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A simulation model of sleep-dependent memory consolidation

Dr. Yihe Lu
University of Edinburgh ~ School of Informatics
Tamas Foldes
CUBRIC - School of Psychology, Cardiff University, United Kingdom ~ School of Psychology
Prof. Penelope Lewis
CUBRIC - School of Psychology, Cardiff University, United Kingdom ~ School of Psychology

Recent qualitative reviews show that sleep-dependent memory consolidation (SDMC) effects are highly task dependent. A growing body of research argues that encoding-related spontaneous reactivation and reactivation due to memory cueing during sleep play a causal role in SDMC, specifically for associative information and gist abstraction (Lewis, Knoblich & Poe, 2018). To better understand the relationship between task-dependency, reactivation, and rapid generalization a formal framework is necessary. We argue that an exemplar-based framework (Hintzman, 1986) is complementary to the existing connectionist computational models of reactivation (e.g: Kumaran & McClelland, 2012). By modelling offline reactivation as internally generated cued recall we can account for numerous behavioural SDMC findings (including episodic inference tasks, categorization, motor memory), some of which have been shown to be related to SWS. We discuss predictions regarding the effects of interference, memory strength, context and how they relate to existing verbal theories of SDMC. We conclude that recurrent similarity-based generalization is an ideal algorithm for modelling consolidation of newly encoded memories.



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Cite this as:

Lu, Y., Foldes, T. A., & Lewis, P. (2021, July). A simulation model of sleep-dependent memory consolidation. Paper presented at Virtual MathPsych/ICCM 2021. Via