pyspike 0.9.0

Citing PySpike

If you use PySpike in your research, please cite our SoftwareX publication on PySpike:

Mario Mulansky, Thomas Kreuz, PySpike - A Python library for analyzing spike train synchrony, Software X 5, 183 (2016) [pdf]

Additionally, depending on the used methods: ISI-distance [1], SPIKE-distance [2], SPIKE-Synchronization [3], or their adaptive generalizations [4], please cite one or more of the following publications:

Important Changelog

With version 0.8.0, Adaptive and Rate Independent algorithms are supported.

With version 0.7.0, support for Python 2 was dropped, PySpike now officially supports Python 3.7, 3.8, 3.9, 3.10.

With version 0.6.0, the spike directionality and spike train order function have been added.

With version 0.5.0, the interfaces have been unified and the specific functions for multivariate computations have become deprecated.

With version 0.2.0, the SpikeTrain class has been introduced to represent spike trains. This is a breaking change in the function interfaces. Hence, programs written for older versions of PySpike (0.1.x) will not run with newer versions.

Requirements and Installation

PySpike is available at Python Package Index and this is the easiest way to obtain the PySpike package. If you have pip installed, just run

sudo pip install pyspike

to install pyspike. PySpike requires numpy as minimal requirement, as well as a C compiler to generate the binaries.

git clone https://github.com/mariomulansky/PySpike.git
cd PySpike
python setup.py build_ext --inplace

pytest

Examples

The following code loads some exemplary spike trains, computes the dissimilarity profile of the ISI-distance of the first two SpikeTrain objects, and plots it with matplotlib:

import matplotlib.pyplot as plt
import pyspike as spk

spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt",
                                              edges=(0, 4000))
isi_profile = spk.isi_profile(spike_trains[0], spike_trains[1])
x, y = isi_profile.get_plottable_data()
plt.plot(x, y, '--k')
print("ISI distance: %.8f" % isi_profile.avrg())
plt.show()

The following example computes the multivariate ISI-, SPIKE- and SPIKE-Sync-profile for a list of spike trains loaded from a text file:

spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt",
                                              edges=(0, 4000))
avrg_isi_profile = spk.isi_profile(spike_trains)
avrg_spike_profile = spk.spike_profile(spike_trains)
avrg_spike_sync_profile = spk.spike_sync_profile(spike_trains)

More examples with detailed descriptions can be found in the tutorial section.

The work on PySpike was supported by the European Comission through the Marie Curie Initial Training Network Neural Engineering Transformative Technologies (NETT) under the project number 289146.

Python/C Programming:

• Mario Mulansky

• Edmund J Butler

Scientific Methods:

• Thomas Kreuz

• Daniel Chicharro

• Conor Houghton

• Nebojsa Bozanic

• Mario Mulansky