Progress in Neuroscience is to a large extent limited by the fact that results are hard to replicate. For example we can come up with a million different spike-sorting algorithms but this is not useful unless we can compare them with the same data sets.

Our policy is to share our codes (hoping they will be useful to other researchers as they are to ourselves) and some of our data (for example, all the simulations we used to test our clustering).

All the following codes and data are given for free. The only thing we ask in return is that you cite the original reference if you use them.


Unsupervised spike detection and sorting of extracellular multiunit recordings. It uses wavelets and Super-paramagnetic clustering. The code is described in:
Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering (zip).



Realistic simulation of extracellular recordings using detailed neuron models

neurocube web










Supplementary Material

A previous software for realistic simulations of extracellular recordings (Martinez et al., J Neurosci Methods, 2009)


Automatic Denoising of single-trial evoked potentials from the background EEG. It is based on wavelet multi-resolution decomposition. The code is described in:

Automatic Denoising of Single-Trial Evoked Potentials

Codes, Tutorial, and Sample Data




A method for extracting information from time patterns using wavelets and information theory. Given a raster of spike trains, WI estimates the information in the spike timing (compared to total spike counts), denoise the spike trains and estimate correlations between neurons. You can dowload the codes and exemplar data (, the help file (tutorial.PDF) and the original reference below.

Visit the WI dedicated page for downloads.


WI screen shot


Calculates the cross-correlation, and non-linear interdependence of bivariate signals.

This program was used in the paper:
Performance of different synchronization measures in real data: a case study on EEG signals.

and with coupled dynamical systems in:
Learning driver-response relationships from synchronization patterns.



Given a 1-column input ascii file, calculates its Windowed Fourier Transform and then calculates the power spectra and the Shannon and Kulback-Leibler (relative) entropies. It also calculates the relative band intensity ratio (RIR).

Download file: spect.m

This software was used for calculating the RIR in:
Searching for Hidden Information with Gabor Transform in Generalized Tonic-Clonic Seizures.

The Windowed Fourier transform in:
Frequency evolution during tonic-clonic seizures.

The Shannon and Kulback-Leibler entropies in:
Kullback-Leibler and Renormalized Entropy: Applications to EEGs of Epilepsy Patients.

Share this page: