BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization

A systematic review of automated methods to perform white matter tract segmentation

White matter tract segmentation is a pivotal research area that leverages diffusion-weighted magnetic resonance imaging (dMRI) for the identification and mapping of individual white matter tracts and their trajectories. This study aims to provide a comprehensive systematic literature review on automated methods for white matter tract segmentation in brain dMRI scans. Articles on PubMed, ScienceDirect [NeuroImage, NeuroImage (Clinical), Medical Image Analysis], Scopus and IEEEXplore databases and Conference proceedings of Medical Imaging Computing and Computer Assisted Intervention Society (MICCAI) and International Symposium on Biomedical Imaging (ISBI), were searched in the range from January 2013 until September 2023. This systematic search and review identified 619 articles. Adhering to the specified search criteria using the query, "white matter tract segmentation OR fiber tract identification OR fiber bundle segmentation OR tractography dissection OR white matter parcellation OR tract segmentation," 59 published studies were selected. Among these, 27% employed direct voxel-based methods, 25% applied streamline-based clustering methods, 20% used streamline-based classification methods, 14% implemented atlas-based methods, and 14% utilized hybrid approaches. The paper delves into the research gaps and challenges associated with each of these categories. Additionally, this review paper illuminates the most frequently utilized public datasets for tract segmentation along with their specific characteristics. Furthermore, it presents evaluation strategies and their key attributes. The review concludes with a detailed discussion of the challenges and future directions in this field.

Cognitive flexibility impairment in temporal lobe epilepsy: The impact of epileptic foci lateralization on executive functions

INTRODUCTION

Temporal Lobe Epilepsy (TLE) has been associated with memory impairments, which are typically linked to hippocampal and mesial temporal cortex lesions. Considering the presence of extensive bidirectional frontotemporal connections, it can be hypothesized that executive dysfunction in TLE is modulated by the lateralization of the epileptic foci.

MATERIAL AND METHODS

A comprehensive neuropsychological executive functions protocol was administered to 63 participants, including 42 individuals with temporal lobe epilepsy (20 with right-TLE and 22 with left-TLE) and 21 healthy controls aged 20-49.

RESULTS

The results indicate that TLE patients exhibit poorer executive performance compared to healthy controls in working memory (F(2,60) = 4.18, p <.01), planning (F(2,60) = 4.71, p <.05), set shifting (F(2,60) = 10.1, p <.001), phonetic verbal fluency (F(2,60) = 11.71, p <.01) and semantic verbal fluency (F(2,60) = 9.61, p <.001. No significant differences were found in cognitive inhibition. Furthermore, right-TLE patients showed lower performance than left-TLE in set shifting (F(1,61) = 6.45, p <.05), while no significant differences were observed in working memory, planning, inhibition, and verbal fluency.

CONCLUSIONS

This research emphasize the importance of considering the lateralization of the temporal lobe focus to achieve a more accurate neuropsychological characterization. The cognitive differences between left and right TLE patients highlight the need for individualized approaches in their treatment and care.

Novel approaches to functional lateralization: Assessing information in activity patterns across hemispheres and more accurately identifying structural homologues

Functional lateralization is typically measured by comparing activation levels across the right and left hemispheres of the brain. Significant additional information, however, exists within distributed multi-voxel patterns of activity - a format not detectable by traditional activation-based analysis of functional magnetic resonance imaging (fMRI) data. We introduce and test two methods -one anatomical, one functional- that allow hemispheric information asymmetries to be detected. We first introduce and apply a novel tool that draws on brain 'surface fingerprints' to pair every location in one hemisphere with its hemispheric homologue. We use anatomical data to show that this approach is more accurate than the common distance-from-midline method for comparing bilateral regions. Next, we introduce a complementary analysis method that quantifies multivariate laterality in functional data. This new 'multivariate Laterality Index' (mLI) reflects both quantitative and qualitative information-differences across homologous activity patterns. We apply the technique here to functional data collected as participants viewed faces and non-faces. Using the previously generated surface fingerprints to pair-up homologous searchlights in each hemisphere, we use the novel multivariate laterality technique to identify face-information asymmetries across right and left counterparts of the fusiform gyrus, inferior temporal gyrus, superior parietal lobule, and early visual areas. The typical location of the fusiform face area has greater information asymmetry for faces than for shapes. More generally, we argue that the field should consider an information-based approach to lateralization.

versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database

The lack of "gold standards" in Diffusion Weighted Imaging (DWI) makes validation cumbersome. To tackle this task, studies use translational analysis where results in humans are benchmarked against findings in other species. Non-Human Primates (NHP) are particularly interesting for this, as their cytoarchitecture is closely related to humans. However, tools used for processing and analysis must be adapted and finely tuned to work well on NHP images. Here, we propose versaFlow, a modular pipeline implemented in Nextflow, designed for robustness and scalability. The pipeline is tailored to in vivo NHP DWI at any spatial resolution; it allows for maintainability and customization. Processes and workflows are implemented using cutting-edge and state-of-the-art Magnetic Resonance Imaging (MRI) processing technologies and diffusion modeling algorithms, namely Diffusion Tensor Imaging (DTI), Constrained Spherical Deconvolution (CSD), and DIstribution of Anisotropic MicrOstructural eNvironments in Diffusion-compartment imaging (DIAMOND). Using versaFlow, we provide an in-depth study of the variability of diffusion metrics computed on 32 subjects from 3 sites of the Primate Data Exchange (PRIME-DE), which contains anatomical T1-weighted (T1w) and T2-weighted (T2w) images, functional MRI (fMRI), and DWI of NHP brains. This dataset includes images acquired over a range of resolutions, using single and multi-shell gradient samplings, on multiple scanner vendors. We perform a reproducibility study of the processing of versaFlow using the Aix-Marseilles site's data, to ensure that our implementation has minimal impact on the variability observed in subsequent analyses. We report very high reproducibility for the majority of metrics; only gamma distribution parameters of DIAMOND display less reproducible behaviors, due to the absence of a mechanism to enforce a random number seed in the software we used. This should be taken into consideration when future applications are performed. We show that the PRIME-DE diffusion data exhibits a great level of variability, similar or greater than results obtained in human studies. Its usage should be done carefully to prevent instilling uncertainty in statistical analyses. This hints at a need for sufficient harmonization in acquisition protocols and for the development of robust algorithms capable of managing the variability induced in imaging due to differences in scanner models and/or vendors.

Language network lateralization is reflected throughout the macroscale functional organization of cortex

Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibit corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses reveal that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization.

