Dear all,

we would like to draw your attention to our two most recent papers and to two new software packages.

1. Two new papers:

This paper provides a detailed description of SPIKY (see 2.) and introduces our new measure SPIKE-synchronization:

•    Kreuz T, Mulansky M, Bozanic N:
     SPIKY: A graphical user interface for monitoring spike train synchrony.
     JNeurophysiol 113, 3432 (2015) [PDF]. 


An overview of all three of our measures (ISI-distance, SPIKE-distance and SPIKE-synchronization) and their mathematical properties can be found in

•    Mulansky M, Bozanic N, Sburlea A, Kreuz T:

     A guide to time-resolved and parameter-free measures of spike train synchrony.

     IEEE Proceedings (in press) and arXiv [PDF] (2015).


2. SPIKY, graphical user interface (Matlab) for monitoring spike train synchrony

Implementations of ISI-distance, SPIKE-distance, and SPIKE-Synchronization
Distances, time profiles, distance matrices, selective averaging, triggered averages, dendrograms, etc.
Plotting, movie generation
Spike train generator, event detector (for continuous data such as EEG)
Matlab with C backend (MEX)
Matlab fallback if no MEX-compiler is not available
Extensive documentation includes many illustrative movies

Matlab source codes and all relevant papers are available on our

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

For further information about new features and updates please check the

SPIKY Facebook page           https://www.facebook.com/SPIKYgui

Here you'll also find a lot of documentation including many images and movies that illustrate how to use SPIKY. All of these movies can also be found on the

SPIKY Youtube channel         https://www.youtube.com/user/SPIKYgui1


3. PySpike, open source Python library hosted on github

Implementations of ISI-distance, SPIKE-distance, and SPIKE-Synchronization
Library of functions to compute distances and profiles (bivariate and multivariate),
distance matrices, selective averages, etc.
Helper functions for plotting, spike train generation
Cython backend for optimal performance (factor 100-200 over plain Python)

Python fallback if Cython is not available

Extensive unit-tests that cover the API as well as the numerics

Automatic build and test runs
Documentation

The github issues system can be used to file bug reports or request new functionality and features.

PySpike webpage         http://www.pyspike.de

PySpike github page    https://github.com/mariomulansky/PySpike

Any feedback on both the papers and the software packages is very welcome.

Best wishes,
Thomas Kreuz


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