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Hi Miao, As I understand if I have plenty of results before permutation and none > after either permutation of FSL fdr, the reason is that the effect in my > dataset is probably small. > Indeed, the effect may be small, looking "significant" in the uncorrected, but unable to survive correction. > I tried to give it a smaller mask (only HG), but still no results. > Sounds another reason to suspect there's no actual effect. Just wondering , are there any other ways that I could try? Or do you have > other suggestions for the data processing procedure of mine? > It seems you run fdr. A suggestion is to make sure you use the option --othresh, which produces an image already thresholded, or, if you use the option -a, remember that it saves p-values (as opposed to 1-p), even if the option --oneminusp is used (yes, the help text is incorrect, and we'll certainly fix this in the next patch). Another suggestion, always useful, is to make sure you use a generous number of permutations (say, 5000 or 10000). More permutations won't increase power, but it makes the p-values more exact, so you can be more confident about the results. All the best, Anderson > > 2014-08-09 11:16 GMT-07:00 Anderson M. Winkler <[log in to unmask]>: > > Hi Miao, >> I don't think the mask needs to explicitly be binarised (it should be >> binarised internally), although it won't hurt in doing so beforehand. >> All the best, >> Anderson >> >> >> >> On 7 August 2014 17:58, Miao Wei <[log in to unmask]> wrote: >> >>> I found nothing significant even though I only have one region of >>> interest (HG). I didn't Binarise the mask.Could this be the reason? >>> Thanks. >>> Miao >>> >>> Sent from my iPhone >>> >>> 在 Aug 7, 2014，1:19 AM，"Anderson M. Winkler" <[log in to unmask]> 写道： >>> >>> Use fslmaths to add masks together and binarise them. >>> >>> >>> On 6 August 2014 23:25, Miao Wei <[log in to unmask]> wrote: >>> >>>> And how do I add in multiple regions in the mask in fslview? >>>> >>>> Sent from my iPhone >>>> >>>> 在 Aug 6, 2014，12:33 PM，"Anderson M. Winkler" <[log in to unmask]> >>>> 写道： >>>> >>>> Hi Miao, >>>> >>>> Nice to hear that the masking solved. >>>> >>>> Regarding the correction, the procedure in randomise isn't strict at >>>> all -- the idea that correction would be stringent is a myth. The >>>> correction produces *exact* p-values, that is, the amount of errors is >>>> right at the nominal level of the test, i.e., the "alpha" of the test, >>>> being not strict, conservative, or any other name that could be given, even >>>> if the data is smooth and/or has a high degree of spatial interdependence >>>> between voxels. >>>> >>>> That said, it is easier to detect significant effects if fewer tests >>>> are performed, so a smaller mask to constrain the search region could be >>>> useful. However, such a smaller mask must come from independent studies, or >>>> from well defined a priori hypothesis, supported by literature. It is not >>>> correct to use surviving clusters from one analysis and reuse that to >>>> further mask regions in the same study. >>>> >>>> All the best, >>>> >>>> Anderson >>>> >>>> >>>> >>>> On 6 August 2014 19:30, miao wei <[log in to unmask]> wrote: >>>> >>>>> Hi Anderson, >>>>> Thanks for the reply. >>>>> I got the mask right and now i don't have results outside brain. Yeah!! >>>>> But after Randomise, there are no significant results left and I tried >>>>> fdr from FSL , nothing left as well. But before corrections, there are >>>>> plenty of results. So I am thinking this is because the corrections are >>>>> tend to be very strict in fsl. >>>>> As I am thinking about the solutions, can i somehow add a extent >>>>> limitation. >>>>> So 1. get my uncorrected p map and then apply a 125 voxel