Journal
NEUROIMAGE
Volume 250, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2022.118927
Keywords
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Funding
- NIH [NS086085, EB022907]
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This study investigates the electrophysiological organization of the human default mode network (DMN) using intracranial EEG recordings. The findings reveal increased intra-DMN phase synchronization in the slow-wave frequency range (<4 Hz) and higher interactions with other brain networks in the beta (12-30 Hz) and gamma (30-80 Hz) bands. The slow-wave intra-DMN synchronization is observed during resting-state and memory encoding and recall, and increases during successful memory retrieval. Nonlinear dynamic causal interactions analysis shows that the DMN acts as a causal outflow network during memory encoding and recall.
Investigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during resting-state and its modulation during a cognitive task involving episodic memory formation. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz), while DMN interactions with other brain networks was higher in the beta (12-30 Hz) and gamma (30-80 Hz) bands. Crucially, slow-wave intra-DMN synchronization was observed in the task-free restingstate and during both verbal memory encoding and recall. Compared to resting-state, slow-wave intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify frequency specific neurophysiological signatures of the DMN which allow it to maintain stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the electrophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.
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