Well, I guess that would be us every time we update our local installation. We’ll let you know how it goes ________________________ gaurav patel gauravpa...@gmail.com pateldsclab.net
> On Mar 2, 2018, at 2:30 PM, Glasser, Matthew <glass...@wustl.edu> wrote: > > Hi Gaurav, > > I guess they are supported on mac for now, but I don¹t know that anyone is > actively testing them for macŠ > > Matt. > > On 3/2/18, 1:28 PM, "Gaurav Patel" <gaurav.pa...@gmail.com on behalf of > gauravpa...@gmail.com> wrote: > >> YesŠwe¹ve been 3.4 for many years without problems, and 3.22 only >> required those minor changes. We recently verified that it was easy to >> install and run on macs when we expanded the network of mac pros we use >> to run the HCP pipelines >> ________________________ >> gaurav patel >> gauravpa...@gmail.com >> pateldsclab.net >> >>> On Mar 2, 2018, at 2:25 PM, Glasser, Matthew <glass...@wustl.edu> wrote: >>> >>> So you are saying that the Pipelines work fine on the Mac for you aside >>> from this cp issue? >>> >>> Matt. >>> >>> From: <hcp-users-boun...@humanconnectome.org> on behalf of "Sanchez, >>> Juan (NYSPI)" <juan.sanc...@nyspi.columbia.edu> >>> Date: Friday, March 2, 2018 at 1:24 PM >>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Subject: Re: [HCP-Users] HCP-Users Digest, Vol 64, Issue 2 >>> >>> Dear >>> Kwan-Jin Jung >>> >>> I had rthe same problems when I installed the 3_22 HCP Pipleines >>> Here is what we did: >>> >>> >>> € >>> syntax in >>> scripts: >>> Just remove the "--preserve=timestamps" from all of the Pipeline >>> scripts >>> 2. workbench: >>> >>> Get the "dev_latest" zip file that says "mac64" from here: >>> >>> http://brainvis.wustl.edu/workbench/ >>> >>> From: hcp-users-boun...@humanconnectome.org >>> <hcp-users-boun...@humanconnectome.org> on behalf of >>> hcp-users-requ...@humanconnectome.org >>> <hcp-users-requ...@humanconnectome.org> >>> Sent: Friday, March 2, 2018 1:00:01 PM >>> To: hcp-users@humanconnectome.org >>> Subject: HCP-Users Digest, Vol 64, Issue 2 >>> >>> ATTENTION: This email came from an external source. Do not open >>> attachments or click on links from unknown senders or unexpected emails. >>> >>> >>> Send HCP-Users mailing list submissions to >>> hcp-users@humanconnectome.org >>> >>> To subscribe or unsubscribe via the World Wide Web, visit >>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>> or, via email, send a message with subject or body 'help' to >>> hcp-users-requ...@humanconnectome.org >>> >>> You can reach the person managing the list at >>> hcp-users-ow...@humanconnectome.org >>> >>> When replying, please edit your Subject line so it is more specific >>> than "Re: Contents of HCP-Users digest..." >>> >>> >>> Today's Topics: >>> >>> 1. Re: Best Approach for using old volumetric data to pick >>> parcels-of-interest (Stevens, Michael) >>> 2. Movement regressor missing (Linnman, Clas,Ph.D.) >>> 3. Re: Movement regressor missing (Glasser, Matthew) >>> 4. Error in FreeSurfer processing "recon-all.v6.hires: command >>> not found" (Pubuditha Abeyasinghe) >>> 5. Re: Error in FreeSurfer processing "recon-all.v6.hires: >>> command not found" (Glasser, Matthew) >>> 6. Re: Error in FreeSurfer processing "recon-all.v6.hires: >>> command not found" (Timothy B. Brown) >>> 7. Re: Best Approach for using old volumetric data to pick >>> parcels-of-interest (Timothy Coalson) >>> 8. Re: ROI cluster centers to surface grayordinates (Timothy Coalson) >>> 9. Re: Best Approach for using old volumetric data to pick >>> parcels-of-interest (Erin W. E. Dickie) >>> 10. Re: Correct interpretation of NIH battery test >>> 'Words-in-Noise' in HCP subjects (Robert Becker) >>> 11. Split dtseries (A R) >>> 12. Re: Split dtseries (Glasser, Matthew) >>> 13. Change of FreeSurferHiresPial.sh for MacBook IOS (Kwan-Jin Jung) >>> 14. Re: Change of FreeSurferHiresPial.sh for MacBook IOS >>> (Glasser, Matthew) >>> >>> >>> ---------------------------------------------------------------------- >>> >>> Message: 1 >>> Date: Thu, 1 Mar 2018 19:22:32 +0000 >>> From: "Stevens, Michael" <michael.stev...@hhchealth.org> >>> Subject: Re: [HCP-Users] Best Approach for using old volumetric data >>> to pick parcels-of-interest >>> To: Timothy Coalson <tsc...@mst.edu>, "Glasser, Matthew" >>> <glass...@wustl.edu> >>> Cc: "Erin W. E. Dickie" <erin.w.dic...@gmail.com>, >>> "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Message-ID: >>> >>> <1cf06fac1128cf49ab6143a2d6a10f859345e...@hhcexchmb04.hhcsystem.org> >>> Content-Type: text/plain; charset="utf-8" >>> >>> Hi Tim, >>> >>> Thanks. That?s clear and sounds like a really reasonable approach. >>> >>> Can you point me towards the exact files I?d need to reference and >>> maybe suggest which function calls I?ll need to use to do the >>> volume-to-surface mapping you describe? I?ll whip up a quick script to >>> loop through about 120 datasets from this R01 project and let you know >>> how well it works. >>> >>> Mike >>> >>> >>> From: Timothy Coalson [mailto:tsc...@mst.edu] >>> Sent: Friday, February 23, 2018 6:49 PM >>> To: Glasser, Matthew >>> Cc: Stevens, Michael; Erin W. E. Dickie; hcp-users@humanconnectome.org >>> Subject: Re: [HCP-Users] Best Approach for using old volumetric data to >>> pick parcels-of-interest >>> >>> This is an email from Outside HHC. USE CAUTION opening attachments or >>> links from unknown senders. >>> >>> Surface-based methods may boost your statistical power enough (by >>> better alignment, exclusion of irrelevant tissue, and smoothing that >>> doesn't cross sulcal banks, if you decide you need smoothing) that you >>> may not need to rely as much on existing ROIs. Parcel-based statistics >>> have a lot of power, because the multiple comparisons are orders of >>> magnitude smaller, spatially independent noise averages out, and the >>> signal averages together. We believe that a lot of old data would >>> benefit