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Dear Bruno,

The model you propose for all the subjects seems fine, but if you want to
test

Beta1>0 & Beta1>Beta2 & Beta1>Beta3.


then the contrasts you want to define are
[ 1  0  0 ]
[ 1 -1  0 ]
[ 1  0 -1 ]

and then take a conjunction of those three t-contrast.

*That* procedure would be correct, and as long as you tell SPM that you have
repeated measures (i.e. don't just treat it as 3*N independent scans) you'll
be fine.

-Tom

On Sat, May 22, 2010 at 4:58 PM, Bruno L. Giordano <
[log in to unmask]> wrote:

> Hello,
>
> I am modeling the extent to which different stimulus-related features
> explain how the BOLD-baseline response varies across stimuli.
>
> For the sake of the argument, let's assume that the baseline and covariates
> of no interest (e.g., head motion parameters) have already been filtered out
> of the data. Let's also assume that the features are perfectly orthogonal,
> i.e., not correlated.
>
> As such, my first level model would be a multiple regression of the type:
>
> BOLD = Beta1*Feature1+Beta2*Feature2+Beta3*Feature3+constant.
>
> At the group level one thing I am interested in is where Beta is positive.
> To this purpose, I run one simple T-test for each of the features using the
> Beta images from each subject as dependent data.
>
> My problem now concerns how to setup a more complex 2nd level model where I
> want to find those regions where, e.g.,:
>
> Beta1>0 & Beta1>Beta2 & Beta1>Beta3.
>
> Again for the sake of the argument, let's assume that the Betas for the
> different features are comparable (e.g., regressors have been standardized
> prior to entering the model).
>
> So, what I am doing for the moment is:
>
>
> [1] setup the following design matrix (N = n subjects):
>
> Beta1   Beta2   Beta3
>  1       0       0     subj1
>  1       0       0     subj2
>  1       0       0     subj...
>  1       0       0     subjN
>  0       1       0     subj1
>  0       1       0     subj2
>  0       1       0     subj...
>  0       1       0     subjN
>  0       0       1     subj1
>  0       0       1     subj2
>  0       0       1     subj...
>  0       0       1     subjN
>
> [2] set up these two contrasts:
>
> c1:[1 0 0]
> c2:[1 -1/2 -1/2]
>
> [3] find those regions where both c1 and c2 are significant (or test the c1
> & c2 conjunction).
>
> Is this procedure correct? I am afraid, for example, of inflating the
> degrees of freedom.
>
> Thank you for any feedback,
>
>        Bruno
>
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> Bruno L. Giordano, PhD
> Postdoctoral Research Fellow
> CIRMMT – Schulich School of Music
> 555 Sherbrooke Street West
> Montréal, QC H3A1E3
> Canada
> +1 514 398 4535, Ext. 00900 (voice)
> +1 514 398 2962 (fax)
> http://www.music.mcgill.ca/~bruno
>



-- 
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry  CV4 7AL
United Kingdom

Email: [log in to unmask]
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax:  +44 24 7652 4532