Source Code


 

Measuring spike train synchrony I:   SPIKE- and ISI-Distance

Matlab codes to calculate both the SPIKE- and the ISI-distances (as well as their extensions) between two (or more) given spike trains

For a detailed description of the methods please refer to:

Kreuz T, Chicharro D, Greschner M, Andrzejak RG:
Time-resolved and time-scale adaptive measures of spike train synchrony.
J Neurosci Methods 195, 92 (2011) [PDF].

Kreuz T, Chicharro D, Andrzejak RG, Haas JS, Abarbanel HDI:
Measuring multiple spike train synchrony.
J Neurosci Methods 183, 287 (2009) [PDF].

Kreuz T, Haas JS, Morelli A, Abarbanel HDI, Politi A:
Measuring spike train synchrony.
J Neurosci Methods 165, 151 (2007) [PDF].

See also:

Python-Implementation of the pairwise ISI-distance (maintained by Michael Chary)

 

Measuring spike train synchrony II:   Event Synchronization

Matlab code to calculate the event synchronization and the event delay between two given spike trains

For a detailed description of the method please refer to:

Quian Quiroga R, Kreuz T, and Grassberger P:
Event Synchronization: A simple and fast method to measure synchronicity and time delay patterns.
Phys.Rev. E, 66, 041904 (2002) [PDF].

 

Measuring spike train synchrony III:   Directionality

Matlab code to calculate the directionality measure L between two given spike trains (or between two continuous datasets or between a spike train and a continuous dataset)

For a detailed description of the method please refer to:

Andrzejak RG, Kreuz T:
Characterizing unidirectional couplings between point processes and flows.
European Physics Letters 96, 50012 (2011) [PDF].

 

Measuring spike train synchrony IV:   van Rossum distance and multi-neuron extension

Matlab codes to calculate the spike train metric by van Rossum and the multi-neuron extension by Houghton and Sen.

For a detailed description of the method please refer to:

Houghton C, Kreuz T:
On the efficient calculation of van Rossum distances.
Network: Computation in neural systems (in press, 2012) [PDF].

 

Measuring spike train synchrony V:   Victor-Purpura distance and multi-neuron extension

Matlab codes to calculate the spike train metric by Victor-Purpura and the multi-neuron extension by Victor-Purpura-Aronov.

(Homepage of Prof. Jonathan D. Victor, Cornell, NY, USA)

See also: Matlab code for the Victor-Purpura distance which also calculates the percentage of spikes that have been matched by a time shift as well as the average time shift

For a detailed description of the algorithm please refer to:

Chicharro D, Kreuz T, Andrzejak RG:
What can spike train distances tell us about the neural code?
J Neurosci Methods 199, 146 (2011) [PDF].