from reanalysis using surfaces. >>> >>> However, our paper is mainly focused on specificity and continuous >>> data. If you have a binary volume ROI and you only need a rough guess >>> of it on the surface, you can get approximate answers, in a way that >>> should reduce false negatives (and give more false positives) from the >>> surface/volume transition problems. You can map the ROI to the >>> anatomical MNI surfaces of a group of subjects, and take the max across >>> subjects. Each individual may miss the expected group ribbon location >>> in any given location, but it is very likely that every point in the >>> expected group ribbon location will overlap with at least one subject in >>> the group. If this isn't enough, you can dilate the volume ROI a few mm >>> first. >>> >>> Tim >>> >>> >>> On Fri, Feb 23, 2018 at 11:18 AM, Glasser, Matthew >>> <glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote: >>> Hi Mike, >>> >>> We have a preprint out on this exact question and the conclusion is >>> that it is really hard to do this accurately for most brain regions: >>> >>> https://www.biorxiv.org/content/early/2018/01/29/255620 >>> >>> Really the best idea is probably to go back and reanalyze the old data >>> without volume-based smoothing and aligned across surfaces. Erin >>> Dickie, CCed is working on tools to make this a little easier, but still >>> there are issues like needing a field map to get accurate fMRI to >>> structural registration. The good news is that one?s statistical power >>> should be much better if brains are actually lined up, and using >>> parcellated analyses instead of smoothing offers further benefits. >>> >>> Matt. >>> >>> From: >>> <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-bounces@humanconn >>> ectome.org>> on behalf of "Stevens, Michael" >>> <michael.stev...@hhchealth.org<mailto:michael.stev...@hhchealth.org>> >>> Date: Friday, February 23, 2018 at 8:58 AM >>> To: >>> "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" >>> <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> >>> Subject: [HCP-Users] Best Approach for using old volumetric data to >>> pick parcels-of-interest >>> >>> Hi everyone, >>> >>> There?s been a lot posted here over the past year or two on the >>> challenges and limitations of going back-and-forth between volumetric >>> space and HCP-defined surface space, with solid arguments for moving to >>> (and sticking with) CIFTI-defined brainordinates. Here, I?m asking a >>> slightly different question? The field has decades of research using >>> volume-space fMRI timeseries analyses that helps to define where to look >>> in the brain to test new hypotheses. Has anyone got a well-thought-out >>> approach for mapping such volume-space ROIs to the parcels within the >>> new HCP 180 atlas? I ask because the specificity of the HCP atlas >>> sometimes offers a half dozen candidate parcels for hypothesis-testing >>> for what we previously thought of as just one or two regions. Even >>> though our group currently has a half dozen newer NIH-funded studies >>> that use HCP compliant sequences, most of that work is still predicated >>> on a ?region-of-interest? approach because the study groups sizes are >>> less than a h >>> undred, not in the thousands typical of the HCP grantwork. So we >>> still have to contend with the statistical power limitations inherent in >>> any ROI approach. It would be great to be able to use our prior >>> volume-space data to have greater confidence in selecting among the >>> various parcel-of-interest candidates when testing hypotheses. >>> >>> I?m wondering if anyone?s yet worked out a step-by-step approach for a >>> series of warps/surface-maps/transformations that can take ROIs from MNI >>> space and give a ?best guess? as to which HCP 180 atlas parcel(s) should >>> be queried in such instances. It would be a nice bridge from older work >>> to newer HCP-guided work, that would allow researchers to circumvent the >>> added burden of having to go back and collect new pilot data using HCP >>> sequences. A thoughtful list of the analytic or conceptual pros/cons of >>> something like this would be helpful as well. >>> >>> Thanks, >>> Mike >>> >>> >>> This e-mail message, including any attachments, is for the sole use of >>> the intended recipient(s) and may contain confidential and privileged >>> information. Any unauthorized review, use, disclosure, or distribution >>> is prohibited. If you are not the intended recipient, or an employee or >>> agent responsible for delivering the message to the intended recipient, >>> please contact the sender by reply e-mail and destroy all copies of the >>> original message, including any attachments. >>> >>> _______________________________________________ >>> 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 >>> >>> >>> >>> Reminder: This e-mail and any attachments are subject to the current >>> HHC email retention policies. Please save or store appropriately in >>> accordance with policy. >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /d798ca00/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 2 >>> Date: Thu, 1 Mar 2018 20:02:08 +0000 >>> From: "Linnman, Clas,Ph.D." <clinn...@partners.org> >>> Subject: [HCP-Users] Movement regressor missing >>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Message-ID: <14e25807-db1b-4132-ad77-1ff863216...