A multi-modal, multi-variate pattern analysis (MVPA) toolbox in Matlab / GNU Octave for cognitive neuroscientists.


  • State-of-the art, yet simple to use MVPA implementations.
  • Runs on the Matlab and GNU Octave platform, on MS Windows, OSX, and GNU/Linux.
  • Handles fMRI volumetric, fMRI surface-based, and MEEG data through a uniform data structure.
  • Support for a wide range of data formats.
  • Searchlights in the volume, on the surface, over sensors, time bins, and frequency bands.
  • Multiple-comparison correction using Threshold-Free Cluster Enhancement Monte Carlo simulations.
  • Extensive documentation, including a variety of runnable scripts and implementation exercises (with solutions).
  • Is Free/Open Source Software (MIT License), see http://github.com/CoSMoMVPA/CoSMoMVPA.
_images/icon_demos.png _images/icon_philosophy.png _images/icon_get_started.png _images/icon_download.png _images/icon_modules.png _images/icon_documentation.png _images/icon_exercises.png _images/icon_tips.png _images/icon_faq.png _images/icon_contact.png _images/icon_develop.png _images/icon_thanks.png


  • our CoSMoMVPA manuscript has been published ([OCH16]): Oosterhof, N. N., Connolly, A. C., and Haxby, J. V. (2016). CoSMoMVPA: multi-modal multivariate pattern analysis of neuroimaging data in Matlab / GNU Octave. Frontiers in Neuroinformatics, doi:10.3389/fninf.2016.00027.

Changes since last month


[EXC]    1 exercise-related changes
[SML]    1 minor changes

All changes

commit 85c54dbc6198a9aba5796f7f9560ce5d090ed16b
Author: Nikolaas N. Oosterhof <n.n.oosterhof@googlemail.com>
Date:   Mon Dec 31 12:15:51 2018 +0100

    SML+EXC: fix typo to link

 doc/source/ex_rsa_tutorial.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)