[HCP-Users] question about link to behavioural measures docs
Hi HCPers, I am looking for a link to the documentation for citation for the following behavioural measures (see below). I had been referring to the following link, but it looks like that is now expired: https://wiki.humanconnectome.org/display/PublicData/HCP+Data+Dictionary+Public-+500+Subject+Release I found also the following, however, this doesn't seem to include documentation for all of the measures: https://wiki.humanconnectome.org/display/PublicData/HCP+Data+Dictionary+Public-+Updated+for+the+1200+Subject+Release Any pointers would be much appreciated. Thanks, Joelle ListSort_AgeAdj PicSeq_AgeAdj CardSort_AgeAdj Flanker_AgeAdj ProcSpeed_AgeAdj WM_Task_2bk_Acc WM_Task_2bk_Median_RT WM_Task_0bk_Acc WM_Task_0bk_Median_RT PMAT24_A_CR PMAT24_A_RTCR ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] motion parameters
Hi HCPers, I was wondering where I can find an average head motion parameter for each subject? Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] regression of potentially confounding variables
Hi HCPers, My goal is to look at variability of SC and FC across subject... I was wondering what would be recommended as regressors? In Stephen Smith's Nature Neuroscience 2015 paper looking at FC and cognition, the following was regressed: 1. Acquisition reconstruction software version (as an improved MRI reconstruction method was implemented in the third quarter of acquisition year 1). 2. A summary statistic quantifying average subject head motion during the resting-state fMRI acquisitions (this is the average, across all timepoints, of the timepoint-to-timepoint head motion, that measure being the linear distance moved, averaged across the head). 3. Weight. 4. Height. 5. Blood pressure – systolic. 6. Blood pressure – diastolic. 7. Hemoglobin A1C measured in blood. 8. The cube-root of total brain volume (including ventricles), as estimated by FreeSurfer. 9. The cube-root of total intracranial volume, as estimated by FreeSurfer. I'm thinking of going along those lines any thoughts? Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] hcp publications
Hi HCPers, Is there a list out there of publications with HCP data ? I'm aware of the few main reference HCP publications, but looking beyond that... Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] variation across connectomes
cool thank you. The MegaTrawl was done on the FC - subject measures only right? Is there any such analysis coming up for SC - subject measures? On Sat, Apr 29, 2017 at 9:46 PM, Harms, Michael <mha...@wustl.edu> wrote: > > Hi, > Have you read the documentation for the MegaTrawl? > > 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 <(314)%20747-6173> > St. Louis, MO 63110 Email: mha...@wustl.edu > > From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle > Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Saturday, April 29, 2017 at 10:30 AM > To: "Glasser, Matthew" <glass...@wustl.edu> > Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > > Subject: Re: [HCP-Users] variation across connectomes > > thanks Matt. Could you explain a bit the 'Correlation/prediction results > for subject measures' ? > > are those the measures that predict variation across subjects for the > different components? which measures predict the variation most strongly? > > apologies for the basic questions - im quite new to the technique. > > On Sat, Apr 29, 2017 at 10:52 AM, Glasser, Matthew <glass...@wustl.edu> > wrote: > >> Undoubtably. Perhaps the megatrawl would be of interest: >> >> >> https://db.humanconnectome.org/megatrawl/ >> >> >> Peace, >> >> >> Matt. >> -- >> *From:* Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> >> *Sent:* Saturday, April 29, 2017 9:15:31 AM >> *To:* Glasser, Matthew >> *Cc:* hcp-users@humanconnectome.org >> *Subject:* Re: [HCP-Users] variation across connectomes >> >> Not necessarily.. Just curious where the variation comes from whether it >> can be attributed to particular variables. I'm doing a PCA for variation >> across subject connectomes (for ex for SC), see a "common" component, but >> there are additional components, some of which for example correlate very >> strongly with age. And i want to check if there's other such variables that >> may explain some of the additional components. >> >> Thanks, >> Joelle >> >> On Fri, Apr 28, 2017 at 6:12 PM, Glasser, Matthew <glass...@wustl.edu> >> wrote: >> >>> What is it that you are trying to do? Control for uninteresting sources >>> of variance? >>> >>> Peace, >>> >>> Matt. >>> >>> From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle >>> Zimmermann <joelle.t.zimmerm...@gmail.com> >>> Date: Friday, April 28, 2017 at 2:17 PM >>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Subject: [HCP-Users] variation across connectomes >>> >>> Hi HCPers, >>> >>> I'm looking at variation across SC and FC connectomes of subjects. I was >>> wondering due to which variables we could potentially expect variability >>> across subjects to arise? >>> >>> I've looked into acquisition, fmri reconstruction version, and age as >>> potential factors of variation. Any other reasonable ones? >>> >>> Thanks, >>> Joelle >>> >>> ___ >>> HCP-Users mailing list >>> 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 i
Re: [HCP-Users] variation across connectomes
Not necessarily.. Just curious where the variation comes from whether it can be attributed to particular variables. I'm doing a PCA for variation across subject connectomes (for ex for SC), see a "common" component, but there are additional components, some of which for example correlate very strongly with age. And i want to check if there's other such variables that may explain some of the additional components. Thanks, Joelle On Fri, Apr 28, 2017 at 6:12 PM, Glasser, Matthew <glass...@wustl.edu> wrote: > What is it that you are trying to do? Control for uninteresting sources > of variance? > > Peace, > > Matt. > > From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle > Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Friday, April 28, 2017 at 2:17 PM > To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > Subject: [HCP-Users] variation across connectomes > > Hi HCPers, > > I'm looking at variation across SC and FC connectomes of subjects. I was > wondering due to which variables we could potentially expect variability > across subjects to arise? > > I've looked into acquisition, fmri reconstruction version, and age as > potential factors of variation. Any other reasonable ones? > > Thanks, > Joelle > > ___ > HCP-Users mailing list > 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. > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] variation across connectomes
Hi HCPers, I'm looking at variation across SC and FC connectomes of subjects. I was wondering due to which variables we could potentially expect variability across subjects to arise? I've looked into acquisition, fmri reconstruction version, and age as potential factors of variation. Any other reasonable ones? Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] comparison across acquisitions
