ArticleFrontiers in systems neuroscience2014
Robust sequential working memory recall in heterogeneous cognitive networks.
Article in Frontiers in systems neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 19 citations in OpenAlex.
- Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions.Neuron · 2017Article
- Itinerancy between attractor states in neural systems.Current opinion in neurobiology · 2016Review
- Hierarchical dynamics of informational patterns and decision-making.Proceedings. Biological sciences · 2016Article
- Learning of Chunking Sequences in Cognition and Behavior.PLoS computational biology · 2015Article
- Metastable dynamics in heterogeneous neural fields.Frontiers in systems neuroscience · 2015Article
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Authors and funding
3 authors at 2 institutions in 1 country.
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Abstract
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.
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