The analysis mask is formed as the intersection of the implicit,
threshold and explicit masks. If you want to get rid of the threshold
mask to impose your explicit mask only, specify your model as usual with
the explicit mask, then run this:
SPM.xM.TH = -Inf(size(SPM.xM.TH));
save SPM.mat SPM -v6
followed by model estimation.
In your previous model estimations, things went a bit funny because your
analysis mask consisted of all voxels within the image (ie including
background) and this affected the estimation of the temporal
autocorrelation, as it is pooled over voxels.
On 23/04/17 07:58, Michael Bannert wrote:
> Dear SPM community,
> I would like to estimate beta parameters for every subject in my sample
> using exactly the same explicit (whole brain) mask. I would like to have
> beta estimates for exactly the same voxels in MNI space. Can SPM do this?
> There is the option to specify an explicit mask when setting up a GLM.
> However, SPM automatically still applies some implicit masking. From
> what I understand the critical parameter for implicit masking is
> mask.tresh in the spm_defaults (usually = .8, meaning that voxels with
> less than 80 % of the global mean signal are discarded).
> The strange thing is that when I set this to 0 in order to disable
> implicit masking, the beta estimates become extremely noisy and my
> effects are gone. This is very odd behavior.
> When I set it to .01, the betas estimates seem to be fine again but it
> is not exactly what I want. The "effective masks" that SPM comes up with
> for every subject still differ a little here and there, so this is no help.
> How can I achieve what I want with fMRI?
> Thanks & best,
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG