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Joonkoo Park wrote: > Thanks for the comments Cyril and Vadim, > (I'm posting this thread back on the listserv for those who might be > interested.) > > First, I would NOT put two columns of ones. If no regressor is > specified, SPM automatically includes the intercept, which makes > things easy. that's what I mean -- in the residuals you'll have the mean removed automatically > > Second, I understand that a scaling factor is estimated in SPM.xY.VY > during model estimation, but I don't understand how exactly this is > computed and what it represents besides that it works as a global > scaling factor to make the average intensity 100 (default). > > In any case, I'm mainly interested in the relative intensity across > different TRs over multiple voxels (like temporal correlations), and > this is why filtering and AR correction is important. So, for this > purpose, I'm thinking that it should not matter how the residuals are > scaled? Please correct me if I'm wrong. agree c > > Joon > > > On Thu, Jul 23, 2009 at 7:27 AM, Vadim Axel <[log in to unmask] > <mailto:[log in to unmask]>> wrote: > > Cyril, > Consider the simple case that I load my Y as raw data directly > from my *.nii files. However, in the estimation SPM uses > SPM.xY.VY, which is not the intensity of the original *.nii data. > Concequernly, you r would be uncomparable to original Y intensity. > Isn't it? > Vadim (not Axel:) > > > On Thu, Jul 23, 2009 at 1:28 PM, cyril pernet > <[log in to unmask] <mailto:[log in to unmask]>> wrote: > > Axel > > not sure to follow here .. as mentioned earlier the residuals > will be without the mean (or intercept as you want) but they > are r = Y-Yhat and Yhat = Beta*X with X the matrix with the > drift and high pass filter + AR included in the estimation of > the Beta via the whitening matrix W Betas = inv(X'*W*X)*X'*Y > (in W there is also a regularization bit --> * c = a very > small number) -- but what is K? where do you scale? > > c > > Hi guys, > > Indeed very interesting idea. However, I am missing > something: there is always last "white" column with "1", > which SPM adds in order that the model will contain > intercept. So, now we will two one columns like this (the > first is our regressor). Is it OK? > In addition, the residiuls which we will get, I believe, > would be with some scaling factor (K),which SPM apllies. > So, it would be difficult quantatively to measure to what > extent the signal have changed at each time point, but > only to run the correlation between two signals. Correct? > > Thanks, > Vadim > > On Thu, Jul 23, 2009 at 12:43 PM, cyril pernet > <[log in to unmask] <mailto:[log in to unmask]> > <mailto:[log in to unmask] > <mailto:[log in to unmask]>>> wrote: > > Joonkoo > > I want to take the "raw signal" and then apply > detrending > (e.g. highpass > filtering at 128Hz) and temporal autocorrelation > correction > (e.g. using > AR(1) model) just as how ordinary SPM procedure does. I > searched for a > script or a thread concerning this issue, but > unfortunately I > wasn't able to > find a good advice on this. > So I came up with one idea which is to use the > conventional > SPM model > estimation procedure *without* any regressor > specified. This > way, the model > matrix will only include the grand mean (column of > ones) for > each run. The > residuals from this estimation should, in theory, > give me the > "highpass > filtered" and "temporal autocorrelation corrected" > which is > further mean > centered for each run. > sounds good to me - change in spm_defaults the residual > number to > 'inf' and in spm_spm comment the bit which actually > delete the > residuals from the disk - also in the design matrix you > can enter > the txt file from the realignment ; residuals here = > data with > variance related to motion removed + filtered as you > wanted :-) > (note the filtering is high pass / AR ~ = low pass / > drift) -- > also the mean will have been removed (that the contant > term in the > design matrix) > > Cyril > > > -- The University of Edinburgh is a charitable body, > registered in > Scotland, with registration number SC005336. > > > > > -- > Dr Cyril Pernet, > fMRI Lead Researcher SINAPSE > SFC Brain Imaging Research Center > Division of Clinical Neurosciences > University of Edinburgh > Western General Hospital > Crewe Road > Edinburgh > EH4 2XU > Scotland, UK > > > [log in to unmask] <mailto:[log in to unmask]> > tel: +44(0)1315373661 > http://www.sbirc.ed.ac.uk/cyril > http://www.sinapse.ac.uk/ > > > > The University of Edinburgh is a charitable body, registered in > Scotland, with registration number SC005336. > > > -- Dr Cyril Pernet, fMRI Lead Researcher SINAPSE SFC Brain Imaging Research Center Division of Clinical Neurosciences University of Edinburgh Western General Hospital Crewe Road Edinburgh EH4 2XU Scotland, UK [log in to unmask] tel: +44(0)1315373661 http://www.sbirc.ed.ac.uk/cyril http://www.sinapse.ac.uk/ The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.