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Hi Indiana,

Please, see below:

On 21 March 2016 at 19:21, SUBSCRIBE FSL Anonymous <
[log in to unmask]> wrote:

> Dear list,
>
> I am running a GLM analysis using FSL-FEAT 5.0.8, and I want to look at
> brain activity as a function of behavioural performance (ie. The
> relationship between how well subjects perform a task, and the resulting
> brain activation).
>
> My experimental design is as follows:
>
> - 4 Experimental runs, each containing 97 trials
> - Within the 97 trials, there are 4 conditions:
> ·         1: Listening to cello sequences
> ·         2: Playing the cello
> ·         3: Playing the cello without having auditory feedback
> ·         4: Imagining cello performance
>
> For each of the Playing Trials (Conditions 2 & 3), the participants’
> behavior is scored based on their pitch and tempo accuracy. The score is
> currently stored as a floating value. The result of this, is that I end up
> with a continuous (dependent) variable for performance, which is not
> typically what you would use as a regressor. For the remaining conditions,
> there is no behavioural score.
>
> My goal would be to use each individual behavioural score on a per-trial
> basis, as opposed to an average behavioural score on a per-subject basis.
> Once again, the end goal for this specific analysis is to observe the
> relationship between brain activation and task performance.
>
> I have 3 main questions about how this should be implemented in FSL:
> 1.      Should I add a new EV file in the full model setup of the first
> level called “Playing_Behaviour” that contains the behavioural scores on a
> per trial basis (in addition to the Playing text file containing 0’s and
> 1’s to model the events)


Yes. This qualifies as a parametric regressor: you'd enter one EV for the
condition (playing) and one for the continuous score that indicates their
pitch and accuracy.


> OR should I simply replace the text file containing 0’s and 1’s with the
> Playing_Behaviour file.
>

No.


> 2.      Does the data need to be demeaned
>

At the 1st level it isn't needed. Mean-centering is done automatically.


> 3.      If it is the case that I enter an additional EV File every time I
> want to include behavioural information, can I enter as many EV Files as I
> want? Is there an upper limit to how many EVs you can include at the first
> level?
>

Yes, there is a theoretical limit, which is as many EVs as timepoints, but
usually we don't want to be even close to that. Fewer is generally better,
but with FMRI usually there are hundreds of timepoints so this is rarely an
issue.

Hope this helps.

All the best,

Anderson



>
> Thank you in advance for your help!
>