Analysis of distributions reveals real differences on dichotic listening scores between left- and right-handers

About 95% of right-handers and 70% of left-handers have a left-hemispheric specialization for language. Dichotic listening is often used as an indirect measure of this language asymmetry. However, while it reliably produces a right-ear advantage (REA), corresponding to the left-hemispheric specialization of language, it paradoxically often fails to obtain statistical evidence of mean differences between left- and right-handers. We hypothesized that non-normality of the underlying distributions might be in part responsible for the similarities in means. Here, we compare the mean ear advantage scores, and also contrast the distributions at multiple quantiles, in two large independent samples (Ns = 1,358 and 1,042) of right-handers and left-handers. Right-handers had an increased mean REA, and a larger proportion had an REA than in the left-handers. We also found that more left-handers are represented in the left-eared end of the distribution. These data suggest that subtle shifts in the distributions of DL scores for right- and left-handers may be at least partially responsible for the unreliability of significantly reduced mean REA in left-handers.

Generative Sampling in Bundle Tractography using Autoencoders (GESTA)

Current tractography methods use the local orientation information to propagate streamlines from seed locations. Many such seeds provide streamlines that stop prematurely or fail to map the true white matter pathways because some bundles are "harder-to-track" than others. This results in tractography reconstructions with poor white and gray matter spatial coverage. In this work, we propose a generative, autoencoder-based method, named GESTA (Generative Sampling in Bundle Tractography using Autoencoders), that produces streamlines achieving better spatial coverage. Compared to other deep learning methods, our autoencoder-based framework uses a single model to generate streamlines in a bundle-wise fashion, and does not require to propagate local orientations. GESTA produces new and complete streamlines for any given white matter bundle, including hard-to-track bundles. Applied on top of a given tractogram, GESTA is shown to be effective in improving the white matter volume coverage in poorly populated bundles, both on synthetic and human brain in vivo data. Our streamline evaluation framework ensures that the streamlines produced by GESTA are anatomically plausible and fit well to the local diffusion signal. The streamline evaluation criteria assess anatomy (white matter coverage), local orientation alignment (direction), and geometry features of streamlines, and optionally, gray matter connectivity. The GESTA framework offers considerable gains in bundle overlap using a reduced set of seeding streamlines with a 1.5x improvement for the "Fiber Cup", and 6x for the ISMRM 2015 Tractography Challenge datasets. Similarly, it provides a 4x white matter volume increase on the BIL&GIN callosal homotopic dataset, and successfully populates bundles on the multi-subject, multi-site, whole-brain in vivo TractoInferno dataset. GESTA is thus a novel deep generative bundle tractography method that can be used to improve the tractography reconstruction of the white matter.

The structural connectivity of the human angular gyrus as revealed by microdissection and diffusion tractography

The angular gyrus (AG) has been described in numerous studies to be consistently activated in various functional tasks. The angular gyrus is a critical connector epicenter linking multiple functional networks due to its location in the posterior part of the inferior parietal cortex, namely at the junction between the parietal, temporal, and occipital lobes. It is thus crucial to identify the different pathways that anatomically connect this high-order association region to the rest of the brain. Our study revisits the three-dimensional architecture of the structural AG connectivity by combining state-of-the-art postmortem blunt microdissection with advanced in vivo diffusion tractography to comprehensively describe the association, projection, and commissural fibers that connect the human angular gyrus. AG appears as a posterior "angular stone" of associative connections belonging to mid- and long-range dorsal and ventral fibers of the superior and inferior longitudinal systems, respectively, to short-range parietal, occipital, and temporal fibers, including U-shaped fibers in the posterior transverse system. Thus, AG is at a pivotal dorso-ventral position reflecting its critical role in the different functional networks, particularly in language elaboration and spatial attention and awareness in the left and right hemispheres, respectively. We also reveal striatal, thalamic, and brainstem connections and a typical inter-hemispheric homotopic callosal connectivity supporting the suggested AG role in the integration of sensory input for modulating motor control and planning. The present description of AG's highly distributed wiring diagram may drastically improve intraoperative subcortical testing and post-operative neurologic outcomes related to surgery in and around the angular gyrus.

TractoInferno - A large-scale, open-source, multi-site database for machine learning dMRI tractography

TractoInferno is the world's largest open-source multi-site tractography database, including both research- and clinical-like human acquisitions, aimed specifically at machine learning tractography approaches and related ML algorithms. It provides 284 samples acquired from 3 T scanners across 6 different sites. Available data includes T1-weighted images, single-shell diffusion MRI (dMRI) acquisitions, spherical harmonics fitted to the dMRI signal, fiber ODFs, and reference streamlines for 30 delineated bundles generated using 4 tractography algorithms, as well as masks needed to run tractography algorithms. Manual quality control was additionally performed at multiple steps of the pipeline. We showcase TractoInferno by benchmarking the learn2track algorithm and 5 variations of the same recurrent neural network architecture. Creating the TractoInferno database required approximately 20,000 CPU-hours of processing power, 200 man-hours of manual QC, 3,000 GPU-hours of training baseline models, and 4 Tb of storage, to produce a final database of 350 Gb. By providing a standardized training dataset and evaluation protocol, TractoInferno is an excellent tool to address common issues in machine learning tractography.

Stroke disconnectome decodes reading networks

Cognitive functional neuroimaging has been around for over 30 years and has shed light on the brain areas relevant for reading. However, new methodological developments enable mapping the interaction between functional imaging and the underlying white matter networks. In this study, we used such a novel method, called the disconnectome, to decode the reading circuitry in the brain. We used the resulting disconnection patterns to predict a typical lesion that would lead to reading deficits after brain damage. Our results suggest that white matter connections critical for reading include fronto-parietal U-shaped fibres and the vertical occipital fasciculus (VOF). The lesion most predictive of a reading deficit would impinge on the left temporal, occipital, and inferior parietal gyri. This novel framework can systematically be applied to bridge the gap between the neuropathology of language and cognitive neuroscience.

A Personalized Longitudinal Strategy in Low-Grade Glioma Patients: Predicting Oncological and Neural Interindividual Variability and Its Changes over Years to Think One Step Ahead

Diffuse low-grade glioma (LGG) is a rare cerebral cancer, mostly involving young adults with an active life at diagnosis. If left untreated, LGG widely invades the brain and becomes malignant, generating neurological worsening and ultimately death. Early and repeat treatments for this incurable tumor, including maximal connectome-based surgical resection(s) in awake patients, enable postponement of malignant transformation while preserving quality of life owing to constant neural network reconfiguration. Due to considerable interindividual variability in terms of LGG course and consecutive cerebral reorganization, a multistage longitudinal strategy should be tailored accordingly in each patient. It is crucial to predict how the glioma will progress (changes in growth rate and pattern of migration, genetic mutation, etc.) and how the brain will adapt (changes in patterns of spatiotemporal redistribution, possible functional consequences such as epilepsy or cognitive decline, etc.). The goal is to anticipate therapeutic management, remaining one step ahead in order to select the optimal (re-)treatment(s) (some of them possibly kept in reserve), at the appropriate time(s) in the evolution of this chronic disease, before malignization and clinical worsening. Here, predictive tumoral and non-tumoral factors, and their ever-changing interactions, are reviewed to guide individual decisions in advance based on patient-specific markers, for the treatment of LGG.

