Hi Everyone, Thanks a lot for this great discussion! I've learned a lot from it. Sorry for the delayed response - to clear this up, I'm interested in using already parcellated functional connectivity matrices. The data Im planning on using is from the Resting State fMRI 1 preprocessed in the 500 Subjects + MEG2.
So I could parcellate each of the 4 NIFTIs (i.e. the 2 runs and the 2 phase encoding directions) into ROIs, and correlate pairs of regional time series to get an FC matrix for each of the 4. And then, based on Michael's advice, average the 4 FC matrices, using the fisher's r to z transform. In general, using these parcellated matrices, I shouldn't have a problem with computational power. Thanks, Joelle On Wed, Nov 25, 2015 at 12:40 PM, Harms, Michael <[email protected]> wrote: > > Ok, but I thought we were talking about correlations here? Another reason > for Joelle to be explicit about what she is wanting to do. > > -- > 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: [email protected] > > From: Stephen Smith <[email protected]> > Date: Wednesday, November 25, 2015 11:34 AM > To: "Harms, Michael" <[email protected]> > Cc: Timothy Coalson <[email protected]>, Greg Burgess <[email protected]>, > "Elam, Jennifer" <[email protected]>, "[email protected]" < > [email protected]> > Subject: Re: [HCP-Users] Phase Encoding left-to-right and right-to-left > > Hi Michael - for raw covariances - summing covariances is equivalent to > temp concat first. > Cheers > > > > On 25 Nov 2015, at 17:29, Harms, Michael <[email protected]> wrote: > > > To Steve's point and the issue of memory: A critical distinction is > whether you are intending to work with dense connectomes or parcellated > connectomes. In the context of parcellated connectomes, both Steve and > myself have found a small advantage in reproducibility if you compute a > parcellated "netmat" for each resting state run, convert those using > r-to-z, and then average those across the 4 resting state runs for a > subject (if you want as output a single parcellated netmat per subject). > In fact, that is how the netmats that are distributed as part of the "PTN" > from ConnectomeDB were themselves created. > > In the context of dense connectomes, generating a dense connectome per run > is a different sort of beast. You can do it (I've done it) using > -cifti-correlation and then average with -cifti-average. But to my > knowledge, no one has looked at whether there is a small reproducibility > advantage to that approach as well with dense connectomes, which is why I > think that most subject specific dense connectomes have probably been > created via the 'concat' approach outlined on the wiki. > > 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 63110Email: [email protected] > > From: Timothy Coalson <[email protected]> > Date: Tuesday, November 24, 2015 4:23 PM > To: Greg Burgess <[email protected]> > Cc: "Elam, Jennifer" <[email protected]>, "[email protected]" < > [email protected]> > Subject: Re: [HCP-Users] Phase Encoding left-to-right and right-to-left > > If you are using -cifti-correlation, there is a -mem-limit option for this > purpose, so there isn't a required minimum memory to do it (even in matlab > where everything has to be in memory, the 90k x 4.8k timeseries input pales > in comparison to the 90k x 90k output). If you are doing everything in > matlab, then the averaging of two 90k x 90k dconns is going to require more > memory than any reasonable concatenated correlation. > > The -cifti-average command should use almost no memory regardless of file > size, as long as you don't overwrite one of the inputs with the output. > > Tim > > > On Tue, Nov 24, 2015 at 2:23 PM, Greg Burgess <[email protected]> wrote: > >> I suggested below that Joelle could average Fisher’s z-transformed >> correlation coefficients (derived from each run within-subject), or treat >> the multiple runs as within-subjects repeated measures. >> >> The idea was that computing correlations between timeseries with 4800 >> time points will take