I'll have a go at answering these - Mark can correct me when I get it
> 1 - Would I have to mask just the initial highres, or both the initial
> highres and task epi? If the latter, would I just mask the middle volume,
> as this is what is used in the registration? If so, my 4D file contains
> 160 volumes. Would the middle correspond to the 79th, or the 80th?
the cost function mask is a separate 3D image in reference (-refweight) or
input (-inweight) space ( you can actually apply both weightings if you
like, but they have to be in the right spaces). Note that Cost function
weighting is different from masking the original images, as masking
introduces artificial edges which will drive the registration - usually
not a good idea.
> 2 - The CBU page recommends co-registering the epi to the structural and
> using the "yoke" function in MRIcro to identify points where there is
> signal dropout in the epi relative to the structural. These are the
> portions that should be masked out. If I register the unmasked epi to the
> structural, wouldn't this yield a (relatively) poor correspondance between
> the images, so that using this as the basis for identifying signal dropout
> would not be the best way to go about it? Are there any alternative ways
> for idetifying which areas to mask out?
If you use -inweight, your cost function weight mask will be directly in
input space so you can just downweight the areas with susceptibility
artefact, and upweight the boundaries you trust ( lateral walls of the
ventricles etc.. ). If you wanted to you could apply a _generic_ MNI space
mask to the reference space (-refweight) which would do the same thing -
downweight occipital pole etc and upweight the ventricle walls. I guess
this would be slightly less accurate than doing it individually for each
input volume, but I would think you could downweight pretty big areas
without really detracting from the registration, so I would think this
should be fine.
> 3 - Following from 2, would there be any problems in doing a straight
> image subtraction to identify the areas to be masked? It seems to me that
> this would be plagued by the same problems as in 2, but that it would be a
> quicker way to go about it?
I think this is answered by the previous point (??)
> 4 - The CBU page recommends smoothing the mask image (8mm in accordance
> with the SPM default). Would I also need to do this with FEAT? Would I use
> 5mm, as this is the FEAT default (or alternatively, whatever level I set
> it to)?
I would think smoothing the mask image would be a good idea. However, the
smoothness here is different from the smoothness in Feat - here we are
smoothing because of uncertainty in the location of the structures of
interest, not due to GRF theory etc. In this case, I would thing 8mm
smoothing of the mask image would be fine.
> 5 - As an aside, can someone tell me why the average epi template in SPM
> would be a poor choice as an intial highres? Does the fact that it's not
> the same brain as your subject introduce more problems than the advantage
> of having the added contrast?
Usually going to an initial highres, you would want to be able to choose a
low number of degrees of freedom to get a really robust registration. If
you use a reference brain which is a different global shape to the input
brain, you will need a high number of degrees of freedom even to get close
to a good registration, so I would think it would not be particularly
advantageous to choose an averaged brain as an initial highres.
Hope this is useful (and accurate!!)
> Sorry if some of these questions seem a bit basic - still trying to get my
> head around all of this!
> Thanks heaps, I really appreciate your ongoing help!