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Hi Anderson, Many thanks for this detailed answer, it helps ! I would have another question yet. I have to deal with non regular missing timepoints as in the example below: *(subj1, visit1)* *(subj1, visit3)* *(subj2, visit2)* *(subj2, visit3)* *(subj3, visit1)* *(subj3, visit2)* *(subj3, visit4)* *(subj4, visit2)* *(subj4, visit3)* *(subj4, visit4)* Subjects 1 and 2 have two visits each, but subject 1 at 1st and 3rd visits whereas subject 2 at 2nd and 3rd visits. In the same manner, subjects 3 and 4 have three visits each but with different numerous of visit. In this case, could I as you explained allow exchangeability between subject 1 and 2, and between subject 3 and 4 even if numerous of the visits don't correspond ? Best regards, Matthieu 2017-11-15 1:27 GMT+00:00 Anderson M. Winkler <[log in to unmask]>: > Hi Matthieu, > > For the design, have a look in the Example 6 of the randomise paper: > https://doi.org/10.1016/j.neuroimage.2014.01.060 > > In the case of subjects with a different number of visits, only those with > same number of visits should be permuted with each other, such that > multi-level exchangeability blocks are required (these are described > elsewhere, though: https://doi.org/10.1016/j.neuroimage.2015.05.092). > Define a block per subject and mark these with negative indices (3rd column > belo). Then one level above (2nd column), define one block for each number > of visits a subject has, and keep these with positive indices. At the top > level, a single block with a negative number (to prevent subjects with > different number of visits from being mixed with each other). At the level > of observations, unique indices per subject (and be one value per visit). > Something like this: > > *-1,2,-1,1 (subj1, visit1)* > *-1,2,-1,2 (subj1, visit2)* > *-1,2,-2,1 (subj2, visit1)* > *-1,2,-2,2 (subj2, visit2)* > *-1,3,-3,1 (subj3, visit1)* > *-1,3,-3,2 (subj3, visit2)* > *-1,3,-3,3 (subj3, visit3)* > *-1,3,-4,1 (subj4, visit1)* > *-1,3,-4,2 (subj4, visit2)* > *-1,3,-4,3 (subj4, visit3)* > > > Subjects 1 and 2 have two visits each; subjects 3 and 4 have three visits. > Subjects 1 and 2 can be permuted with each other; subjects 3 and 4 can be > permuted with each other, but subjects with two visits can't be permuted > with subjects with three visits (negative indices in the 1st column). The > visits cannot be permuted with each other (negative indices at the 3rd > column). > > Hope this helps. > > All the best, > > Anderson > > > > > > On 11 November 2017 at 03:45, Matthieu Vanhoutte < > [log in to unmask]> wrote: > >> Hi Anderson, >> >> Thank you for replying. In case I want to study between subject factors, >> as longitudinal progression in one group vs another one, how should I >> define the design and contrasts with PALM ? >> >> Missing timepoints in some of the subjects will not be problematic ? >> >> Best, >> Matthieu >> >> >> Le 11 nov. 2017 3:17 AM, "Anderson M. Winkler" <[log in to unmask]> >> a écrit : >> >> Hi Matthieu, >> >> It is, but this requires either compound symmetry, or that only >> between-subject factors are investigated. >> >> All the best, >> >> Anderson >> >> >> On 8 November 2017 at 09:34, Matthieu Vanhoutte < >> [log in to unmask]> wrote: >> >>> Hi Anderson, >>> >>> I have 1 to 4 timepoints per subject, depending on the availability and >>> quality of the processed data. In my case, is this possible to deal with >>> PALM ? >>> >>> Best regards, >>> Matthieu >>> >>> >>> 2017-11-08 14:11 GMT+00:00 Anderson M. Winkler <[log in to unmask]>: >>> >>>> Hi Matthieu, >>>> >>>> Regarding the longitudinal aspect, in PALM compound symmetry has to be >>>> assumed. If there are 2 timepoints, this is fine. With more than 2, it >>>> becomes progressively more difficult. How many timepoints do you have? >>>> >>>> About the 2 modalities, these can be entered in the same call as two >>>> separate inputs (two "-i"), and the option "-corrmod" to correct over them, >>>> or "-npc" for a joint analysis via NPC. >>>> >>>> All the best, >>>> >>>> Anderson >>>> >>>> >>>> On 8 November 2017 at 03:44, Matthieu Vanhoutte < >>>> [log in to unmask]> wrote: >>>> >>>>> Dear Anderson, >>>>> >>>>> Thank you for your answer. My question concerns vertex-wise cortical >>>>> surface data I have within 2 modalities over time. And I would like to >>>>> correlate this two modalities across entire cortical surface longitudinally. >>>>> >>>>> Could you indicate me a process or how to do it with PALM ? >>>>> >>>>> Best regards, >>>>> Matthieu >>>>> >>>>> >>>>> 2017-11-08 2:41 GMT+00:00 Anderson M. Winkler <[log in to unmask]> >>>>> : >>>>> >>>>>> Hi Matthieu, >>>>>> >>>>>> Just adding to Niels' answer: for other types of vertexwise data, >>>>>> it's possible to do in PALM (i.e., it will read surface formats such as >>>>>> FreeSurfer's or CIFTI). >>>>>> >>>>>> All the best, >>>>>> >>>>>> Anderson >>>>>> >>>>>> On 7 November 2017 at 15:55, Niels Bergsland <[log in to unmask]> >>>>>> wrote: >>>>>> >>>>>>> Hi Matthieu, >>>>>>> There isn't a direct longitudinal FIRST pipeline, but you can do it. >>>>>>> >>>>>>> What you need to do is run the concat_bvars command with all of your >>>>>>> data. Then you run first_utils like in the guide. At this point, you need >>>>>>> to use fslsplit on the output and then perform the subtractions with >>>>>>> fslmaths and then merge the difference images back together with fslmerge. >>>>>>> You probably know this already, but the order of the inputs to concat_bvars >>>>>>> corresponds to their order in the 4D output from first_utils. So when you >>>>>>> do the fslmaths and fslmerge, just make sure that you have things in the >>>>>>> right order. >>>>>>> Good luck! >>>>>>> Niels >>>>>>> >>>>>>> On Tue, Nov 7, 2017 at 9:43 PM, Matthieu Vanhoutte < >>>>>>> [log in to unmask]> wrote: >>>>>>> >>>>>>>> Dear FSL's experts, >>>>>>>> >>>>>>>> Do you know if there would be a mean to compare longitudinal >>>>>>>> evolution of two vertex-wise data (i.e. kind of longitudinal correlation) >>>>>>>> with PALM or others ? >>>>>>>> >>>>>>>> Best regards, >>>>>>>> Matthieu >>>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Niels Bergsland >>>>>>> Integration Director / Research Assistant Professor of Neurology >>>>>>> Buffalo Neuroimaging Analysis Center / University at Buffalo >>>>>>> 100 High St. Buffalo NY 14203 >>>>>>> <https://maps.google.com/?q=100+High+St.+Buffalo+NY+14203&entry=gmail&source=g> >>>>>>> [log in to unmask] >>>>>>> >>>>>> >>>>>> >>>>> >>>> >>> >> >> >