four times as much RAM as using only 1200 time >> points. For folks with limited RAM, averaging the correlation estimates may >> be a more feasible option. >> >> --Greg >> >> ____________________________________________________________________ >> Greg Burgess, Ph.D. >> Staff Scientist, Human Connectome Project >> Washington University School of Medicine >> Department of Anatomy and Neurobiology >> Phone: 314-362-7864 >> Email: [email protected] >> >> > On Nov 24, 2015, at 1:08 PM, Stephen Smith <[email protected]> >> wrote: >> > >> > I think maybe we need to be explicit about exactly what we're talking >> about averaging? >> > Cheers. >> > >> > -------------------- >> > Stephen M. Smith, Professor of Biomedical Engineering >> > Head of Analysis, Oxford University FMRIB Centre >> > >> > FMRIB, JR Hospital, Headington, >> > Oxford. OX3 9 DU, UK >> > +44 (0) 1865 222726 (fax 222717) >> > [email protected] >> > http://www.fmrib.ox.ac.uk/~steve >> > ---------------------- >> > >> >> On 24 Nov 2015, at 19:03, Greg Burgess <[email protected]> wrote: >> >> >> >> It’s less RAM-intensive since you only need to load one timeseries at >> a time. >> >> >> >> --Greg >> >> >> >> ____________________________________________________________________ >> >> Greg Burgess, Ph.D. >> >> Staff Scientist, Human Connectome Project >> >> Washington University School of Medicine >> >> Department of Anatomy and Neurobiology >> >> Phone: 314-362-7864 >> >> Email: [email protected] >> >> >> >>> On Nov 24, 2015, at 12:29 PM, Glasser, Matthew <[email protected]> >> wrote: >> >>> >> >>> I'm not sure what benefit you'd get from averaging the FCs across >> runs within a subject. That just sounds more computationally intensive. >> >>> >> >>> Peace, >> >>> >> >>> Matt. >> >>> >> >>> >> >>> From: Joelle Zimmermann <[email protected]> >> >>> Sent: Tuesday, November 24, 2015 11:55 AM >> >>> To: Glasser, Matthew >> >>> Cc: Greg Burgess; Elam, Jennifer; [email protected] >> >>> Subject: Re: [HCP-Users] Phase Encoding left-to-right and >> right-to-left >> >>> >> >>> Hi Matt, >> >>> >> >>> Glad you do point that out, because I was previously looking at the >> Resting State fMRI 1 Preprocessed, but the Resting State fMRI FIX-Denoised >> (Compact) is readily available. So I guess for that all I'll need to do is >> demean and variance normalize, and/or average the two FCs. >> >>> >> >>> Thanks, >> >>> Joelle >> >>> >> >>> On Tue, Nov 24, 2015 at 12:19 PM, Glasser, Matthew < >> [email protected]> wrote: >> >>> Indeed I was assuming you were using FIX cleaned data. I wouldn't >> recommend not using FIX cleaned data unless you are testing other clean up >> approaches. >> >>> >> >>> Peace, >> >>> >> >>> Matt. >> >>> ________________________________________ >> >>> From: Joelle Zimmermann [[email protected]] >> >>> Sent: Tuesday, November 24, 2015 11:14 AM >> >>> To: Greg Burgess >> >>> Cc: Glasser, Matthew; Elam, Jennifer; [email protected] >> >>> Subject: Re: [HCP-Users] Phase Encoding left-to-right and >> right-to-left >> >>> >> >>> Hi Greg, >> >>> >> >>> Thanks for your response. Indeed, I was considering that myself, to >> compute the FCs separately and average the LR and RL. >> >>> >> >>> Thanks, >> >>> Joelle >> >>> >> >>> On Tue, Nov 24, 2015 at 11:56 AM, Greg Burgess <[email protected] >> <mailto:[email protected]>> wrote: >> >>> Hi Joelle, >> >>> >> >>> In addition to demeaning and possibly variance normalization, it is >> probably a good idea to detrend each run separately using a linear detrend >> or a high pass filter before concatenation. (FIX-preprocessed data already >> includes a 2000s high pass filter.) >> >>> >> >>> Another option that is not described on the wiki (yet) is to compute >> correlations separately for each run, and then average the Fisher’s >> z-transformed correlation coefficients, or treat the multiple runs as >> within-subjects repeated measures. >> >>> >> >>> --Greg >> >>> >> >>> ____________________________________________________________________ >> >>> Greg Burgess, Ph.D. >> >>> Staff Scientist, Human