Dear Mathieu,
t or F contrasts [1 -1 0 0 0] and [1 0 -1 0 0] are fine; you could also
use a 'two-sample t-test' model for these.
The input images to a GLM should always be contrast images (summary
statistics approach); the spmT/spmF are your final results.
Concerning your second question, this is described for example in these
publications:
http://www.sciencedirect.com/science/article/pii/S1053811911011906
http://www.nature.com/jcbfm/journal/v26/n6/full/9600231a.html
> SPM locates significant clusters based on a ratio of signal to noise
> (a ‘contrast’ of the parameters divided by its standard error)
> meaning that very low noise regions, for example outside the brain,
> can attain artefactually high statistical values. Similarly, the
> commonly applied preprocessing step of Gaussian spatial smoothing can
> shift the peak statistical significance away from the peak of the
> contrast and towards regions of lower variance.
Best regards,
Guillaume.
On 24/02/15 15:19, Matthieu Vanhoutte wrote:
> Dear Guillaume,
>
> Thank you for helping !
>
> 1) So using this design matrix which contrasts should I use to highlight
> column1 > column2 and column1 > column3 ?
>
> 2) In statistical analysis this mean that I have to use spm* images
> instead of con* images ? How is it possible than con* images looks so
> fine and not spm* images (defined largely outside brain and peaks not
> corresponding with those of con* images) ?
>
> Best regards,
>
> -------------------------------------
> Matthieu Vanhoutte, MSc
> Research Engineer - Department of Neuroradiology
> Regional University Hospital, Lille, France
>
> 2015-02-24 16:00 GMT+01:00 Guillaume Flandin <[log in to unmask]
> <mailto:[log in to unmask]>>:
>
> Dear Matthieu,
>
> your design matrix looks fine, I would just not include the last column
> (constant term). For the main effect of group, you can use an
> F-contrast: [1 -1 0 0 0; 0 1 -1 0 0] (i.e. diff(eye(3))).
> Contrast images contain a linear combination of the parameter estimates
> (betas) while the spm* images contain test statistics (t or F) assessing
> the significance of such effects. See this video lecture:
> http://www.fil.ion.ucl.ac.uk/spm/course/video/#Contrasts
>
> Best regards,
> Guillaume.
>
>
> On 23/02/15 16:29, Matthieu Vanhoutte wrote:
> > Dear SPM's experts,
> >
> > I am studying perfusion images on 3 groups (control, left disease,
> right
> > disease) and 3 covariates (age, sexe, constant).
> >
> > My purpose is to see group effect, control > left and control > right
> > contrasts. According to this aim I chose a full factorial design with
> > one factor (group) that has three levels (control, left disease, right
> > disease). I defined for each subject 3 covariates : sex (0 : male, 1 :
> > female), age and constant (=1). You can find joined to this mail
> my SPM
> > design matrix.
> >
> > All my perfusion images have been normalized onto a particular T1
> > template different from the T1 SPM canonical template.
> >
> > I ran the script that computed automatically contrast for this full
> > factorial design, but don't know which of them are the good ones.
> >
> > I) Firstly is my design matrix well defined ?
> >
> > II) Then based on this design matrix, how should I define the
> contrasts
> > to see :
> > 1) group effect : F-contrast [1 1 1 0 0 0] ?
> > 2) control > left : T-contrast [1 -1 0 0 0 0] ?
> > 3) control > right : T-contrast [1 0 -1 0 0 0] ?
> >
> > III) Finally, what is the difference between con*.nii an spmT*.nii
> > output images ?
> > Because I could see superimposed on my particular T1 template that the
> > con*.nii image was so good looking and values well defined inside the
> > mask of my T1 template on precised anatomical areas. Contrary to this
> > coherent con*.nii image, the spmT*.nii image was not good looking, had
> > values defined outside the T1 template mask and the values defined
> > inside the mask weren't well located on anatomical areas.
> >
> > Many thanks in advance for helping !
> >
> > Best regards,
> >
> > -------------------------------------
> > Matthieu Vanhoutte, MSc
> > Research Engineer - Department of Neuroradiology
> > Regional University Hospital, Lille, France
>
> --
> Guillaume Flandin, PhD
> Wellcome Trust Centre for Neuroimaging
> University College London
> 12 Queen Square
> London WC1N 3BG
>
>
--
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG
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