Tonic Resting State Hubness Supports High Gamma Activity Defined Verbal Memory Encoding Network in Epilepsy

Abstract

High gamma activity (HGA) of verbal-memory encoding using invasive-electroencephalogram has laid the foundation for numerous studies testing the integrity of memory in diseased populations. Yet, the functional connectivity characteristics of networks subserving these memory linkages remains uncertain. By integrating this electrophysiological biomarker of memory encoding from IEEG with resting-state BOLD fluctuations, we estimated the segregation and hubness of HGA-memory regions in drug-resistant epilepsy patients and matched healthy controls. HGA-memory regions express distinctly different hubness compared to neighboring regions in health and in epilepsy, and this hubness was more relevant than segregation in predicting verbal memory encoding. The HGA-memory network comprised regions from both the cognitive control and primary processing networks, validating that effective verbal-memory encoding requires integrating brain functions, and is not dominated by a central cognitive core. Our results demonstrate a tonic intrinsic set of functional connectivity, which provides the necessary conditions for effective, phasic, task-dependent memory encoding.