that the identification of sulci appears to be better in the lower part of the endocast compared to the upper part. The results concerning specific anatomical traits have implications for highly debated topics in palaeoanthropology. Endocranial description of fossil specimens should in the future consider the variation in position and shape of sulci in addition to using models of mean brain shape. Moreover, it is clear from this study that researchers can perceive sulcal imprints with reasonably high accuracy, but their correct identification and labelling remains a challenge, particularly when dealing with extinct species for which we lack direct knowledge of the brain.

Exploring the emergence of morphological asymmetries around the brain's Sylvian fissure: a longitudinal study of shape variability in preterm infants.

Brain folding patterns vary within the human species, but some folding properties are common across individuals, including the Sylvian fissure's inter-hemispheric asymmetry. Contrarily to the other brain folds (sulci), the Sylvian fissure develops through the process of opercularization, with the frontal, parietal, and temporal lobes growing over the insular lobe. Its asymmetry may be related to the leftward functional lateralization for language processing, but the time course of these asymmetries' development is still poorly understood. In this study, we investigated refined shape features of the Sylvian fissure and their longitudinal development in 71 infants born extremely preterm (mean gestational age at birth: 26.5 weeks) and imaged once before and once at term-equivalent age (TEA). We additionally assessed asymmetrical sulcal patterns at TEA in the perisylvian and inferior frontal regions, neighbor to the Sylvian fissure. While reproducing renowned strong asymmetries in the Sylvian fissure, we captured an early encoding of its main asymmetrical shape features, and we observed global asymmetrical shape features representative of a more pronounced opercularization in the left hemisphere, contrasting with the previously reported right hemisphere advance in sulcation around birth. This added novel insights about the processes governing early-life brain folding mechanisms, potentially linked to the development of language-related capacities.

A bipolar taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients.

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.

Disentangling the variability of the superficial white matter organization using regional-tractogram-based population stratification.

Each variation of the cortical folding pattern implies a particular rearrangement of the geometry of the fibers of the underlying white matter. While this rearrangement only impacts the ends of the long pathways, it may affect most of the trajectory of the short bundles. Therefore, mapping the short fibers of the human brain using diffusion-based tractography requires a dedicated strategy to overcome the variability of the folding patterns. In this paper, we propose a fiber-based stratification strategy splitting the population into homogeneous groups for disentangling the superficial white matter bundle organization. This strategy introduces a new refined fiber distance which includes angular considerations for inferring fine-grained atlases of the short bundles surrounding a specific sulcus and a subtractogram distance that quantifies the similitude between fiber sets of two different subjects. The stratification splits the population into groups with similar regional fiber organization using manifold learning. We first successfully test the hypothesis that the main source of variability of the regional fiber organization is the variability of the regional folding pattern. Then, in each group, we proceed with the automatic identification of the most stable bundles, at a higher granularity level than what can be achieved with the non-stratified whole population, enabling the disentanglement of the very variable configuration of the short fibers. Finally, the method searches for bundle correspondence across groups to build a population level atlas. As a proof of concept, the atlas refinement achieved by this strategy is illustrated for the fibers that surround the central sulcus and the superior temporal sulcus using the HCP dataset.

Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved via a Warping Strategy.

Brain mapping studies often need to identify brain structures or functional circuits into a set of individual brains. To this end, multiple atlases have been published to represent such structures based on different modalities, subject sets, and techniques. The mainstream approach to exploit these atlases consists in spatially deforming each individual data onto a given atlas using dense deformation fields, which supposes the existence of a continuous mapping between atlases and individuals. However, this continuity is not always verified, and this "iconic" approach has limits. We present in this study an alternative, complementary, "structural" approach, which consists in extracting structures from the individual data, and comparing them without deformation. A "structural atlas" is thus a collection of annotated individual data with a common structure nomenclature. It may be used to characterize structure shape variability across individuals or species, or to train machine learning systems. This study exhibits Anatomist, a powerful structural 3D visualization software dedicated to building, exploring, and editing structural atlases involving a large number of subjects. It has been developed primarily to decipher the cortical folding variability; cortical sulci vary enormously in both size and shape, and some may be missing or have various topologies, which makes iconic approaches inefficient to study them. We, therefore, had to build structural atlases for cortical sulci, and use them to train sulci identification algorithms. Anatomist can display multiple subject data in multiple views, supports all kinds of neuroimaging data, including compound structural object graphs, handles arbitrary coordinate transformation chains between data, and has multiple display features. It is designed as a programming library in both C++ and Python languages, and may be extended or used to build dedicated custom applications. Its generic design makes all the display and structural aspects used to explore the variability of the cortical folding pattern work in other applications, for instance, to browse axonal fiber bundles, deep nuclei, functional activations, or other kinds of cortical parcellations. Multimodal, multi-individual, or inter-species display is supported, and adaptations to large scale screen walls have been developed. These very original features make it a unique viewer for structural atlas browsing.

