Using CoSMoMVPA effectively requires:
- a working installation of Matlab or Octave.
- the CoSMoMVPA source code, available from GitHub; see here for instructions to get you environment ready.
- optionally the tutorial data, available here (to run the exercises).
- optionally some external toolboxes for AFNI, BrainVoyager, and/or FieldTrip file support; see here.
- an advanced beginner level of experience in Matlab programming.
- an advanced beginner level of fMRI or MEEG data analysis.
- a basic understanding of MVPA concepts.
- familiarity with CoSMoMVPA concepts, in particular the Dataset, Targets, Chunks, Dataset operations, Classifier, Neighborhood, and Measure concepts.
Get your environment ready¶
CoSMoMVPA Matlab / Octave code:
- fMRI AK6 and MEEG obj-6 data (for PRNI 2016 exercises): tutorial data with fMRI AK6 and MEEG obj6 data only
- A minimal set of data (only fMRI AK6 data for exercises): tutorial data with AK6 data only
- MEEG data (only obj-6 data for exercises): tutorial data with MEEG obj6 data only
Once you are ready:
- run the demos.
- look at the runnable examples and the associated Matlab outputs.
- try the exercises.
- explore the CoSMoMVPA functions.
Some examples of analyses that can be run with CoSMoMVPA: