Biology subjects

Poupon, C.

Publications and source records attributed to Poupon, C..

9 recordsLinked to original sources

bioRxiv2026

Chenonceau: mesoscopic MRI deep phenotyping of a post-mortem human brain at 7 and 11.7 Tesla

The human brains organization, from macroscopic connectivity to microscopic architecture, has never been mapped across multiple modalities in a single post-mortem specimen at mesoscopic resolution. Here we present Chenonceau, a complete post-mortem human brain atlas acquired using two ultra-high-field preclinical MRI systems. Combining anatomical, diffusion, and quantitative MRI from 100 to 200 m isotropic resolution, the 8000-hour acquisition campaign overcomes the fundamental trade-off between spatial resolution, tissue coverage, and multimodality that commonly constrains MRI neuroimaging in humans. The resulting open-access dataset integrates the first whole-brain mesoscopic connectome along with cortical lamination, myelo-, and cyto-architecture mapping. Importantly, the spatial and angular resolutions achieved reveal the intracortical connectivity at the whole-brain scale. Bridging the scale gap between in vivo imaging and post-mortem microscopic datasets, the Chenonceau brain atlas establishes a foundational reference for joint mesoscale analysis of human brain structure, connectivity, and microarchitecture. The dataset is openly available on the EBRAINS portal.

neuroscience↗

bioRxiv2026

Mapping 3D tissue orientation with tensor-augmented light-sheet microscopy

Mapping the three-dimensional directional organization of biological tissues is essential for understanding their structure and function. However, existing methods cannot resolve micrometer-scale orientation in volumetric samples. We introduce tensor light-sheet scattering microscopy (tLSSM), a label-free method that reconstructs 3D fiber orientations at micrometer resolution in optically cleared tissues, enabling whole-organ imaging. We discovered that even in transparent samples, organized structures such as neural fibers scatter light in directional patterns, consistent with models of light scattering by cylinders. We compared tLSSM against diffusion MRI in the mouse brain, demonstrating strong agreement and orders of magnitude superior spatial resolution. Furthermore, we showcase tLSSMs versatility across diverse contexts, including whole-brain label-free tracing, pathological demyelination lesions, heart tissue, peripheral nerves, and human white matter. By enabling whole-organ fiber orientation mapping compatible with standard light-sheet microscopes, tLSSM establishes a new standard for mesoscopic connectivity studies by mapping tissue architecture beyond the limits of traditional sectioning.

neuroscience↗

bioRxiv2026

An Ultra-High-Resolution 17.2 T MRI Atlas (HypoAtlas) and Multimodal Pipeline to Study the Mouse Hypothalamus: Sexual Dimorphism and Lateralization Insights

Structural and functional insights into the mouse hypothalamus are hampered by its small size and deep location. Here, we leverage ultra-high-field magnetic resonance imaging (UHF-MRI) at 17.2 Tesla to achieve unprecedented spatial resolution in structural, functional and neurochemical imaging of the mouse hypothalamus, including sexual dimorphism in certain nuclei. High-resolution ex vivo anatomical MRI enabled precise hypothalamic parcellation, improving on existing atlases and revealing nuclei previously unresolved by MRI. Diffusion MRI and tractography mapped intra- and extra-hypothalamic pathways, facilitating circuit-level exploration without a priori assumptions. Resting-state fMRI combined with independent component analysis identified novel hypothalamic networks, demonstrating the enhanced capacity of UHF MRI to detect deep-brain activity. {superscript 1}H-magnetic resonance spectroscopy quantified neurochemical profiles, revealing sexually dimorphic heterogeneity within the hypothalamus. Our comprehensive multimodal approach uncovers sex differences in hypothalamic anatomy, microstructure, and neurochemistry, emphasizing the importance of sex as a biological variable. This integrated pipeline offers a valuable resource for dissecting hypothalamic circuits and functions, advancing our understanding of neuroendocrine regulation, behavior, and disease mechanisms, with direct translational relevance.

neuroscience↗

bioRxiv2025

Multimodal imaging of human fetal brain development at the mesoscopic scale using 11.7 T ex vivo MRI

We present the first release of p-HCP (Prenatal Human Connectome Patterns), an imaging dataset of human fetal brain development covering the second half of gestation. This dataset was acquired ex vivo using magnetic resonance imaging (MRI) at ultra high field (11.7 teslas), and includes whole-hemisphere T2-weighted images at 100 {micro}m isotropic resolution, quantitative relaxometry (T1, T2, and [Formula]), and high angular resolution diffusion-weighted images for multiple b-values at 200 {micro}m. Brains larger than the workspace of the small-bore scanner were sectioned into blocks, acquired blockwise, and digitally reconstructed using a dedicated semi-automatic method. This initial data release includes three gestational ages (18, 27, and 31 post-conceptional weeks) with a complete set of anatomical images, relaxometry maps, and diffusion-based microstructure measurements. This dataset offers new opportunities to investigate neurodevelopmental processes that have not yet been explored with full three-dimensional coverage at this resolution by MRI, and may serve as a multimodal mesoscopic reference template for the fetal brain.

neuroscience↗

bioRxiv2025

Affiliative behaviours regulate allostasis development and shape biobehavioural trajectories in horse

