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Detecting synfire chains in parallel spike data

Lookup NU author(s): Dr Elizabeth Williams

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Abstract

The synfire chain model of brain organization has received much theoretical attention since its introduction (Abeles, 1982, 1991). However there has been no convincing experimental demonstration of synfire chains due partly to limitations of recording technology but also due to lack of appropriate analytic methods for large scale recordings of parallel spike trains. We have previously published one such method based on intersection of the neural populations active at two different times (Schrader et al., 2008). In the present paper we extend this analysis to deal with higher firing rates and noise levels, and develop two additional tools based on properties of repeating firing patterns. All three measures show characteristic signatures if synfire chains underlie the recorded data. However we demonstrate that the detection of repeating firing patterns alone (as used in several papers) is not enough to infer the presence of synfire chains. Positive results from all three measures are needed. (C) 2012 Elsevier B.V. All rights reserved.


Publication metadata

Author(s): Gerstein GL, Williams ER, Diesmann M, Grun S, Trengove C

Publication type: Article

Publication status: Published

Journal: Journal of Neuroscience Methods

Year: 2012

Volume: 206

Issue: 1

Pages: 54-64

Print publication date: 14/02/2012

ISSN (print): 0165-0270

ISSN (electronic): 1872-678X

Publisher: Elsevier BV

URL: http://dx.doi.org/10.1016/j.jneumeth.2012.02.003

DOI: 10.1016/j.jneumeth.2012.02.003


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Funding

Funder referenceFunder name
CARMEN
Engineering and Physical Sciences Research Council, UK
Helmholtz Alliance on Systems Biology (Germany)
MEXT (japan)
269921EU
F1.2DIP

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