Not only that, but just because a given physiological trace exists, doesn't necessarily mean that it is a *good* trace.  There is going to be considerable variability in the quality of the physiological measurements, which presents a challenge in using them in a large scale study.  I'm sure that Greg will comment more when he has a chance.

cheers,
-MH

-- 
Michael Harms, Ph.D.
-----------------------------------------------------------
Conte Center for the Neuroscience of Mental Disorders
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid Ave. Tel: 314-747-6173
St. Louis, MO  63110 Email: mha...@wustl.edu

From: <Glasser>, Matt Glasser <glass...@wusm.wustl.edu>
Date: Monday, February 16, 2015 10:10 AM
To: Stephen Smith <st...@fmrib.ox.ac.uk>, Miriam Klein-Flügge <miriam.klein-flu...@psy.ox.ac.uk>
Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Incorporating physiological monitoring data

Note that a major reason we didn’t use these physiological confound regressors was they don’t exist for every subject, so be sure to select a subset of subjects that have them.  We’d also be interested to know if you found they were helpful.

Peace,

Matt.

From: Stephen Smith <st...@fmrib.ox.ac.uk>
Date: Monday, February 16, 2015 at 8:05 AM
To: Miriam Klein-Flügge <miriam.klein-flu...@psy.ox.ac.uk>
Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Incorporating physiological monitoring data

Hi - I think you would probably be best off taking the FIX-cleaned version of the data, and then apply additional confound regressors if they will help.  Don't forget to apply the same highpass filter (to those regressors) that was applied already in the data preproc, before you use them.

Cheers.



On 16 Feb 2015, at 13:35, Miriam Klein-Flügge <miriam.klein-flu...@psy.ox.ac.uk> wrote:

Dear all,

Is it correct that until now the physiological monitoring data is not made use of in the preprocessing of the rfMRI data? I would like to correct for cardiac and respiratory signals and wondered how to best do that. I can see that FIX-denoising probably takes care of this type of noise but I am particularly interested in looking at the brain stem and in my experience, including physiological regressors in the preprocessing makes a big difference there.

Would you recommend using the spatially (minimally) pre-processed rfMRI data, performing the high-pass filtering on it myself and then incorporating the physiological regressors at that stage, or is there a better stage at which to do it? Also, is there a standard procedure for regressing out the physiological regressors that you can recommend?

Many thanks in advance!

Kind regards,

Miriam

-- 
Miriam Klein-Flügge
Sir Henry Wellcome Postdoctoral Fellow
Department of Experimental Psychology
University of Oxford






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