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Review
. 2005 Oct;15(5):585-92.
doi: 10.1016/j.conb.2005.08.002.

Spike train metrics

Jonathan D Victor  1
Affiliations
Review

Spike train metrics

Jonathan D Victor. Curr Opin Neurobiol. 2005 Oct.

Abstract

Quantifying similarity and dissimilarity of spike trains is an important requisite for understanding neural codes. Spike metrics constitute a class of approaches to this problem. In contrast to most signal-processing methods, spike metrics operate on time series of all-or-none events, and are, thus, particularly appropriate for extracellularly recorded neural signals. The spike metric approach can be extended to multineuronal recordings, mitigating the 'curse of dimensionality' typically associated with analyses of multivariate data. Spike metrics have been usefully applied to the analysis of neural coding in a variety of systems, including vision, audition, olfaction, taste and electric sense.

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Figures

Figure 1
Figure 1
A diagram of a sequence of elementary steps that transforms spike train A into spike train B. Each rectangle represents one spike, and the line that they rest on denotes time. Each elementary step is one of three types: deletion of a spike (deleted spike shown in red), insertion of a spike (inserted spike shown in green), or shifting a spike in time (blue arrows).
See this image and copyright information in PMC

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