Electrophysiological foundations of the human default-mode network revealed by brain-wide intracranial-EEG recordings during resting-state and cognition

Abstract

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 brain-wide electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used brain-wide intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during the resting-state and cognition. 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 all higher frequencies. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during verbal memory encoding and recall. Compared to resting-state, 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 dynamic spectro-temporal network features that allow the DMN to maintain a balance between stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the neurophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.