incf-nidash / nidmresults-fsl

A python library to export FSL's feat results to NIDM-Results
http://nidm.nidash.org/specs/nidm-results.html
MIT License
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Support "Voxelwise confound list" #111

Open cmaumet opened 7 years ago

cmaumet commented 7 years ago

screen shot 2017-02-06 at 13 47 43

"PNM is a tool used in conjunction with the GLM (via FEAT) that can be used to model (or "regress out") the effects of physiological noise in functional MRI data. That is, it creates EVs (regressors) that can be used to model the physiological noise within the GLM, alongside other stimulus-related regressors." (Excerpt from the "Physiological Noise Modelling" (PNM) manual)

We need to determine how many evs are created and add them to the list of regressor names.

cmaumet commented 7 years ago

We could do this by using @pauldmccarthy's fsl.data.featdesign (part of fslpy).

cmaumet commented 7 years ago
designfsf = featanalysis.loadSettings('MY_PATH/nidmresults-examples/fsl_gamma_basis/')
designmat = featdesign.FEATFSFDesign('MY_PATH/fsl_gamma_basis/', designfsf)
evs = designmat.getEVs()
evs[0].title