| Multivariate Pattern Analysis in Python

### Navigation

- index
- ExpPsy Project |
- NeuroDebian Project |
- PyMVPA 0.4.x Home |
- PyMVPA Home |
- Documentation »

This content refers to the previous stable release of PyMVPA. Please visit www.pymvpa.org for the most recent version of PyMVPA and its documentation.

# Basic (f)MRI plotting

Estimate basic univariate sensitivity (ANOVA) an plot it overlayed on top of the anatomical.

We start with basic steps: loading PyMVPA and the example fMRI dataset, basic preprocessing, estimation of the ANOVA scores and plotting.

    from mvpa.suite import *

    # load PyMVPA example dataset
    attr = SampleAttributes(os.path.join(pymvpa_dataroot, 'attributes_literal.txt'))
    dataset = NiftiDataset(samples=os.path.join(pymvpa_dataroot, 'bold.nii.gz'),
                           labels=attr.labels,
                           labels_map=True,
                           chunks=attr.chunks,
                           mask=os.path.join(pymvpa_dataroot, 'mask.nii.gz'))

    # since we don't have a proper anatomical -- lets overlay on BOLD
    nianat = NiftiImage(dataset.O[0], header=dataset.niftihdr)

    # do chunkswise linear detrending on dataset
    detrend(dataset, perchunk=True, model='linear')

    # define sensitivity analyzer
    sensana = OneWayAnova(transformer=N.abs)
    sens = sensana(dataset)

It might be convinient to pre-define common arguments for multiple calls to plotMRI

::
  mri_args = {

    > ‘background’ : nianat, # could be a filename ‘background_mask’ : os.path.join(pymvpa_dataroot, ‘mask.nii.gz’), ‘overlay_mask’ : os.path.join(pymvpa_dataroot, ‘mask.nii.gz’), ‘do_stretch_colors’ : False, ‘cmap_bg’ : ‘gray’, ‘cmap_overlay’ : ‘autumn’, # YlOrRd_r # P.cm.autumn ‘fig’ : None, # create new figure

    ‘interactive’ : cfg.getboolean(‘examples’, ‘interactive’, True),
      }
  fig = plotMRI(overlay=dataset.map2Nifti(sens),
    vlim=(0.5, None), #vlim_type=”symneg_z”, **mri_args)

Output of the example analysis:

See also

The full source code of this example is included in the PyMVPA source distribution (doc/examples/mri_plot.py).

### Navigation

- index
- ExpPsy Project |
- NeuroDebian Project |
- PyMVPA 0.4.x Home |
- PyMVPA Home |
- Documentation »