@contoso.com> >>> Content-Type: text/plain; charset="utf-8" >>> >>> Hi, >>> I downloaded the ?resting state fMRI FIX 1 Denoised (Extended)? >>> datasets, but there are no Movement_Regressors.txt included in the >>> unzipped folder. >>> Are these not there for a reason? I can grab them from the other >>> preprocessed datasets, but I was curious as to why they are missing, and >>> if they would be identical to those in the ?Resting State fMRI 1 >>> Preprocessed? package >>> >>> Best >>> Clas >>> >>> >>> The information in this e-mail is intended only for the person to whom >>> it is >>> addressed. If you believe this e-mail was sent to you in error and the >>> e-mail >>> contains patient information, please contact the Partners Compliance >>> HelpLine at >>> http://www.partners.org/complianceline . If the e-mail was sent to you >>> in error >>> but does not contain patient information, please contact the sender and >>> properly >>> dispose of the e-mail. >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /c9c590f9/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 3 >>> Date: Thu, 1 Mar 2018 20:05:01 +0000 >>> From: "Glasser, Matthew" <glass...@wustl.edu> >>> Subject: Re: [HCP-Users] Movement regressor missing >>> To: "Linnman, Clas,Ph.D." <clinn...@partners.org>, >>> "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Message-ID: <d6bdb8ec.1637d7%glass...@wustl.edu> >>> Content-Type: text/plain; charset="windows-1252" >>> >>> That?s right. To keep the packages smaller we tried not to repeat files. >>> >>> Peace, >>> >>> Matt. >>> >>> From: >>> <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-bounces@humanconn >>> ectome.org>> on behalf of "Linnman, Clas,Ph.D." >>> <clinn...@partners.org<mailto:clinn...@partners.org>> >>> Date: Thursday, March 1, 2018 at 2:02 PM >>> To: >>> "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" >>> <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> >>> Subject: [HCP-Users] Movement regressor missing >>> >>> Hi, >>> I downloaded the ?resting state fMRI FIX 1 Denoised (Extended)? >>> datasets, but there are no Movement_Regressors.txt included in the >>> unzipped folder. >>> Are these not there for a reason? I can grab them from the other >>> preprocessed datasets, but I was curious as to why they are missing, and >>> if they would be identical to those in the ?Resting State fMRI 1 >>> Preprocessed? package >>> >>> Best >>> Clas >>> >>> The information in this e-mail is intended only for the person to whom >>> it is >>> addressed. If you believe this e-mail was sent to you in error and the >>> e-mail >>> contains patient information, please contact the Partners Compliance >>> HelpLine at >>> http://www.partners.org/complianceline . If the e-mail was sent to you >>> in error >>> but does not contain patient information, please contact the sender and >>> properly >>> dispose of the e-mail. >>> >>> _______________________________________________ >>> HCP-Users mailing list >>> HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> >>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /6c3b8429/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 4 >>> Date: Thu, 1 Mar 2018 20:09:05 +0000 >>> From: Pubuditha Abeyasinghe <pabey...@uwo.ca> >>> Subject: [HCP-Users] Error in FreeSurfer processing >>> "recon-all.v6.hires: command not found" >>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Message-ID: >>> >>> <ytxpr0101mb1711242b943ee17bf6d1c719af...@ytxpr0101mb1711.canprd01.prod.O >>> UTLOOK.COM> >>> >>> Content-Type: text/plain; charset="iso-8859-1" >>> >>> Hi all, >>> >>> I am very new to the HCP pipeline for preprocessing the data and I am >>> trying to adopt to the pipeline. >>> As the first step I am trying the execution of the pipeline with the >>> example data that is given in the tutorial. The first part which is the >>> PreFreeSurfer processing was completed successfully. >>> >>> But I am having a problem with the second part, the FreeSurfer >>> processing. When I start it, the process instantly comes to an end >>> giving me the following error; >>> >>> ~/Pipelines/FreeSurfer/FreeSurferPipeline.sh: line 41: >>> recon-all.v6.hires: command not found >>> >>> I double check the freesurfer installation and I source it as explained >>> as well. Does this error has something to do with the installation? How >>> can I fix it? >>> >>> >>> Your help is much appreciated! >>> >>> >>> Regards, >>> Pubuditha >>> >>> >>> [Western University] >>> Pubuditha Abeyasinghe >>> PhD Candidate >>> Department of Physics and Astronomy >>> Brain and Mind Institute >>> Western University >>> London, ON, Canada >>> email: pabey...@uwo.ca >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /4c2b4aff/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 5 >>> Date: Thu, 1 Mar 2018 20:12:21 +0000 >>> From: "Glasser, Matthew" <glass...@wustl.edu> >>> Subject: Re: [HCP-Users] Error in FreeSurfer processing >>> "recon-all.v6.hires: command not found" >>> To: Pubuditha Abeyasinghe <pabey...@uwo.ca>, >>> "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Message-ID: <d6bdbab8.1637e5%glass...@wustl.edu> >>> Content-Type: text/plain; charset="us-ascii" >>> >>> We are working on a response to your question. >>> >>> Peace, >>> >>> Matt. >>> >>> From: >>> <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-bounces@humanconn >>> ectome.org>> on behalf of Pubuditha Abeyasinghe >>> <pabey...@uwo.ca<mailto:pabey...@uwo.ca>> >>> Date: Thursday, March 1, 2018 at 2:09 PM >>> To: >>> "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" >>> <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> >>> Subject: [HCP-Users] Error in FreeSurfer processing >>> "recon-all.v6.hires: command not found" >>> >>> >>> Hi all, >>> >>> I am very new to the HCP pipeline for preprocessing the data and I am >>> trying to adopt to the pipeline. >>> As the first step I am trying the execution of the pipeline with the >>> example data that is given in the tutorial. The first part which is the >>> PreFreeSurfer processing was completed successfully. >>> >>> But I am having a problem with the second part, the FreeSurfer >>> processing. When I start it, the process instantly comes to an end >>> giving me the following error; >>> >>> ~/Pipelines/FreeSurfer/FreeSurferPipeline.sh: line 41: >>> recon-all.v6.hires: command not found >>> >>> I double check the freesurfer installation and I source it as explained >>> as well. Does this error has something to do with the installation? How >>> can I fix it? >>> >>> >>> Your help is much appreciated! >>> >>> >>> Regards, >>> Pubuditha >>> >>> >>> [Western University] >>> Pubuditha Abeyasinghe >>> PhD Candidate >>> Department of Physics and Astronomy >>> Brain and Mind Institute >>> Western University >>> London, ON, Canada >>> email: pabey...