Hi - thanks for sending the data. It looks like you probably ordered the
data wrongly when you created the 4D analyze file for input to FEAT, as
your filenames aren't zero-padded. You should use something like:
avwmerge -t data4d *_?.hdr *_??.hdr *_???.hdr
Melodic estimated one component only in the data, and immediately found
the activation in the analysed dataset, showing the ordering problem; see
http://www.fmrib.ox.ac.uk/~steve/ftp/filtered_func_data.ica/report/IC_1.html
Note that this data has quite unrealistic levels of activation (as well as
noise structure); in the analysed datasets you sent, there is _huge_
activation, and in the raw data that you sent, the level of activation is
very low indeed.
Good luck with your study! Cheers, Steve.
On Mon, 24 May 2004, Heather Luo wrote:
> Hi,
>
> We are doing an empirical comparison between different GLM implementations
> in three packages: our proprietory NPAIRS, FSL and SPM2 based on a simple
> simulating image dataset. We sequencially fed the data into NPAIRS, FSL and
> SPM2. We can see obvious activation blobs in tstat maps from NPAIRS and SPM2
> as expected, while no obvious activation found in FSL results. The volume
> correlation R between tstat maps of SPM2 and NPAIRS is 0.64, while the R
> between FSL and NPAIRS is way below 0.1. We are wondering what is causing
> such a different result?
>
> The simulation data were generated using a 2-slice sub-volume(64*64*2)
> extracted from a brain mask volume(64*64*32) from one subject for a 1.5T
> fMRI experiment in which every volunteer was asked to perform two runs of
> static force task alternating six rest and five force periods/run
> (44s/period, TR=4s). Four artificial Gaussian blob(FWHM=1, 1.5, 2, 4
> pixels) activations, each restricted to a 7*7 square, were added to
> different locations in the second slice. To form the simulated time sequenc,
> the blobs were then multiplied by the on-off reference function for two
> parametric static force runs convolved with a Poisson shaped(lamda=7.3)
> hrf. After adding white noise to the sequence and normalizing the CONTRAST
> and CNR(CONTRAST-to NOISE Ratio) at the blobs' center to be 2, the
> simulating data set was obtained.
>
> Here is what we did in FSL:
> 1. avwmerge 120 slices into a 4d analyze image
>
> 2. input 4d data into FEAT, high pass filter cutoff = 100, TR=3.98
>
> 3. IF pre-stats was included, we used the default pre-stats setting except
> that we changed spatial smoothing FWHM=0mm
>
> 4. in Stats part, we used full model setup, original EV = 1.
> - Basic Shape: we prepared a text file as custom entry, the file looks like:
> 00000000111111111100000000001111111111....
> - Convolution if used: Gamma, phase=0, stddev=3, mean lag=6
> - contrast: mean, EV1=1
>
> 5. in Post-stats, Z threshold=2.3, p=0.01
>
> We first ran the data in FEAT with pre-stat and post-stat turned on, we found
>
> - no expected activation blobs found in the color rendered stat image in
> report.html.
> - from the time series for the voxel with max z, the full model fit doesn't
> reflect the contrast = 2.
> - there is no expected high intensity blobs in the unthresholded tstat1.img
> or zstat1.img
> (we used a self-developed idl program to view the t/z map, what the program
> does is to map the t/z score, eg. [-3.9, 4.3] to [0..255] and display the
> greyscale image. when we did comparison, the t/z maps from NPAIRS and SPM
> were viewed through the same program as well.)
>
> Then we tried again with pre-stat, post-stat, and convolution function
> turned off, the results are similar as before, no activion blob seen.
>
>
> Heather Luo
> International Neuroimaging Consortium
> Minneapolis VA Medical Center
>
Stephen M. Smith DPhil
Associate Director, FMRIB and Analysis Research Coordinator
Oxford University Centre for Functional MRI of the Brain
John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask] http://www.fmrib.ox.ac.uk/~steve
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