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Dense-EEG source connectivity and dynamics of brain networks

Abstract : Cognition is a network phenomenon. During cognitive activity, brain networks have to rapidly reorganize on a sub-second time scale. Tracking the dynamics of these networks over this short time duration is an unsolved issue. Here, we propose a new way to tackle this problem by using dense electroencephalography (EEG) recorded during a specific cognitive task: picture naming. We found that the cognitive task can be divided into six functional connectivity states (fcSs) characterized by significantly high synchronization of gamma (30-45 Hz) oscillations. We showed that dense-EEG can reveal the spatiotemporal dynamics of whole-brain functional connectivity at high temporal (in the order of ms) and spatial (similar to 1000 regions of interest) resolution. Our results showed also that the brain cognitive functions are based on fast transitions between fcSs that last from 30 ms to 160 ms. Each identified network can be associated with one or several specific function (visual processing, lexical concept activation, selecting the target word from the mental lexicon, phonological encoding, phonetic encoding, and initiation of articulation) of the whole cognitive process. Finally, we believe that the identification of the dynamics of cognitive brain networks is a very powerful tool to understand the brain information processing.
Keywords : speech
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01380114
Contributor : Laurent Jonchère <>
Submitted on : Wednesday, October 12, 2016 - 2:58:10 PM
Last modification on : Wednesday, May 16, 2018 - 11:23:41 AM

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Mahmoud Hassan, Fabrice Wendling. Dense-EEG source connectivity and dynamics of brain networks. 2015 International Conference On Advances In Biomedical Engineering (icabme), 2015, pp.104--106. ⟨hal-01380114⟩

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