thanks :) On Thu, Apr 27, 2017 at 3:01 PM, Harms, Michael <mha...@wustl.edu> wrote: > > That means that the collection of their fMRI spanned the date of the > change in the recon algorithm, so some was reconned with the “r177” > algorithm, and some with the “r227” algorithm. > > 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 <(314)%20747-6173> > St. Louis, MO 63110 Email: mha...@wustl.edu > > From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle > Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Thursday, April 27, 2017 at 1:50 PM > To: "Glasser, Matthew" <glass...@wustl.edu> > > Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > Subject: Re: [HCP-Users] comparison across acquisitions > > One more question about this - a few subjects have: r177 r227 for the fMRI > recon. Does this mean both were done? Which of the two was used for these > subjects for the S900 release? > > Thanks, > Joelle > > > > On Wed, Apr 26, 2017 at 2:05 PM, Glasser, Matthew <glass...@wustl.edu> > wrote: > >> Yes. >> >> Peace, >> >> Matt. >> >> From: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> >> Date: Wednesday, April 26, 2017 at 1:03 PM >> >> To: Matt Glasser <glass...@wustl.edu> >> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >> Subject: Re: [HCP-Users] comparison across acquisitions >> >> Thanks Michael and Matt. >> >> Were they all collected at the same site? If not, I'd expect this to make >> some difference. >> >> On Wed, Apr 26, 2017 at 2:00 PM, Glasser, Matthew <glass...@wustl.edu> >> wrote: >> >>> It is a variable in the .csv you download out of the database. >>> Diffusion isn’t affected by this, just fMRI because diffusion was processed >>> with the same recon version (old scans were reprocessed). >>> >>> Peace, >>> >>> Matt. >>> >>> From: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> >>> Date: Wednesday, April 26, 2017 at 12:58 PM >>> To: Matt Glasser <glass...@wustl.edu> >>> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Subject: Re: [HCP-Users] comparison across acquisitions >>> >>> Thanks for your reply Matt. >>> >>> By version number, do you mean the "acquisition" - that is, the Q#? >>> >>> So you expect the fMRI to be more different across acquisitions than the >>> diffusion? >>> >>> Do you recall at which acquisition the image reconstruction version >>> change occurred? >>> >>> Joelle >>> >>> On Wed, Apr 26, 2017 at 1:51 PM, Glasser, Matthew <glass...@wustl.edu> >>> wrote: >>> >>>> The main thing to consider was a an image reconstruction version change >>>> that occurred relatively early in the project. Diffusion data were >>>> retroreconned (and so all data have the same version), but fMRI raw data >>>> had not been saved and could not be retroreconned. We advise using a >>>> covariate of no interest for version number. >>>> >>>> Peace, >>>> >>>> Matt. >>>> >>>> From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle >>>> Zimmermann <joelle.t.zimmerm...@gmail.com> >>>> Date: Wednesday, April 26, 2017 at 12:48 PM >>>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>>> Subject: [HCP-Users] comparison across acquisitions >>>> >>>> Hi HCPers, >>>> >>>> I'm working with structural and functional connectomes from the S900 >>>> HCP. I'm wondering how the different acquisitions (ie Q1 Q2 etc) and >>>> releases would affect comparison across all SCs for example. Was data >>>> collected at different sites for example? - which may affect comparison >>>> across acquisitions. >>>> >>>> See below info pasted from behaviour spreadsheet. Do I understand >>>> correctly the "Release" column is when subjects were first released. but if >>>> i am getting all data from the S900, then I shoul
Re: [HCP-Users] comparison across acquisitions
One more question about this - a few subjects have: r177 r227 for the fMRI recon. Does this mean both were done? Which of the two was used for these subjects for the S900 release? Thanks, Joelle On Wed, Apr 26, 2017 at 2:05 PM, Glasser, Matthew <glass...@wustl.edu> wrote: > Yes. > > Peace, > > Matt. > > From: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Wednesday, April 26, 2017 at 1:03 PM > > To: Matt Glasser <glass...@wustl.edu> > Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > Subject: Re: [HCP-Users] comparison across acquisitions > > Thanks Michael and Matt. > > Were they all collected at the same site? If not, I'd expect this to make > some difference. > > On Wed, Apr 26, 2017 at 2:00 PM, Glasser, Matthew <glass...@wustl.edu> > wrote: > >> It is a variable in the .csv you download out of the database. Diffusion >> isn’t affected by this, just fMRI because diffusion was processed with the >> same recon version (old scans were reprocessed). >> >> Peace, >> >> Matt. >> >> From: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> >> Date: Wednesday, April 26, 2017 at 12:58 PM >> To: Matt Glasser <glass...@wustl.edu> >> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >> Subject: Re: [HCP-Users] comparison across acquisitions >> >> Thanks for your reply Matt. >> >> By version number, do you mean the "acquisition" - that is, the Q#? >> >> So you expect the fMRI to be more different across acquisitions than the >> diffusion? >> >> Do you recall at which acquisition the image reconstruction version >> change occurred? >> >> Joelle >> >> On Wed, Apr 26, 2017 at 1:51 PM, Glasser, Matthew <glass...@wustl.edu> >> wrote: >> >>> The main thing to consider was a an image reconstruction version change >>> that occurred relatively early in the project. Diffusion data were >>> retroreconned (and so all data have the same version), but fMRI raw data >>> had not been saved and could not be retroreconned. We advise using a >>> covariate of no interest for version number. >>> >>> Peace, >>> >>> Matt. >>> >>> From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle >>> Zimmermann <joelle.t.zimmerm...@gmail.com> >>> Date: Wednesday, April 26, 2017 at 12:48 PM >>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Subject: [HCP-Users] comparison across acquisitions >>> >>> Hi HCPers, >>> >>> I'm working with structural and functional connectomes from the S900 >>> HCP. I'm wondering how the different acquisitions (ie Q1 Q2 etc) and >>> releases would affect comparison across all SCs for example. Was data >>> collected at different sites for example? - which may affect comparison >>> across acquisitions. >>> >>> See below info pasted from behaviour spreadsheet. Do I understand >>> correctly the "Release" column is when subjects were first released. but if >>> i am getting all data from the S900, then I shouldn't care about this first >>> release? >>> >>> Thanks, >>> Joelle >>> >>> Subject Release Acquisition >>> 14 S900 Q06 >>> 100206 S900 Q11 >>> 100307 Q1 Q01 >>> 100408 Q3 Q03 >>> 100610 S900 Q08 >>> 101006 S500 Q06 >>> 101107 S500 Q06 >>> 101309 S500 Q06 >>> 101410 S500 Q06 >>> 101612 S900 Q11 >>> 101915 Q3 Q04 >>> >>> ___ >>> HCP-Users mailing list >>> 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 >>
Re: [HCP-Users] comparison across acquisitions
Thanks Michael and Matt. Were they all collected at the same site? If not, I'd expect this to make some difference. On Wed, Apr 26, 2017 at 2:00 PM, Glasser, Matthew <glass...@wustl.edu> wrote: > It is a variable in the .csv you download out of the database. Diffusion > isn’t affected by this, just fMRI because diffusion was processed with the > same recon version (old scans were reprocessed). > > Peace, > > Matt. > > From: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Wednesday, April 26, 2017 at 12:58 PM > To: Matt Glasser <glass...@wustl.edu> > Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > Subject: Re: [HCP-Users] comparison across acquisitions > > Thanks for your reply Matt. > > By version number, do you mean the "acquisition" - that is, the Q#? > > So you expect the fMRI to be more different across acquisitions than the > diffusion? > > Do you recall at which acquisition the image reconstruction version change > occurred? > > Joelle > > On Wed, Apr 26, 2017 at 1:51 PM, Glasser, Matthew <glass...@wustl.edu> > wrote: > >> The main thing to consider was a an image reconstruction version change >> that occurred relatively early in the project. Diffusion data were >> retroreconned (and so all data have the same version), but fMRI raw data >> had not been saved and could not be retroreconned. We advise using a >> covariate of no interest for version number. >> >> Peace, >> >> Matt. >> >> From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle >> Zimmermann <joelle.t.zimmerm...@gmail.com> >> Date: Wednesday, April 26, 2017 at 12:48 PM >> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >> Subject: [HCP-Users] comparison across acquisitions >> >> Hi HCPers, >> >> I'm working with structural and functional connectomes from the S900 HCP. >> I'm wondering how the different acquisitions (ie Q1 Q2 etc) and releases >> would affect comparison across all SCs for example. Was data collected at >> different sites for example? - which may affect comparison across >> acquisitions. >> >> See below info pasted from behaviour spreadsheet. Do I understand >> correctly the "Release" column is when subjects were first released. but if >> i am getting all data from the S900, then I shouldn't care about this first >> release? >> >> Thanks, >> Joelle >> >> Subject Release Acquisition >> 14 S900 Q06 >> 100206 S900 Q11 >> 100307 Q1 Q01 >> 100408 Q3 Q03 >> 100610 S900 Q08 >> 101006 S500 Q06 >> 101107 S500 Q06 >> 101309 S500 Q06 >> 101410 S500 Q06 >> 101612 S900 Q11 >> 101915 Q3 Q04 >> >> ___ >> HCP-Users mailing list >> 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. If you have received this email > in error, please immediately notify the sender via telephone or return mail. > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] comparison across acquisitions
Thanks for your reply Matt. By version number, do you mean the "acquisition" - that is, the Q#? So you expect the fMRI to be more different across acquisitions than the diffusion? Do you recall at which acquisition the image reconstruction version change occurred? Joelle On Wed, Apr 26, 2017 at 1:51 PM, Glasser, Matthew <glass...@wustl.edu> wrote: > The main thing to consider was a an image reconstruction version change > that occurred relatively early in the project. Diffusion data were > retroreconned (and so all data have the same version), but fMRI raw data > had not been saved and could not be retroreconned. We advise using a > covariate of no interest for version number. > > Peace, > > Matt. > > From: <hcp-users-boun...@humanconnectome.org> on behalf of Joelle > Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Wednesday, April 26, 2017 at 12:48 PM > To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > Subject: [HCP-Users] comparison across acquisitions > > Hi HCPers, > > I'm working with structural and functional connectomes from the S900 HCP. > I'm wondering how the different acquisitions (ie Q1 Q2 etc) and releases > would affect comparison across all SCs for example. Was data collected at > different sites for example? - which may affect comparison across > acquisitions. > > See below info pasted from behaviour spreadsheet. Do I understand > correctly the "Release" column is when subjects were first released. but if > i am getting all data from the S900, then I shouldn't care about this first > release? > > Thanks, > Joelle > > Subject Release Acquisition > 14 S900 Q06 > 100206 S900 Q11 > 100307 Q1 Q01 > 100408 Q3 Q03 > 100610 S900 Q08 > 101006 S500 Q06 > 101107 S500 Q06 > 101309 S500 Q06 > 101410 S500 Q06 > 101612 S900 Q11 > 101915 Q3 Q04 > > ___ > HCP-Users mailing list > 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. > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] comparison across acquisitions
Hi HCPers, I'm working with structural and functional connectomes from the S900 HCP. I'm wondering how the different acquisitions (ie Q1 Q2 etc) and releases would affect comparison across all SCs for example. Was data collected at different sites for example? - which may affect comparison across acquisitions. See below info pasted from behaviour spreadsheet. Do I understand correctly the "Release" column is when subjects were first released. but if i am getting all data from the S900, then I shouldn't care about this first release? Thanks, Joelle Subject Release Acquisition 14 S900 Q06 100206 S900 Q11 100307 Q1 Q01 100408 Q3 Q03 100610 S900 Q08 101006 S500 Q06 101107 S500 Q06 101309 S500 Q06 101410 S500 Q06 101612 S900 Q11 101915 Q3 Q04 ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] global signal regression on HCP ICA FIX denoised BOLD?
Thanks Stephen. Was there GSR done on the HCP data at any point for the non-denoised version? If I wanted to do GSR myself on the HCP data, are there any recommendations that the HCP group has? Or global signal regressors that have been already processed? Or is this something that is at the discretion of each researcher afterwards? On Thu, Jan 5, 2017 at 12:00 PM, Stephen Smith <st...@fmrib.ox.ac.uk> wrote: > Yes,. > Cheers. > > > On 5 Jan 2017, at 11:57, Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> > wrote: > > Hi HCPers, > > Is it correct that global signal regression was not done on the ICA FIX > denoised fmri BOLD data? > > Thanks, > Joelle > > ___ > HCP-Users mailing list > HCP-Users@humanconnectome.org > 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 <+44%201865%20222726> (fax 222717) > st...@fmrib.ox.ac.ukhttp://www.fmrib.ox.ac.uk/~steve > > --- > > Stop the cultural destruction of Tibet <http://smithinks.net> > > > > > > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] global signal regression on HCP ICA FIX denoised BOLD?
