Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition

Abstract

The idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30–100 Hz) and slow theta (3–8 Hz) spectral neural activity, based on data from 294 neurosurgical patients fitted with indwelling electrodes. Here we report that gamma networks desynchronize and theta networks synchronize during encoding and retrieval. Furthermore, for nearly all brain regions we studied, gamma power rises as that region desynchronizes with gamma activity elsewhere in the brain, establishing gamma as a largely asynchronous phenomenon. The abundant phenomenon of theta synchrony is positively correlated with a brain region’s gamma power, suggesting a predominant low-frequency mechanism for inter-regional communication.

Tonic resting-state hubness supports high-frequency activity defined verbal-memory encoding network in epilepsy

“…Solomon et al, examined high gamma during verbal-memory and observed both synchronous and asynchronous activity. They found that regions in frontal, temporal, and medial temporal lobe cortex asynchronous with other regions, displayed a high level of connection strength, implying a high level of centrality or hubness within the memory network, a finding broadly consistent with the current results (Solomon EA, et al, 2017). We show that through repetitive processes of memory encoding, gamma frequency activity can establish synchrony to the point that even slow-moving resting-state BOLD fluctuations reflect their network impact.…”

“…Kucewicz and colleagues demonstrated that memory related broadband gamma activity centroids were in the range of 30-100Hz (Kucewicz MT, et al, 2017). Two recent studies on human memory network analysis with a pooled cohort of patients similar to that included in this study, have shown that successful memory encoding is associated with asynchronous organization of the memory network in gamma activity less than 100Hz and synchronous theta activity, with widespread high gamma activity considered to be the hallmark of memory encoding (Solomon EA, et al, 2017;Solomon EA, et al, 2019). In this project, we were interested in investigating the intrinsic BOLD correlations of a high frequency network already known to play a major role in human memory, all toward determining if such networks possess distinctive whole-brain organization properties.…”

“…A handful of studies have performed network analysis directly on memory task-IEEG signals, studying the network synchrony present during encoding process (Burke JF, et al, 2013;Solomon EA, et al, 2017;Vecchio F et al, 2016). Such studies have emphasized different properties of the gamma frequency band-width, including spectral power changes, phase-locking value, and exact low-resolution topographical analysis (eLORETA).…”

“…Successful episodic verbal memory encoding, termed the 'Subsequent Memory Effect' (SME) is associated with high-frequency gamma activity (ranging from 30-100Hz) captured using power spectral and synchronization studies during invasive electroencephalography (IEEG) in association with neuronal firing Kucewicz MT et al, 2017;Lega BC et al, 2012;Long NM et al, 2014;Sederberg PB et al, 2006;Serruya MD et al, 2014;Solomon EA et al, 2017;Solomon EA et al, 2019). Despite these well-established linkages, relatively little is known about the whole-brain organization of HFA regions and the degree to which these regions possess either distinct network features relative to other brain areas, or rely on abnormal organizational properties due to epilepsy.…”

“…While evidence exists to suggest that memory-relevant regions in the epileptic brain can take up normative network roles in an effort to preserve function (Jin SH et al, 2015;Powell HW et al, 2007;Solomon EA, et al, 2017;Tracy J et al, 2014), the network properties characterizing these memory regions in health and in disease are unclear. In this study, we integrate IEEG with 2002).…”