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
>
--
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Dr Richard Henson
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