Hi HCPers, Is it correct that global signal regression was not done on the ICA FIX denoised fmri BOLD data? Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] Test-retest reliability / Intra vs inter subject variability of HCP data
Thank you all! Michael, why would you expect the two diffusion scans using the different phase encoding directions to be different? Or do you mean more as in that there is not enough time between 'test' and 'retest'? Joelle On Thu, Jan 28, 2016 at 10:13 PM, Harms, Michael <mha...@wustl.edu> wrote: > > There are about 45 subjects that went through the entire HCP protocol a > 2nd time that will be a good way to assess the reliability of the > diffusion data when released later this spring. > > Note that using one PE polarity as “test” and the other PE polarity as > “retest” would not really be testing the test/retest reliability of the > full diffusion protocol. > > 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: mha...@wustl.edu > > > > > On 1/28/16, 8:04 PM, "hcp-users-boun...@humanconnectome.org on behalf of > David Van Essen" <hcp-users-boun...@humanconnectome.org on behalf of > vanes...@wustl.edu> wrote: > > Data from several dozen test-retest subjects (I don’t recall the exact > number) is currently being processed and will be part of the S1200 > release, currently targeted for mid-spring. > > David VE > > > On Jan 28, 2016, at 6:52 PM, Glasser, Matthew <glass...@wustl.edu> > wrote: > > > > There is some data that was collected for full rescans of the entire > > protocol, however I don¹t know the release plans for this data. > > > > Peace, > > > > Matt. > > > > On 1/28/16, 3:10 PM, "hcp-users-boun...@humanconnectome.org on behalf of > > dgw" <hcp-users-boun...@humanconnectome.org on behalf of > > dgwake...@gmail.com> wrote: > > > >> Since most of HCP has each diffusion scan run twice (once each) with > >> different phase encode directions, you could analyze each of those > >> separately (only using the B0s from the opposite phase encode > >> direction). Then perform whatever test-retest tests you are interested > >> in. Note, that you will end up with slightly different masks using > >> this technique in eddy (I haven't been able to track down why). You > >> should try to come up with a way to control for this. > >> > >> hth > >> d > >> > >> On Thu, Jan 28, 2016 at 4:05 PM, Joelle Zimmermann > >> <joelle.t.zimmerm...@gmail.com> wrote: > >>> Hi HCPers. > >>> > >>> I'm curious about the test-retest reliability and the inter subject > >>> versus > >>> intra subject variability of the HCP resting functional and diffusion > >>> data, > >>> particularly whether anyone has looked at this in SC and FC > >>>connectomes? > >>> > >>> To check this out in the rsFC data is simple, using the two scans (pre > >>> and > >>> post), or alternatively splitting the time series in half to look at > >>> reproducibility. But what about SC derived from diffusion data, since > >>> diffusion was measured only once the intra subject variability/ test > >>> retest. > >>> Does anyone know of a systematic check of variability in the SC data? > >>> > >>> Thanks, > >>> Joelle > >>> > >>> ___ > >>> HCP-Users mailing list > >>> HCP-Users@humanconnectome.org > >>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users > >> ___ > >> HCP-Users mailing list > >> 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. > > > > ___ > > HCP-Users mailing list > > HCP-Users@humanconnectome.org > > http://lists.humanconnectome.org/mailman/listi
[HCP-Users] Test-retest reliability / Intra vs inter subject variability of HCP data
Hi HCPers. I'm curious about the test-retest reliability and the inter subject versus intra subject variability of the HCP resting functional and diffusion data, particularly whether anyone has looked at this in SC and FC connectomes? To check this out in the rsFC data is simple, using the two scans (pre and post), or alternatively splitting the time series in half to look at reproducibility. But what about SC derived from diffusion data, since diffusion was measured only once the intra subject variability/ test retest. Does anyone know of a systematic check of variability in the SC data? Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] ROI parcellation
Hi Michael and all, My goal is to use the aparc+aseg (in MNI from the standard Structural package 100307/MNINonLinear/aparc+aseg.nii.gz)as a parcellation for the volumetric 4D FIX extended clean data that's in MNI (100307/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000_clean.nii.gz). However, the aparc+aseg and the fMRI volumetric 4D data are of different dimensions and resolution. I'm assuming that the warp was really done in the same (MNI) template, but that the aparc+aseg parcellation was not resliced to match the 4D functional data? Is there another aparc+aseg that's of dimensions matching the volumetric 4D data (in MNINonLinear) that can be directly overlaid? Thanks, Joelle On Tue, Dec 15, 2015 at 1:02 PM, Harms, Michael <mha...@wustl.edu> wrote: > > Also, we encourage you to work in CIFTI-land so as to have a surface-based > analysis of the cortical data. But to answer your question, volumetric > versions of both those FS parcellations are available in each subject's > MNINonLinear folder; e.g., > 100307/MNINonLinear/aparc+aseg.nii.gz > 100307/MNINonLinear/aparc.a2009s+aseg.nii.gz > > Those particular files should be part of the standard Structural package. > > 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 > > > > On 12/15/15 11:51 AM, "Greg Burgess" <gcburg...@gmail.com> wrote: > > Hi Joelle, > > You should be aware of potential issues with using anatomically-defined > ROIs for rfMRI network analysis. > > Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., Webster, M., Beckmann, > C. F., Nichols, T. E., et al. (2011). Network modelling methods for FMRI. > NeuroImage, 54(2), 875–891. > http://doi.org/10.1016/j.neuroimage.2010.08.063 > > Gordon, E. M., Laumann, T. O., Adeyemo, B., Huckins, J. F., Kelley, W. M., > & Petersen, S. E. (2014). Generation and Evaluation of a Cortical Area > Parcellation from Resting-State Correlations. Cerebral Cortex. > http://doi.org/10.1093/cercor/bhu239 > > --Greg > > > Greg Burgess, Ph.D. > Staff Scientist, Human Connectome Project > Washington University School of Medicine > Department of Neuroscience > Phone: 314-362-7864 > Email: gburg...@wustl.edu > > On Dec 15, 2015, at 11:24 AM, Joelle Zimmermann < > joelle.t.zimmerm...@gmail.com> wrote: > Hi Michael, > Thanks! So currently, the 2 available parcellation schemes are the > Freesurfer Desikan-Killiany (aparc+aseg.mgz) and Destrieux > (aparc.a2009s+aseg.mgz) in the structural extended preprocessed/T1w/mri > folder? Im presuming these are in the subject's T1 individual subject > space. > Are you aware whether these parcellation schemes are already available in > the MNI standard space? The goal is to parcellate the functional BOLD data > (which are currently in MNI standard space; Ie in the FIX extended package, > the MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000_clean.nii). > Or alternatively, if you could point me to where the volumetric functional > BOLD data in T1 space is (I cannot locate it in the FIX extended package - > this only seems to have func already normalized to MNI), I could directly > apply the aparc+aseg parcellation (that's in T1 space) to this. > Thanks, > Joelle > On Tue, Dec 15, 2015 at 10:46 AM, Harms, Michael <mha...@wustl.edu> wrote: > Hi, > The only purely anatomical parcellation that is available currently are > those provided by FreeSurfer, which you seem to be familiar with. > If you are interested in a functional parcellation, there is the Gordon et > al. parcellation derived from non-HCP rfMRI data. A parcellation that > incorporates the myelin maps and rfMRI data and which is specifically > derived from a subset of HCP participants is in the works (from Matt G.) > 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: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Tuesday, December 15, 2015 9:35 AM > To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > Subject: [HCP-Users] ROI parcellation > Hi everyone, > Does HCP have a specific ROI parcellation that is co