Shape variability of the central sulcus in the developing brain: A longitudinal descriptive and predictive study in preterm infants.

Despite growing evidence of links between sulcation and function in the adult brain, the folding dynamics, occurring mostly before normal-term-birth, is vastly unknown. Looking into the development of cortical sulci in infants can give us keys to address fundamental questions: what is the sulcal shape variability in the developing brain? When are the shape features encoded? How are these morphological parameters related to further functional development? In this study, we aimed to investigate the shape variability of the developing central sulcus, which is the frontier between the primary somatosensory and motor cortices. We studied a cohort of 71 extremely preterm infants scanned twice using MRI - once around 30 weeks post-menstrual age (w PMA) and once at term-equivalent age, around 40w PMA -, in order to quantify the sulcus's shape variability using manifold learning, regardless of age-group or hemisphere. We then used these shape descriptors to evaluate the sulcus's variability at both ages and to assess hemispheric and age-group specificities. This led us to propose a description of ten shape features capturing the variability in the central sulcus of preterm infants. Our results suggested that most of these features (8/10) are encoded as early as 30w PMA. We unprecedentedly observed hemispheric asymmetries at both ages, and the one captured at term-equivalent age seems to correspond with the asymmetry pattern previously reported in adults. We further trained classifiers in order to explore the predictive value of these shape features on manual performance at 5 years of age (handedness and fine motor outcome). The central sulcus's shape alone showed a limited but relevant predictive capacity in both cases. The study of sulcal shape features during early neurodevelopment may participate to a better comprehension of the complex links between morphological and functional organization of the developing brain.

Automatic recognition of specific local cortical folding patterns.

The study of local cortical folding patterns showed links with psychiatric illnesses as well as cognitive functions. Despite the tools now available to visualize cortical folds in 3D, manually classifying local sulcal patterns is a time-consuming and tedious task. In fact, 3D visualization of folds helps experts to identify different sulcal patterns but fold variability is so high that the distinction between these patterns sometimes requires the definition of complex criteria, making manual classification difficult and not reliable. However, the assessment of the impact of these patterns on the functional organization of the cortex could benefit from the study of large databases, especially when studying rare patterns. In this paper, several algorithms for the automatic classification of fold patterns are proposed to allow morphological studies to be extended and confirmed on such large databases. Three methods are proposed, the first based on a Support Vector Machine (SVM) classifier, the second on the Scoring by Non-local Image Patch Estimator (SNIPE) approach and the third based on a 3D Convolution Neural Network (CNN). These methods are generic enough to be applicable to a wide range of folding patterns. They are tested on two types of patterns for which there is currently no method to automatically identify them: the Anterior Cingulate Cortex (ACC) patterns and the Power Button Sign (PBS). The two ACC patterns are almost equally present whereas PBS is a particularly rare pattern in the general population. The three models proposed achieve balanced accuracies of approximately 80% for ACC patterns classification and 60% for PBS classification. The CNN-based model is more interesting for the classification of ACC patterns thanks to its rapid execution. However, SVM and SNIPE-based models are more effective in managing unbalanced problems such as PBS recognition.

Neural entrainment to speech and nonspeech in dyslexia: Conceptual replication and extension of previous investigations.