Longitudinal associations of absolute versus relative moderate-to-vigorous physical activity with brain microstructural decline in aging

Higher moderate-to-vigorous intensity (MVPA) may preserve brain structural integrity, but evidence is mostly cross-sectional and relies on absolute PA measures. We examined longitudinal associations of absolute MVPA using population-level activity count thresholds and relative MVPA using individual heart rate reserve (HRR) via Actiheart with subsequent changes in brain diffusion tensor imaging (DTI) over average of 3.8 years in 248 initially cognitively normal individuals (56-91 years). DTI markers included areas important for memory (temporal areas), executive (prefrontal cortex, superior longitudinal fasciculus), and motor function (precentral gyrus, putamen, caudate, body of corpus callosum). Associations of MVPA with changes in DTI markers were examined using linear mixed-effects models, adjusted for demographics and apolipoprotein e4 carrier status. Each additional 22 min of relative MVPA per day was significantly associated with less decline in fractional anisotropy of uncinate fasciculus and cingulum-hippocampal part and with less increase in mean diffusivity of entorhinal cortex and parahippocampal gyrus. Absolute MVPA was not associated with DTI changes. More time spent in relative MVPA by HRR may prevent brain microstructural decline in selected temporal areas.

Novel characterization of the relationship between verbal list-learning outcomes and hippocampal subfields in healthy adults

The relationship between hippocampal subfield volumetry and verbal list‐learning test outcomes have mostly been studied in clinical and elderly populations, and remain controversial. For the first time, we characterized a relationship between verbal list‐learning test outcomes and hippocampal subfield volumetry on two large separate datasets of 447 and 1,442 healthy young and middle‐aged adults, and explored the processes that could explain this relationship. We observed a replicable positive linear correlation between verbal list‐learning test free recall scores and CA1 volume, specific to verbal list learning as demonstrated by the hippocampal subfield volumetry independence from verbal intelligence. Learning meaningless items was also positively correlated with CA1 volume, pointing to the role of the test design rather than word meaning. Accordingly, we found that association‐based mnemonics mediated the relationship between verbal list‐learning test outcomes and CA1 volume. This mediation suggests that integrating items into associative representations during verbal list‐learning tests explains CA1 volume variations: this new explanation is consistent with the associative functions of the human CA1.

Large-Scale Phenomic and Genomic Analysis of Brain Asymmetrical Skew

The human cerebral hemispheres show a left-right asymmetrical torque pattern, which has been claimed to be absent in chimpanzees. The functional significance and developmental mechanisms are unknown. Here, we carried out the largest-ever analysis of global brain shape asymmetry in magnetic resonance imaging data. Three population datasets were used, UK Biobank (N = 39 678), Human Connectome Project (N = 1113), and BIL&GIN (N = 453). At the population level, there was an anterior and dorsal skew of the right hemisphere, relative to the left. Both skews were associated independently with handedness, and various regional gray and white matter metrics oppositely in the two hemispheres, as well as other variables related to cognitive functions, sociodemographic factors, and physical and mental health. The two skews showed single nucleotide polymorphisms-based heritabilities of 4-13%, but also substantial polygenicity in causal mixture model analysis, and no individually significant loci were found in genome-wide association studies for either skew. There was evidence for a significant genetic correlation between horizontal brain skew and autism, which requires future replication. These results provide the first large-scale description of population-average brain skews and their inter-individual variations, their replicable associations with handedness, and insights into biological and other factors which associate with human brain asymmetry.

The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.

CHDGKB: a knowledgebase for systematic understanding of genetic variations associated with non-syndromic congenital heart disease

Congenital heart disease (CHD) is one of the most common birth defects, with complex genetic and environmental etiologies. The reports of genetic variation associated with CHD have increased dramatically in recent years due to the revolutionary development of molecular technology. However, CHD is a heterogeneous disease, and its genetic origins remain inconclusive in most patients. Here we present a database of genetic variations for non-syndromic CHD (NS-CHD). By manually literature extraction and analyses, 5345 NS-CHD-associated genetic variations were collected, curated and stored in the public online database. The objective of our database is to provide the most comprehensive updates on NS-CHD genetic research and to aid systematic analyses of pathogenesis of NS-CHD in molecular level and the correlation between NS-CHD genotypes and phenotypes. Database URL: http://www.sysbio.org.cn/CHDGKB/.

3D Segmentation of Perivascular Spaces on T1-Weighted 3 Tesla MR Images With a Convolutional Autoencoder and a U-Shaped Neural Network

We implemented a deep learning (DL) algorithm for the 3-dimensional segmentation of perivascular spaces (PVSs) in deep white matter (DWM) and basal ganglia (BG). This algorithm is based on an autoencoder and a U-shaped network (U-net), and was trained and tested using T1-weighted magnetic resonance imaging (MRI) data from a large database of 1,832 healthy young adults. An important feature of this approach is the ability to learn from relatively sparse data, which gives the present algorithm a major advantage over other DL algorithms. Here, we trained the algorithm with 40 T1-weighted MRI datasets in which all "visible" PVSs were manually annotated by an experienced operator. After learning, performance was assessed using another set of 10 MRI scans from the same database in which PVSs were also traced by the same operator and were checked by consensus with another experienced operator. The Sorensen-Dice coefficients for PVS voxel detection in DWM (resp. BG) were 0.51 (resp. 0.66), and 0.64 (resp. 0.71) for PVS cluster detection (volume threshold of 0.5 within a range of 0 to 1). Dice values above 0.90 could be reached for detecting PVSs larger than 10 mm3 and 0.95 for PVSs larger than 15 mm3. We then applied the trained algorithm to the rest of the database (1,782 individuals). The individual PVS load provided by the algorithm showed a high agreement with a semi-quantitative visual rating done by an independent expert rater, both for DWM and for BG. Finally, we applied the trained algorithm to an age-matched sample from another MRI database acquired using a different scanner. We obtained a very similar distribution of PVS load, demonstrating the interoperability of this algorithm.