@uwo.ca<mailto:pabey...@uwo.ca> >>> >>> _______________________________________________ >>> HCP-Users mailing list >>> HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> >>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /4fad907d/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 6 >>> Date: Thu, 1 Mar 2018 14:30:18 -0600 >>> From: "Timothy B. Brown" <tbbr...@wustl.edu> >>> Subject: Re: [HCP-Users] Error in FreeSurfer processing >>> "recon-all.v6.hires: command not found" >>> To: hcp-users@humanconnectome.org, pabey...@uwo.ca >>> Message-ID: <c2e47123-5ab6-a82c-7d3e-4f9f187ec...@wustl.edu> >>> Content-Type: text/plain; charset="windows-1252" >>> >>> Hi Pubuditha, >>> >>> >>> I'm assuming that you are using the latest release of the HCP Pipelines >>> (v3.25.0). The changes that are causing you a problem are part of those >>> being made as part of conversion to using FreeSurfer version 6. Those >>> changes should not have made it in to a release as of yet. I apologize >>> for that mistake. >>> >>> >>> Please try using version v3.24.0. I have briefly reviewed that version, >>> and I believe that those FreeSurfer 6 related changes were not included >>> in that release. >>> >>> >>> In the meantime, I will back those changes out of version v3.25.0 and >>> create a new "bug-fix" release (v3.25.1). >>> >>> >>> Thank you for pointing this problem out so that others (hopefully) do >>> not have to encounter it also. >>> >>> >>> Best Regards, >>> >>> >>> ? Tim >>> >>> >>> On 03/01/2018 02:12 PM, Glasser, Matthew wrote: >>>> We are working on a response to your question. >>>> >>>> Peace, >>>> >>>> Matt. >>>> >>>> From: <hcp-users-boun...@humanconnectome.org >>>> <mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Pubuditha >>>> Abeyasinghe <pabey...@uwo.ca <mailto:pabey...@uwo.ca>> >>>> Date: Thursday, March 1, 2018 at 2:09 PM >>>> To: "hcp-users@humanconnectome.org >>>> <mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org >>>> <mailto:hcp-users@humanconnectome.org>> >>>> Subject: [HCP-Users] Error in FreeSurfer processing >>>> "recon-all.v6.hires: command not found" >>>> >>>> Hi all, >>>> >>>> I am very new to the HCP pipeline for preprocessing the data and I am >>>> trying to adopt to the pipeline. >>>> As the first step I am trying the execution of the pipeline with the >>>> example data that is given in the tutorial. The first part which is >>>> the PreFreeSurfer processing was completed successfully. >>>> >>>> But I am having a problem with the second part, the FreeSurfer >>>> processing. When I start it, the process instantly comes to an end >>>> giving me the following error; >>>> >>>> ~/Pipelines/FreeSurfer/FreeSurferPipeline.sh: line 41: >>>> recon-all.v6.hires: command not found >>>> >>>> I double check the freesurfer installation and I source it as >>>> explained as well. Does this error has something to do with the >>>> installation? How can I fix it? >>>> >>>> >>>> Your help is much appreciated! >>>> >>>> >>>> Regards, >>>> Pubuditha >>>> >>>> >>>> Western University >>>> *Pubuditha Abeyasinghe* >>>> PhD Candidate >>>> Department of Physics and Astronomy >>>> Brain and Mind Institute >>>> Western University >>>> London, ON, Canada >>>> email: pabey...@uwo.ca <mailto:pabey...@uwo.ca> >>>> >>>> _______________________________________________ >>>> 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 >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>>> >>> >>> -- >>> /Timothy B. Brown >>> Business & Technology Application Analyst III >>> Pipeline Developer (Connectome Coordination Facility) >>> tbbrown(at)wustl.edu >>> / >>> ------------------------------------------------------------------------ >>> The material in this message is private and may contain Protected >>> Healthcare Information (PHI). 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. >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /abfce907/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 7 >>> Date: Thu, 1 Mar 2018 16:40:54 -0600 >>> From: Timothy Coalson <tsc...@mst.edu> >>> Subject: Re: [HCP-Users] Best Approach for using old volumetric data >>> to pick parcels-of-interest >>> To: "Stevens, Michael" <michael.stev...@hhchealth.org> >>> Cc: "Erin W. E. Dickie" <erin.w.dic...@gmail.com>, >>> "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Message-ID: >>> >>> <CAK_=tayd6uzegzd1qgpf6l238tsg4rqazqnh4t9qomt8yfx...@mail.gmail.com> >>> Content-Type: text/plain; charset="utf-8" >>> >>> The command to use is wb_command -volume-to-surface-mapping, the main >>> surface should generally be the midthickness. Using the >>> -ribbon-constrained method will give you small positive values on the >>> surface when the cortical ribbon just grazes your ROI, so it may be the >>> thing to use (use pial and white surfaces as outer and inner). You >>> could >>> use -trilinear which is simpler, but it has more risk of false >>> negatives. >>> You may need to experiment, I don't think the effectiveness of this >>> kind of >>> salvage effort has been explored much. >>> >>> Tim >>> >>> >>> On Thu, Mar 1, 2018 at 1:22 PM, Stevens, Michael < >>> michael.stev...@hhchealth.org> wrote: >>> >>>> Hi Tim, >>>> >>>> >>>> >>>> Thanks. That?s clear and sounds like a really reasonable approach. >>>> >>>> >>>> >>>> Can you point me towards the exact files I?d need to reference and >>> maybe >>>> suggest which function calls I?ll need to use to do the >>> volume-to-surface >>>> mapping you describe? I?ll whip up a quick script to loop through >>> about >>>> 120 datasets from this R01 project and let you know how well it works. >>>> >>>> >>>> >>>> Mike >>>> >>>> >>>> >>>> >>>> >>>> *From:* Timothy Coalson [mailto:tsc...