Whether phonological deficits in developmental dyslexia are associated with impaired neural sampling of auditory information is still under debate. Previous findings suggested that dyslexic participants showed atypical neural entrainment to slow and/or fast temporal modulations in speech, which might affect prosodic/syllabic and phonemic processing respectively. However, the large methodological variations across these studies do not allow us to draw clear conclusions on the nature of the entrainment deficit in dyslexia. Using magnetoencephalography, we measured neural entrainment to nonspeech and speech in both groups. We first aimed to conceptually replicate previous studies on auditory entrainment in dyslexia, using the same measurement methods as in previous studies, and also using new measurement methods (cross-correlation analyses) to better characterize the synchronization between stimulus and brain response. We failed to observe any of the significant group differences that had previously been reported in delta, theta and gamma frequency bands, whether using speech or nonspeech stimuli. However, when analyzing amplitude cross-correlations between noise stimuli and brain responses, we found that control participants showed larger responses than dyslexic participants in the delta range in the right hemisphere and in the gamma range in the left hemisphere. Overall, our results are weakly consistent with the hypothesis that dyslexic individuals show an atypical entrainment to temporal modulations. Our attempt at replicating previously published results highlights the multiple weaknesses of this research area, particularly low statistical power due to small sample size, and the lack of methodological standards inducing considerable heterogeneity of measurement and analysis methods across studies.

The reliability and heritability of cortical folds and their genetic correlations across hemispheres.

Cortical folds help drive the parcellation of the human cortex into functionally specific regions. Variations in the length, depth, width, and surface area of these sulcal landmarks have been associated with disease, and may be genetically mediated. Before estimating the heritability of sulcal variation, the extent to which these metrics can be reliably extracted from in-vivo MRI must be established. Using four independent test-retest datasets, we found high reliability across the brain (intraclass correlation interquartile range: 0.65-0.85). Heritability estimates were derived for three family-based cohorts using variance components analysis and pooled (total N > 3000); the overall sulcal heritability pattern was correlated to that derived for a large population cohort (N > 9000) calculated using genomic complex trait analysis. Overall, sulcal width was the most heritable metric, and earlier forming sulci showed higher heritability. The inter-hemispheric genetic correlations were high, yet select sulci showed incomplete pleiotropy, suggesting hemisphere-specific genetic influences.

Neocortical morphometry in Huntington's disease: Indication of the coexistence of abnormal neurodevelopmental and neurodegenerative processes.

Huntington's disease (HD) is an inherited, autosomal dominant disorder that is characteristically thought of as a degenerative disorder. Despite cellular and molecular grounds suggesting HD could also impact normal development, there has been scarce systems-level data obtained from in vivo human studies supporting this hypothesis. Sulcus-specific morphometry analysis may help disentangle the contribution of coexisting neurodegenerative and neurodevelopmental processes, but such an approach has never been used in HD. Here, we investigated cortical sulcal depth, related to degenerative process, as well as cortical sulcal length, related to developmental process, in early-stage HD and age-matched healthy controls. This morphometric analysis revealed significant differences in the HD participants compared with the healthy controls bilaterally in the central and intra-parietal sulcus, but also in the left intermediate frontal sulcus and calcarine fissure. As the primary visual cortex is not connected to the striatum, the latter result adds to the increasing in vivo evidence for primary cortical degeneration in HD. Those sulcal measures that differed between HD and healthy populations were mainly atrophy-related, showing shallower sulci in HD. Conversely, the sulcal morphometry also revealed a crucial difference in the imprint of the Sylvian fissure that could not be related to loss of grey matter volume: an absence of asymmetry in the length of this fissure in HD. Strong asymmetry in that cortical region is typically observed in healthy development. As the formation of the Sylvian fissure appears early in utero, and marked asymmetry is specifically found in this area of the neocortex in newborns, this novel finding likely indicates the foetal timing of a disease-specific, genetic interplay with neurodevelopment.

Automatic labeling of cortical sulci using patch- or CNN-based segmentation techniques combined with bottom-up geometric constraints.

