Volume 25, Issue 8, August 2021, Pages 648-659


Aperiodic sleep networks promote memory consolidation

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Randolph F. Helfrich 1, Janna D. Lendner 2, Robert T. Knight 3 4 rights and content


  • The quality of cortical slow oscillation–spindle coupling shapes hippocampal ripple expression and indexes the integrity of memory pathways.

  • Synchronized and desynchronized network states alternate on a slow timescale to temporally segregate reactivation and subsequent information processing.

  • Temporally specific disruption of bidirectional network interactions impairs information transfer and leads to increased forgetting.

  • Desynchronized network states are characterized by broadband electrophysiological signatures potentially reflecting rapid shifts in population excitation–inhibition balance.

  • Novel methods to conceptualize and analyze aperiodic network states are required.

Hierarchical synchronization of sleep oscillations establishes communication pathways to support memory reactivation, transfer, and consolidation. From an information-theoretical perspective, oscillations constitute highly structured network states that provide limited information-coding capacity. Recent findings indicate that sleep oscillations occur in transient bursts that are interleaved with aperiodic network states, which were previously considered to be random noise. We argue that aperiodic activity exhibits unique and variable spatiotemporal patterns, providing an ideal information-rich neurophysiological substrate for imprinting new mnemonic patterns onto existing circuits. We discuss novel avenues in conceptualizing and quantifying aperiodic network states during sleep to further understand their relevance and interplay with sleep oscillations in support of memory consolidation.

Section snippets

Multiscale rhythms support memory reactivation, transformation, and consolidation during sleep

How does the human brain turn novel experiences into long-lasting stable memories? Over the past four decades a large body of work has established that sleep plays a key role in memory formation [1,2]. The influential active systems memory consolidation hypothesis suggests a two-stage process in which novel information is initially encoded in the hippocampus and the neocortex, and subsequently becomes neocortex-dependent as new information is consolidated [1,3., 4., 5.]. The sleeping brain

The prevalence of oscillatory and aperiodic states in the sleeping brain

Although oscillations constitute the most salient feature of electrophysiological sleep recordings, one cannot assume that this also reflects their degree of functional significance. During a typical night of 8 h of sleep, we spend ~25% (2 h) in REM sleep, which in humans is not characterized by continuous oscillations, unlike the very prominent ongoing theta (3–8 Hz) activity observed in rodent REM sleep [20]. Furthermore, we spend ~50% (4 h) in NREM2 and another 25% (2 h) in deep slow wave

Recent trends in understanding systems memory consolidation

The conceptualization of the two-stage process of memory formation typically takes a hippocampus-centric perspective [6,7,25]. Specifically, the hippocampal ripple is proposed to serve as a conductor that orchestrates the network organization supporting sleep-dependent memory formation [7,26]. For instance, electrical or optogenetic manipulation of hippocampal ripple expression has a profound impact on cortical slow oscillation–spindle timing and subsequent memory formation [10,27]. Similarly

Out of sync, out of memory: integrity of memory pathways is indexed by precision of the temporal coordination

Sleep oscillations do not occur in isolation, but often emerge sequentially on a rapid timescale [1,8]. Crucially, cardinal sleep signatures do not merely coincide in time, but are synchronized to each other through phase–amplitude cross-frequency coupling (PAC) where the oscillatory phase of the slower frequency modulates the amplitude of the faster component [1,8,13,42]. For instance, it has repeatedly been shown that the slow oscillation phase predicts the spindle amplitude (Figure 1A) [8,43.

Information processing in the sleeping brain: stable representations in a dynamic system

Sleep oscillations are not a continuous phenomenon, but appear in bursts. At every occurrence, the precise manifestation is variable and depends on the present network state. For instance, it has recently been shown that hippocampal ripple expression is dynamically shaped by the precision of cortical slow oscillation–spindle coupling. Specifically, if the spindle failed to peak within a narrow phase range, hippocampal ripple expression was diminished [13].

Furthermore, several lines of inquiry

The physiologic basis of non-oscillatory brain activity during sleep

Neuronal oscillations are thought to emerge from the synchronized firing of multiple neurons within a population [82,83]. Conversely, it could be assumed that desynchronized electrophysiological field patterns should also be the result of asynchronous neuronal firing [84]. However, to date it is not established how the collective firing of different neuron types gives rise to the local field potential [82]. Several lines of research suggest that there might be a region- and state-specific

Concluding remarks

The mechanisms that support the self-organization of the sleeping brain to optimally support information reactivation, processing, transfer, and consolidation remain elusive. Converging evidence suggests that sleep oscillations may provide key messengers to coordinate memory consolidation in space and time. These oscillations likely constitute an endogenous timing mechanism that provides distinct windows of opportunity for information processing, as exemplified by the spindle pulsing every 3–6


This work was supported by the German Research Foundation (DFG; HE 8329/2-1 to R.F.H. and LE 3863/2-1 to J.D.L.), the Hertie Foundation (Hertie Network for Excellence in Clinical Neuroscience, R.F.H.), National Institute of Neurological Disorders and Stroke (NINDS) Javits Award R37NS21135 (R.T.K.) and U19 Brain Initiative 1U19NS107609-01 (R.T.K.). The authors would like to thank Jan Weber, Frank van Schalkwijk, and Michael Hahn for valuable feedback on the manuscript, as well as Joe Winer,

Declaration of interests

No interests are declared.



desynchronized network states are characterized by the absence of strong oscillations, and thus lack a prominent periodic signal and reflect increased variability. Aperiodic activity follows a power law (1/f) and indicates that no predominant temporal activity, such as an oscillation, is present (see also desynchronization).


we define complexity in the temporal domain as a state of high Shannon entropy, namely with high variability and low redundancy. In the spatial domain at

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