Re: [HCP-Users] FIX-denoised
elements stopped working during the scan). One of the reasons we >> know there aren¹t global movement related effects being left in the HCP >> data is that regressing WM out doesn¹t do much (if there were, one would >> expect them to be picked up by the WM timeseries). CSF may be more >> correlated with physiological noise, but it isn¹t a very clean regressor >> for this (nor is WM). >> >> 2) Indeed there does appear to be global grey matter physiological noise >> which we need to separate from global neural signal. We are working on >> ways to do this (it is likely that we will want to investigate both >> external approaches like regressing physiological regressors out and >> internal approaches that attempt to separate physiological noise from the >> data itself). It would certainly be helpful if the HCP¹s physiological >> noise regressors were preprocessed for heart rate and respiratory end >> tidal volume traces and those regressors were released publicly. >> >> 3) I don¹t understand this. >> >> Peace, >> >> Matt. >> >> On 12/9/15, 5:39 PM, "hcp-users-boun...@humanconnectome.org on behalf of >> Greg Burgess" <hcp-users-boun...@humanconnectome.org on behalf of >> gcburg...@gmail.com> wrote: >> >> >Just a few comments: >> > >> >1) I agree with Maarten that FIX-denoising is effectively removing WM and >> >CSF components from the FIX timeseries data. My understanding is that >> >Matt Glasser has evaluated the incremental benefit for regressing the >> >(average) WM and CSF timeseries and concluded that there is no additional >> >benefit after FIX. I don¹t believe that anyone has tested whether >> >additional WM and CSF components (such as implemented in CompCor) can >> >remove noise variance above and beyond FIX, though, in theory, FIX should >> >capture those as well. >> > >> >2) Some analyses that I have conducted suggest that FIX denoising may >> >leave behind some proportion of physiological noise, especially that >> >which is more globally-distributed across gray matter. I am hoping to >> >investigate whether physiological regressors can remove that additional >> >proportion. >> > >> >3) It is probably important to regress physiological regressors, motion >> >regressors, and FIX noise regressors simultaneously from the timeseries. >> >Otherwise, the fit of some regressors to the timeseries will be worsened >> >by removing the other regressors from the timeseries. It might work to >> >regress motion and noise ICs from the physio regressors, and then regress >> >physio from the FIX timeseries, but I am not certain that it will (e.g., >> >for RETROICOR-type regressors). >> > >> >4) If you decide to investigate physiological regressors, please use >> >those release in the 900 subject packages, because the physiological >> >measures in the 500 subject release had a timing bug. There will be >> >additional information about the updated physiological measures coming in >> >the near future. >> > >> >--Greg >> > >> > >> >Greg Burgess, Ph.D. >> >Staff Scientist, Human Connectome Project >> >Washington University School of Medicine >> >Department of Neuroscience >> >Phone: 314-362-7864 >> >Email: gburg...@wustl.edu >> > >> >> On Dec 9, 2015, at 4:40 PM, Maarten Mennes <mennes.maar...@gmail.com> >> >>wrote: >> >> >> >> One could also argue that WM and CSF regression is not needed anymore >> >>if the FIX denoising worked as intended... Given that FIX will look for >> >>components that correlate with WM and CSF signal these signals are >> >>already regressed out if components were properly identified. The same >> >>is true for the physiological data. >> >> >> >> Note that this is different from a tool like ICA-AROMA which is not >> >>trained to identify WM/CSF/physiological components, in this case extra >> >>nuisance regression might effectively come in handy. But I don't see >> >>this need in FIX-denoised data. >> >> >> >> Or am I missing something obvious? >> >> >> >> Cheers, >> >> Maarten >> >> >> >> >> >> On Wed, Dec 9, 2015 at 11:10 PM, Harms, Michael <mha...@wustl.edu> >> >>wrote: >> >> >> >> See inline below. >> &
[HCP-Users] FIX-denoised
Hi everyone, I'm interested in using the FIX-denoised data, and am currently looking at the extended package, as I'm interested in the volumetric data. I'm wondering whether the motion parameters have already been regressed out from the FIX denoised rfMRI_REST1_LR_hp2000_clean.nii.gz? I'm assuming yes, that the FIX denoised actually already deals with this by separating the motion-related noise into a component and filtering that out of the signal? I assume so based on the following snippet from the manual describing FIX-ed data: "As part of this cleanup, we also used 24 confound timeseries derived from the motion estimation (the 6 rigid-body parameter timeseries, their backwards-looking temporal derivatives, plus all 12 resulting regressors squared — Satterthwaite et al., 2013). The motion parameters have the temporal highpass filtering applied to them and are then regressed out of the data aggressively, as they are not expected to contain variance of interest." Am I correct? Has white matter and/or cerebrospinal fluid been regressed already from the FIX denoised fMRI timeseries? Has physiological data (“rfMRI_REST1_LR_Physio_log”) already been regressed from the FIX denoised data? Any pointers would be much appreciated. Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] FIX-denoised
Hi Michael, Thanks for your help. I have a few more questions below.. Has an average timeseries for WM (and CSF) signal been already computed by HCP? Perhaps this is the "rfMRI_REST1_LR_WM.txt" and the "rfMRI_REST1_LR_CSF.txt" in the FIX extended package? Is there a recommended way of regressing these out? Related to my previous question: Has physiological data (“rfMRI_REST1_LR_Physio_log”) already been regressed from the FIX denoised data? I cannot actually find a rfMRI Physio log file in the FIX-ed dataset, I can only find this Physio log file in the minimally preprocessed dataset. I suppose I can use that one? But I'd assume there should be one in the FIX-ed dataset folder as well... Thanks, Joelle On Wed, Dec 9, 2015 at 2:43 PM, Harms, Michael <mha...