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Hi Stephen, EB stands for "exchangeability blocks". This is necessary if you intend to use permutation tests. If you run the analysis in FEAT, it won't be needed. All the best, Anderson On 7 February 2017 at 16:36, Stephen Wilson <[log in to unmask]> wrote: > Hi Anderson, > Thank you so much for the very helpful reply. I've considered both of the > approaches that you mentioned, so the details that you gave will be quite > useful. Regarding the spreadsheet with the design set-up that you kindly > shared - may I ask, what does the column labeled "EB" refers to? It > probably isn't relevant to my specific question, but I am trying to become > more familiar with this contrast coding approach and thought it could be > useful in terms of ensuring that I am following the design properly. Thank > you again. > All the best, > Steve > > > Stephen J. Wilson, Ph.D. > Associate Professor > Department of Psychology > The Pennsylvania State University > 311 Moore Building > University Park, PA 16802 > Telephone: 814-865-6219 <(814)%20865-6219> > Fax: 814-863-7002 <(814)%20863-7002> > wilsonlab.la.psu.edu > > On Tue, Feb 7, 2017 at 6:24 AM, Anderson M. Winkler < > [log in to unmask]> wrote: > >> Hi Stephen, >> >> For the 1st level you would code/model the stimuli/responses that are of >> interest. If I am understanding correctly, you want one for each run, test >> between training vs. control, not mixing or comparing the runs, but rather, >> having 3 separate tests, is this correct? If yes, then 3 separate paired >> t-tests will work. If each run is considered a "modality", then these can >> be corrected across with "-corrmod" in PALM. >> >> If, however, you'd like to compare the three runs, then have a look into >> the first sheet of this file: https://dl.dropboxuserco >> ntent.com/u/2785709/outbox/mailinglist/design_karolina.ods >> >> This design can be used in FEAT. >> >> Hope this helps. If not, please feel free to ask again. >> >> All the best, >> >> Anderson >> >> >> >> On 7 February 2017 at 01:28, Stephen Wilson <[log in to unmask]> wrote: >> >>> Dear FSL experts, >>> I am in the process of transitioning to using FSL from another software >>> package, and I have what is probably a very simple question. I apologize if >>> this has been answered elsewhere on this listserv; I searched but could not >>> find anything. I am working through analysis for an fMRI neurofeedback >>> study. Participants received neurofeedback training (or a control >>> intervention) across three runs. I expect there to be training effects >>> across runs, so I would like to set things up so that I do not average >>> across runs for higher level analyses. What I'd like to end up with are >>> separate parameter estimates for each run in MNI space, which will allow me >>> to pull estimates (ideally expressed as percent signal change) for each run >>> from subject-level ROIs (registered to MNI space) for offline analyses and >>> to conduct whole-brain analyses comparing, for example, responses during >>> the third vs. the first run within and across groups. Could you please tell >>> me how I would need to set up my second level models in this case? Would >>> it just be a separate EV for each run? Thank you very much for any guidance. >>> >> >> >