Filtering in tractography using autoencoders (FINTA)

Current brain white matter fiber tracking techniques show a number of problems, including: generating large proportions of streamlines that do not accurately describe the underlying anatomy; extracting streamlines that are not supported by the underlying diffusion signal; and under-representing some fiber populations, among others. In this paper, we describe a novel autoencoder-based learning method to filter streamlines from diffusion MRI tractography, and hence, to obtain more reliable tractograms. Our method, dubbed FINTA (Filtering in Tractography using Autoencoders) uses raw, unlabeled tractograms to train the autoencoder, and to learn a robust representation of brain streamlines. Such an embedding is then used to filter undesired streamline samples using a nearest neighbor algorithm. Our experiments on both synthetic and in vivo human brain diffusion MRI tractography data obtain accuracy scores exceeding the 90% threshold on the test set. Results reveal that FINTA has a superior filtering performance compared to conventional, anatomy-based methods, and the RecoBundles state-of-the-art method. Additionally, we demonstrate that FINTA can be applied to partial tractograms without requiring changes to the framework. We also show that the proposed method generalizes well across different tracking methods and datasets, and shortens significantly the computation time for large (>1 M streamlines) tractograms. Together, this work brings forward a new deep learning framework in tractography based on autoencoders, which offers a flexible and powerful method for white matter filtering and bundling that could enhance tractometry and connectivity analyses.

The inferior fronto-occipital fascicle: a century of controversies from anatomy theaters to operative neurosurgery

INTRODUCTION

Since its first description in the early 19th century, the inferior frontooccipital fascicle (IFOF) and its anatomo-functional features were neglected in the neuroscientific literature for the last century. In the last decade, the rapid development of in vivo imaging for the reconstruction of white matter (WM) connectivity (i.e., tractography) and the consequent interest in more traditional ex vivo methods (postmortem dissection) have allowed a renewed debate about course, termination territories, anatomical relationships, and functional roles of this fascicle.

EVIDENCE ACQUISITION

We reviewed the main current knowledge concerning the structural and functional anatomy of the IFOF and possible implications in neurosurgical practice.

EVIDENCE SYNTHESIS

The IFOF connects the occipital cortex, the temporo-basal areas, the superior parietal lobule, and the pre-cuneus to the frontal lobe, passing through the ventral third of subinsular WM of the external capsule. This wide distribution of cortical terminations provides multimodal integration between several functional networks, including language, non-verbal semantic processing, object identification, visuo-spatial processing and planning, reading, facial expression recognition, memory and conceptualization, emotional and neuropsychological behavior. This anatomo-functional organization has important implication also in neurosurgical practice, especially when approaching the frontal, insular, temporo-parieto-occipital regions and the ventricular system.

CONCLUSIONS

The IFOF is the most extensive associative bundle of the human connectome. Its multi-layer organization reflects important implications in many aspects of brain functional processing. Accurate awareness of IFOF functional anatomy and integration between multimodal datasets coming from different sources has crucial implications for both neuroscientific knowledge and quality of neurosurgical treatments.

Manual praxis and language-production networks, and their links to handedness

While Liepmann was one of the first researchers to consider a relationship between skilled manual actions (praxis) and language for tasks performed "freely from memory", his primary focus was on the relations between the organization of praxis and left-hemisphere dominance. Subsequent attempts to apply his apraxia model to all cases he studied - including his first patient, a "non-pure right-hander" treated as an exception - left the praxis-handedness issue unresolved. Modern neuropsychological and recent neuroimaging evidence either showed closer associations of praxis and language, than between handedness and any of these two functions, or focused on their dissociations. Yet, present-day developments in neuroimaging and statistics allow us to overcome the limitations of the earlier work on praxis-language-handedness links, and to better quantify their interrelationships. Using functional magnetic resonance imaging (fMRI), we studied tool use pantomimes and subvocal word generation in 125 participants, including righthanders (N_RH = 52), ambidextrous individuals (mixedhanders; N_MH = 31), and lefthanders (N_LH = 42). Laterality indices were calculated both in two critical cytoarchitectonic maps, and 180 multi-modal parcellations of the human cerebral cortex, using voxel count and signal intensity, and the most relevant regions of interest and their networks were further analyzed. We found that atypical organization of praxis was present in all handedness groups (RH = 25.0%, MH = 22.6%; LH = 45.2%), and was about two and a half times as common as atypical organization of language (RH = 3.8%; MH = 6.5%; LH = 26.2%), contingent on ROI selection/LI-calculation method. Despite strong associations of praxis and language, regardless of handedness and typicality, dissociations of atypically represented praxis from typical left-lateralized language were common (~20% of cases), whereas the inverse dissociations of atypically represented language from typical left-lateralized praxis were very rare (in ~2.5% of all cases). The consequences of the existence of such different phenotypes for theoretical accounts of manual praxis, and its links to language and handedness are modeled and discussed.

Deep Learning-based Classification of Resting-state fMRI Independent-component Analysis

Functional connectivity analyses of fMRI data have shown that the activity of the brain at rest is spatially organized into resting-state networks (RSNs). RSNs appear as groups of anatomically distant but functionally tightly connected brain regions. Inter-RSN intrinsic connectivity analyses may provide an optimal spatial level of integration to analyze the variability of the functional connectome. Here we propose a deep learning approach to enable the automated classification of individual independent-component (IC) decompositions into a set of predefined RSNs. Two databases were used in this work, BIL&GIN and MRi-Share, with 427 and 1811 participants, respectively. We trained a multilayer perceptron (MLP) to classify each IC as one of 45 RSNs, using the IC classification of 282 participants in BIL&GIN for training and a 5-dimensional parameter grid search for hyperparameter optimization. It reached an accuracy of 92 %. Predictions for the remaining individuals in BIL&GIN were tested against the original classification and demonstrated good spatial overlap between the cortical RSNs. As a first application, we created an RSN atlas based on MRi-Share. This atlas defined a brain parcellation in 29 RSNs covering 96 % of the gray matter. Second, we proposed an individual-based analysis of the subdivision of the default-mode network into 4 networks. Minimal overlap between RSNs was found except in the angular gyrus and potentially in the precuneus. We thus provide the community with an individual IC classifier that can be used to analyze one dataset or to statistically compare different datasets for RSN spatial definitions.

Neural support of manual preference revealed by BOLD variations during right and left finger-tapping in a sample of 287 healthy adults balanced for handedness

We have identified the brain areas involved in Manual Preference (MP) in 143 left-handers (LH) and 144 right-handers (RH). First, we selected the pairs of homotopic regions of interest (hROIs) of the AICHA atlas with significant contralateral activation and asymmetry during the right hand and the left hand Finger-Tapping (FT) both in RH and LH. Thirteen hROIs were selected, including the primary and secondary sensorimotor and premotor cortices, thalamus, dorsal putamen, and cerebellar lobule IV. In both groups, contralateral activations and ipsilateral deactivations were seen, with stronger asymmetries when the preferred hand was used. Comparing with different models for the prediction of MP, we found that the differences in activity during preferred hand minus non-preferred hand movement in 11 contralateral and/or ipsilateral hROIS were best at explaining handedness distribution. Two different mechanisms were identified: 1. Stronger contralateral activity of cortical and cerebellar motor areas during right hand movement, seen in both groups but modulated by handedness; 2. Stronger deactivation in ipsilateral areas during dominant hand movement in both groups, LH here mirroring RH. The present study thus demonstrates that handedness neural support is complex and not simply based on a mirrored organization of hand motor areas.

