Conference on Cognitive Computational Neuroscience

Oxford, UK • August 24 - 27, 2023

P-1A.55

Computational Modeling of Traveling Waves Using MEG-EEG in Human

Laetitia Grabot, Garance Merholz, Université Paris Cité, CNRS, France; Jonathan Winawer, David J. Heeger, Department of Psychology, New York University, United States; Laura Dugué, Université Paris Cité, CNRS, France
Session:
Posters 1A Poster
Track:
Cognitive science
Location:
North Schools
Presentation Time:
Thu, 24 Aug, 17:00 - 19:00 United Kingdom Time
Abstract:
Recent studies suggest that brain oscillations are traveling waves in cortex. Yet, studying oscillations propagating within single cortical areas has so far been restricted by the need for invasive measurements. Non-invasive techniques such as MEG or EEG are limited by technical and biophysical constraints (e.g., source summation, volume conduction, low signal-to-noise ratios). To overcome these issues, we developed a novel model-based neuroimaging approach. (1) The putative neural sources of a propagating oscillation were modeled within the primary visual region (V1) via retinotopic mapping from functional MRI recordings (encoding model); and (2) the modeled sources were projected onto the M-EEG sensor space to predict the resulting signal (forward biophysical head model). We tested our model by comparing its predictions against the M-EEG signal obtained when participants viewed visual stimuli designed to elicit either fovea-to-periphery or periphery-to-fovea traveling waves, or standing waves in V1. Correlations on pairwise sensor relationships between predicted and measured data revealed good model performance. Crucially, the model was able to distinguish M-EEG recordings while participants viewed traveling stimuli in one direction compared to the opposite direction. Our model aims at recovering the spatio-temporal dynamics of cerebral activity from non-invasive measurements to better apprehend the neurophysiological bases of cognition.
Manuscript:
View Manuscript
License:
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI:
10.32470/CCN.2023.1086-0
Publication:
2023 Conference on Cognitive Computational Neuroscience
Presentation
Discussion
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Last updated Last updated 22 August 2023.