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Dr. Smith would know better than me, but I personally wouldn't do it using the dual regression script. It's not exactly the same as using the mean time course of the voxel mask as your regressor, and you don't really have control over things like whether or not you want to use a global signal regressor or if you would like to include covariates (e.g. motion parameters) in the model. I would either use fsl_glm manually or do it in FEAT as per http://www.fmrib.ox.ac.uk/Members/joreilly/how-to-run-a-ppi-analysis-in-feat I think, ultimately, you should use a technique you understand well so that you can interpret and defend your results. On Monday, May 21, 2012 21:44:29 you wrote: > Hello Benjamin and thanks a lot for your answer, I appreciate it! > > Though, I think you've answered a slightly different question. Perhaps I didn't make my question clear. I fact what I asked was in regards to a seed-based correlation analysis. That is, I already have the ROIs and I want to use them in the seed_based analysis, so I was wondering (which were my questions) > > 1) what is the best option for doing a seed-based correlation analysis of fMRI data in FSL, using FEAT (similar than a PPI analysis as in Castellanos at al., 2008 cited in my previous post) or using dual regression script as have suggested professor Stephen Smith in the following post: > > https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1112&L=fsl&P=R46634&1=fsl&9=A&I=-3&J=on&X=4FDE1362374539B9A8&Y=lojicas%40yahoo.com&d=No+Match%3BMatch%3BMatches&z=4 > > > 2)Why one analysis could be better than the other? > > > > I know that running a seed-based analysis in FEAT involves several steps, but in addition to that, Is there any other reason to choose dual_regression instead of running the analysis in FEAT? > > > I would greatly appreciate any input about these questions, > > > Lorena > __________________ > Lorena Jimenez-Castro, MD > Postdoctoral Fellow > UTHSCSA > > > ______________________ > Subject: Re: correlation analysis > > From: Benjamin Kay <[log in to unmask]> > > Reply-To: FSL - FMRIB's Software Library <[log in to unmask]> > > Date: Mon, 21 May 2012 20:43:38 -0400 > > > Reply > > Someone else may clarify this, but I think that dual regression is a tool to use with ICA, ICA being an alternative to seed-based voxel correlation. Seed based correlation is a farily straightfoward way to find regions connected with a seed of interest. ICA doesn't require you to specify a seed region, so it's advantageous when you don't really know what region is serving as the connectivity "hub" of your resting state network. When it comes to canonical networks like the default mode network, I don't think it makes *that* much of a difference since you're going to find the network either way. > > On Monday, May 21, 2012 10:17:14 you wrote: > > Dear FSL users (Especially professor Christian Beckmann), > > > > I sent the message below on May 8, 2012 9:54 AM. I have not received any answer yet; I would appreciate very much any input on this matter. My questions are: > > > > I would like to know, 1) what is the best option for doing a seed-based correlation analysis of fMRI data in FSL, using FEAT (as implemented in "Cingulate-precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder. > > Biol Psychiatry. 2008 Feb 1;63(3):332-7. Epub 2007 Sep 21.Castellanos FX et al.,") or running the dual-regression script ( applying fsl_glm to get the nuisance covariate time-courses and then randomize)? and > > 2) Why one analysis is better than the other? > > > > I know that running a seed-based analysis in FEAT involves several steps, but in addition to that, Is there any other reason to choose dual_regression instead of running the analysis in FEAT? > > > > Best > > Lorena > > > > > > __________________ > > Lorena Jimenez-Castro, MD > > Postdoctoral Fellow > > UTHSCSA > > > > > > > > > > > > > > --------------------------------- > > Print - Close Window > > Subject: [FSL] Seed-based analysis > > From: Lorena Jimenez-Castro ([log in to unmask]) > > To: [log in to unmask]; > > Date: Tuesday, May 8, 2012 9:54 AM > > > > > > Hello experts, > > > > I would like to know, what is the best option for doing a seed-based correlation analysis of fMRI data in FSL, using FEAT or running the dual-regression script ( applying fsl_glm to get the nuisance covariate time-courses and then randomize)? and > > Why one analysis is better than the other? > > > > I know that running a seed-based analysis in FEAT involves several steps, but in addition to that, Is there any other reason to choose dual_regression instead of running the analysis in FEAT? > > > > Thank you very much > > > > > > Lorena Jimenez-Castro, MD >