Take a look at my VOI tool posts. Here is the critical part:
peak_extract_nii
(dependent on peak_nii): extracts peaks, mean and eigenvariate of
spheres around peaks, means around subject peaks, mean and eigenvariate
of clusters. The outputs are clearly labelled by peak number or cluster
number. The outputs can then be used to plot against other predictor
variables.
Usage:
[resultsvoxels columnlistvoxels resultscluster columnlistcluster clusters]=peak_extract_nii(subjectparameters,mapparameters)
OR
[resultsvoxels columnlistvoxels resultscluster columnlistcluster clusters]=peak_extract_nii([],mapparameters)
**mapparameters.voxel
and mapparameter.beta are also possible fields. The latter plots beta
estimates rather than the raw subject values.
**Output
is in cells and then matrices. (e.g. resultsvoxels{2}(:,1) would give
you the average signal in a 6mm sphere @ 18 -34 -35).
columnlistvoxels{2}(1) gives average 6mm sphere @ 18 -34 -35. {3} is eigenvariate for voxels.
The files are available at: www.martinos.org/~mclaren/ftp/Utilities_DGM
If you extract the mean of the ROI you want for each timepoint, then you can compute the mean and standard deviation over time.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
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2011/8/26 Peter Ferjančič
<[log in to unmask]>
Dear SPM-ers!
I am a physics undergraduate student dabbling in fMRI analysis and i am trying to analyse the quality of some images - for specified ROIs (one background, one high intensity signal) i want to measure mean values and standard deviation.
I started my work in marsbar, but i soon found out that i need quite some information on the experiments when filling in the design, which i don't have.
Is there a more elegant way to do this than conning the program with a blank/irrelevant design?
Please, forgive me, if this question is too beginner-like, i'm just starting to learn about this software.
--
Lep pozdrav
Peter Ferjančič