@wustl.edu> wrote: > > Hi, > See inline below. > > -- > 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: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Wednesday, December 9, 2015 1:26 PM > To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > Subject: [HCP-Users] FIX-denoised > > Hi everyone, > > I'm interested in using the FIX-denoised data, and am currently looking at > the extended package, as I'm interested in the volumetric data. > > I'm wondering whether the motion parameters have already been regressed > out from the FIX denoised rfMRI_REST1_LR_hp2000_clean.nii.gz? > YES > > I'm assuming yes, that the FIX denoised actually already deals with this > by separating the motion-related noise into a component and filtering that > out of the signal? I assume so based on the following snippet from the > manual describing FIX-ed data: > "As part of this cleanup, we also used 24 confound timeseries derived from > the motion estimation (the 6 rigid-body parameter timeseries, their > backwards-looking temporal derivatives, plus all 12 resulting regressors > squared — Satterthwaite et al., 2013). The motion parameters have the > temporal highpass filtering applied to them and are then regressed out of > the data aggressively, as they are not expected to contain variance of > interest." > Am I correct? > YES > > Has white matter and/or cerebrospinal fluid been regressed already from > the FIX denoised fMRI timeseries? > NO > > Has physiological data (“rfMRI_REST1_LR_Physio_log”) already been > regressed from the FIX denoised data? > NO > > Any pointers would be much appreciated. > > Thanks, > Joelle > > > > > > > ___ > HCP-Users mailing list > 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. > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] Demographic and behavioral subject data
Hello everyone, I want to pick a group of subjects from the 500 subjects +MEG2 for which I will perform (rsfMRI and dMRI) analysis. These should be young, healthy, subjects that have no abnormalities and cognitively able. Does anyone have any pointers about how I can go weeding out subjects? Under "Subject Information" of all subjects, I can see a list of all subjects, where I can see age, release and gender. And when I click on the subject, I find a bunch of behavioral tests and their results for that subject. Should subjects from different releases be combined? Which is the most recent release? Are there certain scores for cognitive assessments that are considered to weed out the cognitively able, healthy subjects? Is this data available somewhere in a spreadsheet form, without having to go into each subject and scrolling though their various assessment scores? Anything would help. Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] Demographic and behavioral subject data
Hi Michael and Jennifer, Thank you both for your help, much appreciated. One remaining question - is there currently any cutoff for cognitive scores (i.e. for the MMSE for ex) for subjects being included in the 500 release dataset? Can't find mention of it in the ref manual, so Im guessing probably not. Thanks, Joelle On Mon, Nov 30, 2015 at 11:49 AM, Jennifer Elam <el...@pcg.wustl.edu> wrote: > Hi Joelle, > > All the HCP subjects are considered healthy young adults with no diagnosed > cognitive abnormalities. They do, of course, have a range of abilities and > scores on the behavioral tests we conduct. > > > > There is a lot of information in Chapter 1 of the current 500 Subjects > Reference Manual > <http://humanconnectome.org/documentation/S500/HCP_S500+MEG2_Release_Reference_Manual.pdf> > for navigating the behavioral data and for filtering subjects—please check > it out. There is also a “Download CSV button” at the upper right of the > subject Dashboard that will allow you to download all the open access > behavioral data in one spreadsheet. Look at the sections of the Reference > Manual on Restricted access data to see if you need to apply for access to > that data for your purposes. > > > > As detailed in the Introduction section of the Reference Manual, subjects > that were originally acquired or released in different quarters/releases > can be combined in analyses because we ran all subjects through the same > analysis pipelines as of the 500 subjects release (as long as you are using > data currently in ConnectomeDB, the S500 Connectome in a Box, or S500 S3 > Bucket data). Again, as stated in the Ref Manual Introduction, one thing > you should be aware of is that the fMRI data collected in Q1 and part of Q2 > was reconstructed with a slightly different reconstruction algorithm than > subsequent data. You can filter on Study Completion>Image Reconstruction > Info: 3T MR>3T MR fMRI Recon Version, if you think it might make a > difference to your analyses. > > > > In the upcoming 900 Subjects release (coming within the next couple of > weeks!), the new subject data will also be comparable to the 500 Subject > release data. Pipeline changes since the S500 release have been mostly > minor and have only added to the data available (more details to come). > > > > 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 > el...@pcg.wustl.edu > www.humanconnectome.org > > > > *From:* hcp-users-boun...@humanconnectome.org [mailto: > hcp-users-boun...@humanconnectome.org] *On Behalf Of *Joelle Zimmermann > *Sent:* Monday, November 30, 2015 10:27 AM > *To:* hcp-users@humanconnectome.org > *Subject:* [HCP-Users] Demographic and behavioral subject data > > > > Hello everyone, > > > > I want to pick a group of subjects from the 500 subjects +MEG2 for which > I will perform (rsfMRI and dMRI) analysis. These should be young, healthy, > subjects that have no abnormalities and cognitively able. > > > > Does anyone have any pointers about how I can go weeding out subjects? > Under "Subject Information" of all subjects, I can see a list of all > subjects, where I can see age, release and gender. And when I click on the > subject, I find a bunch of behavioral tests and their results for that > subject. > > > > Should subjects from different releases be combined? Which is the most > recent release? > > > > Are there certain scores for cognitive assessments that are considered to > weed out the cognitively able, healthy subjects? Is this data available > somewhere in a spreadsheet form, without having to go into each subject and > scrolling though their various assessment scores? > > > > Anything would help. > > Thanks, > > Joelle > > > > ___ > HCP-Users mailing list > HCP-Users@humanconnectome.org > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] Demographic and behavioral subject data
Hi Jennifer, Thanks a lot for your help, that's really useful. With regard to the reconstruction - I just wanted to clarify, and apologies if this is in the manual but I did not find it - When I filter by 'Study Completion' > 'Image Reconstruction' > 3T MR fMRI recon, I have 2 options - r177 and r227. Which is the more recent/ considered 'better' reconstruction method? I suspect that the r227 is better if I am interested in using both diffusion MRI data and fMRI data, as the r227 is available for both, whereas r177 is only available for fMRI data, and not for dMRI. Is that correct? Thanks, Joelle On Mon, Nov 30, 2015 at 1:48 PM, Jennifer Elam <el...@pcg.wustl.edu> wrote: > Hi Joelle, > > > > Here are the *HCP Inclusion Criteria*: > > Inclusion Criteria: > > No significant history of psychiatric disorder, substance abuse, > neurological, or cardiovascular disease > > -No person report of diagnosis by a treating physician > > -No hospitalization > > No pharmacologic or behavioral treatment (12 months duration or longer) by > a specialty-trained physician (psychiatrist, neurologist, cardiologist) or > therapist (e.g., psychologist, social worker) > > -Childhood ADHD with no current treatment is allowed > > -Transient childhood seizures allowed (clarify what type) > > -Migraines allowed if not taking daily psychoactive > medications > > Age 22 to 35 > > Ability to give valid informed consent > > MMSE score of 24 or above > > > > Here are the *HCP Exclusion Criteria*: > > Two or more non-provoked (e.g., not due to fever) seizures or a diagnosis > of epilepsy > > Any genetic disorder, such as Cystic Fibrosis > > Use of daily prescription medications for migraines in the past month > > Multiple Sclerosis, Cerebral Palsy > > Brain tumor or Stroke > > Currently on chemotherapy or immunomodulatory agents, or history of > radiation or chemotherapy that could affect the brain > > Sickle Cell Disease > > Thyroid Hormone Treatment in the past month > > Treatment for Diabetes in the past month (do not exclude for gestational > or diet controlled diabetes) > > Head Injury If: > > LOC>30 minutes or Amnesia >24 hours > > Change in Mental Status >24 hours or CT findings consistent with TBI > > 3 or more concussive (mild) TBIs > > Premature Birth (Born >37 weeks for non-twins, born <34 weeks for twins. > If weeks unknown, less than 5 lbs. at birth for non-twins. > > Current Pregnancy > > Unsafe metal or devices in the body (Cardiac Pacemaker, cochlear implant, > aneurism clip) > > Moderate to Severe Claustrophobia > > > > Hope that helps. > > > > 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 > el...@pcg.wustl.edu > www.humanconnectome.org > > > > *From:* Joelle Zimmermann [mailto:joelle.t.zimmerm...@gmail.com] > *Sent:* Monday, November 30, 2015 11:12 AM > *To:* Jennifer Elam > *Cc:* hcp-users@humanconnectome.org > *Subject:* Re: [HCP-Users] Demographic and behavioral subject data > > > > Hi Michael and Jennifer, > > > > Thank you both for your help, much appreciated. One remaining question - > is there currently any cutoff for cognitive scores (i.e. for the MMSE for > ex) for subjects being included in the 500 release dataset? Can't find > mention of it in the ref manual, so Im guessing probably not. > > > > Thanks, > > Joelle > > > > On Mon, Nov 30, 2015 at 11:49 AM, Jennifer Elam <el...@pcg.wustl.edu> > wrote: > > Hi Joelle, > > All the HCP subjects are considered healthy young adults with no diagnosed > cognitive abnormalities. They do, of course, have a range of abilities and > scores on the behavioral tests we conduct. > > > > There is a lot of information in Chapter 1 of the current 500 Subjects > Reference Manual > <http://humanconnectome.org/documentation/S500/HCP_S500+MEG2_Release_Reference_Manual.pdf> > for navigating the behavioral data and for filtering subjects—please check > it out. There is also a “Download CSV button” at the upper right of the > subject Dashboard that will allow you to download all the open access > behavioral data in one spreadsheet. Look at the sections of the Reference > Manual on Restricted access data to see if you need to apply for access to > that data for your purposes. > > > > As detailed in the Introduction
Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI
Hi Michael and Tim, Thanks for your help. Does the HCP have its own parcellations that are surface based, or do you have any recommendations? Are you familiar with the Freesurfer Desikan Killiany cortical atlas - it seems that it for example respects the cortical surface?: "The FreeSurfer utilities mris_ca_train and mris_ca_label together implement a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from a manually labeled training set." ( https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation). My ultimate goal is to get a region-wise FC matrix. After parcellating the cifti into my chosen parcellation atlas, I will be left with region-wise time series, is that correct? After that, could I just convert the cifti to nifti and work with that? I presume at that point I wouldn't need the spatial info (actually Im not actually sure what kind of spatial info this is?) Thanks, Joelle On Wed, Nov 25, 2015 at 5:21 PM, Timothy Coalson <tsc...@mst.edu> wrote: > Because the surface data in our Cifti files is mapped from the volume > using subject-specific surfaces, it avoids mixing csf and white matter data > into the cortical signal. With a volume parcellation, in order to do > something similar, you would need to parcellate each individual somehow, or > have an overly generous parcellation and mask it with the per-subject > cortical segmentation. > > Indeed, putting surface and volume data into one file is the main feature > of the Cifti format (though it also has additional mapping types, notably > being able to represent a parcellated file in a way that is easy to use for > visualization). Cifti also allows the exclusion of vertices and voxels > that we aren't interested in (medial wall, white matter, csf, skull, air, > etc), which means that some translation is needed in order to use spatial > relationships between elements. If you want the gory details, suitable for > those implementing their own reader/writer for cifti in other programming > languages, see the NITRC page: > > http://www.nitrc.org/projects/cifti/ > > The good news is, if you have a parcellation you want to use, and can get > it into a cifti label file (see -volume-label-to-surface-mapping > and -cifti-create-label), then you can easily parcellate a cifti file with > the "wb_command -cifti-parcellate" command. > > Tim > > > On Wed, Nov 25, 2015 at 2:53 PM, Harms, Michael <mha...@wustl.edu> wrote: > >> >> If you want connectivity matrices based on a parcellation that respects >> the cortical surface, then you'll need to use the CIFTI data, and you'll >> need a parcellation to go along with it that is also based on the surfaces >> (for the cortical grayordinates). We would definitely suggest that you go >> this route, since much of the HCP effort, from acquisition through >> processing, is designed around surface-based analyses of the cortical data. >> >> Also, you probably want to use the "FIX" cleaned data, which has >> "*clean*" in the file name, rather than just the minimally pre-processed >> .dtseries.nii. >> >> I think the basic file types are well documented in the release >> documentation. >> >> 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: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> >> Date: Wednesday, November 25, 2015 2:40 PM >> To: Timothy Coalson <tsc...@mst.edu> >> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >> Subject: Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI >> >> Hi Tim, >> >> Thanks for your response. Within the Resting State fMRI 1 preprocessed >> in the 500 Subjects + MEG2, I see the rfMRI_REST1_LR.nii.gz, which I >> presume is the Nifti-1 data. And then I see an >> rfMRI_REST1_LR_Atlas.dtseries.nii - Is that the dtseries.nii Cifti you >> refer to? Could you explain a bit more about what's special about the Cifti >> file? I understand it Cifti is able to handle surface vertices and >> subcortical voxels in one file (i.e. gray ordinates). >> >> My ultimate goal is to parcellate the brain into cortical regions of >> interest, in order to ultimately look at regional functional connectivity >> matrices. Do I need the dtseries
Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI
