A small world of neuronal synchrony

  • A small-world network has been suggested to be an efficient solution for achieving both modular and global processing-a property highly desirable for brain computations. Here, we investigated functional networks of cortical neurons using correlation analysis to identify functional connectivity. To reconstruct the interaction network, we applied the Ising model based on the principle of maximum entropy. This allowed us to assess the interactions by measuring pairwise correlations and to assess the strength of coupling from the degree of synchrony. Visual responses were recorded in visual cortex of anesthetized cats, simultaneously from up to 24 neurons. First, pairwise correlations captured most of the patterns in the population´s activity and, therefore, provided a reliable basis for the reconstruction of the interaction networks. Second, and most importantly, the resulting networks had small-world properties; the average path lengths were as short as in simulated random networks, but the clustering coefficients were larger. Neurons differed considerably with respect to the number and strength of interactions, suggesting the existence of "hubs" in the network. Notably, there was no evidence for scale-free properties. These results suggest that cortical networks are optimized for the coexistence of local and global computations: feature detection and feature integration or binding.

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Author:Shan Yu, Debin Huang, Wolf SingerORCiDGND, Danko NikolićORCiDGND
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/18400792
Parent Title (English):Cerebral cortex
Publisher:Oxford Univ. Press
Place of publication:Oxford
Document Type:Article
Date of Publication (online):2008/11/12
Date of first Publication:2008/04/09
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2008/11/12
Tag:ising model; maximum entropy; orientation selectivity; parallel recording; scale free; visual cortex
Page Number:11
First Page:2891
Last Page:2901
© 2008 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Source:Cerebral Cortex. 2008 Apr 9. doi:10.1093/cercor/bhn047
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Angeschlossene und kooperierende Institutionen / MPI für Hirnforschung
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Sammlung Biologie / Sondersammelgebiets-Volltexte
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell 2.0