CE45 - Interfaces: mathématiques, sciences du numérique –biologie, santé

Revealing the brain's white matter crossing fibers' topology: toward a new generation of tractography algorithms integrating the ground truth neuroanatomy. – CROSS-TRACTS

Submission summary

In the innovative connectomics field, only diffusion magnetic resonance imaging (dMRI) tractography allows building a complete structural connectome non-invasively. However, dMRI tractography results are still controversial compared to the ground truth white matter (WM) anatomy. DMRI tractography algorithms aim at inferring WM fiber direction information based uniquely on a water diffusion displacement profile and thus fail to reconstruct complex WM crossings pathways reliably. The CROSS-TRACTS project will study the topology of the WM crossing fibers in the mouse brain at an unprecedented degree of accuracy, thanks to advanced multimodal tractography approaches. We will first apply a gold standard methodological approach for unraveling the WM's anatomical features by combining viral tract labeling, whole-brain clearing, and light-sheet microscopy imaging (LSI). Second, in addition to advanced dMRI tractography, we will investigate the fanning, bending, or 3-way asymmetric crossings of WM fibers at the macroscopic scale by using rs-fMRI. CROSS-TRACTS will thus produce tractograms across different modalities (dMRI, rs-fMRI, LSI) and at multiple scales (macroscopic, mesoscopic). We will tackle the compound challenge of integrating tractograms across modalities by applying a new deep neural network-based methodology that combines the dMRI-, rs-fMRI- and LSI-based tractograms within a correspondence autoencoding architecture.
We will thus provide the neuroscience community with groundbreaking anatomical knowledge of the WM crossings' topology. We will provide the "neural-tracing/LSI" community with an unprecedented LSI-based tractography tool to track their cleared fluorescent samples. We will give the fMRI community a dedicated fMRI-based asymmetrical tractography algorithm. We will provide the dMRI community with a new generation of tractography algorithms that actually considers the ground truth of WM anatomy through a deep neural network autoencoder framework. CROSS-TRACTS has a strong potential for back-translation to human studies. Our preclinical approach is crucial in developing tools for integrating prior knowledge in dMRI tractography, and this can be extensively applied to clinical studies and large multimodal neuroimaging databases.

Project coordination

Laurent Petit (Université de Bordeaux)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


CRMSB Université de Bordeaux
IMN Université de Bordeaux

Help of the ANR 629,297 euros
Beginning and duration of the scientific project: September 2022 - 48 Months

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