Social interactions shape both physiological and behavioural development of offspring and poor care/early caregiver loss are known to promote negative outcomes in adulthood in both animals and humans. How affiliative behaviours impact future development of offspring remains unknown. Here, we used Equus caballus (domestic horse) as a model to investigate this question. By coupling magnetic resonance imaging, longitudinal biobehavioural assessment and advanced multivariate statistical modelling we found that maternal presence during childhood promotes maturation of brain territories involved in both social behaviour (anterior cingulate, retrosplenial cortex) and physiological regulation (hypothalamus, amygdala). Additionally, we found that offsprings benefiting from prolonged maternal presence showed higher default mode network (DMN) connectivity, improved social competences, more efficient feeding behaviours, and metabolic profiles. The present study underscores the salient role of social interactions for the development of allostatic regulation in offspring.

neuroscience↗

bioRxiv2023

In vivo mapping of the deep and superficial whitematter connectivity in the chimpanzee brain

Mapping the chimpanzee brain connectome, and comparing it to humans, is key to our understanding of similarities and differences in primate evolution that occurred after the split from their common ancestor around 6 million years ago. In contrast with macaque species brain studies, less studies have specifically addressed the structural connectivity of the chim-panzee brain and its comparison with the human brain. Most comparative studies in the liter-ature focus on the anatomy of the cortex and deep nuclei to evaluate how their morphometry and asymmetry differs from that of the human brain, and some studies have emerged concern-ing the study of brain connectivity between primates. In this work, we established a new white matter atlas of the deep and superficial white matter structural connectivity in chimpanzees. In vivo anatomical and diffusion weighted magnetic resonance imaging (MRI) data were collected on a 3 Tesla magnetic resonance imaging (MRI) system in 39 chimpanzees. These datasets were subsequently processed using a dedicated fiber clustering pipeline adapted to the chimpanzee brain enabling us to create two novel deep and superficial white matter connectivity atlases representative of the chimpanzee brain. These atlases provide the scientific community with an important and novel set of reference data for understanding the commonalities and differ-ences of the structural connectivity between the human and chimpanzee brains, which will contribute to a better understanding of the hominin brain evolution.

neuroscience↗

bioRxiv2023

Characterization of early white matter changes in CADASIL using microscopic diffusion imaging and relaxometry

Background and purposeCerebral small vessel diseases (SVDs) are characterized by early white matter (WM) changes, whose pathological underpinnings are yet poorly understood. CADASIL is a monogenic and archetypal SVD, providing an ideal model for investigating these changes. Here, we used multicompartment microscopic diffusion imaging and relaxometry to elucidate microstructural changes underlying early WM abnormalities in CADASIL. MethodsWe acquired diffusion MRI data with a multiple-shell Q-space sampling strategy, and relaxometry T1 and T2 data, with a 160 and 80-m isotropic resolution respectively, ex vivo, in CADASIL and control mice. Diffusion datasets were computed with the Neurite Orientation Dispersion and Density Imaging model to extract the neurite density index, the extracellular free water and the orientation dispersion index. Relaxometry datasets were computed with a 3-compartment myelin water imaging model to extract the myelin content. MRI metrics were compared between CADASIL and control mice using voxel and WM tract-based analyses and with electron microscopy analysis. ResultsWM in CADASIL mice displayed a widespread reduction in general fractional anisotropy, a large increase in extracellular free water, a reduction in the myelin content, but no reduction in neurite density. Electron microscopy analysis showed a {bsim}2-fold increase in the extracellular spaces and an elevation of the g-ratio indicative of myelin sheath thinning in CADASIL WM. ConclusionOur findings suggest that accumulation of interstitial fluid and myelin damage are 2 major factors underlying early WM changes in CADASIL. Advanced diffusion MRI and relaxometry are promising approaches to decipher the underpinnings of WM alterations in SVDs.

neuroscience↗

bioRxiv2018

Increased and decreased superficial white matter structural connectivity in schizophrenia and bipolar disorder

Schizophrenia (SZ) and bipolar disorder (BD) are often conceptualized as \"disconnection syndromes\", with substantial evidence of abnormalities in deep white matter tracts, forming the substrates of long-range connectivity, seen in both disorders. However, the study of superficial white matter (SWM) U-shaped short-range tracts remained challenging until recently, although findings from post-mortem studies suggest they are likely integral components of SZ and BD neuropathology. This diffusion weighted imaging (DWI) study aimed to investigate SWM microstructure in vivo in both SZ and BD for the first time. We performed whole brain tractography in 31 people with SZ, 32 people with BD and 54 controls using BrainVISA and Connectomist 2.0. Segmentation and labelling of SWM tracts were performed using a novel, comprehensive U-fiber atlas. Analysis of covariances yielded significant generalized fractional anisotropy (gFA) differences for 17 SWM bundles in frontal, parietal and temporal cortices. Post hoc analyses showed gFA reductions in both patient groups as compared with controls in bundles connecting regions involved in language processing, mood regulation, working memory and motor function (pars opercularis, insula, anterior cingulate, precentral gyrus). We also found increased gFA in SZ patients in areas overlapping the default mode network (inferior parietal, middle temporal, precuneus), supporting functional hyperconnectivity of this network evidenced in SZ. We thus illustrate that short U-fibers are vulnerable to the pathological processes in major psychiatric illnesses, encouraging improved understanding of their anatomy and function.

neuroscience↗

bioRxiv2018

Analysis of brain network dynamics estimated from fMRI data: A new framework based on communicability and flow

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 (in which input properties play a role), 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.

neuroscience↗