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Dynamic small-world behavior in functional brain networks unveiled by an event-related networks approach.

Abstract : There is growing interest in studying the role of connectivity patterns in brain functions. In recent years, functional brain networks were found to exhibit small-world properties during different brain states. In previous studies, time-independent networks were recovered from long time periods of brain activity. In this paper, we propose an approach, the event-related networks, that allows one to characterize the dynamical evolution of functional brain networks in time-frequency space. We illustrate this approach by characterizing connectivity patterns in magnetoencephalographic signals recorded during a visual stimulus paradigm. When compared with equivalent random and regular networks, the results reveal that functional connectivity varies with time and frequency during the processing of the stimulus, while maintaining a small-world structure. This approach may provide insights into the connectivity of other complex and spatially extended nonstationary systems.
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https://hal.inria.fr/hal-00805455
Contributor : Olivier Colliot <>
Submitted on : Wednesday, March 27, 2013 - 7:58:36 PM
Last modification on : Monday, August 23, 2021 - 11:20:13 AM

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  • HAL Id : hal-00805455, version 1
  • PUBMED : 18643019

Citation

M. Valencia, J. Martinerie, Samuel Dupont, M. Chavez. Dynamic small-world behavior in functional brain networks unveiled by an event-related networks approach.. Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, American Physical Society, 2008, 77 (5 Pt 1), pp.050905. ⟨hal-00805455⟩

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