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000137486 0247_ $$2doi$$a10.1162/NECO_a_00432
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000137486 037__ $$aFZJ-2013-03923
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000137486 1001_ $$0P:(DE-HGF)0$$aPipa, Gordon$$b0$$eCorresponding author
000137486 245__ $$aImpact of Spike Train Autostructure on Probability Distribution of Joint Spike Events
000137486 260__ $$aCambridge, Mass.$$bMIT Press$$c2013
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000137486 520__ $$aThe discussion whether temporally coordinated spiking activity really exists and whether it is relevant has been heated over the past few years. To investigate this issue, several approaches have been taken to determine whether synchronized events occur significantly above chance, that is, whether they occur more often than expected if the neurons fire independently. Most investigations ignore or destroy the autostructure of the spiking activity of individual cells or assume Poissonian spiking as a model. Such methods that ignore the autostructure can significantly bias the coincidence statistics. Here, we study the influence of the autostructure on the probability distribution of coincident spiking events between tuples of mutually independent non-Poisson renewal processes. In particular, we consider two types of renewal processes that were suggested as appropriate models of experimental spike trains: a gamma and a log-normal process. For a gamma process, we characterize the shape of the distribution analytically with the Fano factor (FFc). In addition, we perform Monte Carlo estimations to derive the full shape of the distribution and the probability for false positives if a different process type is assumed as was actually present. We also determine how manipulations of such spike trains, here dithering, used for the generation of surrogate data change the distribution of coincident events and influence the significance estimation. We find, first, that the width of the coincidence count distribution and its FFc depend critically and in a nontrivial way on the detailed properties of the structure of the spike trains as characterized by the coefficient of variation CV. Second, the dependence of the FFc on the CV is complex and mostly nonmonotonic. Third, spike dithering, even if as small as a fraction of the interspike interval, can falsify the inference on coordinated firing.
000137486 536__ $$0G:(DE-HGF)POF2-331$$a331 - Signalling Pathways and Mechanisms in the Nervous System (POF2-331)$$cPOF2-331$$fPOF II$$x0
000137486 536__ $$0G:(DE-Juel1)HGF-SystemsBiology$$aHASB - Helmholtz Alliance on Systems Biology (HGF-SystemsBiology)$$cHGF-SystemsBiology$$fHASB-2008-2012$$x1
000137486 536__ $$0G:(EU-Grant)269921$$aBRAINSCALES - Brain-inspired multiscale computation in neuromorphic hybrid systems (269921)$$c269921$$fFP7-ICT-2009-6$$x2
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000137486 7001_ $$0P:(DE-Juel1)144168$$aGrün, Sonja$$b1$$ufzj
000137486 7001_ $$0P:(DE-HGF)0$$avan Vreeswijk, Carl$$b2
000137486 773__ $$0PERI:(DE-600)1498403-9$$a10.1162/NECO_a_00432$$gVol. 25, no. 5, p. 1123 - 1163$$n5$$p1123 - 1163$$tNeural computation$$v25$$x1530-888X$$y2013
000137486 8564_ $$yPublishers version according to licensing conditions.$$zPublished final document.
000137486 8564_ $$uhttps://juser.fz-juelich.de/record/137486/files/FZJ-2013-03923.pdf$$yOpenAccess$$zPublished final document.
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