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Measuring spike train synchrony and reliability

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Estimating the degree of synchrony or reliability between two or more spike trains is a frequent task in both experimental and computational neuroscience. In recent years, many different methods have been proposed that typically compare the timing of spikes on a certain time scale to be fixed beforehand. In this study [1], we propose the ISI-distance, a simple complementary approach that extracts information from the interspike intervals by evaluating the ratio of the instantaneous frequencies. The method is parameter free, time scale independent and easy to visualize as illustrated by an application to real neuronal spike trains obtained in vitro from rat slices (cf. [2]). We compare the method with six existing approaches (two spike train metrics [3, 4], a correlation measure [2, 5], a similarity measure [6], and event synchronization [7]) using spike trains extracted from a simulated Hindemarsh-Rose network [8]. In this comparison the ISI-distance performs as well as the best time-scale-optimized measure based on spike timing, without requiring an externally determined time scale for interaction or comparison.

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Acknowledgements

TK has been supported by the Marie Curie Individual Intra-European Fellowship "DEAN", project No 011434. JSH acknowledges financial support by the San Diego Foundation.

Author information

Correspondence to Thomas Kreuz.

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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Kreuz, T., Haas, J.S., Morelli, A. et al. Measuring spike train synchrony and reliability. BMC Neurosci 8, P79 (2007) doi:10.1186/1471-2202-8-S2-P79

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Keywords

  • Animal Model
  • Similarity Measure
  • Spike Train
  • Instantaneous Frequency
  • Complementary Approach