Fast Metric Space Analysis for Multineuronal Responses

Fast algorithm for the metric-space analysis of simultaneous responses of multiple single neurons

D. Aronov

Journal of Neuroscience Methods 124, 175-179 (2003)


Spike train metrics quantify the notion of dissimilarity, or distance, between spike trains and between multineuronal responses (Victor and Purpura 1996, 1997). We present a new algorithm for the implementation of a metric based on the timing of individual spikes and on their neurons of origin. This algorithm surpasses the earlier approach in speed by a factor that grows exponentially with the number of neurons, substantially extending the applicability of metric-space methods to the study of coding in larger neuronal populations.

Related paper: analysis of coding of spatial phase in V1
Related paper: demonstration that these metrics are intrinsically non-Euclidean
Related paper: generalizing and parallelizing the algorithm
Related publication: overview of the Spike Train Analysis Toolkit
Download the Spike Train Analysis Toolkit
Background on spike metrics
Code to carry out this algorithm
Download manuscript as pdf courtesy Science Direct
Download related article ("Case Study") from Cornell Theory Center
A primer on metric space analysis of spike trains
Metric space analysis of single-neuron responses
Publications related to temporal coding
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