Hi Steve,
I did turn off the HRF convolution in the FEAT run. I also did not use
derivatives, and no low pass filter. Also, I tried the FEAT with and
without the high pass filter, and got the same worrisome results.
One thought: the timecourse of the seed region was generated with Featquery
from a resting state scan, so there was no meaningful PEs etc in the
design, just a "dummy" one. All I did is extract the mean_mask_ts.txt.
Would that make a difference for how the timecourse is calculated?
Dost
On Mon, 4 Feb 2008 13:34:17 +0000, Steve Smith <[log in to unmask]> wrote:
>Hi Dost,
>
>If you're putting a seed voxel's timecourse back in as a regressor of
>the same data, you should definitely see that voxel (and probably
>neighbouring ones) as highly 'activated' - so it does sound like
>there's a problem here. Is it possible that you forgot to turn off the
>HRF convolution for the final FEAT run? The voxel-extracted timecourse
>already contains the HRF convolution.
>
>Cheers.
>
>
>On 1 Feb 2008, at 19:44, Dost Ongur wrote:
>
>> We have recently started to perform whole brain signal correlations,
>> to test
>> hypotheses about resting state circuits based on our ICA. Our first
>> such
>> test used the LMFG portion of area 46 as the seed ROI, and we
>> noticed that
>> neither patients nor controls yielded significantly correlated
>> voxels in
>> left sided area 46 itself. Does FEAT know to exclude the seed ROI
>> in some
>> fashion, or are we simply looking at poor auto-correlation within
>> the ROI?
>>
>
>
>---------------------------------------------------------------------------
>Stephen M. Smith, Professor of Biomedical Engineering
>Associate Director, Oxford University FMRIB Centre
>
>FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
>+44 (0) 1865 222726 (fax 222717)
>[log in to unmask] http://www.fmrib.ox.ac.uk/~steve
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