Re: [HCP-Users] Phase Encoding left-to-right and right-to-left

[Harms, Michael]

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  63110 Email: mha...@wustl.edu From: Timothy Coalson <tsc...@mst.edu> Date: Tuesday, November 24, 2015 4:23 PM To: Greg Burgess <gcburg...@gmail.com> Cc: "Elam, Jennifer" <e...@wustl.edu>, "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> 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 <gcburg...@gmail.com> 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: gburg...@wustl.edu > On Nov 24, 2015, at 1:08 PM, Stephen Smith <st...@fmrib.ox.ac.uk> 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) > st...@fmrib.ox.ac.uk > http://www.fmrib.ox.ac.uk/~steve > ---------------------- > >> On 24 Nov 2015, at 19:03, Greg Burgess <gcburg...@gmail.com> 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: gburg...@wustl.edu >> >>> On Nov 24, 2015, at 12:29 PM, Glasser, Matthew <glass...@wustl.edu> 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 <joelle.t.zimmerm...@gmail.com> >>> Sent: Tuesday, November 24, 2015 11:55 AM >>> To: Glasser, Matthew >>> Cc: Greg Burgess; Elam, Jennifer; hcp-users@humanconnectome.org >>> 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 <glass...@wustl.edu> 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 [joelle.t.zimmerm...@gmail.com] >>> Sent: Tuesday, November 24, 2015 11:14 AM >>> To: Greg Burgess >>> Cc: Glasser, Matthew; Elam, Jennifer; hcp-users@humanconnectome.org >>> 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 <gcburg...@gmail.com<mailto:gcburg...@gmail.com>> 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: gburg...@wustl.edu<mailto:gburg...@wustl.edu> >>> >>>> On Nov 23, 2015, at 4:40 PM, Glasser, Matthew <glass...@wustl.edu<mailto:glass...@wustl.edu>> 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: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Joelle Zimmermann <joelle.t.zimmerm...@gmail.com<mailto:joelle.t.zimmerm...@gmail.com>> >>>> Date: Monday, November 23, 2015 at 12:48 PM >>>> To: "Elam, Jennifer" <e...@wustl.edu<mailto:e...@wustl.edu>> >>>> Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> >>>> 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 <el...@pcg.wustl.edu<mailto:el...@pcg.wustl.edu>> 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> >>>>> el...@pcg.wustl.edu<mailto:el...@pcg.wustl.edu> >>>>> www.humanconnectome.org<http://www.humanconnectome.org> >>>>> >>>>> From:hcp-users-boun...@humanconnectome.org<mailto:from%3ahcp-users-boun...@humanconnectome.org> [mailto:hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>] On Behalf Of Glasser, Matthew >>>>> Sent: Monday, November 23, 2015 12:16 PM >>>>> To: Joelle Zimmermann; hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org> >>>>> 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:hcp-users-boun...@humanconnectome.org<mailto:from%3ahcp-users-boun...@humanconnectome.org> <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Joelle Zimmermann <joelle.t.zimmerm...@gmail.com<mailto:joelle.t.zimmerm...@gmail.com>> >>>>> Sent: Monday, November 23, 2015 11:33 AM >>>>> To: hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org> >>>>> 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 >>>>> HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> >>>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>>>> >>>>> _______________________________________________ >>>>> HCP-Users mailing list >>>>> HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> >>>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>>> >>>> _______________________________________________ >>>> HCP-Users mailing list >>>> HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>>> _______________________________________________ >>>> HCP-Users mailing list >>>> HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> >>>> 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. 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