Hi there
I don't know how to do the combined SPM and FSL analysis you want, but I can offer you some reassurance if you don't want to bother with it...!
In SPM the physiological data is deconvolved, combined with the task regressor, and the result is recombined.
In FSL the physiological data is not deconvolved, instead it is combined with the convolved task regressor.
You are right that some authors (e.g. Gitelman) have argued that deconvolution is important, especially for event related designs. However, what you get in both cases is a convolved PPI regressor in which your physiological data and task regressor were in the same state (either convolved or deconvolved) when you combined them. Thus the assumption you are making by not deconvolving in FSL are that the shape of the HRF should be roughly what you used to combine your task regressor. This seems to me not very unreasonable, since in most analyses people do just assume a certain shape for the HRF.
Hope that helps
Jill
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Dr Jill O'Reilly
FMRIB Centre, Dept Clinical Neurology, Oxford University
Phone +44 1865 222466
________________________________________
From: Stephen Smith [[log in to unmask]]
Sent: 23 February 2010 04:56
To: Jill OReilly
Subject: Fwd: [FSL] PPI: deconvolve a timecourse?
Yo - two related queries below....?
Ta ;-)
Begin forwarded message:
From: Cornelius Werner <[log in to unmask]<mailto:[log in to unmask]>>
Date: 22 February 2010 09:04:42 GMT
To: [log in to unmask]<mailto:[log in to unmask]>
Subject: Re: [FSL] PPI: deconvolve a timecourse?
Reply-To: FSL - FMRIB's Software Library <[log in to unmask]<mailto:[log in to unmask]>>
Hi,
I am also interested in running a PPI on ER-data. Could you point me
to the paper in question?
Could it be that in SPM there is/has been no option to leave
regressors unconvolved as it is with FSL? Perhaps this would not make
such a difference with a large block, but rather more so with a stick
function (if it became convolved twice, once physiologically, and the
second time by SPM) - could that be the reason? From Jill Kelly's
instructions I gathered that if you enter a timecourse you extracted
beforehand and choose "do not convolve", you should be fine, as the
brain "convolved" the timeseries with its genuine HRF anyway. Any
experts have an opinion on this?
If you get any news on this, I'd be interested to hear about it.
Thanks
Cornelius
On Wed, Feb 17, 2010 at 5:35 PM, Ilya Veer <[log in to unmask]<mailto:[log in to unmask]>> wrote:
Hi all,
I would like to do a PPI analysis on event-related task data which have been
analyzed in FSL already. Following Gitelman’s paper, it seems that
deconvolution of the physiological time-course (derived from the seed ROI)
is a prerequisite when doing PPI’s on event-related designs. However, FSL
doesn’t provide a tool for this. I tried to deconvolve the time-course using
SPM, but I couldn’t manage to do this without running the entire analysis of
the task data in SPM. Does anyone have experience in analyzing PPI’s on
event-related data in FSL? Is it at all possible to obtain a deconvolved
time-course without running the entire analysis in SPM? Lastly, is there an
alternative for deconvolution when doing a PPI on event-related data in FSL?
Any help with this issue would be greatly appreciated!
Cheers,
Ilya Veer
______________________________________
Ilya Veer, M.Sc.
Leiden Institute for Brain and Cognition (LIBC)
Postzone C2-S
P.O. Box 9600
2300 RC Leiden
The Netherlands
Tel. +31 71 526 1375
--
Dr. med. Cornelius J. Werner
Department of Neurology
RWTH Aachen University
Pauwelsstr. 30
52074 Aachen
Germany
Institute of Neuroscience and Medicine
MR Physics - INM4
Research Centre Juelich
52425 Juelich
Germany
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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director, Oxford University FMRIB Centre
FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask]<mailto:[log in to unmask]> http://www.fmrib.ox.ac.uk/~steve
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