Typical and atypical language brain organization based on intrinsic connectivity and multitask functional asymmetries

Based on the joint investigation in 287 healthy volunteers (150 left-Handers (LH)) of language task-induced asymmetries and intrinsic connectivity strength of the sentence-processing supramodal network, we show that individuals with atypical rightward language lateralization (N = 30, 25 LH) do not rely on an organization that simply mirrors that of typical leftward lateralized individuals. Actually, the resting-state organization in the atypicals showed that their sentence processing was underpinned by left and right networks both wired for language processing and highly interacting by strong interhemispheric intrinsic connectivity and larger corpus callosum volume. Such a loose hemispheric specialization for language permits the hosting of language in either the left and/or right hemisphere as assessed by a very high incidence of dissociations across various language task-induced asymmetries in this group.

Gene Expression Correlates of the Cortical Network Underlying Sentence Processing

A pivotal question in modern neuroscience is which genes regulate brain circuits that underlie cognitive functions. However, the field is still in its infancy. Here we report an integrated investigation of the high-level language network (i.e., sentence-processing network) in the human cerebral cortex, combining regional gene expression profiles, task fMRI, large-scale neuroimaging meta-analysis, and resting-state functional network approaches. We revealed reliable gene expression-functional network correlations using three different network definition strategies, and identified a consensus set of genes related to connectivity within the sentence-processing network. The genes involved showed enrichment for neural development and actin-related functions, as well as association signals with autism, which can involve disrupted language functioning. Our findings help elucidate the molecular basis of the brain's infrastructure for language. The integrative approach described here will be useful for studying other complex cognitive traits.

Large-scale plurimodal networks common to listening to, producing and reading word lists: an fMRI study combining task-induced activation and intrinsic connectivity in 144 right-handers

We aimed at identifying plurimodal large-scale networks for producing, listening to and reading word lists based on the combined analyses of task-induced activation and resting-state intrinsic connectivity in 144 healthy right-handers. In the first step, we identified the regions in each hemisphere showing joint activation and joint asymmetry during the three tasks. In the left hemisphere, 14 homotopic regions of interest (hROIs) located in the left Rolandic sulcus, precentral gyrus, cingulate gyrus, cuneus and inferior supramarginal gyrus (SMG) met this criterion, and 7 hROIs located in the right hemisphere were located in the preSMA, medial superior frontal gyrus, precuneus and superior temporal sulcus (STS). In a second step, we calculated the BOLD temporal correlations across these 21 hROIs at rest and conducted a hierarchical clustering analysis to unravel their network organization. Two networks were identified, including the WORD-LIST_CORE network that aggregated 14 motor, premotor and phonemic areas in the left hemisphere plus the right STS that corresponded to the posterior human voice area (pHVA). The present results revealed that word-list processing is based on left articulatory and storage areas supporting the action-perception cycle common not only to production and listening but also to reading. The inclusion of the right pHVA acting as a prosodic integrative area highlights the importance of prosody in the three modalities and reveals an intertwining across hemispheres between prosodic (pHVA) and phonemic (left SMG) processing. These results are consistent with the motor theory of speech postulating that articulatory gestures are the central motor units on which word perception, production, and reading develop and act together.

The depth and breadth of multiple perceptual asymmetries in right handers and non-right handers

Several non-verbal perceptual and attentional processes have been linked with specialization of the right cerebral hemisphere. Given that most people have a left hemispheric specialization for language, it is tempting to assume that functions of these two classes of dominance are related. Unfortunately, such models of complementarity are notoriously hard to test. Here we suggest a method which compares frequency of a particular perceptual asymmetry with known frequencies of left hemispheric language dominance in right-handed and non-right handed groups. We illustrate this idea using the greyscales and colourscales tasks, chimeric faces, emotional dichotic listening, and a consonant-vowel dichotic listening task. Results show a substantial "breadth" of leftward bias on the right hemispheric tasks and rightward bias on verbal dichotic listening. Right handers and non-right handers did not differ in terms of proportions of people who were left biased for greyscales/colourscales. Support for reduced typical biases in non-right handers was found for chimeric faces and for CV dichotic listening. Results are discussed in terms of complementary theories of cerebral asymmetries, and how this type of method could be used to create a taxonomy of lateralized functions, each categorized as related to speech and language dominance, or not.

Intracortical Myelination of Heschl's Gyrus and the Planum Temporale Varies With Heschl's Duplication Pattern and Rhyming Performance: An Investigation of 440 Healthy Volunteers

We investigated, in 445 healthy adults whose Heschl's gyrus (HG) gyrification patterns had been previously identified, how an in vivo MRI marker of intracortical myelination of HG and the planum temporale (PT) varied as a function of HG gyrification pattern and, in cases of duplication, of anatomical characteristics of the second HG (H2). By measuring the MRI T1/T2 ratio in regions of interest covering the first HG (H1), H2 in cases of common stem (H2CSD), or complete posterior duplication (H2CPD) and the PT, we showed that H1 had the highest T1/T2 values, while the PT had the lowest. The major impact of duplication was a decrease in both H1 and PT T1/T2 values in cases of left CPD. Concerning H2, the right and left T1/T2 values of right H2CSD were closer to those of H1, and those of left H2CPD were closer to those of PT. After adjusting for verbal skills, rhyming performance was not associated with T1/T2 values in left regions, but it decreased with increasing right PT T1/T2 values. These results reveal the existence of hemispheric differences in H2 myelination and underline the importance of neuroimaging markers of intracortical myelination for investigating brain structure-function relationships.

