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Thank you for this information!

I have one query. What is the meaning of mean time series in Y that you
have mentioned? Is it time series after subtracting mean?

Thanks & regards,
Priya

On Sat, Jan 9, 2016 at 1:20 AM, Guillaume Flandin <[log in to unmask]>
wrote:

> Dear Priya,
>
> just to add that if Y contains a mean fMRI time series and X is a matrix
> of confounds then you can compute:
>
> % residual forming matrix:
> R = eye(size(X,1)) - X*pinv(X);
> % residuals:
> r = R * Y;
>
> A related function in SPM would be spm_ancova.m.
>
> Best regards,
> Guillaume.
>
>
> On 08/01/16 03:48, Priya Aggarwal wrote:
> > Thank you so much! this code is very useful...:)
> >
> > On Thu, Jan 7, 2016 at 9:40 PM, <[log in to unmask]
> > <mailto:[log in to unmask]>> wrote:
> >
> >     The stats toolbox has a regress function. The neural network toolbox
> >     has a function regression, which I think is not as good as you would
> >     need to extract residuals on your own. ____
> >
> >     __ __
> >
> >     I attached a function I wrote for this, which also removed a 3^rd
> >     order poly from the data. It needs CSF and WM masks in nii files,
> >     and was really specifically written for one data set of mine, but
> >     you are free to steal any code if it is helpful. I certainly won’t
> >     work out of the box on anything though, it was a one-study-use
> >     function.  : )____
> >
> >     __ __
> >
> >     __ __
> >
> >     Colin Hawco, PhD____
> >
> >     Neuranalysis Consulting____
> >
> >     Neuroimaging analysis and consultation____
> >
> >     www.neuranalysis.com <http://www.neuranalysis.com>____
> >
> >     [log in to unmask] <mailto:[log in to unmask]>____
> >
> >     __ __
> >
> >     __ __
> >
> >     __ __
> >
> >     *From:*SPM (Statistical Parametric Mapping)
> >     [mailto:[log in to unmask] <mailto:[log in to unmask]>] *On Behalf
> >     Of *Priya Aggarwal
> >     *Sent:* January-07-16 12:59 AM
> >     *To:* [log in to unmask] <mailto:[log in to unmask]>
> >     *Subject:* Re: [SPM] linear regression of cofounds____
> >
> >     __ __
> >
> >     Thank you for this information!____
> >
> >     __ __
> >
> >     I would like to use matlab for removing cofounds. Is there any
> >     inbuild command for running regression in matlab.____
> >
> >     __ __
> >
> >     Thanks,____
> >
> >     Priya____
> >
> >     __ __
> >
> >     On Thu, Jan 7, 2016 at 12:41 AM, <[log in to unmask]
> >     <mailto:[log in to unmask]>> wrote:____
> >
> >     You have a few options. You can download an existing Matlab toolbox,
> >     such as the Conn toolbox, which has some of this functionality built
> in.
> >
> >     Personally I tend to code these things myself. You can grab the
> >     nifti toolbox for Matlab (off NITRICS), which will allow you to load
> >     your images as Matlab variables (I find it a bit easier to use than
> >     SPM's functions).
> >
> >     Then loop through voxels, run regress in matlab on the time series,
> >     and save the residuals into a new data structure.
> >
> >     If you want to do a really good job removing motion effects, I would
> >     suggest using the Pythagorean transform of the motion parameters
> >     (Damion Faire did some good work on this), of if you are more
> >     ambitious use a voxel-specific set of regressors as done by Ted
> >     Satterthwaite
> >
> >     http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3811142/
> >
> >     Which really seems to make a difference in removing motion effects,
> >     especially for analysis between groups where motion may differ, a
> >     major confound in most analyses.
> >
> >     Good luck!
> >
> >     Colin Hawco, PhD
> >     Neuranalysis Consulting
> >     Neuroimaging analysis and consultation
> >     www.neuranalysis.com <http://www.neuranalysis.com>
> >     [log in to unmask] <mailto:[log in to unmask]>____
> >
> >
> >
> >
> >     -----Original Message-----
> >     From: SPM (Statistical Parametric Mapping)
> >     [mailto:[log in to unmask] <mailto:[log in to unmask]>] On Behalf Of
> >     Priya Aggarwal
> >     Sent: January-06-16 12:18 PM
> >     To: [log in to unmask] <mailto:[log in to unmask]>
> >     Subject: [SPM] linear regression of cofounds
> >
> >     Hi everyone,
> >
> >     I want to regress out various cofounds (such as realignment
> >     parameters and its derivative, white matter signal etc.)  from my
> >     regional mean fMRI time series. This linear regression is essential
> >     step in resting state fMRI functional connectivity analysis.
> >
> >     Can anyone please help me how can i do it?
> >
> >     Thank you for this help!
> >
> >     regards,
> >     Priya____
> >
> >
> >
> >     ____
> >
> >     __ __
> >
> >     -- ____
> >
> >     Thanks and Warm Regards,____
> >
> >     __ __
> >
> >     Priya Aggarwal____
> >
> >     Indraprastha Institute of Information Technology, Delhi (IIIT-D)____
> >
> >     Okhla Industrial Estate,Phase III
> >     (Near Govind Puri Metro Station)
> >     New Delhi, India - 110020____
> >
> >
> >
> >
> > --
> > Thanks and Warm Regards,
> >
> > Priya Aggarwal
> > Indraprastha Institute of Information Technology, Delhi (IIIT-D)
> > Okhla Industrial Estate,Phase III
> > (Near Govind Puri Metro Station)
> > New Delhi, India - 110020
>
> --
> Guillaume Flandin, PhD
> Wellcome Trust Centre for Neuroimaging
> University College London
> 12 Queen Square
> London WC1N 3BG
>



-- 
Thanks and Warm Regards,

Priya Aggarwal
Indraprastha Institute of Information Technology, Delhi (IIIT-D)
Okhla Industrial Estate,Phase III
(Near Govind Puri Metro Station)
New Delhi, India - 110020