Connectome Project >> >>> Washington University School of Medicine >> >>> Department of Anatomy and Neurobiology >> >>> Phone: 314-362-7864<tel:314-362-7864> >> >>> Email: [email protected]<mailto:[email protected]> >> >>> >> >>>> On Nov 23, 2015, at 4:40 PM, Glasser, Matthew <[email protected] >> <mailto:[email protected]>> wrote: >> >>>> >> >>>> It doesn’t matter what order you concatenate the data in, but I >> would not recommend only analyzing the data of one phase encoding direction. >> >>>> >> >>>> Peace, >> >>>> >> >>>> Matt. >> >>>> >> >>>> From: <[email protected]<mailto: >> [email protected]>> on behalf of Joelle Zimmermann < >> [email protected]<mailto:[email protected]>> >> >>>> Date: Monday, November 23, 2015 at 12:48 PM >> >>>> To: "Elam, Jennifer" <[email protected]<mailto:[email protected]>> >> >>>> Cc: "[email protected]<mailto: >> [email protected]>" <[email protected]<mailto: >> [email protected]>> >> >>>> Subject: Re: [HCP-Users] Phase Encoding left-to-right and >> right-to-left >> >>>> >> >>>> Hi Jennifer and Matt, >> >>>> >> >>>> Thanks for your help. I have a few clarification questions below: >> >>>> Does it matter in which order I concatenate the LR and the RL >> .nii's? My ultimate goal is to create a functional connectivity matrix from >> the time series. >> >>>> #3 in the link you sent describes that there are 4 runs per subject. >> Is this the REST 1, and REST 2, each with LR and RL phase encoding >> directions? >> >>>> Would using only one phase encoding direction (i.e. do analysis on >> LR) expect to effect the results? >> >>>> >> >>>> Thanks, >> >>>> Joelle >> >>>> >> >>>>> On Mon, Nov 23, 2015 at 1:17 PM, Jennifer Elam <[email protected] >> <mailto:[email protected]>> wrote: >> >>>>> #3 on >> https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ may be >> of help. >> >>>>> >> >>>>> Best, >> >>>>> Jenn >> >>>>> >> >>>>> Jennifer Elam, Ph.D. >> >>>>> Outreach Coordinator, Human Connectome Project >> >>>>> Washington University School of Medicine >> >>>>> Department of Anatomy and Neurobiology, Box 8108 >> >>>>> 660 South Euclid Avenue >> >>>>> St. Louis, MO 63110 >> >>>>> 314-362-9387<tel:314-362-9387> >> >>>>> [email protected]<mailto:[email protected]> >> >>>>> www.humanconnectome.org<http://www.humanconnectome.org> >> >>>>> >> >>>>> From:[email protected]<mailto: >> from%[email protected]> [mailto: >> [email protected]<mailto: >> [email protected]>] On Behalf Of Glasser, Matthew >> >>>>> Sent: Monday, November 23, 2015 12:16 PM >> >>>>> To: Joelle Zimmermann; [email protected]<mailto: >> [email protected]> >> >>>>> Subject: Re: [HCP-Users] Phase Encoding left-to-right and >> right-to-left >> >>>>> >> >>>>> >> >>>>> >> >>>>> Usually you concatenate them temporally after demeaning (and >> perhaps variance normalizing). >> >>>>> >> >>>>> >> >>>>> >> >>>>> Peace, >> >>>>> >> >>>>> >> >>>>> >> >>>>> Matt. >> >>>>> >> >>>>> >> >>>>> >> >>>>> From:[email protected]<mailto: >> from%[email protected]> < >> [email protected]<mailto: >> [email protected]>> on behalf of Joelle Zimmermann < >> [email protected]<mailto:[email protected]>> >> >>>>> Sent: Monday, November 23, 2015 11:33 AM >> >>>>> To: [email protected]<mailto: >> [email protected]> >> >>>>> Subject: [HCP-Users] Phase Encoding left-to-right and right-to-left >> >>>>> >> >>>>> >> >>>>> >> >>>>> Hi all, >> >>>>> >> >>>>> >> >>>>> >> >>>>> Would anyone be able to explain a bit more about the phase-encoding >> directions LR and RL for the (preprocessed) REST1 session data from 500 >> subjects +MEG2? I understand that LR is left to right and RL is right to >> left. >> >>>>> >> >>>>> >> >>>>> >> >>>>> I'm wondering, are these meant to be somehow combined, or is only >> one of these typically chosen? >> >>>>> >> >>>>> >> >>>>> >> >>>>> Thanks, >> >>>>> >> >>>>> Joelle >> >>>>> >> >>>>> >> >>>>> >> >>>>> >> >>>>> >> >>>>> >> http://www.humanconnectome.org/documentation/Q1/data-in-this-release.html >> >>>>> >> >>>>> Q1 Data Release: About the Dataset | Human Connectome Project >> >>>>> 76 healthy adult