Hi all,
I have a naive question about some of the preprocessing steps in PyMVPA.
I am loading in my data and detrending as follows (similar to some
examples listed):
##Load Data##
dataset = NiftiDataset((wb_file),
labels=attr.labels,
chunks=attr.chunks,
mask=os.path.join(roidir,'wb.nii.gz'))
##Detrend Data##
detrend(dataset, perchunk=True, model='linear')
zscore(dataset, targetdtype='float32')
I have two types of trials (A and B from the labels).
If I plot the average voxel value of A trials versus B trials, I get a
perfectly negatively correlated line.
In other words, if mean(sample voxel on A trials) = .5, then
mean(sample voxel on B trials) = -.5. This is true for all voxels.
I have looked over miscfx.py, but I thought would send an email to see
if (1) this is what "should happen" and (2) if so, what the idea is
for making such a split before running a classifier.
Best,
John
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