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Dear Carlotta, In this case you are better off separating the four different conditions into different EVs and modelling each separately. The contrasts will then allow you to look at combinations of them according to you questions of interest. It is effectively the same as the contrasts in the 2x2 group-level ANOVA example here: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#ANOVA:_2-factors_2-levels_.282-way_between-subjects_ANOVA.29 for the cell means approach. Your EVs will look very different, but each one will represent the average activation level within a single condition. The contrasts will be exactly the same as in this group example. I hope this helps. All the best, Mark > On 19 Sep 2018, at 08:45, Carlotta Fabris <[log in to unmask]> wrote: > > Hi FSL experts! > > I have some task-based data on which I already did all the preprocessing and now I have to do the GLM using FEAT. > > I wanted to start with a first-level analysis, but I have some doubts on the GLM. > > This is the experiment: 6 blocks run. 30 sentences were presented in random order for 10 seconds each, after an interstimulus interval i.e. blank screen, ranging from 2-6 seconds, a question screen was presented for 4 seconds asking subjects to rate the question on a 4-point Likert-type scale. Each sentence was assigned to one of four conditions (A: high, low) x (B: high, low). > > I was thinking about doing a GLM with all the stimuli, so the 30 sentences and then use as contrasts the 4-point LIkert-type scale. Would it be a right approach or do you suggest me something different? > > Thank you, > Carlotta. > > ######################################################################## > > To unsubscribe from the FSL list, click the following link: > https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 ######################################################################## To unsubscribe from the FSL list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1