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  Dynamics of excitable neural networks with heterogeneous connectivity

Chavez, M., Besserve, M., & Le Van Quyen, M. (2011). Dynamics of excitable neural networks with heterogeneous connectivity. Progress in Biophysics and Molecular Biology, 105(1-2), 29-33. doi:10.1016/j.pbiomolbio.2010.11.002.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-BC58-F Version Permalink: http://hdl.handle.net/21.11116/0000-0001-BA57-C
Genre: Journal Article

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Chavez, M, Author
Besserve, M1, 2, Author              
Le Van Quyen, M, Author
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: A central issue of neuroscience is to understand how neural units integrates internal and external signals to create coherent states. Recently, it has been shown that the sensitivity and dynamic range of neural assemblies are optimal at a critical coupling among its elements. Complex architectures of connections seem to play a constructive role on the reliable coordination of neural units. Here we show that, the synchronizability and sensitivity of excitable neural networks can be tuned by diversity in the connections strengths. We illustrate our findings for weighted networks with regular, random and complex topologies. Additional comparisons of real brain networks support previous studies suggesting that heterogeneity in the connectivity may play a constructive role on information processing. These findings provide insights into the relationship between structure and function of neural circuits.

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 Dates: 2011-03
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1016/j.pbiomolbio.2010.11.002
BibTex Citekey: ChavezBL2011
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Title: Progress in Biophysics and Molecular Biology
  Other : Prog. Biophys. Mol. Biol.
Source Genre: Journal
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Publ. Info: Oxford : Pergamon
Pages: - Volume / Issue: 105 (1-2) Sequence Number: - Start / End Page: 29 - 33 Identifier: ISSN: 0079-6107
CoNE: https://pure.mpg.de/cone/journals/resource/110992357272224