@mst.edu] >>>> *Sent:* Friday, February 23, 2018 6:49 PM >>>> *To:* Glasser, Matthew >>>> *Cc:* Stevens, Michael; Erin W. E. Dickie; >>> hcp-users@humanconnectome.org >>>> *Subject:* Re: [HCP-Users] Best Approach for using old volumetric >>> data to >>>> pick parcels-of-interest >>>> >>>> >>>> >>>> This is an email from Outside HHC. USE CAUTION opening attachments or >>>> links from unknown senders. >>>> >>>> Surface-based methods may boost your statistical power enough (by >>> better >>>> alignment, exclusion of irrelevant tissue, and smoothing that doesn't >>> cross >>>> sulcal banks, if you decide you need smoothing) that you may not need >>> to >>>> rely as much on existing ROIs. Parcel-based statistics have a lot of >>>> power, because the multiple comparisons are orders of magnitude >>> smaller, >>>> spatially independent noise averages out, and the signal averages >>>> together. We believe that a lot of old data would benefit from >>> reanalysis >>>> using surfaces. >>>> >>>> >>>> >>>> However, our paper is mainly focused on specificity and continuous >>> data. >>>> If you have a binary volume ROI and you only need a rough guess of it >>> on >>>> the surface, you can get approximate answers, in a way that should >>> reduce >>>> false negatives (and give more false positives) from the >>> surface/volume >>>> transition problems. You can map the ROI to the anatomical MNI >>> surfaces of >>>> a group of subjects, and take the max across subjects. Each >>> individual may >>>> miss the expected group ribbon location in any given location, but it >>> is >>>> very likely that every point in the expected group ribbon location >>> will >>>> overlap with at least one subject in the group. If this isn't >>> enough, you >>>> can dilate the volume ROI a few mm first. >>>> >>>> >>>> >>>> Tim >>>> >>>> >>>> >>>> >>>> >>>> On Fri, Feb 23, 2018 at 11:18 AM, Glasser, Matthew >>> <glass...@wustl.edu> >>>> wrote: >>>> >>>> Hi Mike, >>>> >>>> >>>> >>>> We have a preprint out on this exact question and the conclusion is >>> that >>>> it is really hard to do this accurately for most brain regions: >>>> >>>> >>>> >>>> https://www.biorxiv.org/content/early/2018/01/29/255620 >>>> >>>> >>>> >>>> Really the best idea is probably to go back and reanalyze the old data >>>> without volume-based smoothing and aligned across surfaces. Erin >>> Dickie, >>>> CCed is working on tools to make this a little easier, but still >>> there are >>>> issues like needing a field map to get accurate fMRI to structural >>>> registration. The good news is that one?s statistical power should >>> be much >>>> better if brains are actually lined up, and using parcellated analyses >>>> instead of smoothing offers further benefits. >>>> >>>> >>>> >>>> Matt. >>>> >>>> >>>> >>>> *From: *<hcp-users-boun...@humanconnectome.org> on behalf of "Stevens, >>>> Michael" <michael.stev...@hhchealth.org> >>>> *Date: *Friday, February 23, 2018 at 8:58 AM >>>> *To: *"hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>>> *Subject: *[HCP-Users] Best Approach for using old volumetric data to >>>> pick parcels-of-interest >>>> >>>> >>>> >>>> Hi everyone, >>>> >>>> >>>> >>>> There?s been a lot posted here over the past year or two on the >>> challenges >>>> and limitations of going back-and-forth between volumetric space and >>>> HCP-defined surface space, with solid arguments for moving to (and >>> sticking >>>> with) CIFTI-defined brainordinates. Here, I?m asking a slightly >>> different >>>> question? The field has decades of research using volume-space fMRI >>>> timeseries analyses that helps to define where to look in the brain >>> to test >>>> new hypotheses. Has anyone got a well-thought-out approach for >>> mapping >>>> such volume-space ROIs to the parcels within the new HCP 180 atlas? >>> I ask >>>> because the specificity of the HCP atlas sometimes offers a half dozen >>>> candidate parcels for hypothesis-testing for what we previously >>> thought of >>>> as just one or two regions. Even though our group currently has a >>> half >>>> dozen newer NIH-funded studies that use HCP compliant sequences, most >>> of >>>> that work is still predicated on a ?region-of-interest? approach >>> because >>>> the study groups sizes are less than a hundred, not in the thousands >>>> typical of the HCP grantwork. So we still have to contend with the >>>> statistical power limitations inherent in any ROI approach. It would >>> be >>>> great to be able to use our prior volume-space data to have greater >>>> confidence in selecting among the various parcel-of-interest >>> candidates >>>> when testing hypotheses. >>>> >>>> >>>> >>>> I?m wondering if anyone?s yet worked out a step-by-step approach for a >>>> series of warps/surface-maps/transformations that can take ROIs from >>> MNI >>>> space and give a ?best guess? as to which HCP 180 atlas parcel(s) >>> should be >>>> queried in such instances. It would be a nice bridge from older work >>> to >>>> newer HCP-guided work, that would allow researchers to circumvent the >>> added >>>> burden of having to go back and collect new pilot data using HCP >>>> sequences. A thoughtful list of the analytic or conceptual pros/cons >>> of >>>> something like this would be helpful as well. >>>> >>>> >>>> >>>> Thanks, >>>> >>>> Mike >>>> >>>> >>>> >>>> >>>> *This e-mail message, including any attachments, is for the sole use >>> of >>>> the intended recipient(s) and may contain confidential and privileged >>>> information. Any unauthorized review, use, disclosure, or >>> distribution is >>>> prohibited. If you are not the intended recipient, or an employee or >>> agent >>>> responsible for delivering the message to the intended recipient, >>> please >>>> contact the sender by reply e-mail and destroy all copies of the >>> original >>>> message, including any attachments. * >>>> >>>> _______________________________________________ >>>> 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 >>>> >>>> >>>> >>>> >>>> >>>> *Reminder: This e-mail and any attachments are subject to the current >>> HHC >>>> email retention policies. Please save or store appropriately in >>> accordance >>>> with policy. * >>>> >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /b0aca16d/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 8 >>> Date: Thu, 1 Mar 2018 17:08:39 -0600 >>> From: Timothy Coalson <tsc...