Phase reset dynamics of memory encoding

Abstract

Human and animal studies implicate theta and alpha oscillations in memory function. We tested whether theta, alpha, and beta phase consistency predicts memory encoding dynamics in neurosurgical patients performing delayed free recall tasks with either unrelated (N=188) or categorized words (N=157). We observed widespread post-stimulus phase consistency (3- 21 Hz) and, crucially, identified distinct frequency-specific patterns predictive of successful encoding. Specifically, increased early-list item recall was significantly correlated across subjects with increased theta (3-7 Hz) phase consistency. Subsequent recall analyses, controlling for serial position, revealed distinct frequency signatures for successfully encoded items: theta (3-6 Hz) and alpha (9-14 Hz) for unrelated lists, and theta (3-6 Hz) and beta (14-19 Hz) for categorized lists. Regional analyses for unrelated lists highlighted the lateral temporal cortex for theta effects and the prefrontal cortex for both theta and alpha consistency. These findings provide novel evidence for the frequency-specific presence of increased phase consistency during episodic encoding, revealing its sensitivity to both item context and temporal position within a learning sequence. Significance StatementNeural oscillations are implicated in human memory encoding, but their precise roles are still being defined. Our study leverages large-scale intracranial EEG datasets from participants undergoing word recall experiments, and introduces analytical innovations for robustly quantifying phase consistency with differing numbers of recalled versus forgotten items. This methodology reveals that phase consistency across different frequency bands (theta, alpha, beta) predicts memory formation. We demonstrate a specific role for theta consistency in encoding early list items and show that the brain adaptively recruits different oscillatory patterns (alpha or beta alongside theta) depending on item context (unrelated vs. categorized lists). These findings advance our understanding of the frequency-specific neural mechanisms supporting human episodic memory, revealing how the brain adapts its encoding strategies based on informational structure.