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Hi Miao, Yes, that's it. The literature review should be done well ahead of the data analysis -- it's easy to later cherry-pick papers that seem to confirm whatever finding there might be, and use those to suggest significance. Surely you don't want false positives in your study, and guarding against it is a priority. All the best, Anderson On 6 August 2014 21:11, miao wei <[log in to unmask]> wrote: > Oh, that make sense. > Then I can review the papers related and generate a list of regions that > is of my interest and use fslview to get a mask of these regions. > Then to apply this mask using the -m option in either randomise or fdr to > do the corrections? > > Thanks. > Regards, > Miao > > > 2014-08-06 12:33 GMT-07:00 Anderson M. Winkler <[log in to unmask]>: > > 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/ >