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This article is part of the supplement: Twentieth Annual Computational Neuroscience Meeting: CNS*2011

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Finding the event structure of neuronal spike trains

Vincent J Toups1, Jean-Marc Fellous2, Peter J Thomas34, Terrence J Sejnowski56 and Paul H Tiesinga17*

Author Affiliations

1 Department of Physics & Astronomy, University of North Carolina, Chapel Hill, NC 27599, USA

2 Psychology Department, University of Arizona, Tucson, AZ 85721, USA

3 Departments of Mathematics, Biology and Cognitive Science, Case Western Reserve University, Cleveland, OH 44106, USA

4 Department of Neuroscience, Oberlin College, Oberlin, OH 44074, USA

5 Howard Hughes Medical Institute, The Salk Institute, La Jolla, CA 92037, USA

6 Division of Biological Sciences, University of California San Diego, La Jolla, CA 92037, USA

7 Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, 6525 AJ, The Netherlands

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BMC Neuroscience 2011, 12(Suppl 1):P333  doi:10.1186/1471-2202-12-S1-P333

The electronic version of this article is the complete one and can be found online at:

Published:18 July 2011

© 2011 Toups et al; licensee BioMed Central Ltd.

This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

Neurons in sensory systems convey information about physical stimuli in their spike trains. In vitro, single neurons respond precisely and reliably to the repeated injection of the same fluctuating current, producing regions of elevated firing rate, termed events. Analysis of these spike trains reveals that multiple distinct spike patterns can be identified as trial-to-trial correlations between spike times [1]. Finding events in data with realistic spiking statistics is challenging because events belonging to different spike patterns may overlap. We propose a method for finding spiking events that uses contextual information to disambiguate which pattern a trial belongs to. The procedure can be applied to spike trains of the same neuron across multiple trials to detect and separate responses obtained during different brain states. The procedure can also be applied to spike trains from multiple simultaneously recorded neurons in order to identify volleys of near synchronous activity or to distinguish between excitatory and inhibitory neurons. The procedure was tested using artificial data as well as recordings in vitro in response to fluctuating current waveforms.


This research was supported in part by the National Institutes of Health (R01-MH68481); the Human Frontier Science Program (JVT & PHT); the National Science Foundation (DMS-0720142) (PJT), and the Howard Hughes Medical Institute (TJS). PJT acknowledges research support from the Oberlin College Library.


  1. Fellous JM, Tiesinga PHE, Thomas PJ, Sejnowski TJ: Discovering Spike Patterns in Neuronal Responses.

    Journal of Neurosci 2004, 24:2989-3001. Publisher Full Text OpenURL