Dear all,
may I kindly draw your attention to our paper on the new SPIKE-distance which has just appeared in the Journal of Neurophysiology (Section 'Innovative methodology'). This improved method opens up several novel possibilities in spike train analysis. Among others, it allows to estimate spike train synchrony online and in real-time.
Monitoring spike train synchrony
Kreuz T, Chicharro D, Houghton C, Andrzejak RG, Mormann F
Abstract: Recently, the SPIKE-distance has been proposed as a parameter-free and time-scale 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 event-like firing patterns. Here we present a substantial improvement of this measure which 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.
The paper is accessible on the webpage of the Journal of Neurophysiology:
A preprint can also be found on the arXiv (with permission):
On my webpage you can find improved Matlab source codes (including documentation):
The updated version uses MEX- instead of m-files for the most time-consuming calculations. This reduces the computational cost considerably (on my notebook the code running all the examples below was faster by a factor of 85). It also uses a new output-structure 'results' which allows easy access not only to the overall dissimilarity value but also to the measure profiles and the pairwise distance matrices for all the selected measures.
The source codes include a file "Distances_Main_Demo" which reproduces the figures 1-9 and the movie from the paper. To provide a better illustration of what is done the parameter settings for each figure are detailed on the webpage.
On the same webpage there are also two movies (in both avi and wmv format) which demonstrate the new method best. The first one is described in Fig. 9 of the paper, the second one extends the analysis performed in Fig. 7D-F.
Finally, a short review on the SPIKE-distance can be found on Scholarpedia:
Any feedback is very welcome!
Best regards,
Thomas Kreuz
Institute for complex systems, CNR
Via Madonna del Piano 10
50119 Sesto Fiorentino (Italy)
Tel: +39-349-0748506
Email: thomas.kreuz@cnr.it
Webpage: http://www.fi.isc.cnr.it/users/thomas.kreuz/
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