Augmenting hippocampal–prefrontal neuronal synchrony during sleep enhances memory consolidation in humans

Abstract

Memory consolidation during sleep is thought to depend on the coordinated interplay between cortical slow waves, thalamocortical sleep spindles and hippocampal ripples, but direct evidence is lacking. Here, we implemented real-time closed-loop deep brain stimulation in human prefrontal cortex during sleep and tested its effects on sleep electrophysiology and on overnight consolidation of declarative memory. Synchronizing the stimulation to the active phases of endogenous slow waves in the medial temporal lobe (MTL) enhanced sleep spindles, boosted locking of brain-wide neural spiking activity to MTL slow waves, and improved coupling between MTL ripples and thalamocortical oscillations. Furthermore, synchronized stimulation enhanced the accuracy of recognition memory. By contrast, identical stimulation without this precise time-locking was not associated with, and sometimes even degraded, these electrophysiological and behavioral effects. Notably, individual changes in memory accuracy were highly correlated with electrophysiological effects. Our results indicate that hippocampo–thalamocortical synchronization during sleep causally supports human memory consolidation.

Brainwide hemodynamics predict neural rhythms across sleep and wakefulness in humans

“…Activity in the putamen is linked to memory consolidation, which is facilitated by slow waves 3,48 . Past work has identified experience-dependent activity in putamen during sleep 49 and increased putamen activity during spindle-slow wave complexes 50 , which play a causal role in memory consolidation 1,[6][7][8] . While slow waves have well-established direct cortical generators 51,52 , the subcortex still exerts a role in controlling or initiating cortical slow waves [53][54][55] .…”

“…As the brain transitions between wakefulness and sleep stages, oscillations wax and wane, signaling distinct arousal states. Arousal-related oscillations are linked to diverse cognitive processes, including several forms of memory [1][2][3][4][5][6][7][8][9] and attention 10,11 , along with basic physiological processes such as brain waste clearance 12 . EEG oscillations during sleep thus have strong relationships to cognition and physiology 13 ; however, the large-scale brain network activity giving rise to these oscillations remains poorly understood.…”

SleepEEGpy: a Python-based software “wrapper” package to organize preprocessing, analysis, and visualization of sleep EEG data

“…First, import both the spectral and grand spectral tools (line 1-2). Initialize a spectral tool object for each subject (l. [5][6][7][8][9]. With these, initialize the grand spectral tool (l. 10 The resulting topographical distributions of PSDs per frequency band per sleep stage averaged over all 40 subjects are shown in Figure 5.…”

Mapping sleep's oscillatory events as a biomarker of Alzheimer's disease

“…While the mechanisms underlying sleep‐dependent memory consolidation are a topic of debate among several competing (and non‐mutually exclusive) models, there is a general consensus that sleep's oscillatory events support memory processing 15,33,34 . In this context, some of the most insightful studies have focused on the coupling relationships between SW and SP events, which have emerged as a critical mechanistic component of sleep's memory functions 19,35,36,37–39 . Indeed, experiments in preclinical models and human research participants demonstrate that memory processing can be disrupted or enhanced via modulation of SW and SP events 35–36,40,39 .…”

“…19,35,36,[37][38][39] Indeed, experiments in preclinical models and human research participants demonstrate that memory processing can be disrupted or enhanced via modulation of SW and SP events. [35][36]40,39 In addition, age-associated changes in the temporal coupling of SW and SP events correlate with performance in sleep-dependent memory tests. 37,41 Timing irregularities of SW and SP coupling are also correlated with amyloid 42 and tau 43 in positron emission tomography (PET) imaging studies.…”