Cargando…
Robust sequential working memory recall in heterogeneous cognitive networks
Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a r...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231877/ https://www.ncbi.nlm.nih.gov/pubmed/25452717 http://dx.doi.org/10.3389/fnsys.2014.00220 |
_version_ | 1782344490873257984 |
---|---|
author | Rabinovich, Mikhail I. Sokolov, Yury Kozma, Robert |
author_facet | Rabinovich, Mikhail I. Sokolov, Yury Kozma, Robert |
author_sort | Rabinovich, Mikhail I. |
collection | PubMed |
description | Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions. |
format | Online Article Text |
id | pubmed-4231877 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-42318772014-12-01 Robust sequential working memory recall in heterogeneous cognitive networks Rabinovich, Mikhail I. Sokolov, Yury Kozma, Robert Front Syst Neurosci Neuroscience Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions. Frontiers Media S.A. 2014-11-14 /pmc/articles/PMC4231877/ /pubmed/25452717 http://dx.doi.org/10.3389/fnsys.2014.00220 Text en Copyright © 2014 Rabinovich, Sokolov and Kozma. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Rabinovich, Mikhail I. Sokolov, Yury Kozma, Robert Robust sequential working memory recall in heterogeneous cognitive networks |
title | Robust sequential working memory recall in heterogeneous cognitive networks |
title_full | Robust sequential working memory recall in heterogeneous cognitive networks |
title_fullStr | Robust sequential working memory recall in heterogeneous cognitive networks |
title_full_unstemmed | Robust sequential working memory recall in heterogeneous cognitive networks |
title_short | Robust sequential working memory recall in heterogeneous cognitive networks |
title_sort | robust sequential working memory recall in heterogeneous cognitive networks |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231877/ https://www.ncbi.nlm.nih.gov/pubmed/25452717 http://dx.doi.org/10.3389/fnsys.2014.00220 |
work_keys_str_mv | AT rabinovichmikhaili robustsequentialworkingmemoryrecallinheterogeneouscognitivenetworks AT sokolovyury robustsequentialworkingmemoryrecallinheterogeneouscognitivenetworks AT kozmarobert robustsequentialworkingmemoryrecallinheterogeneouscognitivenetworks |