Sleep Spindle Refractoriness Segregates Periods of Memory Reactivation

Abstract

The stability of long-term memories is enhanced by reactivation during sleep. Correlative evidence has linked memory reactivation with thalamocortical sleep spindles, although their functional role is not fully understood. Our initial study replicated this correlation and also demonstrated a novel rhythmicity to spindles, such that a spindle is more likely to occur approximately 3-6 s following a prior spindle. We leveraged this rhythmicity to test the role of spindles in memory by using real-time spindle tracking to present cues within versus just after the presumptive refractory period; as predicted, cues presented just after the refractory period led to better memory. Our findings demonstrate a precise temporal link between sleep spindles and memory reactivation. Moreover, they reveal a previously undescribed neural mechanism whereby spindles may segment sleep into two distinct substates: prime opportunities for reactivation and gaps that segregate reactivation events.

Posterior hippocampal spindle-ripples co-occur with neocortical theta-bursts and down-upstates, and phase-lock with parietal spindles during NREM sleep in humans

“…We observed SS in HC with no ictal or interictal involvement, and HC-SS are observed in animals (Miyawaki and Diba, 2016), suggesting that they represent healthy activity. Our confirmation of phase-modulation of HC-ripples by HC-SS, and our demonstration of their coordination with NC-GE, provides a possible framework for HC-NC information transfer, as previously suggested (Siapas and Wilson, 1998;Sirota et al, 2003;Staresina et al, 2015) Antony et al, 2018). However, despite our efforts to eliminate contamination by epileptiform events, our study is limited by the possibility of pathological restructuring, and the possible role of SSR in memory replay is unconfirmed in mechanistic studies.…”

Changes in cross-frequency coupling following closed-loop auditory stimulation in non-rapid eye movement sleep

“…Similar to previous findings, our TFR results have shown that up-phases of slow waves were associated with a robust increase of 44±26% in fast sigma power (p<0.001, d=0.77), with a center frequency of ~16 Hz and extending to higher frequencies (slow gamma, ~30 Hz). Interestingly, at the end of the 2-s analysis window, there was also a suppression of activity in the sigma band following the enhancement (p=0.03, d=-0.38; mean decrease -13±6%), which is in line with previous findings on refractory periods of spindle occurrence (Antony et al, 2018). Superimposed grand-averaged ERP waveforms (in C4 target channel) for STIM (solid line) and SHAM (dashed line) conditions in an overlay, with (left) time-frequency power plots (relative change in power between STIM and SHAM collapsed across all channels) and (right) time-frequency t-value plots (shaded area indicates nonsignificant difference between conditions, cluster corrected two-sided p<.05).…”

Multiple memories can be simultaneously reactivated during sleep as effectively as a single memory

“…To deal with this possible bias, we conducted two complementary analyses ( Supplementary Figure 1). First, we regressed out pre-sleep results to eliminate set-dependent effects of regression to the mean 20,26 (see Methods). This analysis produced similar results, with a significant effect for cuing (F(1,30)=17.89, p<0.001) and a nonsignificant interaction between set-size and cuing status (F(2,30)=0.11, p=0.9).…”

“…Throughout the experiment, we collected scalp electroencephalographic data. We used these data for sleep staging and also to analyze responses to cue presentation during sleep, focusing on two frequency bands shown to be modulated by cues in previous studies 26,31 . The sigma range (11)(12)(13)(14)(15)(16) Hz) encompasses sleep spindles, which are ramped waves lasting between 500-3000 ms. Spindles have been linked to memory consolidation (see 32 for review).…”