Journal
JOURNAL OF NEUROPHYSIOLOGY
Volume 109, Issue 5, Pages 1457-1472Publisher
AMER PHYSIOLOGICAL SOC
DOI: 10.1152/jn.00873.2012
Keywords
data analysis; synchronization; spike trains; clustering; SPIKE-distance
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Funding
- European Commission through the Marie Curie Initial Training Network Neural Engineering Transformative Technologies (NETT) [289146]
- Italian Ministry of Foreign Affairs regarding the activity of the Joint Italian-Israeli Laboratory on Neuroscience
- James S McDonnell Foundation
- Spanish Ministry of Education and Science [FIS-2010-18204]
- Lichtenberg Program of the Volkswagen Foundation
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Kreuz T, Chicharro D, Houghton C, Andrzejak RG, Mormann F. Monitoring spike train synchrony. J Neurophysiol 109: 1457-1472, 2013. First published December 5, 2012; doi:10.1152/jn.00873.2012.-Recently, the SPIKE-distance has been proposed as a parameter-free and timescale-independent measure of spike train synchrony. This measure is time resolved since it relies on instantaneous estimates of spike train dissimilarity. However, its original definition led to spuriously high instantaneous values for eventlike firing patterns. Here we present a substantial improvement of this measure that eliminates this shortcoming. The reliability gained allows us to track changes in instantaneous clustering, i.e., time-localized patterns of (dis)similarity among multiple spike trains. Additional new features include selective and triggered temporal averaging as well as the instantaneous comparison of spike train groups. In a second step, a causal SPIKE-distance is defined such that the instantaneous values of dissimilarity rely on past information only so that time-resolved spike train synchrony can be estimated in real time. We demonstrate that these methods are capable of extracting valuable information from field data by monitoring the synchrony between neuronal spike trains during an epileptic seizure. Finally, the applicability of both the regular and the real-time SPIKE-distance to continuous data is illustrated on model electroencephalographic (EEG) recordings.
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