@mst.edu> >>> Subject: Re: [HCP-Users] ROI cluster centers to surface grayordinates >>> To: Manasij Venkatesh <mana...@umd.edu> >>> Cc: hcp-users@humanconnectome.org >>> Message-ID: >>> >>> <CAK_=tawZFTcB-L2KUw1A--=ouz-+pbuq5zd4wdbwl-3d5hg...@mail.gmail.com> >>> Content-Type: text/plain; charset="utf-8" >>> >>> Unfortunately, it is worse than that - even ignoring the individual >>> variability issue (which should not be ignored), a small change in MNI >>> coordinate can jump from one bank of a sulcus to the other, so having >>> only >>> the center coordinate of a cluster makes this a badly posed problem (and >>> thus explains why peak or center of gravity MNI coordinate reporting is >>> not >>> nearly as useful as actual data files). >>> >>> Coordinates of each vertex are contained in .surf.gii files, but >>> different >>> files can represent different depths of cortex (gray/white boundary >>> ("white"), csf/gray boundary ("pial"), halfway between ("midthickness), >>> etc), or other things entirely (inflated, sphere). What you could do to >>> get an idea of the problem, is to take a group of subjects, get the >>> vertex >>> coordinates of the midthickness surface, and compute the euclidean >>> distance >>> to each of your cluster centers. If you average these across subjects, >>> I >>> suspect you will generally end up with 2 similarly low-distance spots >>> for >>> each cluster center, on opposite sides of a sulcus (for consistent >>> sulci, >>> anyway - if it is in or near a high-folding-variability region, one of >>> the >>> two low spots may get blurred out of existence (or the two may be >>> blurred >>> into one larger spot) because the folding patterns don't align, but it >>> is >>> the folding patterns that determine where the MNI coordinate is close to >>> cortex). To make it easier to see this issue, you could transform these >>> distances into a gaussian kernel (matching the size of the original >>> cluster >>> if you know it, or the amount of smoothing that was used, or...) and >>> then >>> average that across subjects. >>> >>> For a less-rigorous answer, there is a -surface-closest-vertex command >>> in >>> wb_command that will simply find the closest vertex on the given surface >>> (you will need to separate your right and left coordinates), but as this >>> demonstration should show, MNI coordinate data is generally ambiguous to >>> begin with. Also note that group-average surfaces are missing a lot of >>> folding detail that individual subjects have, and while that may >>> incidentally make "closest vertex" more stable, it doesn't imply that it >>> makes the answer more correct. >>> >>> Tim >>> >>> >>> On Thu, Mar 1, 2018 at 9:32 AM, Manasij Venkatesh <mana...@umd.edu> >>> wrote: >>> >>>> Hi, >>>> >>>> I have a set of ROI cluster center coordinates in MNI space. My goal >>> is to >>>> create similar ROI clusters to use with HCP data. I understand >>> there's no >>>> true equivalent in terms of surface grayordinates but what would be >>> the >>>> best way to find their approximate position on the surface? Is this >>> the >>>> information contained in the surf.gii files? Please let me know. >>>> >>>> Sincerely, >>>> Manasij >>>> >>>> _______________________________________________ >>>> HCP-Users mailing list >>>> HCP-Users@humanconnectome.org >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>>> >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /125e4d25/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 9 >>> Date: Thu, 1 Mar 2018 17:02:04 -0500 >>> From: "Erin W. E. Dickie" <erin.w.dic...@gmail.com> >>> Subject: Re: [HCP-Users] Best Approach for using old volumetric data >>> to pick parcels-of-interest >>> To: "Stevens, Michael" <michael.stev...@hhchealth.org> >>> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Message-ID: >>> >>> <CADig-n81fqn6z1cc_jnE6mizX++ViKHrbmsx=iwtnweywed...@mail.gmail.com> >>> Content-Type: text/plain; charset="utf-8" >>> >>> Hey Mike, >>> >>> Here's the link to the tools Matt was referring to in the last email. >>> https://edickie.github.io/ciftify >>> >>> I think I'm still a little confused about your exact problem. What do >>> you >>> need to map? Do you already have surfaces for all your participants in >>> GIFTI format? >>> >>> Thanks, >>> Erin >>> >>> On Thu, Mar 1, 2018 at 2:22 PM, Stevens, Michael < >>> michael.stev...@hhchealth.org> wrote: >>> >>>> Hi Tim, >>>> >>>> >>>> >>>> Thanks. That?s clear and sounds like a really reasonable approach. >>>> >>>> >>>> >>>> Can you point me towards the exact files I?d need to reference and >>> maybe >>>> suggest which function calls I?ll need to use to do the >>> volume-to-surface >>>> mapping you describe? I?ll whip up a quick script to loop through >>> about >>>> 120 datasets from this R01 project and let you know how well it works. >>>> >>>> >>>> >>>> Mike >>>> >>>> >>>> >>>> >>>> >>>> *From:* Timothy Coalson [mailto:tsc...