Dear Fred,

An F-test will test for _any_ quadratic effect. Use t-tests instead,
with the same contrast vectors [0 0 1] and 0 0 -1], to detect U shape
and inverted U shape relationships.

Best regards,
Guillaume.


On 12/04/17 08:17, Fred Sampedro wrote:
> Dear Guillaume,
> 
> 
> That was really helpful, it worked perfectly. One last simply question I
> have is that all significant voxels on the obtained F-contrast show a
> quadratic U shape on the plot. I can’t figure out how to obtain those
> voxels (if any) that fit an inversed U shape with the variable V. Trying
> the F-contrast [0 0 -1] shows the same voxel map that the [0 0 1]
> contrast. Does this mean that in this particular case there are no
> voxels fitting an inverted U shape in the relationship GMV with V? Or
> maybe do I have to define another multiple regression model using  [1  V
>  –V^2]  ?
> 
> 
> Thanks a lot again for your help,
> 
> Fred
> 
> 
> On Tue, Apr 11, 2017 at 1:11 PM, Guillaume Flandin <[log in to unmask]
> <mailto:[log in to unmask]>> wrote:
> 
>     Dear Fred,
> 
>     The multiple regression would be [1 V V.^2] where V has been
>     mean-centred:
>       V = V - mean(V);
>     Then you can test for a nonlinear (quadratic) effect with the F-contrast
>     [0 0 1].
>     In SPM, when looking at results, you can do a plot for a selected voxel
>     by clicking on the "plot" button, choosing "fitted response", "adjusted"
>     and "plot against an explanatory variable" 'V'.
> 
>     Best regards,
>     Guillaume.
> 
> 
>     On 10/04/17 17:53, Fred Sampedro wrote:
>     > Dear Guillaume,
>     >
>     >
>     > Thanks a lot for your quick response. I watched the presentation you
>     > mention and thought I had understood the approach.
>     >
>     > So my attempt was to define a gray matter voxel-based-morphometry model
>     > as follows: Set up a Regression model with my clinical variable V and
>     > its squared values V2. Then after estimating the model, set the
>     > following F-contrast: 0 0 1, that is to say I am only interested in the
>     > V2 parameter (the first 0 is a “mean” column that I see in the design
>     > matrix and the second 0 is the V variable).
>     >
>     >
>     > Several clusters appear at p<0.005. In one of them, I compute the gray
>     > matter volume for each subject (GMVc), and plot the relationship between
>     > V and GMVc. I was expecting a quite good quadratic fit given that
>     > p-value. However, I think I did some step wrong because the data does
>     > not seem very quadratic.
>     >
>     >
>     > In short, could you or anyone go in a little more detail in SPM on how
>     > to accomplish this kind of  quadratic voxel map?
>     >
>     >
>     > Thank you very again for your help,
>     >
>     > Best regards,
>     >
>     > F.
>     >
>     >
>     > On Mon, Apr 10, 2017 at 1:28 PM, Guillaume Flandin <[log in to unmask] <mailto:[log in to unmask]>
>     > <mailto:[log in to unmask] <mailto:[log in to unmask]>>> wrote:
>     >
>     >     Dear Fred,
>     >
>     >     You can use a polynomial expansion of the clinical variable,
>     see slice
>     >     18 of this presentation:
>     >       http://www.fil.ion.ucl.ac.uk/spm/course/video/#Design
>     <http://www.fil.ion.ucl.ac.uk/spm/course/video/#Design>
>     >     <http://www.fil.ion.ucl.ac.uk/spm/course/video/#Design
>     <http://www.fil.ion.ucl.ac.uk/spm/course/video/#Design>>
>     >
>     >     Best regards,
>     >     Guillaume.
>     >
>     >
>     >     On 10/04/17 08:39, Fred Sampedro wrote:
>     >     > Dear SPM experts,
>     >     >
>     >     >
>     >     > I’ve been using SPM to obtain voxelwise GMV or FDG
>     correlations with
>     >     > clinical variables. Naturally, by using the standard Regression
>     >     option I
>     >     > obtain linear (either positive or negative) correlations
>     with the
>     >     variables.
>     >     >
>     >     >
>     >     > However, sometimes I would like to know if there is a quadratic
>     >     > (typically inverted U shape) voxelwise relationship between the
>     >     clinical
>     >     > variable and the voxel’s GMV or FDG. Please find an illustrative
>     >     picture
>     >     > attached.
>     >     >
>     >     >
>     >     > Could anyone guide me on how to obtain a statistical
>     voxelwise map
>     >     where
>     >     > the significant voxels fit some inverse quadratic model?
>     >     >
>     >     >
>     >     > Thanks a lot in advance,
>     >     >
>     >     > F.Sampedro
>     >     >
>     >
>     >     --
>     >     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
> 
> 

-- 
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG