What can spike train distances tell us about the neural code?

Welcome to the UPF Digital Repository

Chicharro D, Kreuz T, Andrzejak R G. What can spike train distances tell us about the neural code?. Journal of Neuroscience Methods. 2011; 199(1): 146-165. DOI 10.1016/j.jneumeth.2011.05.002
http://hdl.handle.net/10230/16205
To cite or link this document: http://hdl.handle.net/10230/16205
dc.contributor.author Chicharro Raventós, Daniel
dc.contributor.author Kreuz, Thomas
dc.contributor.author Andrzejak, Ralph Gregor
dc.contributor.other Universitat Pompeu Fabra
dc.date.accessioned 2012-02-09T09:47:30Z
dc.date.available 2012-02-09T09:47:30Z
dc.date.issued 2011
dc.identifier.citation Chicharro D, Kreuz T, Andrzejak R G. What can spike train distances tell us about the neural code?. Journal of Neuroscience Methods. 2011; 199(1): 146-165. DOI 10.1016/j.jneumeth.2011.05.002
dc.identifier.issn 0165-0270
dc.identifier.uri http://hdl.handle.net/10230/16205
dc.description.abstract Time scale parametric spike train distances like the Victor and the van Rossum distances are often applied to study the neural code based on neural stimuli discrimination. Different neural coding hypotheses, such as rate or coincidence coding, can be assessed by combining a time scale parametric spike train distance with a classifier in order to obtain the optimal discrimination performance. The time scale for which the responses to different stimuli are distinguished best is assumed to be the discriminative precision of the neural code. The relevance of temporal coding is evaluated by comparing the optimal discrimination performance with the one achieved when assuming a rate code. We here characterize the measures quantifying the discrimination performance, the discriminative precision, and the relevance of temporal coding. Furthermore, we evaluate the information these quantities provide about the neural code. We show that the discriminative precision is too unspecific to be interpreted in terms of the time scales relevant for encoding. Accordingly, the time scale parametric nature of the distances is mainly an advantage because it allows maximizing the discrimination performance across a whole set of measures with different sensitivities determined by the time scale parameter, but not due to the possibility to examine the temporal properties of the neural code.
dc.description.sponsorship DC is supported by the grant 2010FI-B2 00079 of the ”Comissionat per a Universitats i Recerca del Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya i del Fons Social Europeu” and grant 2008BE1 00166 of the ”Comissionat per a Universitats i Recerca del Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya”. RGA acknowledges grant BFU2007-61710 of the Spanish Ministry of Education and Science.
dc.language.iso eng
dc.publisher Elsevier
dc.rights (c) 2011 Elsevier. Published article is available at: http://dx.doi.org/10.1016/j.jneumeth.2011.05.002
dc.subject.other Xarxes neuronals (Informàtica)
dc.subject.other Neurociència computacional
dc.title What can spike train distances tell us about the neural code?
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1016/j.jneumeth.2011.05.002
dc.subject.keyword Spike trains
dc.subject.keyword Spike train distances
dc.subject.keyword Discrimination
dc.subject.keyword Mutual information
dc.subject.keyword Precision
dc.subject.keyword Temporal coding
dc.subject.keyword Neural coding
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/submittedVersion


See full text

Search


Advanced Search

Browse

My Account

Statistics