The extreme variability of the folding pattern of the human cortex makes the recognition of cortical sulci, both automatic and manual, particularly challenging. Reliable identification of the human cortical sulci in its entirety, is extremely difficult and is practiced by only a few experts. Moreover, these sulci correspond to more than a hundred different structures, which makes manual labeling long and fastidious and therefore limits access to large labeled databases to train machine learning. Here, we seek to improve the current model proposed in the Morphologist toolbox, a widely used sulcus recognition toolbox included in the BrainVISA package. Two novel approaches are proposed: patch-based multi-atlas segmentation (MAS) techniques and convolutional neural network (CNN)-based approaches. Both are currently applied for anatomical segmentations because they embed much better representations of inter-subject variability than approaches based on a single template atlas. However, these methods typically focus on voxel-wise labeling, disregarding certain geometrical and topological properties of interest for sulcus morphometry. Therefore, we propose to refine these approaches with domain specific bottom-up geometric constraints provided by the Morphologist toolbox. These constraints are utilized to provide a single sulcus label to each topologically elementary fold, the building blocks of the pattern recognition problem. To eliminate the shortcomings associated with the Morphologist's pre-segmentation into elementary folds, we complement this regularization scheme using a top-down perspective which triggers an additional cleavage of the elementary folds when required. All the newly proposed models outperform the current Morphologist model, the most efficient being a CNN U-Net-based approach which carries out sulcus recognition within a few seconds.

"Plis de passage" Deserve a Role in Models of the Cortical Folding Process.

Cortical folding is a hallmark of brain topography whose variability across individuals remains a puzzle. In this paper, we call for an effort to improve our understanding of the pli de passage phenomenon, namely annectant gyri buried in the depth of the main sulci. We suggest that plis de passage could become an interesting benchmark for models of the cortical folding process. As an illustration, we speculate on the link between modern biological models of cortical folding and the development of the Pli de Passage Frontal Moyen (PPFM) in the middle of the central sulcus. For this purpose, we have detected nine interrupted central sulci in the Human Connectome Project dataset, which are used to explore the organization of the hand sensorimotor areas in this rare configuration of the PPFM.

Network analysis of whole-brain fMRI dynamics: A new framework based on dynamic communicability.

Neuroimaging techniques such as MRI have been widely used to explore the associations between brain areas. Structural connectivity (SC) captures the anatomical pathways across the brain and functional connectivity (FC) measures the correlation between the activity of brain regions. These connectivity measures have been much studied using network theory in order to uncover the distributed organization of brain structures, in particular FC for task-specific brain communication. However, the application of network theory to study FC matrices is often "static" despite the dynamic nature of time series obtained from fMRI. The present study aims to overcome this limitation by introducing a network-oriented analysis applied to whole-brain effective connectivity (EC) useful to interpret the brain dynamics. Technically, we tune a multivariate Ornstein-Uhlenbeck (MOU) process to reproduce the statistics of the whole-brain resting-state fMRI signals, which provides estimates for MOU-EC as well as input properties (similar to local excitabilities). The network analysis is then based on the Green function (or network impulse response) that describes the interactions between nodes across time for the estimated dynamics. This model-based approach provides time-dependent graph-like descriptor, named communicability, that characterize the roles that either nodes or connections play in the propagation of activity within the network. They can be used at both global and local levels, and also enables the comparison of estimates from real data with surrogates (e.g. random network or ring lattice). In contrast to classical graph approaches to study SC or FC, our framework stresses the importance of taking the temporal aspect of fMRI signals into account. Our results show a merging of functional communities over time, moving from segregated to global integration of the network activity. Our formalism sets a solid ground for the analysis and interpretation of fMRI data, including task-evoked activity.

Measurement of Sylvian Fissure asymmetry and occipital bending in humans and Pan troglodytes.

