Measuring spike train synchrony

Year: 2007

Authors: Kreuz T., Haas J.S., Morelli A., Abarbanel H.D.I., Politi A.

Autors Affiliation: R, Ist Sistemi Complessi, Sesto Fiorentino, Italy; Univ Calif San Diego, Inst Nonlinear Sci, San Diego, CA 92103 USA; Ist Nazl Ott Applicata, Florence, Italy; Univ Calif San Diego, Dept Phys, San Diego, CA 92103 USA; Univ Calif San Diego, Scripps Inst Oceanog, Marine Phys Lab, San Diego, CA 92103 USA.

Abstract: 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 optimized by the analyst. Here, we propose the ISI-distance, a simple complementary approach that extracts information from the interspike intervals by evaluating the ratio of the instantaneous firing rates. 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. In a comparison with existing approaches on spike trains extracted from a simulated Hindemarsh-Rose network, the ISI-distance performs as well as the best time-scale-optimized measure based on spike timing. (c) 2007 Elsevier B.V. All rights reserved.

Journal/Review: JOURNAL OF NEUROSCIENCE METHODS

Volume: 165 (1)      Pages from: 151  to: 161

More Information: We thank S. Luccioli, A. Torcini and K. Ulbrich for useful discussions and P. Grassberger for carefully reading this manuscript. 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.
KeyWords: time series analysis; spike trains; event synchronization; reliability clustering; neuronal coding
DOI: 10.1016/j.jneumeth.2007.05.031

ImpactFactor: 1.884
Citations: 161
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