Kambiz wrote:
> Rik
> Thanks for the response. I am not sure exactly what you mean by
> comment 1. This is a repeated measures design, and if I understand you
> correct, I should add subject as a random effect to the design matrix.
> How does one do that in the SPM environment?
Please search the archives and/or look at the manual - there should be
several explanations (I don't use the GUI much myself, so am not best to
ask).
R
>
> NB Vladimir I don't believe I have the most up to date version of the
> program. Thanks.
>
> -K.
>
> On Wed, Jan 13, 2010 at 10:52 AM, Rik Henson
> <[log in to unmask] <mailto:[log in to unmask]>>
> wrote:
>
>
> Kambiz -
>
> I haven't considered your parameters in detail, but just note:
>
> 1. If this is a repeated-measures design, you may get more
> significant results after removing between-subject variance by
> adding subject effects to your design matrix.
>
> 2. Changing the smoothness in time may have a small effect, but
> probably not much. RFT takes into account the smoothness, so
> greater smoothing than you already have (which is plenty for RFT
> relative to voxel size) will not help correction per se, but only
> improve stats if the signal is smoother (and the noise not; match
> filter theorem).
>
> 3. Reducing the epoch length will reduce the multiple comparison
> problem. However, if you truly have a priori predictions for
> timing, you could also use a SVC on existing epochs based on a
> smaller time window (rather than correcting for whole scalp-time
> image).
>
> R
>
>
> Kambiz Tavabi wrote:
>
> Dear Forum,
>
> In trying to understand the results out put for a 2x2x2 MEEG
> ANOVA. I fail
> to understand how the number of voxels is derived. Data was
> acquired at 1KHz
> no filtering, downsampled to 600 Hz, epochs of 676 samples
> (200 ms baseline)
> were filtered with a 1.5 Hz high-pass. The data was then
> baseline corrected
> and scanned for artifacts using peak-to-peak algorithm with an
> amplitude
> threshold of 3.5 pT, the data was averaged and converted to
> images by
> interpolating to 64x64 image size. Images were smoothed using
> a (6,6,5)
> kernel. We assume that the number of voxels in the results
> (see attached
> PDF) is derived by 64x64x676?
> Application of FWE or a conservative P value (<0.01) results
> in nothing, and
> thresholding 0.01<p<0.05 results in everything significant.
> Any advise to
> find a sensible middle ground in the results would be
> appreciated. We plan
> to use a (6,6,7) kernel. But to improve the situation is it
> advisable to
> reduce the number of corrections by smoothing to a smaller
> image, or using a
> smaller epoch size?
>
> Thanks
>
>
>
> --
>
> -------------------------------------------------------
> Dr Richard Henson
> MRC Cognition & Brain Sciences Unit
> 15 Chaucer Road
> Cambridge
> CB2 7EF, UK
>
> Office: +44 (0)1223 355 294 x522
> Mob: +44 (0)794 1377 345
> Fax: +44 (0)1223 359 062
>
> http://www.mrc-cbu.cam.ac.uk/people/rik.henson/personal
> -------------------------------------------------------
>
>
>
>
>
> --
> Kambiz
--
-------------------------------------------------------
Dr Richard Henson
MRC Cognition & Brain Sciences Unit
15 Chaucer Road
Cambridge
CB2 7EF, UK
Office: +44 (0)1223 355 294 x522
Mob: +44 (0)794 1377 345
Fax: +44 (0)1223 359 062
http://www.mrc-cbu.cam.ac.uk/people/rik.henson/personal
-------------------------------------------------------
|