@mst.edu] >>>> *Sent:* Friday, February 23, 2018 6:49 PM >>>> *To:* Glasser, Matthew >>>> *Cc:* Stevens, Michael; Erin W. E. Dickie; >>> hcp-users@humanconnectome.org >>>> *Subject:* Re: [HCP-Users] Best Approach for using old volumetric >>> data to >>>> pick parcels-of-interest >>>> >>>> >>>> >>>> This is an email from Outside HHC. USE CAUTION opening attachments or >>>> links from unknown senders. >>>> >>>> Surface-based methods may boost your statistical power enough (by >>> better >>>> alignment, exclusion of irrelevant tissue, and smoothing that doesn't >>> cross >>>> sulcal banks, if you decide you need smoothing) that you may not need >>> to >>>> rely as much on existing ROIs. Parcel-based statistics have a lot of >>>> power, because the multiple comparisons are orders of magnitude >>> smaller, >>>> spatially independent noise averages out, and the signal averages >>>> together. We believe that a lot of old data would benefit from >>> reanalysis >>>> using surfaces. >>>> >>>> >>>> >>>> However, our paper is mainly focused on specificity and continuous >>> data. >>>> If you have a binary volume ROI and you only need a rough guess of it >>> on >>>> the surface, you can get approximate answers, in a way that should >>> reduce >>>> false negatives (and give more false positives) from the >>> surface/volume >>>> transition problems. You can map the ROI to the anatomical MNI >>> surfaces of >>>> a group of subjects, and take the max across subjects. Each >>> individual may >>>> miss the expected group ribbon location in any given location, but it >>> is >>>> very likely that every point in the expected group ribbon location >>> will >>>> overlap with at least one subject in the group. If this isn't >>> enough, you >>>> can dilate the volume ROI a few mm first. >>>> >>>> >>>> >>>> Tim >>>> >>>> >>>> >>>> >>>> >>>> On Fri, Feb 23, 2018 at 11:18 AM, Glasser, Matthew >>> <glass...@wustl.edu> >>>> wrote: >>>> >>>> Hi Mike, >>>> >>>> >>>> >>>> We have a preprint out on this exact question and the conclusion is >>> that >>>> it is really hard to do this accurately for most brain regions: >>>> >>>> >>>> >>>> https://www.biorxiv.org/content/early/2018/01/29/255620 >>>> >>>> >>>> >>>> Really the best idea is probably to go back and reanalyze the old data >>>> without volume-based smoothing and aligned across surfaces. Erin >>> Dickie, >>>> CCed is working on tools to make this a little easier, but still >>> there are >>>> issues like needing a field map to get accurate fMRI to structural >>>> registration. The good news is that one?s statistical power should >>> be much >>>> better if brains are actually lined up, and using parcellated analyses >>>> instead of smoothing offers further benefits. >>>> >>>> >>>> >>>> Matt. >>>> >>>> >>>> >>>> *From: *<hcp-users-boun...@humanconnectome.org> on behalf of "Stevens, >>>> Michael" <michael.stev...@hhchealth.org> >>>> *Date: *Friday, February 23, 2018 at 8:58 AM >>>> *To: *"hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>>> *Subject: *[HCP-Users] Best Approach for using old volumetric data to >>>> pick parcels-of-interest >>>> >>>> >>>> >>>> Hi everyone, >>>> >>>> >>>> >>>> There?s been a lot posted here over the past year or two on the >>> challenges >>>> and limitations of going back-and-forth between volumetric space and >>>> HCP-defined surface space, with solid arguments for moving to (and >>> sticking >>>> with) CIFTI-defined brainordinates. Here, I?m asking a slightly >>> different >>>> question? The field has decades of research using volume-space fMRI >>>> timeseries analyses that helps to define where to look in the brain >>> to test >>>> new hypotheses. Has anyone got a well-thought-out approach for >>> mapping >>>> such volume-space ROIs to the parcels within the new HCP 180 atlas? >>> I ask >>>> because the specificity of the HCP atlas sometimes offers a half dozen >>>> candidate parcels for hypothesis-testing for what we previously >>> thought of >>>> as just one or two regions. Even though our group currently has a >>> half >>>> dozen newer NIH-funded studies that use HCP compliant sequences, most >>> of >>>> that work is still predicated on a ?region-of-interest? approach >>> because >>>> the study groups sizes are less than a hundred, not in the thousands >>>> typical of the HCP grantwork. So we still have to contend with the >>>> statistical power limitations inherent in any ROI approach. It would >>> be >>>> great to be able to use our prior volume-space data to have greater >>>> confidence in selecting among the various parcel-of-interest >>> candidates >>>> when testing hypotheses. >>>> >>>> >>>> >>>> I?m wondering if anyone?s yet worked out a step-by-step approach for a >>>> series of warps/surface-maps/transformations that can take ROIs from >>> MNI >>>> space and give a ?best guess? as to which HCP 180 atlas parcel(s) >>> should be >>>> queried in such instances. It would be a nice bridge from older work >>> to >>>> newer HCP-guided work, that would allow researchers to circumvent the >>> added >>>> burden of having to go back and collect new pilot data using HCP >>>> sequences. A thoughtful list of the analytic or conceptual pros/cons >>> of >>>> something like this would be helpful as well. >>>> >>>> >>>> >>>> Thanks, >>>> >>>> Mike >>>> >>>> >>>> >>>> >>>> *This e-mail message, including any attachments, is for the sole use >>> of >>>> the intended recipient(s) and may contain confidential and privileged >>>> information. Any unauthorized review, use, disclosure, or >>> distribution is >>>> prohibited. If you are not the intended recipient, or an employee or >>> agent >>>> responsible for delivering the message to the intended recipient, >>> please >>>> contact the sender by reply e-mail and destroy all copies of the >>> original >>>> message, including any attachments. * >>>> >>>> _______________________________________________ >>>> 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 >>>> >>>> >>>> >>>> >>>> >>>> *Reminder: This e-mail and any attachments are subject to the current >>> HHC >>>> email retention policies. Please save or store appropriately in >>> accordance >>>> with policy. * >>>> >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180301 >>> /386b7e49/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 10 >>> Date: Fri, 2 Mar 2018 09:11:39 +0100 >>> From: Robert Becker <em...