Overlapping memory replay during sleep builds cognitive schemata.

By Penelope A. Lewis, Simon J. Durrant. 2011

493 citations recorded by the source corpus.

Sleep enhances integration across multiple stimuli, abstraction of general rules, insight into hidden solutions and false memory formation. Newly learned information is better assimilated if compatible with an existing cognitive framework or schema. This article proposes a mechanism by which the reactivation of newly learned memories during sleep could actively underpin both schema formation and the addition of new knowledge to existing schemata. Under this model, the overlapping replay of related memories selectively strengthens shared elements. Repeated reactivation of memories in different combinations progressively builds schematic representations of the relationships between stimuli. We argue that this selective strengthening forms the basis of cognitive abstraction, and explain how it facilitates insight and false memory formation.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

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Citations in the corpus

Replay in Deep Learning: Current Approaches and Missing Biological Elements (2021, neutral): “Partial replay has also been proposed to build cognitive schemata (Lewis & Durrant, 2011).”
About sleep's role in memory. (2013, background): “The hypothesis that sleep supports the formation of longterm memory in an active system consolidation process has been elaborated in several previous reviews (293, 345, 734, 828, 957, 958, 984, 988, 1284, 1305).”
Schema-conformant memories are preferentially consolidated during REM sleep. (2015, unknown): “…even be that SWS, which occurs earlier in the night, is involved in strengthening or even forming schemata, as suggested by the recent iOtA model (Lewis & Durrant, 2011), and REM sleep follows on the same night taking advantage of the new schema in a multi-step process as suggested by Stickgold…”
Episodic Memory and Beyond: The Hippocampus and Neocortex in Transformation (2016, unknown): “With respect to episodic memory, there is evidence that recollection can be preserved or degraded and transformed to familiarity, but the conditions that lead to one or the other outcome, and the neural mechanisms involved, have yet to be elucidated (Lewis & Durrant 2011).”
The content of hippocampal “replay” (2018, background): “…Buzs aki, 2016), raising the intriguing possibility that forward replay itself can serve two purposes depending on the behavioral state of the animal (Diekelmann et al., 2011): memory retrieval during the awake state and memory consolidation during sleep (Carr et al., 2011; Lewis & Durrant, 2011).”
Sleep and the Price of Plasticity: From Synaptic and Cellular Homeostasis to Memory Consolidation and Integration (2014, background): “For example, it has been proposed that synapses subject to replay during sleep may first be selectively potentiated and then globally downscaled (Lewis and Durrant, 2011) or may first be ‘‘tagged’’ for potentiation during NREM sleep replays in the context of an overall downscaling and then…”
The Tolman-Eichenbaum Machine: Unifying Space and Relational Memory through Generalization in the Hippocampal Formation (2019, background): “It has been suggested that abstractions and structural learning may rely on hippocampal replay (Foster andWilson, 2006; Lewis and Durrant, 2011; Liu et al., 2019) with sleep playing a crucial role in replay extracting regularities from wake experience.”
How Memory Replay in Sleep Boosts Creative Problem-Solving (2018, background): “Work over the past 10 years has shown that sleep is critical for integrating memories into an ordered framework [6], assimilating new memories with older knowledge [7,8], and facilitating the abstraction of general rules [9–11].”
Cellular and Systems Consolidation of Declarative Memory (2017, background): “…replay on the one hand ( " push " equals potentiating " important " traces) and scaling on the other ( " pull " equals weakening irrelevant traces) may together aid the construction and updating of memory networks in the cortex (Diekelmann and Born 2010; Genzel et al. 2014; Lewis and Durrant 2011).”
Integration of New Information in Memory: New Insights from a Complementary Learning Systems Perspective (2020, background): “A considerable body of recent work in human cognitive neuroscience also investigates the learning of structured bodies of knowledge and the role of schema consistency [14, 15, 16, 17].”
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks (2020, background): “It has been hypothesized that in the mammalian brain sleep helps to create generalized representations of an input learned during the awake state (Stickgold & Walker (2013); Lewis & Durrant (2011)).”