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Population imaging markedly increased the size of functional-imaging datasets, shedding new light on the neural basis of inter-individual differences. Analyzing these large data entails new scalability challenges, computational and statistical. For this reason, brain images are typically summarized in a few signals, for instance reducing voxel-level measures with brain atlases or functional modes. A good choice of the corresponding brain networks is important, as most data analyses start from these reduced signals. We contribute finely-resolved atlases of functional modes, comprising from 64 to 1024 networks. These dictionaries of functional modes (DiFuMo) are trained on millions of fMRI functional brain volumes of total size 2.4 ​TB, spanned over 27 studies and many research groups. We demonstrate the benefits of extracting reduced signals on our fine-grain atlases for many classic functional data analysis pipelines: stimuli decoding from 12,334 brain responses, standard GLM analysis of fMRI across sessions and individuals, extraction of resting-state functional-connectomes biomarkers for 2500 individuals, data compression and meta-analysis over more than 15,000 statistical maps. In each of these analysis scenarii, we compare the performance of our functional atlases with that of other popular references, and to a simple voxel-level analysis. Results highlight the importance of using high-dimensional “soft” functional atlases, to represent and analyze brain activity while capturing its functional gradients. Analyses on high-dimensional modes achieve similar statistical performance as at the voxel level, but with much reduced computational cost and higher interpretability. In addition to making them available, we provide meaningful names for these modes, based on their anatomical location. It will facilitate reporting of results. •We contribute finely-resolved high-dimensional functional modes for fMRI analysis.•Those are trained on millions of varied fMRI functional brain volumes, using a sparse matrix factorisation algorithm. The total training size is 2.4TB.•These Dictionaries of Functional Modes (DiFuMo) are multi-scale, with a number of functional networks ranging from 64 to 1024.•Our benchmarks reveal the importance of using high-dimensional “soft” continuous-valued functional atlases when extracting image-derived phenotypes.•We provide an anatomical name to each of the modes of the DiFuMo atlases. Those are available at https://parietal-inria.github.io/DiFuMo/.

This book provides an atlas of the normal human brain based on three dimensional reconstructions of magnetic resonance scans obtained in normal living adults as well as neurological patients with focal brain lesions. It provides detailed descriptions of sulci and gyri and illustrates how they appear in different brains. The book shows how different slice orientations obtained in the same brain produce different images that can be anatomically misinterpreted, in normal brains as well as brains with lesions. The book also addresses quantitative differences between the human brain and the brains of apes; gray and white matter differences between the hemispheres; and differences related to gender, age, and congenital deafness.

The recent progress of medical imaging due to the scanner, the MRI, and the three-dimensional reconstruction of cerebral structures calls for a better knowledge of brain anatomy; it is to be noted, though, that the accurate anatomy of the brain surface was already known thanks to the pio­ neering work of late-nineteenth-and early-twentieth-century research workers, such as Eberstal­ ler (1884), Cunningham (1892), Dejerine (1895), Retzius (1896), Zuckerkandl (1903), Elliot-Smith (1907) [14, 15,22,29, 30, 56, 751. Since then, more recent techniques have led to a precise view of the deeper structures. But, as those details were not visible in vivo before the diffusion of scanner and magnetic-resonance-imaging (MRI) exploration, such knowledge was deemed superfluous, or even useless. Nowadays, this situation has drastically changed and the neurologists, neurosur­ geons, and neuroradiologists acknowledge the need to know more about anatomy. The aim of this volume is to provide those specialists with that information for their own research. A number of atlases do exist at the present time [15,52,58, 156-195], but we felt that the serial were not enough if not made obvious, being defined in relation with the sections by themselves brain surface as shown in Figs. 26, 139, and 175. However, this three-dimensional-representation technique of coronal, sagittal, and horizontal sections makes the study of only one hemisphere ne­ cessary so as to locate each section with respect to its several aspects.

We present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science. •A new software package for standardised and automated cross-species tractography.•Homologous white matter bundles in the human and macaque brain.•Human white matter tract atlases generated from large datasets (1000 subjects).•Tractography protocols are standardised, but preserve individual variability.•Generalisability across datasets shown using the HCP and the UK Biobank data.

The structural and functional organization of brain networks subserving basic daily activities (i.e. language, visuo-spatial cognition, movement, semantics, etc.) are not completely understood to date. Here, we report the first probabilistic cortical and subcortical atlas of critical structures mediating human brain functions based on direct electrical stimulation (DES), a well-validated tool for the exploration of cerebral processing and for performing safe surgical interventions in eloquent areas. We collected 1162 cortical and 659 subcortical DES responses during testing of 16 functional domains in 256 patients undergoing awake surgery. Spatial coordinates for each functional response were calculated, and probability distributions for the entire patient cohort were mapped onto a standardized three-dimensional brain template using a multinomial statistical analysis. In addition, matching analyses were performed against prior established anatomy-based cortical and white matter (WM) atlases. The probabilistic maps for each functional domain were provided. The topographical analysis demonstrated a wide spatial distribution of cortical functional responses, while subcortical responses were more restricted, localizing to known WM pathways. These DES-derived data showed reliable matching with existing cortical and WM atlases as well as recent neuroimaging and neurophysiological data. We present the first integrated and comprehensive cortical-subcortical atlas of structures essential for humans’ neural functions based on highly-specific DES mapping during real-time neuropsychological testing. This novel atlas can serve as a complementary tool for neuroscientists, along with data obtained from other modalities, to improve and refine our understanding of the functional anatomy of critical brain networks. •1821 direct electrical stimulation sites from 256 awake brain surgeries analyzed.•Probability maps of 16 key human brain functions generated.•Cortical stimulation points widely distributed over the brain surface.•Subcortical responses more restricted, localize to known major white matter tracts.

