Title
Finding the event structure of neuronal spike trains.
Abstract
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 (Fellous, Tiesinga, Thomas, & Sejnowski, 2004 ). 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.
Year
DOI
Venue
2011
10.1162/NECO_a_00173
Neural computation
Keywords
Field
DocType
bioinformatics,biomedical research
Contextual information,Neuroscience,Computer science,Excitatory postsynaptic potential,Inhibitory postsynaptic potential,Stimulus (physiology),Sensory system,Neuron,Event structure
Journal
Volume
Issue
ISSN
23
9
1530-888X
Citations 
PageRank 
References 
4
0.43
8
Authors
5
Name
Order
Citations
PageRank
J. Vincent Toups140.43
Jean-marc Fellous21157167.09
Peter J. Thomas313341.24
Terrence J. Sejnowski482782135.10
Paul H. E. Tiesinga540.43