Literature DB >> 31319180

White matter information flow mapping from diffusion MRI and EEG.

Samuel Deslauriers-Gauthier1, Jean-Marc Lina2, Russell Butler3, Kevin Whittingstall3, Guillaume Gilbert4, Pierre-Michel Bernier3, Rachid Deriche5, Maxime Descoteaux3.   

Abstract

The human brain can be described as a network of specialized and spatially distributed regions. The activity of individual regions can be estimated using electroencephalography and the structure of the network can be measured using diffusion magnetic resonance imaging. However, the communication between the different cortical regions occurring through the white matter, coined information flow, cannot be observed by either modalities independently. Here, we present a new method to infer information flow in the white matter of the brain from joint diffusion MRI and EEG measurements. This is made possible by the millisecond resolution of EEG which makes the transfer of information from one region to another observable. A subject specific Bayesian network is built which captures the possible interactions between brain regions at different times. This network encodes the connections between brain regions detected using diffusion MRI tractography derived white matter bundles and their associated delays. By injecting the EEG measurements as evidence into this model, we are able to estimate the directed dynamical functional connectivity whose delays are supported by the diffusion MRI derived structural connectivity. We present our results in the form of information flow diagrams that trace transient communication between cortical regions over a functional data window. The performance of our algorithm under different noise levels is assessed using receiver operating characteristic curves on simulated data. In addition, using the well-characterized visual motor network as grounds to test our model, we present the information flow obtained during a reaching task following left or right visual stimuli. These promising results present the transfer of information from the eyes to the primary motor cortex. The information flow obtained using our technique can also be projected back to the anatomy and animated to produce videos of the information path through the white matter, opening a new window into multi-modal dynamic brain connectivity.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Brain networks; Diffusion MRI; Dynamic connectivity; EEG; Functional connectivity; MEG; Structural connectivity

Mesh:

Year:  2019        PMID: 31319180     DOI: 10.1016/j.neuroimage.2019.116017

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  6 in total

1.  Brain connections derived from diffusion MRI tractography can be highly anatomically accurate-if we know where white matter pathways start, where they end, and where they do not go.

Authors:  Kurt G Schilling; Laurent Petit; Francois Rheault; Samuel Remedios; Carlo Pierpaoli; Adam W Anderson; Bennett A Landman; Maxime Descoteaux
Journal:  Brain Struct Funct       Date:  2020-08-20       Impact factor: 3.270

2.  Uncovering Cortical Units of Processing From Multi-Layered Connectomes.

Authors:  Kristoffer Jon Albers; Matthew G Liptrot; Karen Sandø Ambrosen; Rasmus Røge; Tue Herlau; Kasper Winther Andersen; Hartwig R Siebner; Lars Kai Hansen; Tim B Dyrby; Kristoffer H Madsen; Mikkel N Schmidt; Morten Mørup
Journal:  Front Neurosci       Date:  2022-03-10       Impact factor: 4.677

3.  Dynamic functional networks in idiopathic normal pressure hydrocephalus: Alterations and reversibility by CSF tap test.

Authors:  Alessandra Griffa; Giulia Bommarito; Frédéric Assal; François R Herrmann; Dimitri Van De Ville; Gilles Allali
Journal:  Hum Brain Mapp       Date:  2020-12-09       Impact factor: 5.038

Review 4.  The functional characterization of callosal connections.

Authors:  Giorgio M Innocenti; Kerstin Schmidt; Chantal Milleret; Mara Fabri; Maria G Knyazeva; Alexandra Battaglia-Mayer; Francisco Aboitiz; Maurice Ptito; Matteo Caleo; Carlo A Marzi; Muhamed Barakovic; Franco Lepore; Roberto Caminiti
Journal:  Prog Neurobiol       Date:  2021-11-12       Impact factor: 11.685

5.  In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data.

Authors:  Rita Oliveira; Andria Pelentritou; Giulia Di Domenicantonio; Marzia De Lucia; Antoine Lutti
Journal:  Front Neurosci       Date:  2022-04-21       Impact factor: 5.152

6.  An integrated TMS-EEG and MRI approach to explore the interregional connectivity of the default mode network.

Authors:  Romina Esposito; Marta Bortoletto; Domenico Zacà; Paolo Avesani; Carlo Miniussi
Journal:  Brain Struct Funct       Date:  2022-02-04       Impact factor: 3.270

  6 in total

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