Brain atlases are fundamental to understanding the topographic organization of the human brain, yet many contemporary human atlases cover only the cerebral cortex, leaving the subcortex a terra incognita. We use functional MRI (fMRI) to map the complex topographic organization of the human subcortex, revealing large-scale connectivity gradients and new areal boundaries. We unveil four scales of subcortical organization that recapitulate well-known anatomical nuclei at the coarsest scale and delineate 27 new bilateral regions at the finest. Ultrahigh field strength fMRI corroborates and extends this organizational structure, enabling the delineation of finer subdivisions of the hippocampus and the amygdala, while task-evoked fMRI reveals a subtle subcortical reorganization in response to changing cognitive demands. A new subcortical atlas is delineated, personalized to represent individual differences and used to uncover reproducible brain–behavior relationships. Linking cortical networks to subcortical regions recapitulates a task-positive to task-negative axis. This new atlas enables holistic connectome mapping and characterization of cortico–subcortical connectivity.This work by Tian and colleagues unveils the extraordinarily complex layout of the human subcortex by identifying 27 new functional regions that organize hierarchically across four scales and adapt to changing cognitive demands.

The recent availability of comprehensive, brain-wide gene expression atlases such as the Allen Human Brain Atlas (AHBA) has opened new opportunities for understanding how spatial variations on molecular scale relate to the macroscopic neuroimaging phenotypes. A rapidly growing body of literature is demonstrating relationships between gene expression and diverse properties of brain structure and function, but approaches for combining expression atlas data with neuroimaging are highly inconsistent, with substantial variations in how the expression data are processed. The degree to which these methodological variations affect findings is unclear. Here, we outline a seven-step analysis pipeline for relating brain-wide transcriptomic and neuroimaging data and compare how different processing choices influence the resulting data. We suggest that studies using the AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field. [Display omitted]

A comprehensive map of the structural connectome in the human brain has been a coveted resource for understanding macroscopic brain networks. Here we report an expert-vetted, population-averaged atlas of the structural connectome derived from diffusion MRI data (N = 842). This was achieved by creating a high-resolution template of diffusion patterns averaged across individual subjects and using tractography to generate 550,000 trajectories of representative white matter fascicles annotated by 80 anatomical labels. The trajectories were subsequently clustered and labeled by a team of experienced neuroanatomists in order to conform to prior neuroanatomical knowledge. A multi-level network topology was then described using whole-brain connectograms, with subdivisions of the association pathways showing small-worldness in intra-hemisphere connections, projection pathways showing hub structures at thalamus, putamen, and brainstem, and commissural pathways showing bridges connecting cerebral hemispheres to provide global efficiency. This atlas of the structural connectome provides representative organization of human brain white matter, complementary to traditional histologically-derived and voxel-based white matter atlases, allowing for better modeling and simulation of brain connectivity for future connectome studies.

•For the study of fetal brain development, terminological clarification is urgent.•To characterize major structures of fetal brain ontogenesis is clinically relevant.•18 fetal brain atlases and 3 datasets of MR images have been reviewed.•Multimodal spatio-temporal atlas providing age-dependent segmentations is required.•To consider future clinical and ethical implications of fetal neuroimaging is crucial. Fetal brain development is a complex process involving different stages of growth and organization which are crucial for the development of brain circuits and neural connections. Fetal atlases and labeled datasets are promising tools to investigate prenatal brain development. They support the identification of atypical brain patterns, providing insights into potential early signs of clinical conditions. In a nutshell, prenatal brain imaging and post-processing via modern tools are a cutting-edge field that will significantly contribute to the advancement of our understanding of fetal development. In this work, we first provide terminological clarification for specific terms (i.e., “brain template” and “brain atlas”), highlighting potentially misleading interpretations related to inconsistent use of terms in the literature. We discuss the major structures and neurodevelopmental milestones characterizing fetal brain ontogenesis. Our main contribution is the systematic review of 18 prenatal brain atlases and 3 datasets. We also tangentially focus on clinical, research, and ethical implications of prenatal neuroimaging. [Display omitted]

Three-dimensional atlases of subcortical brain structures are valuable tools to reference anatomy in neuroscience and neurology. For instance, they can be used to study the position and shape of the three most common deep brain stimulation (DBS) targets, the subthalamic nucleus (STN), internal part of the pallidum (GPi) and ventral intermediate nucleus of the thalamus (VIM) in spatial relationship to DBS electrodes. Here, we present a composite atlas based on manual segmentations of a multimodal high resolution brain template, histology and structural connectivity. In a first step, four key structures were defined on the template itself using a combination of multispectral image analysis and manual segmentation. Second, these structures were used as anchor points to coregister a detailed histological atlas into standard space. Results show that this approach significantly improved coregistration accuracy over previously published methods. Finally, a sub-segmentation of STN and GPi into functional zones was achieved based on structural connectivity. The result is a composite atlas that defines key nuclei on the template itself, fills the gaps between them using histology and further subdivides them using structural connectivity. We show that the atlas can be used to segment DBS targets in single subjects, yielding more accurate results compared to priorly published atlases. The atlas will be made publicly available and constitutes a resource to study DBS electrode localizations in combination with modern neuroimaging methods. •Composite subcortical atlas based on a multimodal, high definition MNI template series, histology and tractography.•High definition atlas of DBS targets matching MNI 152 NLIN 2009b space.•Tractography based parcellation of the two primary DBS target regions STN and GPi into functional zones.•Multimodal subcortical segmentation algorithm applied to MNI template.