On similarity measures for spike trains

Justin Dauwels, François Vialatte, Theophane Weber, Andrzej Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

24 Citations (Scopus)


A variety of (dis)similarity measures for one-dimensional point processes (e.g., spike trains) are investigated, including the Victor-Purpura distance metric, the van Rossum distance metric, the Schreiber et al. similarity measure, the Hunter-Milton similarity measure, the event synchronization proposed by Quiroga, and the stochastic event synchrony measures (SES) recently proposed by Dauwels et al. By analyzing surrogate data, it is demonstrated that most measures are not able to distinguish timing precision and event reliability, i.e., they depend on both aspects of synchrony. There are two exceptions: with appropriate choice of parameters, event synchronization quantifies event reliability, independently of timing precision; the two SES parameters quantify both timing precision and event reliability separately. Before one can apply the (dis)similarity measures (with the exception of SES), one needs to determine potential lags between the point processes. On the other hand, SES deals with lags in a natural and direct way, and therefore, the SES similarity measures are robust to lags. As an illustration, neuronal spike data generated by the Morris-Lecar neuron model is considered.

Original languageEnglish
Title of host publicationAdvances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers
Number of pages9
EditionPART 1
Publication statusPublished - 2009
Externally publishedYes
Event15th International Conference on Neuro-Information Processing, ICONIP 2008 - Auckland, New Zealand
Duration: 25 Nov 200828 Nov 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5506 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on Neuro-Information Processing, ICONIP 2008
Country/TerritoryNew Zealand


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