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Measures of Spike Train Synchrony and Directionality

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Mathematical and Theoretical Neuroscience

Part of the book series: Springer INdAM Series ((SINDAMS,volume 24))

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Abstract

Measures of spike train synchrony have become important tools in both experimental and theoretical neuroscience. Three time-resolved measures called the ISI-distance, the SPIKE-distance, and SPIKE-synchronization have already been successfully applied in many different contexts. These measures are time scale independent, since they consider all time scales as equally important. However, in real data one is typically less interested in the smallest time scales and a more adaptive approach is needed. Therefore, in the first part of this Chapter we describe recently introduced generalizations of the three measures, that gradually disregard differences in smaller time-scales. Besides similarity, another very relevant property of spike trains is the temporal order of spikes. In the second part of this chapter we address this property and describe a very recently proposed algorithm, which quantifies the directionality within a set of spike train. This multivariate approach sorts multiple spike trains from leader to follower and quantifies the consistency of the propagation patterns. Finally, all measures described in this chapter are freely available for download.

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Notes

  1. 1.

    http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/SPIKY.html.

  2. 2.

    http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/cSPIKE.html.

  3. 3.

    http://mariomulansky.github.io/PySpike.

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Acknowledgements

We acknowledge funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. #642563 ‘Complex Oscillatory Systems: Modeling and Analysis’ (COSMOS). T.K. also acknowledges support from the European Commission through Marie Curie Initial Training Network ‘Neural Engineering Transformative Technologies’ (NETT), project 289146. We thank Ralph G. Andrzejak, Nebojsa Bozanic, Kerstin Lenk, Mario Mulansky, and Martin Pofahl for useful discussions.

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Authors and Affiliations

  1. Department of Physics and Astronomy, University of Florence, Sesto Fiorentino, Italy

    Eero Satuvuori & Irene Malvestio

  2. Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

    Eero Satuvuori

  3. Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain

    Irene Malvestio

  4. Institute for Complex Systems, CNR, Sesto Fiorentino, Italy

    Thomas Kreuz

Authors
  1. Eero Satuvuori
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  2. Irene Malvestio
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  3. Thomas Kreuz
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Correspondence to Eero Satuvuori .

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Editors and Affiliations

  1. Environment Science and Policy, University of Milan, Milan, Italy

    Giovanni Naldi

  2. Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy

    Thierry Nieus

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Satuvuori, E., Malvestio, I., Kreuz, T. (2017). Measures of Spike Train Synchrony and Directionality. In: Naldi, G., Nieus, T. (eds) Mathematical and Theoretical Neuroscience. Springer INdAM Series, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-68297-6_13

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