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A lightweight multivariate pattern analysis (MVPA) toolbox in Matlab

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CoSMoMVPA

A lightweight multi-variate pattern analysis (MVPA) toolbox in Matlab

Features

  • Matlab implementations of the most common types of Multi-Variate Pattern Analysis (MVPA) of functional magnetic resonance imaging (fMRI) data, including correlation analysis, classifiers, partitioning, cross-validation, representational similarity analysis, searchlights
  • Includes a variety of example scripts that show implementations of common MVP analyses.
  • Comes with extended documentation and a variety of exercises showing how parts of common MVPA functions can be implemented.
  • Free/Open Source Software (MIT License).

Note: CoSMoMVPA is currently in a pre-first-release state. Code, features and documentation may change rapidly.

Requirements

A working installation of Matlab.

History

The CoSMoMVPA project was started as preparation for the 2013 CoSMO workshop in Kingston, Ontario, Canada.

Documentation

Documentation is hosted online (TODO).

For developers; building the documentation is currently only supported on Unix-like operating systems. To build the matlab output from the /mvpa/run*.m files, run the cosmo_publish_run_scripts script. To build the documentation in /doc, run ./build.sh html.

Installation instructions

The toolbox is avalaible from github. Either clone the repository using git, or download and unzip the zip archive. In Matlab, add the /mvpa and /externals folders (and their subfolders) to your path.

To use the example data, download the dataset archive (TODO) and put it in /data/.

Getting started

Please the documentation in /doc. To get an idea of the functionality of the toolbox, first download the example data, then have a look at the mvpa/run* files.

Developers

CoSMoMVPA is developed by:

Contact information is presented on our webpages.

Contribution guidelines

The preferred way to contribute is through github. More information will be added later.

Acknowledgements

  • Gunnar Blohm and Sara Fabri: for the invitation to speak at the CoSMo 2013 workshop. This invitation formed the basis of this toolbox.
  • Michael Hanke and Yaroslav Halchenko: for their work on PyMVPA, which inspired the semantics and data structure of datasets in CoSMoMVPA.

License

The CoSMoMVPA Matlab code is available under the MIT License; documentation is available under the Creative Commons Attribution-ShareAlike 3.0 Unported license. . See the LICENSE file for details. For licenses of external toolboxes, see the respective license files under _/externals/.

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