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SPM  July 2009

SPM July 2009

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Subject:

Re: highpass filtering and correcting for temporal autocorrelation on raw signal

From:

cyril pernet <[log in to unmask]>

Reply-To:

cyril pernet <[log in to unmask]>

Date:

Thu, 23 Jul 2009 15:01:46 +0100

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text/plain

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text/plain (181 lines)

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.

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