A SENtence Supramodal Areas AtlaS (SENSAAS) based on multiple task-induced activation mapping and graph analysis of intrinsic connectivity in 144 healthy right-handers

We herein propose an atlas of 32 sentence-related areas based on a 3-step method combining the analysis of activation and asymmetry during multiple language tasks with hierarchical clustering of resting-state connectivity and graph analyses. 144 healthy right-handers performed fMRI runs based on language production, reading and listening, both with sentences and lists of over-learned words. Sentence minus word-list BOLD contrast and left-minus-right BOLD asymmetry for each task were computed in pairs of homotopic regions of interest (hROIs) from the AICHA atlas. Thirty-two hROIs were identified that were conjointly activated and leftward asymmetrical in each of the three language contrasts. Analysis of resting-state temporal correlations of BOLD variations between these 32 hROIs allowed the segregation of a core network, SENT_CORE including 18 hROIs. Resting-state graph analysis applied to SENT_CORE hROIs revealed that the pars triangularis of the inferior frontal gyrus and the superior temporal sulcus were hubs based on their degree centrality (DC), betweenness, and participation values corresponding to epicentres of sentence processing. Positive correlations between DC and BOLD activation values for SENT_CORE hROIs were observed across individuals and across regions regardless of the task: the more a SENT_CORE area is connected at rest the stronger it is activated during sentence processing. DC measurements in SENT_CORE may thus be a valuable index for the evaluation of inter-individual variations in language areas functional activity in relation to anatomical or clinical patterns in large populations. SENSAAS (SENtence Supramodal Areas AtlaS), comprising the 32 supramodal sentence areas, including SENT_CORE network, can be downloaded at http://www.gin.cnrs.fr/en/tools/ .

The relationship between behavioral language laterality, face laterality and language performance in left-handers

Left-handers provide unique information about the relationship between cognitive functions because of their larger variability in hemispheric dominance. This study presents the laterality distribution of, correlations between and test-retest reliability of behavioral lateralized language tasks (speech production, reading and speech perception), face recognition tasks, handedness measures and language performance tests based on data from 98 left-handers. The results show that a behavioral test battery leads to percentages of (a)typical dominance that are similar to those found in neuropsychological studies even though the incidence of clear atypical lateralization (about 20%) may be overestimated at the group level. Significant correlations were found between the language tasks for both reaction time and accuracy lateralization indices. The degree of language laterality could however not be linked to face laterality, handedness or language performance. Finally, individuals were classified less consistently than expected as being typical, bilateral or atypical across all tasks. This may be due to the often good (speech production and perception tasks) but sometimes weak (reading and face tasks) test-retest reliabilities. The lack of highly reliable and valid test protocols for functions unrelated to speech remains one of the largest impediments for individual analysis and cross-task investigations in laterality research.

A population-based atlas of the human pyramidal tract in 410 healthy participants

With the advances in diffusion MRI and tractography, numerous atlases of the human pyramidal tract (PyT) have been proposed, but the inherent limitation of tractography to resolve crossing bundles within the centrum semiovale has so far prevented the complete description of the most lateral PyT projections. Here, we combined a precise manual positioning of individual subcortical regions of interest along the descending pathway of the PyT with a new bundle-specific tractography algorithm. This later is based on anatomical priors to improve streamlines tracking in crossing areas. We then extracted both left and right PyT in a large cohort of 410 healthy participants and built a population-based atlas of the whole-fanning PyT with a complete description of its most corticolateral projections. Clinical applications are envisaged, the whole-fanning PyT atlas being likely a better marker of corticospinal integrity metrics than those currently used within the frame of prediction of poststroke motor recovery. The present population-based PyT, freely available, provides an interesting tool for clinical applications to locate specific PyT damage and its impact to the short- and long-term motor recovery after stroke.

Bundle-specific tractography with incorporated anatomical and orientational priors

Anatomical white matter bundles vary in shape, size, length, and complexity, making diffusion MRI tractography reconstruction of some bundles more difficult than others. As a result, bundles reconstruction often suffers from a poor spatial extent recovery. To fill-up the white matter volume as much and as best as possible, millions of streamlines can be generated and filtering techniques applied to address this issue. However, well-known problems and biases are introduced such as the creation of a large number of false positives and over-representation of easy-to-track parts of bundles and under-representation of hard-to-track. To address these challenges, we developed a Bundle-Specific Tractography (BST) algorithm. It incorporates anatomical and orientational prior knowledge during the process of streamline tracing to increase reproducibility, sensitivity, specificity and efficiency when reconstructing certain bundles of interest. BST outperforms classical deterministic, probabilistic, and global tractography methods. The increase in anatomically plausible streamlines, with larger spatial coverage, helps to accurately represent the full shape of bundles, which could greatly enhance and robustify tract-based and connectivity-based neuroimaging studies.

The Nomenclature of Human White Matter Association Pathways: Proposal for a Systematic Taxonomic Anatomical Classification

The heterogeneity and complexity of white matter (WM) pathways of the human brain were discretely described by pioneers such as Willis, Stenon, Malpighi, Vieussens and Vicq d'Azyr up to the beginning of the 19th century. Subsequently, novel approaches to the gross dissection of brain internal structures have led to a new understanding of WM organization, notably due to the works of Reil, Gall and Burdach highlighting the fascicular organization of WM. Meynert then proposed a definitive tripartite organization in association, commissural and projection WM pathways. The enduring anatomical work of Dejerine at the turn of the 20th century describing WM pathways in detail has been the paramount authority on this topic (including its terminology) for over a century, enriched sporadically by studies based on blunt Klingler dissection. Currently, diffusion-weighted magnetic resonance imaging (DWI) is used to reveal the WM fiber tracts of the human brain in vivo by measuring the diffusion of water molecules, especially along axons. It is then possible by tractography to reconstitute the WM pathways of the human brain step by step at an unprecedented level of precision in large cohorts. However, tractography algorithms, although powerful, still face the complexity of the organization of WM pathways, and there is a crucial need to benefit from the exact definitions of the trajectories and endings of all WM fascicles. Beyond such definitions, the emergence of DWI-based tractography has mostly revealed strong heterogeneity in naming the different bundles, especially the long-range association pathways. This review addresses the various terminologies known for the WM association bundles, aiming to describe the rules of arrangements followed by these bundles and to propose a new nomenclature based on the structural wiring diagram of the human brain.

Frontoparietal Tracts Linked to Lateralized Hand Preference and Manual Specialization

Humans show a preference for using the right hand over the left for tasks and activities of everyday life. While experimental work in non-human primates has identified the neural systems responsible for reaching and grasping, the neural basis of lateralized motor behavior in humans remains elusive. The advent of diffusion imaging tractography for studying connectional anatomy in the living human brain provides the possibility of understanding the relationship between hemispheric asymmetry, hand preference, and manual specialization. In this study, diffusion tractography was used to demonstrate an interaction between hand preference and the asymmetry of frontoparietal tracts, specifically the dorsal branch of the superior longitudinal fasciculus, responsible for visuospatial integration and motor planning. This is in contrast to the corticospinal tract and the superior cerebellar peduncle, for which asymmetry was not related to hand preference. Asymmetry of the dorsal frontoparietal tract was also highly correlated with the degree of lateralization in tasks requiring visuospatial integration and fine motor control. These results suggest a common anatomical substrate for hand preference and lateralized manual specialization in frontoparietal tracts important for visuomotor processing.

