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Poster F75

Oscillatory mechanisms of intrinsic brain networks

Poster Session F - Tuesday, April 16, 2024, 8:00 – 10:00 am EDT, Sheraton Hall ABC

Youjing Luo1 (, Xianghong Meng4, Fuyong Chen3, Pengfei Xu2; 1Department of Sport, Physical Education and Health, Hong Kong Baptist University, 2Faculty of Psychology, Beijing Normal University, 3The University of Hong Kong - Shenzhen Hospital, 4Shenzhen General Hospital, Shenzhen University

Non-invasive neuroimaging has revealed specific network-based resting-state networks in the human brain, yet underlying neurophysiology remains unclear. In the current study, we recorded and analyzed intracranial electroencephalography (iEEG) data from 42 participants to characterize local field potentials (LFPs) within three major intrinsic connectivity networks—the default mode network (DMN), frontoparietal network (FPN), and salience network (SN). The result showed significantly stronger within-network phase coherence in low frequencies (4-13 Hz) within the DMN and high frequencies (30-100 Hz) within the FPN. Further analysis using Hidden Markov Modeling (HMM) indicated a preferential pattern of low-frequency phase coupling within the DMN. Phase-amplitude coupling analysis further revealed that the low-frequency phase in the DMN modulated the high-frequency amplitude envelopes within the FPN, providing support for interactions between intrinsic networks. These novel intracranial electrophysiological findings corroborate the network model of intrinsic brain architecture, observing distinct oscillatory profiles between networks, with the DMN preferentially engaging slower frequencies. This research sheds new light on how various networks coordinate resting-state activity through the integration and segregation of neural signals across frequencies— advancing theoretical understanding of network communication mechanisms underlying the brain's intrinsic functional architecture.

Topic Area: METHODS: Electrophysiology


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April 13–16  |  2024