spatial >>>>> limitation. All clusters have to be at least 125 voxels big to be entered >>>>> to next step >>>>> 2. take the results from step 1 and then get a mask of those clusters. >>>>> 3. use this cluster in either Randomise or FDR, to only correct for >>>>> those clusters. This way we are reducing the voxels we are testing and >>>>> increase our power. >>>>> Does this seem right? And how can i do it technically? Thanks a lot >>>>> for any help. >>>>> >>>>> >>>>> Miao >>>>> >>>>> >>>>> 2014-08-06 3:48 GMT-07:00 Anderson M. Winkler <[log in to unmask]> >>>>> : >>>>> >>>>> Hi Miao, >>>>>> >>>>>> Check if the mask is appropriate and tight around the cortex. Also >>>>>> make sure you are looking at the corrected p-values, and note that the >>>>>> files are saved as 1-p, rather than p itself. >>>>>> >>>>>> The manual for FSLView is here: >>>>>> http://fsl.fmrib.ox.ac.uk/fsl/fslview/ >>>>>> >>>>>> All the best, >>>>>> >>>>>> Anderson >>>>>> >>>>>> >>>>>> >>>>>> On 4 August 2014 18:13, miao wei <[log in to unmask]> wrote: >>>>>> >>>>>>> Hi Anderson, >>>>>>> Thanks for the continuos help. >>>>>>> I got the result from Randonmise. However, why some of the results >>>>>>> are out of the brain? >>>>>>> I checked my template_4D_GM.nii.gz and GM_mod_merg_s3.nii.gz and >>>>>>> they looks fine in the movie model. >>>>>>> What could cause this and how can I correct it to get meaningful >>>>>>> results? >>>>>>> Plus, I found out that sometimes when I overlay my tfce results to >>>>>>> MNI template, it is red and sometimes it is blue (the same one file) which >>>>>>> is really weird. >>>>>>> >>>>>>> Could you please suggest? >>>>>>> Thanks a bunch!! >>>>>>> Miao >>>>>>> >>>>>>> >>>>>>> 2014-08-01 17:31 GMT-07:00 Anderson M. Winkler < >>>>>>> [log in to unmask]>: >>>>>>> >>>>>>> Hi Miao, >>>>>>>> >>>>>>>> The TFCE is more interesting, more powerful, and more spatially >>>>>>>> specific than cluster extent, and I'd focus my attention to it. The tstat1 >>>>>>>> and tstat2 are the results for contrasts C1 and C2 respectively. You should >>>>>>>> also have files tstat3 and tstat4, for contrasts C3 and C4. If these >>>>>>>> weren't produced, this means that these contrasts actually don't exist in >>>>>>>> your contrast file (i.e., the file that you give to randomise with the >>>>>>>> option -t). You may want to double check that. >>>>>>>> >>>>>>>> About FSLview, if the orientation labels disappear, this means that >>>>>>>> the information in the header of your NIFTI files wasn't sufficient to >>>>>>>> determine exactly the orientation for display. There are various ways to >>>>>>>> fix this, but if you know which side is which (or pay attention to small >>>>>>>> asymmetries), the labels may not be all that necessary, and you can figure >>>>>>>> out what the correct sides are. >>>>>>>> >>>>>>>> All the best, >>>>>>>> >>>>>>>> Anderson >>>>>>>> >>>>>>>> >>>>>>>> On 1 August 2014 18:54, miao wei <[log in to unmask]> wrote: >>>>>>>> >>>>>>>>> Dear Anderson, >>>>>>>>> I was able to make it run by adding in ~ as you suggested! >>>>>>>>> Now I have >>>>>>>>> stats_clustere_corrp_tstat1.nii >>>>>>>>> stats_clustere_corrp_tstat2.nii >>>>>>>>> stats_tfce_corrp_tstat1.nii >>>>>>>>> stats_tfce_corrp_tstat2.nii >>>>>>>>> >>>>>>>>> which one should i pay more attention on? I understand the >>>>>>>>> clustere one is the cluster extent based one. >>>>>>>>> And why there is 1 and 2? Recall that my contrast was >>>>>>>>> C1 1000 >>>>>>>>> C2-1000 >>>>>>>>> C3 0001 >>>>>>>>> C4 000-1 >>>>>>>>> Which contrast do they represent? >>>>>>>>> >>>>>>>>> One odd thing is that after i select the standard MNI 152 template >>>>>>>>> and overlay with these results, the Left and right sign which can tell me >>>>>>>>> which hemisphere shows the effect disappeared. >>>>>>>>> >>>>>>>>> Forgive