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 <http://jn.physiology.org/content/113/9/3432> 113, 3432 (2015) [PDF] <http://www.fi.isc.cnr.it/users/thomas.kreuz/images/Kreuz_JNeurophysiol_2015_SPIKY.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] <http://arxiv.org/pdf/1502.02027v2.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 -- 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/