Differential roles of sleep spindles and sleep slow oscillations in memory consolidation

By Yina Wei, Giri Panamoottil Krishnan, M. Komarov, Maxim Bazhenov. 2017

84 citations recorded by the source corpus.

Sleep plays an important role in consolidation of recent memories. However, the mechanisms of consolidation remain poorly understood. In this study, using a realistic computational model of the thalamocortical network, we demonstrated that sleep spindles (the hallmark of N2 stage sleep) and slow oscillations (the hallmark of N3 stage sleep) both facilitate spike sequence replay as necessary for consolidation. When multiple memories were trained, the local nature of spike sequence replay during spindles allowed replay of the memories independently, while during slow oscillations replay of the weak memory was competing to the strong memory replay. This led to the weak memory extinction unless when sleep spindles (N2 sleep) preceded slow oscillations (N3 sleep), as observed during natural sleep. Our study presents a mechanistic explanation for the role of sleep rhythms in memory consolidation and proposes a testable hypothesis how the natural structure of sleep stages provides an optimal environment to consolidate memories. Significant Statement Numerous studies suggest importance of NREM sleep rhythms – spindles and slow oscillations - in sleep related memory consolidation. However, synaptic mechanisms behind the role of these rhythms in memory and learning are still unknown. Our new study predicts that sleep replay - the neuronal substrate of memory consolidation - is organized within the sleep spindles and coordinated by the Down to Up state transitions of the slow oscillation. For multiple competing memories, slow oscillations facilitated only strongest memory replay, while sleep spindles allowed a consolidation of the multiple competing memories independently. Our study predicts how the basic structure of the natural sleep stages provides an optimal environment for consolidation of multiple memories.

Subfields: Cognitive Neuroscience

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Citations in the corpus

Sleep prevents catastrophic forgetting in spiking neural networks by forming a joint synaptic weight representation (2022, background): “…thought to contribute to memory consolidation through repeated reactivation, or replay, of specific memory traces acquired during learning [16,21,39,44,47–49] These studies suggest that through replay, sleep can support the process of off-line memory consolidation to circumvent the problem of…”
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks (2020, background): “Using biophysical model of a cortical network Gonzalez et al. (2019) and Wei et al. (2018) showed that sleep dynamics promotes reactivation and helps to create distinct representations for unique memories by devoting synapses to speciﬁc memory traces.”
Bidirectional Interaction of Hippocampal Ripples and Cortical Slow Waves Leads to Coordinated Spiking Activity During NREM Sleep. (2020, background): “Connectivity of the thalamocortical circuity closely follows (Wei et al. 2018), and hippocampal connectivity is”
Can sleep protect memories from catastrophic forgetting? (2019, unknown): “In line with our previous work (Wei et al., 2018), these changes were a result of memory sequence replays during Up states of slow-waves.”