The evolution of human-specific lateralised functions such as language has been linked to the development of structural asymmetries in the brain. Here we applied state of the art image analysis techniques to measure Sylvian Fissure (SF) asymmetry and Occipital Bending (OB) in 3D Magnetic Resonance (MR) images of the brain obtained in-vivo for 30 humans and 30 chimpanzees (Pan troglodytes). SF morphology differed between species, with the human SF terminating more superiorly in right inferior parietal lobe, an asymmetry that was on average absent in chimpanzees (F (1,52) = 5.963, p = 0.018). Irrespective of morphology, Total SF Length was, as previously reported, leftward in humans but not in chimpanzees, although the difference did not reach significance between species. However, when only brains possessing comparable bilateral SF bifurcation morphology were compared, humans showed previously reported "Typical" left-lateralised Anterior-Horizontal (AH-SF) and right-lateralised Vertical (V-SF) SF asymmetries. In contrast, chimpanzees lacked both asymmetries, and this approached being a significant difference between-species in the AH-SF segment (F (1, 34) = 3.680, p = 0.064). On average in humans the left occipital lobe crossed the midline toward the right (Rightward OB) which was significantly different from the chimpanzee cohort that showed no average OB (Independent-Samples Mann-Whitney U Test, p = 0.012). Furthermore, OB was related to SF asymmetry in humans, such that the more rightward V-SF and leftward AH-SF, the more rightward the OB. This "Default" pattern of SF and OB asymmetries was found in 41.7% of human individuals with bilateral SF bifurcation but none of the chimpanzees. To our knowledge, this is the first study highlighting that a pattern of SF and OB asymmetry distinguishes the human from the chimpanzee brain, and suggests this may be associated with a unique trajectory of brain development and functional abilities in humans.

eQTL of KCNK2 regionally influences the brain sulcal widening: evidence from 15,597 UK Biobank participants with neuroimaging data.

The grey and white matter volumes are known to reduce with age. This cortical shrinkage is visible on magnetic resonance images and is conveniently identified by the increased volume of cerebrospinal fluid in the sulci between two gyri. Here, we replicated this finding using the UK Biobank dataset and studied the genetic influence on these cortical features of aging. We divided all individuals genetically confirmed of British ancestry into two sub-cohorts (12,162 and 3435 subjects for discovery and replication samples, respectively). We found that the heritability of the sulcal opening ranges from 15 to 45% (SE = 4.8%). We identified 4 new loci that contribute to this opening, including one that also affects the sulci grey matter thickness. We identified the most significant variant (rs864736) on this locus as being an expression quantitative trait locus (eQTL) for the KCNK2 gene. This gene regulates the immune-cell into the central nervous system (CNS) and controls the CNS inflammation, which is implicated in cortical atrophy and cognitive decline. These results expand our knowledge of the genetic contribution to cortical shrinking and promote further investigation into these variants and genes in pathological context such as Alzheimer's disease in which brain shrinkage is a key biomarker.

Three-Dimensional Probabilistic Maps of Mesial Temporal Lobe Structures in Children and Adolescents' Brains.

The hippocampus and the adjacent perirhinal, entorhinal, temporopolar, and parahippocampal cortices are interconnected in a hierarchical MTL system crucial for memory processes. A probabilistic description of the anatomical location and spatial variability of MTL cortices in the child and adolescent brain would help to assess structure-function relationships. The rhinal sulcus (RS) and the collateral sulcus (CS) that border MTL cortices and influence their morphology have never been described in these populations. In this study, we identified the aforementioned structures on magnetic resonance images of 38 healthy subjects aged 7-17 years old. Relative to sulcal morphometry in the MTL, we showed RS-CS conformation is an additional factor of variability in the MTL that is not explained by other variables such as age, sex and brain volume; with an innovative method using permutation testing of the extrema of structures of interest, we showed that RS-SC conformation was not associated with differences of location of MTL sulci. Relative to probabilistic maps, we offered for the first time a systematic mapping of MTL structures in children and adolescent, mapping all the structures of the MTL system while taking sulcal morphology into account. Our results, with the probabilistic maps described here being freely available for download, will help to understand the anatomy of this region and help functional and clinical studies to accurately test structure-function hypotheses in the MTL during development. Free access to MTL pediatric atlas: http://neurovault.org/collections/2381/.

IntrAnat Electrodes: A Free Database and Visualization Software for Intracranial Electroencephalographic Data Processed for Case and Group Studies.

