Skip to main content
  • Poster presentation
  • Open access
  • Published:

Measuring spike train synchrony and reliability

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.

References

  1. Kreuz T, Haas JS, Morelli A, Abarbanel HDI, Politi A: Measuring spike train synchronization. [http://arxiv.org/abs/physics/0701261]

  2. Haas JS, White JA: Frequency selectivity of layer II stellate cells in the medial entorhinal cortex. J Neurophysiol. 2002, 88: 2422-2429. 10.1152/jn.00598.2002.

    Article  PubMed  Google Scholar 

  3. Victor J, Purpura K: Nature and precision of temporal coding in visual cortex: A metric-space analysis. J Neurophysiol. 1996, 76: 1310-

    PubMed  CAS  Google Scholar 

  4. van Rossum MCW: A novel spike distance. Neural Computation. 2001, 13: 751-10.1162/089976601300014321.

    Article  PubMed  CAS  Google Scholar 

  5. Schreiber S, Fellous JM, Whitmer JH, Tiesinga PHE, Sejnowski TJ: A new correlation-based measure of spike timing reliability. Neurocomputing. 2003, 52: 925-

    Article  PubMed  Google Scholar 

  6. Hunter JD, Milton G: Amplitude and frequency dependence of spike timing: implications for dynamic regulation. J Neurophysiol. 2003, 90: 387-10.1152/jn.00074.2003.

    Article  PubMed  Google Scholar 

  7. Quian Quiroga R, Kreuz T, Grassberger P: Event synchronization: A simple and fast method to measure synchronicity and time delay patterns. Phys Rev E. 2002, 66: 041904-10.1103/PhysRevE.66.041904.

    Article  CAS  Google Scholar 

  8. Morelli A, Grotto RL, Arecchi FT: Neural coding for the retrieval of multiple memory patterns. Biosystems. 2006, 86: 100-10.1016/j.biosystems.2006.03.011.

    Article  PubMed  CAS  Google Scholar 

Download references

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

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Kreuz.

Rights and permissions

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.

Reprints and permissions

About this article

Cite this article

Kreuz, T., Haas, J.S., Morelli, A. et al. Measuring spike train synchrony and reliability. BMC Neurosci 8 (Suppl 2), P79 (2007). https://doi.org/10.1186/1471-2202-8-S2-P79

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/1471-2202-8-S2-P79

Keywords