The Impact of Handedness, Sex, and Cognitive Abilities on Left-Right Discrimination: A Behavioral Study

The present study examined the relationship between left–right discrimination (LRD) performance and handedness, sex and cognitive abilities. In total, 31 men and 35 women – with a balanced ratio of left-and right-handers – completed the Bergen Left–Right Discrimination Test. We found an advantage of left-handers in both identifying left hands and in verifying “left” propositions. A sex effect was also found, as women had an overall higher error rate than men, and increasing difficulty impacted their reaction time more than it did for men. Moreover, sex interacted with handedness and manual preference strength. A negative correlation of LRD reaction time with visuo-spatial and verbal long-term memory was found independently of sex, providing new insights into the relationship between cognitive skills and performance on LRD.

The Neural Correlates of Grasping in Left-Handers: When Handedness Does Not Matter

Neurophysiological studies showed that in macaques, grasp-related visuomotor transformations are supported by a circuit involving the anterior part of the intraparietal sulcus, the ventral and the dorsal region of the premotor area. In humans, a similar grasp-related circuit has been revealed by means of neuroimaging techniques. However, the majority of "human" studies considered movements performed by right-handers only, leaving open the question of whether the dynamics underlying motor control during grasping is simply reversed in left-handers with respect to right-handers or not. To address this question, a group of left-handed participants has been scanned with functional magnetic resonance imaging while performing a precision grasping task with the left or the right hand. Dynamic causal modeling was used to assess how brain regions of the two hemispheres contribute to grasping execution and whether the intra- and inter-hemispheric connectivity is modulated by the choice of the performing hand. Results showed enhanced inter-hemispheric connectivity between anterior intraparietal and dorsal premotor cortices during grasping execution with the left dominant hand (LDH) (e.g., right hemisphere) compared to the right (e.g., left hemisphere). These findings suggest that that the left hand, although dominant and theoretically more skilled in left handers, might need additional resources in terms of the visuomotor control and on-line monitoring to accomplish a precision grasping movement. The results are discussed in light of theories on the modulation of parieto-frontal networks during the execution of prehensile movements, providing novel evidence supporting the hypothesis of a handedness-independent specialization of the left hemisphere in visuomotor control.

Is the planum temporale surface area a marker of hemispheric or regional language lateralization?

We investigated the association between the left planum temporale (PT) surface area or asymmetry and the hemispheric or regional functional asymmetries during language production and perception tasks in 287 healthy adults (BIL&GIN) who were matched for sex and handedness. The measurements of the PT surface area were performed after manually delineating the region using brain magnetic resonance images (MRI) and considering the Heschl's gyrus (HG) duplication pattern; the measurements either included (PT_tot) or did not include (PT_post) the second gyrus. A region encompassing both the PT and HG (HGPT) was also studied. Regardless of the ROI measured, 80% of the sample had a positive left minus right PT asymmetry. We first tested whether the PT_tot, PT_post and HGPT surface areas in the left or right hemispheres or PT asymmetries differed in groups of individuals varying in language lateralization by assessing their hemispheric index during a sentence production minus word list production task. We then investigated the association between these different measures of the PT anatomy and the regional asymmetries measured during the task. Regardless of the anatomical definition used, we observed no correlations between the left surface areas or asymmetries and the hemispheric or regional functional asymmetries during the language production task. We then performed a similar analysis using the same sample measuring language functional lateralization during speech listening tasks (i.e., listening to sentences and lists of words). Although the hemispheric lateralization during speech listening was not correlated with the left PT_tot, PT_post or HGPT surface areas or the PT asymmetries, significant positive correlations were observed between the asymmetries in these regions and the regional functional asymmetries measured in areas adjacent to the end of the Sylvian fissure while participants listened to the word lists or sentences. The PT asymmetry thus appears to be associated with the local functional asymmetries in auditory areas but is not a marker of inter-individual variability in language dominance.

Predicting hemispheric dominance for language production in healthy individuals using support vector machine

We used a Support Vector Machine (SVM) classifier to assess hemispheric pattern of language dominance of 47 individuals categorized as non-typical for language from their hemispheric functional laterality index (HFLI) measured on a sentence minus word-list production fMRI-BOLD contrast map. The SVM classifier was trained at discriminating between Dominant and Non-Dominant hemispheric language production activation pattern on a group of 250 participants previously identified as Typicals (HFLI strongly leftward). Then, SVM was applied to each hemispheric language activation pattern of 47 non-typical individuals. The results showed that at least one hemisphere (left or right) was found to be Dominant in every, except 3 individuals, indicating that the "dominant" type of functional organization is the most frequent in non-typicals. Specifically, left hemisphere dominance was predicted in all non-typical right-handers (RH) and in 57.4% of non-typical left-handers (LH). When both hemisphere classifications were jointly considered, four types of brain patterns were observed. The most often predicted pattern (51%) was left-dominant (Dominant left-hemisphere and Non-Dominant right-hemisphere), followed by right-dominant (23%, Dominant right-hemisphere and Non-Dominant left-hemisphere) and co-dominant (19%, 2 Dominant hemispheres) patterns. Co-non-dominant was rare (6%, 2 Non-Dominant hemispheres), but was normal variants of hemispheric specialization. In RH, only left-dominant (72%) and co-dominant patterns were detected, while for LH, all types were found, although with different occurrences. Among the 10 LH with a strong rightward HFLI, 8 had a right-dominant brain pattern. Whole-brain analysis of the right-dominant pattern group confirmed that it exhibited a functional organization strictly mirroring that of left-dominant pattern group. Hum Brain Mapp 38:5871-5889, 2017. © 2017 Wiley Periodicals, Inc.

Network modeling of resting state connectivity points towards the bottom up theories of schizophrenia

The dysconnectivity theory of schizophrenia proposes that schizophrenia symptoms arise from abnormalities in neuronal synchrony. Resting-state Functional Connectivity (FC) techniques allow us to highlight synchronization of large-scale networks, the Resting-state Networks (RNs). A large body of work suggests that disruption of RN synchronization could give rise to specific schizophrenia symptoms. The present study aimed to explore within- and between-network FC strength of 34 RNs in 29 patients suffering from schizophrenia, and their relationships with schizophrenia symptoms. Resting-state data were analyzed using independent component analysis and dual-regression techniques. Our results showed that both within-RN and between-RN FC were disrupted in patients with schizophrenia, with a global trend toward weaker FC. This decrease affected more particularly visual, auditory and crossmodal binding networks. These alterations were correlated with negative symptoms, positive symptoms and hallucinations, indicating abnormalities in visual processing and crossmodal binding in schizophrenia. Moreover, we stressed an anomalous synchronization between a visual network and a network thought to be engaged in mental imaging processes, correlated with delusions and hallucinations. Altogether, our results supported the assumption that some schizophrenia symptoms may be related to low-order sensory alterations impacting higher-order cognitive processes, i.e. the "bottom-up" hypothesis of schizophrenia symptoms.