Hi Tim, Thanks for your response. Within the Resting State fMRI 1 preprocessed in the 500 Subjects + MEG2, I see the rfMRI_REST1_LR.nii.gz, which I presume is the Nifti-1 data. And then I see an rfMRI_REST1_LR_Atlas.dtseries.nii - Is that the dtseries.nii Cifti you refer to? Could you explain a bit more about what's special about the Cifti file? I understand it Cifti is able to handle surface vertices and subcortical voxels in one file (i.e. gray ordinates). My ultimate goal is to parcellate the brain into cortical regions of interest, in order to ultimately look at regional functional connectivity matrices. Do I need the dtseries.nii cifti for that? It seems like the advantage of that is having surface vertices (i.e. knowing the precise shape of the surface of the brain) - which I don't think I need for a standard FC matrix... Thanks, Joelle On Tue, Nov 24, 2015 at 6:16 PM, Timothy Coalson <tsc...@mst.edu> wrote: > The .nii.gz files are nifti-1 volumes, while the .dtseries.nii files are > Cifti files. If you need spatial information, converting Cifti to nifti-1 > is not the way to go about it, instead you could use wb_command > -cifti-separate into metric (.func.gii, one per hemisphere) and volume > files, or use whatever -cifti-* commands are applicable to what you want to > do spatially. > > Tim > > > On Tue, Nov 24, 2015 at 11:14 AM, Joelle Zimmermann < > joelle.t.zimmerm...@gmail.com> wrote: > >> Hi all, >> >> I'm working with the 500subjects + MEG2 preprocessed Resting State fMRI >> 1 Preprocessed dataset. >> >> Is the data just standard voxel-wise Nifti (it indeed looks like >> Nifti-1), or is it in a Cifti format that I need to convert to Nifti? My >> goal is to parcellate this data into ROI's, and I have a script that does >> this based on voxel-wise data, but as I understand Cifti is in gray >> ordinates. >> >> Thanks, >> Joelle >> >> ___ >> HCP-Users mailing list >> HCP-Users@humanconnectome.org >> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> > > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
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> 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 > Email: gburg...@wustl.edu > > > On Nov 23, 2015, at 4:40 PM, Glasser, Matthew <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> on behalf of Joelle > Zimmermann <joelle.t.zimmerm...@gmail.com> > > Date: Monday, November 23, 2015 at 12:48 PM > > To: "Elam, Jennifer" <e...@wustl.edu> > > Cc: "hcp-users@humanconnectome.org" <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> > 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 > >> el...@pcg.wustl.edu > >> www.humanconnectome.org > >> > >> From: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 > >> 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 < > hcp-users-boun...@humanconnectome.org> on behalf of Joelle Zimmermann < > joelle.t.zimmerm...@gmail.com> > >> Sent: Monday, November 23, 2015 11:33 AM > >> To: 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 > &
[HCP-Users] CIFTI and NIFTI -parcellating rfMRI
Hi all, I'm working with the 500subjects + MEG2 preprocessed Resting State fMRI 1 Preprocessed dataset. Is the data just standard voxel-wise Nifti (it indeed looks like Nifti-1), or is it in a Cifti format that I need to convert to Nifti? My goal is to parcellate this data into ROI's, and I have a script that does this based on voxel-wise data, but as I understand Cifti is in gray ordinates. Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
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 > 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 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 > >> el...@pcg.wustl.edu<mailto:el...@pcg.wustl.edu> > >> www.humanconnectome.org<http://www.humanconnectome.org> > >> > >> From:hcp-users-boun...@humanconnectome.org from%3ahcp-users-boun...@humanconnectome.org> [mailto: > hcp-users-boun...@humanconnectome.org 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 hcp-users@humanconnectome.org> > >> Subject: Re: [HCP-Users
Re: [HCP-Users] Tractography on diffusion data for SC matrices
Hi Jennifer, That's good to hear! I don't have much experience with tractography, but it looks like bedpostX creates all the files you need for running probabilistic tractography (probabilistic tractography itself is run with probtrackX for example). I suppose the probabilistic tractography is something that would come in a later release. Thanks, Joelle On Mon, Nov 23, 2015 at 2:10 PM, Jennifer Elam <el...@pcg.wustl.edu> wrote: > Hi Joelle and all, > > HCP does have running bedpostX on the diffusion data for HCP Subjects on > our to do list, but this data has not been released yet. We are hoping to > have this available to users by late winter/early spring 2016 after we > release 7T data. > > > > 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 > el...@pcg.wustl.edu > www.humanconnectome.org > > > > *From:* Joelle Zimmermann [mailto:joelle.t.zimmerm...@gmail.com] > *Sent:* Monday, November 23, 2015 12:54 PM > *To:* Jennifer Elam; hcp-users@humanconnectome.org > *Subject:* Tractography on diffusion data for SC matrices > > > > Hi Jennifer, > > > > I previously posted a question to the mailing list, and wanted to check > with you as you may have a bit more of an insiders scoop. > > > > I was wondering whether tractography has been performed on the diffusion > data for the end of creating structural connectivity matrices for > individual subjects; or something that is in the plans? I would expect > this is something that would be of interest to quite a few people, and > would definitely be of a lot of use to me. > > > > Thanks, > > Joelle > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
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> 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 > el...@pcg.wustl.edu > www.humanconnectome.org > > > > *From:* 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 > *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 < > hcp-users-boun...@humanconnectome.org> on behalf of Joelle Zimmermann < > joelle.t.zimmerm...@gmail.com> > *Sent:* Monday, November 23, 2015 11:33 AM > *To:* 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... > <http://www.humanconnectome.org/documentation/Q1/data-in-this-release.html> > > > > ___ > HCP-Users mailing list > HCP-Users@humanconnectome.org > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > > ___ > HCP-Users mailing list > HCP-Users@humanconnectome.org > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] Tractography on diffusion data for SC matrices
Hi Jennifer, I previously posted a question to the mailing list, and wanted to check with you as you may have a bit more of an insiders scoop. I was wondering whether tractography has been performed on the diffusion data for the end of creating structural connectivity matrices for individual subjects; or something that is in the plans? I would expect this is something that would be of interest to quite a few people, and would definitely be of a lot of use to me. Thanks, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] Has anybody done tractography on HCP diffusion data?
Hi - I'm a researcher at the McIntosh lab at the Rotman Research Institute. A few of us here are planning on working with HCP data. I was wondering whether anybody is working on (or aware of a group working on) fully preprocessing and tractography on HCP diffusion data, parcellated into some kind of structural connectivity matrix? Of course we would provide authorship to whoever is providing the tractographied data. I'd expect there must be quite a few folks who would be interested in this. I'm also interested in preprocessed rfMRI functional connectivity matrices in a matching parcellation. However, more important is that diffusion data already undergone tractography and in a certain parcellation in the form of a SC matrix. Any direction would really help. Thanks a lot, Joelle ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
