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Hi Amande, I'm afraid I still don't understand what you want to do, What do you mean by " a correlation with B _given_ A " ? Is it a partial correlation " a correlation of the data with B accounting for the effects A " ? or a multiple regression "How much of the variance in the data can a prescribe to both A and B together?" I'm sure there will be a simple way of answering your question. The GLM is amazingly flexible. I just can't see exactly what the question is yet.. wrt non-orthogonal EVs If your EVs are not orthogonal, then any shared variance will be dished out between them in a way which is not easily predictable a priori. However, if you are comparing conditions, this shared variance is accounted for in the statisitics, so you can still accurately answer the question "Where is the response to A bigger than that to B?" for example. Sorry I'm not more use Tim On Sun, 27 Jun 2004, Amande Pauls wrote: > Hi, > > no, what I was wondering about is whether there is any way I can test > whether there is a correlation with B (behavioural covariate) given A > (task), e.g. by not making the EVs orthogonal. So really what I want to > know is what it means if the two EVs are not orthogonal and whether this > is in any way statistically meaningful. Such as activation in a certain > area given RT on the task, or activation in a task given IQ or something. > > Amande > > > > Tim Behrens wrote: > > > ... > > > > "At which voxels does my signal contain variance which can be explained by > > my RTs _but not_ by my task EV ?" > > > > sorry - this might be confusing. > > > > more accurate is > > > > "At which voxels does my signal contain variance which can be explained by > > my RTs after accounting for variance explained by my task EV ?" > > > > > > > > ------------------------------------------------------------------------------- > > Tim Behrens > > Centre for Functional MRI of the Brain > > The John Radcliffe Hospital > > Headley Way Oxford OX3 9DU > > Oxford University > > Work 01865 222782 > > Mobile 07980 884537 > > ------------------------------------------------------------------------------- > > > > ---------- Forwarded message ---------- > > Date: Wed, 23 Jun 2004 16:16:33 +0100 (BST) > > From: Tim Behrens <[log in to unmask]> > > To: FSL - FMRIB's Software Library <[log in to unmask]> > > Subject: Re: [FSL] higher level analyses - using additional (behavioural) > > covariates > > > > Hi Amande - I'm not sure whether I've understood this right, but it sounds > > like what you want is exactly the opposite of the previous scenario. That > > is > > > > "At which voxels does my signal contain variance which can be explained by > > my RTs _but not_ by my task EV ?" > > > > If this is the case, you want to run the orthoganisation the other way > > round. That is, you want to orthoganalise the RTs wrt the task covariates. > > > > This will remove from the RT EV, any variance which could be explained by > > the task. > > > > Hope this is what you want > > > > T > > > > > > > > > > > > > > On Wed, 23 Jun 2004, Amande Pauls wrote: > > > > > >>Hi there, > >> > >>thanks for the quick reply. > >> > >>I have another question about point (3). Say I don't want to factor out > >>the additional covariate, but want to see whether there are areas whose > >>variance reflects the additional covariate given the task. An example > >>would be some motor task and I want to 'rank' people according to RTs > >>I've got from them in some other task (or rather see whether activity in > >>this task somehow reflects their prior motor performance). Do I use RTs > >>from the other task as additional covariate and then don't make the EVs > >>orthogonal? Or do I have to set that up in the contrasts somehow, after > >>they have been orthogonalised? > >> > >>What I would like to know is whether my additional covariate, of > >>interest or not, will correlate only with areas activated by the task, > >>or whether what I see could also reflect baseline activity in some > >>resting state network (like language areas etc). > >> > >>Thanks again. > >>Amande > >> > >> > >> > >> > >> > >>Tim Behrens wrote: > >> > >>>Hi there > >>> > >>>On Tue, 22 Jun 2004, Amande Pauls wrote: > >>> > >>> > >>> > >>>>(1) Is it possible to control for an additional covariate that I am not > >>>>interested in but suspect to have an influence on the outcome of the > >>>>experiment (like measures of intelligence)? By modelling all of them as > >>>>an additional EV? Or by making it one per subject (like when allowing > >>>>for individual differences in variance)? > >>> > >>> > >>>Yep - you should use a single EV for each covariate of no interest (e.g. > >>>one EV for IQ, ine for age etc. etc. ) > >>> > >>> > >>> > >>>>(2) If I want to know whether there is a negative correlation between my > >>>>additional covariate (modelled as a separate EV) and the data, do I need > >>>>to set the contrast to -1? > >>>> > >>> > >>> > >>>Yes - absolutely right. > >>> > >>> > >>> > >>>>(3) Having used an additional covariate (like the RT example in the > >>>>webpages) and using that precise contrast, what does the result mean? > >>>>I'm unclear on whether the brain area correlates both with RT and the > >>>>task itself, or whether the level activity in that area somehow reflects > >>>>RT, potentially independent of the task. Can I distinguish between those > >>>>two cases, or make sure that my contrast reflects 'correlation with > >>>>EV, given the task'? > >>>> > >>> > >>> > >>>It depends on the precise setup that you have chosen, but if you > >>>orthogonalise such that RT explains the maximum possible variance (i.e. > >>>orthogonalise all covariates of interest wrt RT) then the RT contrast > >>>represents all the variance in the signal which _might possibly_ be > >>>explained by RT. The copes of interest cannot then describe any variance > >>>in the signal which could be ascribed to RT. > >>> > >>>JHupw this is clear > >>> > >>>Tim > >>> > >>> > >>> > >>> > >>> > >>> > >>>>I hope this makes sense. Thanks for any help. > >>>> > >>>>Amande Pauls > >>>> > >>>>-------------------------------------------------------------------- > >>>>Amande Pauls > >>>>University Laboratory of Physiology, Oxford, UK > >>>>mailto:[log in to unmask] > >>>> > >>> > >>> > >> > >>-- > >>-------------------------------------------------------------------- > >>Amande Pauls > >>University Laboratory of Physiology, Oxford, UK > >>mailto:[log in to unmask] > >> > > > > > > > -- > -------------------------------------------------------------------- > Amande Pauls > University Laboratory of Physiology, Oxford, UK > mailto:[log in to unmask] > -- ------------------------------------------------------------------------------- Tim Behrens Centre for Functional MRI of the Brain The John Radcliffe Hospital Headley Way Oxford OX3 9DU Oxford University Work 01865 222782 Mobile 07980 884537 -------------------------------------------------------------------------------