subjects in the age range 22 – 35 participated in >> the first quarter of data collection. These include 68 subjects with data >> from all or nearly all ... >> >>>>> Read more... >> >>>>> >> >>>>> >> >>>>> _______________________________________________ >> >>>>> HCP-Users mailing list >> >>>>> [email protected]<mailto:[email protected]> >> >>>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> >>>>> >> >>>>> _______________________________________________ >> >>>>> HCP-Users mailing list >> >>>>> [email protected]<mailto:[email protected]> >> >>>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> >>>> >> >>>> _______________________________________________ >> >>>> HCP-Users mailing list >> >>>> [email protected]<mailto:[email protected]> >> >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> >>>> _______________________________________________ >> >>>> HCP-Users mailing list >> >>>> [email protected]<mailto:[email protected]> >> >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> >>> >> >>> >> >>> >> >>> ________________________________ >> >>> The materials in this message are private and may contain Protected >> Healthcare Information or other information of a sensitive nature. If you >> are not the intended recipient, be advised that any unauthorized use, >> disclosure, copying or the taking of any action in reliance on the contents >> of this information is strictly prohibited. If you have received this email >> in error, please immediately notify the sender via telephone or return mail. >> >>> >> >>> >> >>> The materials in this message are private and may contain Protected >> Healthcare Information or other information of a sensitive nature. If you >> are not the intended recipient, be advised that any unauthorized use, >> disclosure, copying or the taking of any action in reliance on the contents >> of this information is strictly prohibited. If you have received this email >> in error, please immediately notify the sender via telephone or return mail. >> >> >> >> >> >> _______________________________________________ >> >> HCP-Users mailing list >> >> [email protected] >> >> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> >> >> _______________________________________________ >> HCP-Users mailing list >> [email protected] >> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> > > _______________________________________________ > HCP-Users mailing list > [email protected] > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > > > ------------------------------ > The materials in this message are private and may contain Protected > Healthcare Information or other information of a sensitive nature. If you > are not the intended recipient, be advised that any unauthorized use, > disclosure, copying or the taking of any action in reliance on the contents > of this information is strictly prohibited. If you have received this email > in error, please immediately notify the sender via telephone or return mail. > _______________________________________________ > HCP-Users mailing list > [email protected] > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > > > > --------------------------------------------------------------------------- > Stephen M. Smith, Professor of Biomedical Engineering > Head of Analysis, Oxford University FMRIB Centre > > FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK > +44 (0) 1865 222726 (fax 222717) > [email protected] http://www.fmrib.ox.ac.uk/~steve > --------------------------------------------------------------------------- > > Stop the cultural destruction of Tibet <http://smithinks.net> > > > > > > > ------------------------------ > > The materials in this message are private and may contain Protected > Healthcare Information or other information of a sensitive nature. If you > are not the intended recipient, be advised that any unauthorized use, > disclosure, copying or the taking of any action in reliance on the contents > of this information is strictly prohibited. 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