In some cases of pharmaco-resistant and focal epilepsies, intracranial recordings performed epidurally (electrocorticography, ECoG) and/or in depth (stereoelectroencephalography, SEEG) can be required to locate the seizure onset zone and the eloquent cortex before surgical resection. In SEEG, each electrode contact records brain's electrical activity in a spherical volume of 3 mm diameter approximately. The spatial coverage is around 1% of the brain and differs between patients because the implantation of electrodes is tailored for each case. Group studies thus need a large number of patients to reach a large spatial sampling, which can be achieved more easily using a multicentric approach such as implemented in our F-TRACT project (f-tract.eu). To facilitate group studies, we developed a software-IntrAnat Electrodes-that allows to perform virtual electrode implantation in patients' neuroanatomy and to overlay results of epileptic and functional mapping, as well as resection masks from the surgery. IntrAnat Electrodes is based on a patient database providing multiple search criteria to highlight various group features. For each patient, the anatomical processing is based on a series of software publicly available. Imaging modalities (Positron Emission Tomography (PET), anatomical MRI pre-implantation, post-implantation and post-resection, functional MRI, diffusion MRI, Computed Tomography (CT) with electrodes) are coregistered. The 3D T1 pre-implantation MRI gray/white matter is segmented and spatially normalized to obtain a series of cortical parcels using different neuroanatomical atlases. On post-implantation images, the user can position 3D models of electrodes defined by their geometry. Each electrode contact is then labeled according to its position in the anatomical atlases, to the class of tissue (gray or white matter, cerebro-spinal fluid) and to its presence inside or outside the resection mask. Users can add more functionally informed labels on contact, such as clinical responses after electrical stimulation, cortico-cortical evoked potentials, gamma band activity during cognitive tasks or epileptogenicity. IntrAnat Electrodes software thus provides a means to visualize multimodal data. The contact labels allow to search for patients in the database according to multiple criteria representing almost all available data, which is to our knowledge unique in current SEEG software. IntrAnat Electrodes will be available in the forthcoming release of BrainVisa software and tutorials can be found on the F-TRACT webpage.

The chaotic morphology of the left superior temporal sulcus is genetically constrained.

The asymmetry of the superior temporal sulcus (STS) has been identified as a species-specific feature of the human brain. The so-called superior temporal asymmetrical pit (STAP) area is observed from the last trimester of gestation onwards and is far less pronounced in the chimpanzee brain. This asymmetry is associated with more frequent sulcal interruptions, named plis de passage (PPs), leading to the irregular morphology of the left sulcus. In this paper, we aimed to characterize the variability, asymmetry, and heritability of these interruptions in the STS in comparison with the other main sulci. We developed an automated method to extract PPs across the cortex based on a highly reproducible grid of sulcal pits across individuals, which we applied to a subset of Human Connectome Project (HCP) subjects (N = 820). We report that only a few PPs across the cortex are genetically constrained, namely in the collateral, postcentral and superior temporal sulci and the calcarine fissure. Moreover, some PPs occur more often in one hemisphere than the other, namely in the precentral, postcentral, intraparietal sulci, as well as in both inferior and superior temporal sulci. Most importantly, we found that only the interruptions within the STAP region are both asymmetric and genetically constrained. Because this morphological pattern is located in an area of the left hemisphere related to speech, our results suggest structural constraints on the architecture of the linguistic network.

A validation dataset for Macaque brain MRI segmentation.

Validation data for segmentation algorithms dedicated to preclinical images is fiercely lacking, especially when compared to the large number of databases of Human brain images and segmentations available to the academic community. Not only is such data essential for validating methods, it is also needed for objectively comparing concurrent algorithms and detect promising paths, as segmentation challenges have shown for clinical images. The dataset we present here is a first step in this direction. It comprises 10 T2-weighted MRIs of healthy adult macaque brains, acquired on a 7 T magnet, along with corresponding manual segmentations into 17 brain anatomic labelled regions spread over 5 hierarchical levels based on a previously published macaque atlas (Calabrese et al., 2015) [1]. By giving access to this unique dataset, we hope to provide a reference needed by the non-human primate imaging community. This dataset was used in an article presenting a new primate brain morphology analysis pipeline, Primatologist (Balbastre et al., 2017) [2]. Data is available through a NITRC repository (https://www.nitrc.org/projects/mircen_macset).