Recognition of white matter bundles using local and global streamline-based registration and clustering

Virtual dissection of diffusion MRI tractograms is cumbersome and needs extensive knowledge of white matter anatomy. This virtual dissection often requires several inclusion and exclusion regions-of-interest that make it a process that is very hard to reproduce across experts. Having automated tools that can extract white matter bundles for tract-based studies of large numbers of people is of great interest for neuroscience and neurosurgical planning. The purpose of our proposed method, named RecoBundles, is to segment white matter bundles and make virtual dissection easier to perform. This can help explore large tractograms from multiple persons directly in their native space. RecoBundles leverages latest state-of-the-art streamline-based registration and clustering to recognize and extract bundles using prior bundle models. RecoBundles uses bundle models as shape priors for detecting similar streamlines and bundles in tractograms. RecoBundles is 100% streamline-based, is efficient to work with millions of streamlines and, most importantly, is robust and adaptive to incomplete data and bundles with missing components. It is also robust to pathological brains with tumors and deformations. We evaluated our results using multiple bundles and showed that RecoBundles is in good agreement with the neuroanatomical experts and generally produced more dense bundles. Across all the different experiments reported in this paper, RecoBundles was able to identify the core parts of the bundles, independently from tractography type (deterministic or probabilistic) or size. Thus, RecoBundles can be a valuable method for exploring tractograms and facilitating tractometry studies.

Improving data availability for brain image biobanking in healthy subjects: Practice-based suggestions from an international multidisciplinary working group

Brain imaging is now ubiquitous in clinical practice and research. The case for bringing together large amounts of image data from well-characterised healthy subjects and those with a range of common brain diseases across the life course is now compelling. This report follows a meeting of international experts from multiple disciplines, all interested in brain image biobanking. The meeting included neuroimaging experts (clinical and non-clinical), computer scientists, epidemiologists, clinicians, ethicists, and lawyers involved in creating brain image banks. The meeting followed a structured format to discuss current and emerging brain image banks; applications such as atlases; conceptual and statistical problems (e.g. defining 'normality'); legal, ethical and technological issues (e.g. consents, potential for data linkage, data security, harmonisation, data storage and enabling of research data sharing). We summarise the lessons learned from the experiences of a wide range of individual image banks, and provide practical recommendations to enhance creation, use and reuse of neuroimaging data. Our aim is to maximise the benefit of the image data, provided voluntarily by research participants and funded by many organisations, for human health. Our ultimate vision is of a federated network of brain image biobanks accessible for large studies of brain structure and function.

Variations of planum temporale asymmetries with Heschl's Gyri duplications and association with cognitive abilities: MRI investigation of 428 healthy volunteers

In a large sample of 428 healthy adults balanced for gender and manual preference (MP), we investigated planum temporale (PT) surface area variability in relation with Heschl's gyrus (HG) duplication pattern, MP, and familial sinistrality (FS), considering different PT definitions. In a sub-sample of 362 participants, we also investigated whether variability of PT asymmetry was associated with differences in verbal abilities. On each participant brain hemisphere MRI, we delineated a posterior PT area (PT_post), excluding the second Heschl gyrus in case of either complete posterior duplication (CPD) or common stem partial duplication (CSD). We then defined a total PT area (PT_tot) as the union of PT_post and of the second HG when present, and a HGPT area as the union of PT_tot and of the first HG. The HG duplication pattern of one hemisphere was found to significantly affect the PT_post surface area of the same hemisphere, a larger reduction being present in case of CPD than in case of CSD, leading to a strong impact of both left and right HG duplication patterns on PT_post asymmetry. The HG duplication pattern had no effect on PT_tot surface areas, while a significant effect of the left HG duplication was present on PT_tot asymmetry that was larger in case of a CSD as compared to a single HG. By contrast, the type of HG duplication did not affect HGPT and neither left nor right HG duplication pattern had an effect on HGPT asymmetry. Meanwhile, MP had no effect on PT_post, PT_tot, HGPT, or their asymmetries. The absence of a left PT_post was associated with existence of FS (FS+) (7FS+ among nine without PT_post). Removing the nine individuals lacking PT_post, a lower left PT_post surface area was observed in FS+ participants with left CPD. In the sub-sample of 362 participants, we observed a significant interaction between PT_post asymmetry and cognitive abilities due to poorer lexical performances in individuals having a symmetric PT_post as compared to individuals having either a leftward or a rightward asymmetric PT_post. By contrast, there was no significant effect of PT_tot or HGPT asymmetry on cognitive abilities. This study shows that HG duplication pattern mainly affects the surface area of the most posterior part of PT and its asymmetry, this PT_post area being specifically associated with variability in verbal performances. This study also shows, for the first time, an association between decreased performances and lack of PT_post anatomical asymmetry, being rightward asymmetrical having no deleterious effect on verbal abilities, thereby supporting the idea that anatomical lateralization is necessary for optimal verbal performances.

Cortical Asymmetries during Hand Laterality Task Vary with Hand Laterality: A fMRI Study in 295 Participants

The aim of this study was to characterize, using fMRI, the functional asymmetries of hand laterality task (HLT) in a sample of 295 participants balanced for handedness. During HLT, participants have to decide whether the displayed picture of a hand represent a right or a left hand. Pictures of hands' back view were presented for 150 ms in the right or left hemifield. At the whole hemisphere level, we evidenced that the laterality of the hand and of the hemifield in which the picture was displayed combined their effects on the hemispheric asymmetry in an additive way. We then identified a set of 17 functional homotopic regions of interest (hROIs) including premotor, motor, somatosensory and parietal regions, whose activity and asymmetry varied with the laterality of the presented hands. When the laterality of a right hand had to be evaluated, these areas showed stronger leftward asymmetry, the hROI located in the primary motor area showing a significant larger effect than all other hROIs. In addition a subset of six parietal regions involved in visuo-motor integration together with two postcentral areas showed a variation in asymmetry with hemifield of presentation. Finally, while handedness had no effect at the hemispheric level, two regions located in the parietal operculum and intraparietal sulcus exhibited larger leftward asymmetry with right handedness independently of the hand of presentation. The present results extend those of previous works in showing a shift of asymmetries during HLT according to the hand presented in sensorimotor areas including primary motor cortex. This shift was not affected by manual preference. They also demonstrate that the coordination of visual information and handedness identification of hands relied on the coexistence of contralateral motor and visual representations in the superior parietal lobe and the postcentral gyrus.