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Robust sequential working memory recall in heterogeneous cognitive networks

Overview of attention for article published in Frontiers in Systems Neuroscience, November 2014
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Title
Robust sequential working memory recall in heterogeneous cognitive networks
Published in
Frontiers in Systems Neuroscience, November 2014
DOI 10.3389/fnsys.2014.00220
Pubmed ID
Authors

Mikhail I. Rabinovich, Yury Sokolov, Robert Kozma

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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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 4%
Netherlands 1 2%
Unknown 43 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 22%
Researcher 10 22%
Student > Master 7 15%
Student > Postgraduate 4 9%
Professor 4 9%
Other 6 13%
Unknown 5 11%
Readers by discipline Count As %
Psychology 7 15%
Physics and Astronomy 7 15%
Neuroscience 6 13%
Agricultural and Biological Sciences 5 11%
Mathematics 5 11%
Other 10 22%
Unknown 6 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 October 2014.
All research outputs
#15,308,698
of 22,768,097 outputs
Outputs from Frontiers in Systems Neuroscience
#959
of 1,341 outputs
Outputs of similar age
#150,332
of 258,053 outputs
Outputs of similar age from Frontiers in Systems Neuroscience
#29
of 42 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,341 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.