Title:	Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events
Authors:	Shahi, Mina van Vreeswijk, Carl Pipa, Gordon
Abstract:	Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.
Citations:	Frontiers in Computational Neuroscience, Vol. 10, Article 139, 2016, S. 1-14
URL:	https://osnadocs.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2017021315530
Subject Keywords:	renewal process; Poisson process; synchrony; ISI; joint spike events; coincidence distribution
Issue Date:	13-Feb-2017
License name:	Namensnennung 4.0 International
License url:	http://creativecommons.org/licenses/by/4.0/
Type of publication:	Einzelbeitrag in einer wissenschaftlichen Zeitschrift [article]
Appears in Collections:	FB08 - Hochschulschriften Open-Access-Publikationsfonds

This item is licensed under a Creative Commons License