> Depends on what particular set of p-values you are interested in...
> (which I think is why SPM shows the (unique) t-values instead, as you
or because p-values are attributed to topological features of the field
and not to each and every voxel.
I'm not sure to see what an image of p-values could be but am happy to
be enlightened ;-)
All the best,
> It's easy to convert a t-map to a map of uncorrected voxel-wise
> p-values (I think both Volkmar's Volumes toolbox and Christian's VBM
> toolboxes have this functionality, or you can do it with imcalc).
> It's also easy to convert the above uncorrected p-map to a voxel-wise
> FDR p-map (or q-map), though it was a bit slow with spm_P_FDR last
> time I tried (you've just reminded that I have a much faster version
> of this, that I should probably inlclude in a future update...).
> RFT voxel-wise FWE p-values are fairly easy to get from spm_P, though
> if I remember correctly, you can get NaNs (perhaps even errors) with
> very small t-values, which might need sorting out before you saved the
> image for later visualisation. This might have been fixed since the
> last time I tried though.
> Cluster-wise p-values are not so easy to get, and would require a bit
> of coding. Also, they would not show you any information about
> relative signal within the clusters, whereas SPM's use of voxel-wise
> t-values within significant clusters gives you a little extra
> Finally, note that overlaying p-values in e.g. MRIcroN will probably
> not look good, firstly because more significant values are smaller,
> whereas most colour-maps expect larger=better, and secondly because
> the difference between 0.1 and 0.01 will probably end up being a very
> small difference in the colour-map, while it's actually a very
> important difference. One way to deal with this is to use
> abs(log10(p)) instead of p, then e.g. 0.1 maps to 1, 0.01 maps to 2,
> and the overlays look reasonably nice. The only complication with this
> is that 0.05 maps to 1.301, so if this is the alpha-level you are
> interested in, labelling the colour-bar with this value might look a
> bit messy.
> All things considered, it's probably not worth all this trouble, as
> the thing you are usually interested in is which blobs survive a
> particular significance threshold. There's also an argument that the
> best thing you could look at within these blobs is the raw contrast
> image, rather than the t-values or (any of) the p-values:
> On 6 May 2010 12:11, Joćo Duarte <[log in to unmask]> wrote:
>> Dear Ged,
>> thank you very much. It was easy...
>> By the way, as far as I understand, the colorbar displayed is the one with
>> the T values, right? Is it possibe to show a colorbar with p-values instead?
>> On Thu, May 6, 2010 at 11:42 AM, DRC SPM <[log in to unmask]> wrote:
>>> Dear Joćo,
>>> When you've got the glass brain results up in SPM, click the "save"
>>> button near the bottom right of the interactive window, and enter a
>>> filename for the output image. You should then be able to load this
>>> thresholded t-map as an overlay in MRIcroN etc.
>>> Note that you can display the blobs overlaid on an image in SPM itself
>>> too, just click the "overlays..." menu, and pick "sections" and then
>>> select an image you want to overlay onto (e.g. an average image,
>>> created by warping your original images with the same transformations
>>> used to create your VBM data, and then using imcalc with expression
>>> mean(X) and the data matrix (dmtx) flag true). If you've used DARTEL,
>>> the simplest thing to overlay onto is the GM of the final template,
>>> e.g. Template_6.nii.
>>> Hope that helps,
>>> 2010/5/6 Joćo Duarte <[log in to unmask]>:
>>>> Dear SPMers,
>>>> how can I display the map of significant blobs that is output of VBM
>>>> analysis in SPM8, using for example MRIcroN?
>>>> Thanks in advance.
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG