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| author | Mario Mulansky <mario.mulansky@gmx.net> | 2014-10-13 15:44:09 +0200 |
|---|---|---|
| committer | Mario Mulansky <mario.mulansky@gmx.net> | 2014-10-13 15:44:09 +0200 |
| commit | cb3c4dc6b023c309f21b832ccc5616a22083586d (patch) | |
| tree | ac9224c172efb080b4d849870b1362732e02158d | |
| parent | e827249fecb88ad5835201a9fb2a975bf7476a41 (diff) | |
separate scholarpedia links, scientific references
| -rw-r--r-- | Readme.md | 6 |
1 files changed, 5 insertions, 1 deletions
@@ -1,12 +1,16 @@ # PySpike
PySpike is a Python library for the numerical analysis of spike train similarity.
-Its core functionality is the implementation of the bivariate [ISI and SPIKE distance](http://www.scholarpedia.org/article/Measures_of_spike_train_synchrony).
+Its core functionality is the implementation of the bivariate [ISI](http://www.scholarpedia.org/article/Measures_of_spike_train_synchrony#ISI-distance) [1] and [SPIKE](http://www.scholarpedia.org/article/SPIKE-distance) [2] distance.
Additionally, it provides functions to compute multi-variate SPIKE and ISI distances, as well as averaging and general spike train processing.
All computation intensive parts are implemented in C via [cython](http://www.cython.org) to reach a competitive performance (factor 100-200 over plain Python).
All source codes are published under the [BSD License](http://opensource.org/licenses/BSD-2-Clause).
+>[1] Kreuz T, Haas JS, Morelli A, Abarbanel HDI, Politi A, *Measuring spike train synchrony.* J Neurosci Methods 165, 151 (2007)
+
+>[2] Kreuz T, Chicharro D, Houghton C, Andrzejak RG, Mormann F, *Monitoring spike train synchrony.* J Neurophysiol 109, 1457 (2013)
+
## Requirements and Installation
To use PySpike you need Python installed with the following additional packages:
|