[Comp-neuro] Vastly improved spike train distance (incl. Matlab source codes & movies)

Thomas Kreuz thomaskreuz at yahoo.de
Mon Jan 14 04:20:43 CET 2013

Dear all,
may I kindly draw your attention to our paper on the new SPIKE-distance. 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)
The paper is soon to appear in the Journal of Neurophysiology:
A preprint has also been uploaded on the arXiv (with permission): 

On my webpage you can find the Matlab source codes (including documentation):
These source codes include a file “Distances_Main_Demo” which reproduces the figures 1-9 and a supplementary movie
(see below) from the paper. To provide a better illustration of what is done, the parameter settings for each figure are detailed on the
[Note that we are in the process of programming a graphical
user interface which should be finished in a week or two.]
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.
Any feedback (on both the paper and the source codes) is
very welcome!
Finally, a shorter review on the SPIKE-distance can be
found on Scholarpedia:
Kreuz T
Scholarpedia 7(12), 30652 (2012).
With this article I am taking part in the competition for
Brain Corporation Prize in Computational Neuroscience
which basically gives prizes to the three articles that have
received the most Google +1 votes by January 31. So if this is of interest to
you and you have a Google account could you please vote for me. In the top
right corner of the article (“SPIKE-distance”)
you will see the Google +1 button.
Thank you very much for your support!
Best regards,
Thomas Kreuz
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