Inference and Visualization of Information Flow in the Visual Pathway Using dMRI and EEG

  • Samuel Deslauriers-Gauthier
  • Jean-Marc Lina
  • Russell Butler
  • Pierre-Michel Bernier
  • Kevin Whittingstall
  • Rachid Deriche
  • Maxime Descoteaux
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10433)

Abstract

We propose a method to visualize information flow in the visual pathway following a visual stimulus. Our method estimates structural connections using diffusion magnetic resonance imaging and functional connections using electroencephalography. First, a Bayesian network which represents the cortical regions of the brain and their connections is built from the structural connections. Next, the functional information is added as evidence into the network and the posterior probability of activation is inferred using a maximum entropy on the mean approach. Finally, projecting these posterior probabilities back onto streamlines generates a visual depiction of pathways used in the network. We first show the effect of noise in a simulated phantom dataset. We then present the results obtained from left and right visual stimuli which show expected information flow traveling from eyes to the lateral geniculate nucleus and to the visual cortex. Information flow visualization along white matter pathways has potential to explore the brain dynamics in novel ways.

Supplementary material

455905_1_En_58_MOESM1_ESM.mp4 (15 kb)
Supplementary material 1 (mp4 14 KB)
455905_1_En_58_MOESM2_ESM.mp4 (190 kb)
Supplementary material 2 (mp4 190 KB)
455905_1_En_58_MOESM3_ESM.mp4 (194 kb)
Supplementary material 3 (mp4 193 KB)

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Samuel Deslauriers-Gauthier
    • 1
  • Jean-Marc Lina
    • 2
  • Russell Butler
    • 3
  • Pierre-Michel Bernier
    • 3
  • Kevin Whittingstall
    • 3
  • Rachid Deriche
    • 1
  • Maxime Descoteaux
    • 3
  1. 1.InriaUniversité Côte d’AzurParisFrance
  2. 2.École de technologie supérieureMontréalCanada
  3. 3.Université de SherbrookeSherbrookeCanada

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