Claus -
I then used an F-contrast (1 0 0; 0 1 0; 0 0 1) testing for whether
any of the three regressors explains some variance in my data.
In addition, I calculated a T-contrast (1 0 0) for the canonical hrf only.
In general, the pattern of results looks very similar for the two
contrasts. However, what I do not understand is why the t-contrast shows some voxels
and clusters which fail to be significant at all in the F-contrast.
 
The reason is that, if the majority of variance is captured by the canonical HRF, then the T-test is a more sensitive test of this (it tests only one dimension of the subspace tested by the F-test, including a specific direction - ie one-tailed). As you say, if variance loaded on the derivatives, you could find the opposite pattern of significance in the F but not T map.
 
In many conditions, subjects and brain regions, the canonical HRF does seem the capture the majority of variance. However, there are some regions/subjects/conditions where the derivatives capture additional variance, see, eg, section 3.1 of:
 
ftp://ftp.fil.ion.ucl.ac.uk/spm/data/rfx-multiple/rfx-multiple.htm
 
 
Rik

----------------------------------------
Dr Richard Henson
MRC Cognition & Brain Sciences Unit
15 Chaucer Road
Cambridge
CB2 2EF, UK
 
Tel: +44 (0)1223 355 294 x522
Fax: +44 (0)1223 359 062
 
http://www.mrc-cbu.cam.ac.uk/~rik.henson
----------------------------------------
 
 
----- Original Message -----
From: [log in to unmask] href="mailto:[log in to unmask]">Claus Lamm
To: [log in to unmask] href="mailto:[log in to unmask]">[log in to unmask]
Sent: Monday, October 10, 2005 1:39 PM
Subject: [SPM] t-test on hrf for model with derivatives

Dear SPM community,

I recently reanalyzed data I had modeled before using the hrf only, this
time using a model with hrf+temporal and dispersion derivative.

According to the suggestions by Rick Henson (e.g.
ftp://ftp.fil.ion.ucl.ac.uk/spm/data/rfx-multiple/rfx-multiple.htm) I set up
a rfx 2nd level analysis for this.

I then used an F-contrast (1 0 0; 0 1 0; 0 0 1) testing for whether
any of the three regressors explains some variance in my data.

In addition, I calculated a T-contrast (1 0 0) for the canonical hrf only.
In general, the pattern of results looks very similar for the two
contrasts.
However, what I do not understand is why the t-contrast shows some voxels
and clusters which fail to be significant at all in the F-contrast.

Shouldn't it be the other way round (if at all)? I.e. that I see activation
in the F contrast which I do not see in the T contrast (with the reason for
this being that the F test also uses variance explained by the derivatives)?

Thx a lot for helping me with this

claus