me for so many questions. >>>>>>>>> Really appreciated. >>>>>>>>> Miao >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> 2014-08-01 3:32 GMT-07:00 Anderson M. Winkler < >>>>>>>>> [log in to unmask]>: >>>>>>>>> >>>>>>>>> Hi Miao, >>>>>>>>>> >>>>>>>>>> Yes, the added EV and the new two contrasts are fine (for some >>>>>>>>>> reason the numbers are glued together in your email, but I believe they >>>>>>>>>> were entered correctly in the GLM GUI). >>>>>>>>>> >>>>>>>>>> About the error, are you sure that there is a directory called >>>>>>>>>> "/Downloads" and even if it exists, you have writting permissions to it? >>>>>>>>>> Try instead putting a tilde symbol (~) >>>>>>>>>> in front of the output string, like this: >>>>>>>>>> >>>>>>>>>> randomise -i GM_mod_merg_s3.nii.gz -o >>>>>>>>>> ~/Downloads/fsl_vbm/E_assembled -d fsl_vbm.mat -t fsl_vbm.con.txt -n 10000 >>>>>>>>>> -D -T >>>>>>>>>> >>>>>>>>>> It's probably not the cause of an error, but in general there's >>>>>>>>>> no .txt extension on these design files. It'd be good to make sure that >>>>>>>>>> they look ok inside (i.e., weren't screwed up by some text editor). >>>>>>>>>> >>>>>>>>>> All the best, >>>>>>>>>> >>>>>>>>>> Anderson >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On 1 August 2014 06:32, miao wei <[log in to unmask]> wrote: >>>>>>>>>> >>>>>>>>>>> Hi Anderson, >>>>>>>>>>> Thank you for getting back to me. >>>>>>>>>>> I just constructed the .mat and .con files as described above. >>>>>>>>>>> And I added another regressor which is one of my cognitive scores. >>>>>>>>>>> So I entered all the values for .mat file and the contrast was >>>>>>>>>>> C1 1000 >>>>>>>>>>> C2-1000 >>>>>>>>>>> C3 0001 >>>>>>>>>>> C4 000-1 >>>>>>>>>>> Where I am interested to test the correlations of the brain >>>>>>>>>>> volume of each voxel with the first and last variables. (1. learning rate, >>>>>>>>>>> 2. age, 3. IQ, 4. how fast subjct can subject read words) while other >>>>>>>>>>> non-interested variables were controlled. Am I right? >>>>>>>>>>> >>>>>>>>>>> Then I ran >>>>>>>>>>> randomise -i GM_mod_merg_s3.nii.gz -o >>>>>>>>>>> /Downloads/fsl_vbm/E_assembled -d fsl_vbm.mat -t fsl_vbm.con.txt -n 10000 >>>>>>>>>>> -D -T >>>>>>>>>>> >>>>>>>>>>> After running for hours, it now gave me the error message: >>>>>>>>>>> >>>>>>>>>>> Starting permutation 10000 >>>>>>>>>>> >>>>>>>>>>> Error: failed to open file >>>>>>>>>>> /Downloads/fsl_vbm/E_assembled_tstat1.nii.gz >>>>>>>>>>> >>>>>>>>>>> Image Exception : #22 :: ERROR: Could not open image >>>>>>>>>>> /Downloads/fsl_vbm/E_assembled_tstat1 >>>>>>>>>>> >>>>>>>>>>> ERROR: Program failed >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> An exception has been thrown >>>>>>>>>>> >>>>>>>>>>> ERROR: Could not open image >>>>>>>>>>> /Downloads/fsl_vbm/E_assembled_tstat1Trace: save_basic_volume4D. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Exiting >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> I am not sure what went wrong. When I ls the folder it only has >>>>>>>>>>> fsl_vbm.con.txt, not fsl_vbm.con >>>>>>>>>>> >>>>>>>>>>> Or the problem is that I should have put -c option? I want the >>>>>>>>>>> cluster larger than 125 voxels to show on the image. How should I put it? >>>>>>>>>>> But most importantly, why this failed? >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Please suggest. Thanks a lot. >>>>>>>>>>> >>>>>>>>>>> Miao >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> 2014-07-31 19:41 GMT-07:00 Anderson M. Winkler < >>>>>>>>>>> [log in to unmask]>: >>>>>>>>>>> >>>>>>>>>>> Hi, >>>>>>>>>>>> >>>>>>>>>>>> Please see below: >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On 31 July 2014 20:05, Miao Wei <[log in to unmask]> >>>>>>>>>>>> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> Dear FSL