Please use this identifier to cite or link to this item: https://repositorio.ufrn.br/jspui/handle/1/6195
Title: A Mismatch-Based Model for Memory Reconsolidation and Extinction in Attractor Networks
Authors: Osan, Remus
Adriano B. L., Tort
Olavo B., Amaral
Issue Date: 2011
Publisher: Gennady Cymbalyuk, Georgia State University, United States of America
Citation: Osan, R., Tort , A. B. L., Amaral O. B. (2011)
Abstract: The processes of memory reconsolidation and extinction have received increasing attention in recent experimental research, as their potential clinical applications begin to be uncovered. A number of studies suggest that amnestic drugs injected after reexposure to a learning context can disrupt either of the two processes, depending on the behavioral protocol employed. Hypothesizing that reconsolidation represents updating of a memory trace in the hippocampus, while extinction represents formation of a new trace, we have built a neural network model in which either simple retrieval, reconsolidation or extinction of a stored attractor can occur upon contextual reexposure, depending on the similarity between the representations of the original learning and reexposure sessions. This is achieved by assuming that independent mechanisms mediate Hebbian-like synaptic strengthening and mismatch-driven labilization of synaptic changes, with protein synthesis inhibition preferentially affecting the former. Our framework provides a unified mechanistic explanation for experimental data showing (a) the effect of reexposure duration on the occurrence of reconsolidation or extinction and (b) the requirement of memory updating during reexposure to drive reconsolidation
Description: OSAN, R. , TORT, A. B. L. , AMARAL, O. B. . A mismatch-based model for memory reconsolidation and extinction in attractor networks. Plos One, v. 6, p. e23113, 2011.
URI: https://repositorio.ufrn.br/jspui/handle/1/6195
Appears in Collections:ICe - Artigos publicados em periódicos

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