Computational models of memory consolidation and long-term synaptic plasticity during sleep

Autores: Wilfredo Blanco, CésarRennó-Costa, Ana Cláudia Costa da Silva e SidartaRibeiro

Abstract
The brain stores memories by persistently changing the connectivity between neurons. Sleep is known to be critical for these changes to endure. Research on the neurobiology of sleep and the mechanisms of long-term synaptic plasticity has provided data in support of various theories of how brain activity during sleep affects long-term synaptic plasticity. The experimental findings – and therefore the theories – are apparently quite contradictory, with some evidence pointing to a role of sleep in the forgetting of irrelevant memories, whereas other results indicate that sleep supports the reinforcement of the most valuable recollections. A unified theoretical framework is in need. Computational modeling and simulation provide grounds for the quantitative testing and comparison of theoretical predictions and observed data, and might serve as a strategy to organize the rather complicated and diverse pool of data and methodologies used in sleep research. This review article outlines the emerging progress in the computational modeling and simulation of the main theories on the role of sleep in memory consolidation.

Keywords
Homeostasis; Sequential; Replay; Activeconsolidation; Embossing; Down-scaling; Up-scaling; Simulation; LTP; LTD

DOI: https://doi.org/10.1016/j.nlm.2018.10.003

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