[pymvpa] question about detrend and zscore

[John Clithero]

Hi,

On Tue, Oct 6, 2009 at 4:39 PM, Yaroslav Halchenko
<debian at onerussian.com> wrote:
> On Tue, 06 Oct 2009, John Clithero wrote:
>> The 'wb_file' is func data with the relevant timepoints... it has had
>> some preprocessing done in FSL (motion correction, slice timing, brain
>> extraction). The ROI mask is a whole brain mask. It seems (I hope)
>> that the NiftiDataset is being put together correctly.
> wild guess - may be while doing FSL preprocessing you've done some
> intensity normalization?
I don't think this would be it....but here (sorry if I didn't list
them) are the preprocessing steps done in FSL
(1) brain extraction
(2) motion correction
(3) slice-timing correction
(4) high-pass filtering


>
>
>> This perfect negative correlation occurs even if I feed in arbitrary
>> labels to the NiftiDataset, so there must be some sort of error in how
>> I'm using detrend and/or score?? I am guessing this is my erros since
>> the raw feature data looks fine to me.
>
>> This perfect negative correlation also occurs after just implementing
>> "zscore" or "detrend", although obviously the values are different.
> so, they aren't present in just loaded dataset but if you do zscore or
> detrend -- they come?

If I break data in half (A trials vs B trials, or random) before using
zscore or detrend, I generally see strong positive correlation (some
voxels are just more active than others across the experiment...this
makes sense).  But, once I use zscore or detrend....then goes to
perfect negative correlation (when looking at meanA vs meanB).
Each voxel after zscore, as it was said early, will have a mean of
zero across all trials...this is true for all the voxels.

>
> could you just plot 1 voxel (which later carries perfect correlation)
> before/after detrend?

Attached are two example voxels. Left side is before, right side is
after. As you can see, we had 5 runs per subject.
Thanks for the help!

Best,
John

>
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