DESLAURIERS-GAUTHIER , Samuel

The different lengths and conduction velocities of axons connecting cortical regions of the brain yield information transmission delays which are believed to be fundamental to brain dynamics. A critical step in the estimation of axon conduction speed in vivo is the estimation of the inter hemispheric transfer time (IHTT). The IHTT is estimated...

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Data were provided by the Human Connectome Project (HCP), WU-MinnConsortium (Principal Investigators: David Van Essen and Kamil Ugurbil;1U54MH091657) funded by the 16 NIH Institutes and Centers that supportthe NIH Blueprint for Neuroscience Research; and by the McDonnell Center forSystems Neuroscience at Washington University

Null models are crucial for determining the degree of significance when testing hypotheses about brain dynamics modeled as a temporal complex network [7, 12]. The comparison between the hypothesis being tested on empirical data and on the null model enables us to assess the extent to which an apparently remarkable feature of the former can be...

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In this work, we present a novel computational framework for analytically generating a complete set of algebraically independent Rotation Invariant Features (RIF) given the Laplace-series expansion of a spherical function. Our computational framework provides a closed-form solution for these new invariants, which are the natural expansion of...

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Context: Functional Magnetic Resonance Imaging (fMRI) is a non-invasive imaging technique that provides an indirect view into brain activity via the blood oxygen level dependent (BOLD) response. In particular, resting-state fMRI poses challenges to the recovery of brain activity without prior knowledge on the experimental paradigm, as it is the...

3D-Polarized Light Imaging (3D-PLI) is an optical approach that utilizes the birefringence in postmortem organs (brain/ heart) to map their spatial fiber structure at a submillimeter resolution. Recently, Axer et al. proposed a strategy to bridge it to relatively low diffusion MRI spatial resolution by introducing an estimate of the fiber...

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Diffusion Magnetic Resonance Imaging (dMRI) is the only available imaging technique for probing the brain tissue microstructure in-vivo. Through the years, dMRI has been used for both estimating brain connectivity via the use of tractography algorithms [1] and to obtain indices that represent numerically the brain tissue microstructure....

In recent years, multi-compartmental models have been widely used to try to characterize brain tissue microstructure from Diffusion Magnetic Resonance Imaging (dMRI) data. One of the main drawbacks of this approach is that the number of microstructural features needs to be decided a priori and it is embedded in the model definition. However,...

Objective: To infer information flow in the white matter of the brain and recover cortical activity using functional MRI, diffusion MRI, and MEG without a manual selection of the white matter connections of interest. Approach: A Bayesian network which encodes the priors knowledge of possible brain states is built from imaging data. Diffusion...

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Three-dimensional Polarized Light Imaging (3D-PLI) is an optical approach presented as a good candidate for validation of diffusion Magnetic Resonance Imaging (dMRI) results such as orientation estimates (fiber Orientation Distribution Functions) and tractography. We developed an anlytical approach to reconstruct fiber ODFs from 3D-PLI...

Brain dynamics can be modeled as a temporal brain network starting from the activity of different brain regions in functional magnetic resonance imaging (fMRI) signals. When validating hypotheses about temporal networks, it is important to use an appropriate statistical null model that shares some features with the treated empirical data. The...

Rotation Invariant Features (RIFs) [1] extracted from dMRI scans represent a generalisation of the usually used 2nd order invariants such as Fractional Anisotropy (FA) and Mean Diffusivity (MD). This work studies the usefulness all of the 12 algebraically independent RIFs extracted from 4th order Spherical Harmonics in the context of Alzheimer...

State-of-the-art techniques for denoising functional MRI (fMRI) images consider the problems of spatial and temporal regularization as decoupled tasks. In this work we propose a partial differential equations (PDEs)-based algorithm that acts directly on the 4-D fMRI image. Our approach is based on the idea that large image variations should be...

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The dataset contains a collection of temporal brain networks. The networks are obtained from resting-state fMRI data of 1047 subjects from the Human Connectome Project (HCP).