experts, >>>>>>>>>>>>> I am doing a structural analysis using FSL and now I am at the >>>>>>>>>>>>> step of >>>>>>>>>>>>> fslvbm_3_proc >>>>>>>>>>>>> It requires me to construct a design.mat and a design.con file. >>>>>>>>>>>>> I want to do the correlation between brain volume and a >>>>>>>>>>>>> continuous variable （learning rate of a foreign language） >>>>>>>>>>>>> and with partialing out the effect of Age and IQ scores on >>>>>>>>>>>>> brain volumes. >>>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> I understand that by "brain volume" you mean the volume of gray >>>>>>>>>>>> matter on each voxel, as assessed through VBM, as opposed to an overall >>>>>>>>>>>> measurement of brain volume as a whole, is this right? I'll take from here >>>>>>>>>>>> that this is a VBM study. >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>>> 1.i understand that I need to use glm to get .mat and .con >>>>>>>>>>>>> file. How many EVs should I set up? 3 ? >>>>>>>>>>>>> >>>>>>>>>>>>> Do I just put a column of values of each regressor that I am >>>>>>>>>>>>> interested >>>>>>>>>>>>> in the glm Gui? EV1 for learning rate, EV 2 for age and EV 3 >>>>>>>>>>>>> for IQ. >>>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> Yes, exactly. >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> 2. How about the contrast and F test tab? >>>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> It sounds that age and IQ are nuisance variables, and aren't to >>>>>>>>>>>> be tested. The contrasts then would be: >>>>>>>>>>>> >>>>>>>>>>>> C1: 1 0 0 >>>>>>>>>>>> C2: -1 0 0 >>>>>>>>>>>> >>>>>>>>>>>> An F-test isn't needed here (but if you want, you can divide >>>>>>>>>>>> the significance level of these tests by 2, that is, consider as >>>>>>>>>>>> significant p-values equal or below 0.05/2 = 0.025). >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> 3. I know that there is an -D option to demean the data in the >>>>>>>>>>>>> next >>>>>>>>>>>>> step- randomise. Should i use -D? >>>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> Yes, you definitely want to use the -D option here, because in >>>>>>>>>>>> the model you are not including an intercept (i.e., a column full of a >>>>>>>>>>>> constant non-zero value, such as 1). >>>>>>>>>>>> >>>>>>>>>>>> All the best, >>>>>>>>>>>> >>>>>>>>>>>> Anderson >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> Miao Wei >>>>>>>>>>> Graduate Student, Brain and Cognitive Science >>>>>>>>>>> Psychology Department >>>>>>>>>>> University of Southern California >>>>>>>>>>> 3620 South McClintock Ave, SGM 501 >>>>>>>>>>> Los Angeles, CA 90089-1061 >>>>>>>>>>> http://lobes.usc.edu/ >>>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> -- >>>>>>>>> Miao Wei >>>>>>>>> Graduate Student, Brain and Cognitive Science >>>>>>>>> Psychology Department >>>>>>>>> University of Southern California >>>>>>>>> 3620 South McClintock Ave, SGM 501 >>>>>>>>> Los Angeles, CA 90089-1061 >>>>>>>>> http://lobes.usc.edu/ >>>>>>>>> >>>>>>>> >>>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Miao Wei >>>>>>> Graduate Student, Brain and Cognitive Science >>>>>>> Psychology Department >>>>>>> University of Southern California >>>>>>> 3620 South McClintock Ave, SGM 501 >>>>>>> Los Angeles, CA 90089-1061 >>>>>>> http://lobes.usc.edu/ >>>>>>> >>>>>> >>>>>> >>>>> >>>>> >>>>> -- >>>>> Miao Wei >>>>> Graduate Student, Brain and Cognitive Science >>>>> Psychology Department >>>>> University of Southern California >>>>> 3620 South McClintock Ave, SGM 501 >>>>> Los Angeles, CA 90089-1061 >>>>> http://lobes.usc.edu/ >>>>> >>>> >>>> >>> >> > > > -- > Miao Wei > Graduate Student, Brain and Cognitive Science > Psychology Department > University of Southern California > 3620 South McClintock Ave, SGM 501 > Los Angeles, CA 90089-1061 > http://lobes.usc.edu/ >