@robertbecker.info> >>> Subject: Re: [HCP-Users] Correct interpretation of NIH battery test >>> 'Words-in-Noise' in HCP subjects >>> To: "Elam, Jennifer" <e...@wustl.edu>, "hcp-users@humanconnectome.org" >>> <hcp-users@humanconnectome.org> >>> Message-ID: <1bebeeb6-ff94-2473-d78a-b7860b5a0...@robertbecker.info> >>> Content-Type: text/plain; charset="windows-1252" >>> >>> Hi, Jennifer, >>> >>> That's great, thanks for the clarification! >>> >>> >>> Best, >>> Robert >>> >>> Am 01/03/2018 um 18:26 schrieb Elam, Jennifer: >>>> >>>> Hi?Robert, >>>> >>>> Thank you for pointing us to this problem. The HCP Words in Noise >>>> score?is indeed the NIH Toolbox Words in Noise (WIN)?Test computed >>>> score, rather than the Toolbox Hearing Threshold Test that was >>>> erroneously used for?the description in the Data Dictionary. We will >>>> fix the data dictionary with the upcoming data release of the >>>> corrected 7T fMRI data slated to occur within the month. >>>> >>>> >>>> Here's the full description for the Words in Noise measure from the >>>> NIH Toolbox Interpretation Guide from the 2012 version we used for >>> HCP: >>>> >>>> >>>> NIH Toolbox Words-in-Noise Test (WIN)Description: >>>> This test measures a person?s ability to recognize single words >>>> presented amid varying levels of background noise. It measures how >>>> much difficulty a person might have hearing in a noisy environment. A >>>> recorded voice instructs the participant to listen to and then repeat >>>> words. The task becomes increasingly difficult as the background noise >>>> gets louder, thus reducing the signal-to-noise ratio. The test is >>>> recommended for participants ages 6-85 and takes approximately six >>>> minutes to administer. >>>> Scoring Process: The examiner scores the participant?s responses as >>>> correct or incorrect, and a total raw score (out of a maximum of 35 >>>> points) is calculated by the software for each ear. A percent correct >>>> is calculated, which is then translated into a threshold score for >>>> each ear, in decibels of signal-to-noise ratio (dB S/N), using a >>>> look-up table (see Appendix C). Alternatively, the following equation >>>> can be used to calculate the S/N score based on the raw score, in lieu >>>> of the look-up table. For each ear:WIN_Score = 26-0.8*WIN_NCorrect >>>> Thus, the best score that can be attained (35 correct) for either ear >>>> is -2.0 dB S/N, and the worst score (0correct) is 26.0 dB S/N. Lower >>>> scores, therefore, are indicative of better performance on this test. >>>> In the Toolbox Assessment Scores output file, the score for the better >>>> ear is provided in the Computed Score column. >>>> Interpretation: Assessment of the ability to understand speech in a >>>> noisy background yields an ecologically valid measure of hearing >>>> because a substantial portion of communication in the real world >>>> occurs in less-than-ideal environments. Moreover, speech perception in >>>> noise is often difficult to predict from pure-tone thresholds or from >>>> speech perception in quiet settings. The NIH Toolbox version of the >>>> Words-in-Noise Test is newly released, so the interpretive guidelines >>>> provided are preliminary and may need further adjustment as future >>>> studies are conducted.As noted above, the range of possible scores for >>>> each ear is -2.0 to 26.0 dB S/N, with lower scores indicative of >>>> better performance and, conversely, higher scores potentially >>>> suggestive of hearing difficulties. For score interpretation with ages >>>> 13 and above, a cutoff of 10 dB S/N is recommended for the Toolbox >>>> version of this measure. Participants with a score higher than this >>>> cutoff should follow up with a hearing professional, specifically an >>>> otolaryngologist, who would then refer to an audiologist as needed. >>>> Users should note that the cutoff suggested here is slightly higher >>>> than other published versions of this test because other versions were >>>> conducted in quieter environments. >>>> >>>> Again, sorry for the oversight. Let me know if you have further >>> questions. >>>> >>>> Best, >>>> Jenn >>>> >>>> >>>> Jennifer Elam, Ph.D. >>>> Scientific Outreach, Human Connectome Project >>>> Washington University School of Medicine >>>> Department of Neuroscience, Box 8108 >>>> 660 South Euclid Avenue >>>> St. Louis, MO 63110 >>>> 314-362-9387<tel:314-362-9387> >>>> e...@wustl.edu<mailto:e...@wustl.edu> >>>> www.humanconnectome.org<http://www.humanconnectome.org/> >>>> >>>> >>>> >>> ------------------------------------------------------------------------ >>>> *From:* hcp-users-boun...@humanconnectome.org >>>> <hcp-users-boun...@humanconnectome.org> on behalf of Robert Becker >>>> <em...@robertbecker.info> >>>> *Sent:* Thursday, March 1, 2018 8:41:06 AM >>>> *To:* hcp-users@humanconnectome.org >>>> *Subject:* [HCP-Users] Correct interpretation of NIH battery test >>>> 'Words-in-Noise' in HCP subjects >>>> >>>> Dear all, >>>> >>>> we have trouble understanding what the above test actually tests in >>>> the context of HCP data. Despite its suggestive name, this test is >>>> described (in the updated HCP Data Dictionary and its previous >>>> version), as a pure-tone thresholding test that seems to have nothing >>>> to do with understanding words embedded in noise or any similar >>> scenario. >>>> >>>> The description in the Data Dictionary is pretty clear and excludes >>>> any such interpretation, it is just that the naming seems confusing >>>> and also, there actually is a NIH toolbox test called >>>> '"Words-in-Noise" that does test how subjects comprehend one-syllable >>>> words. >>>> >>>> >>>> Can anyone comment on the exact nature of this test and help us out? >>>> >>>> Thanks for your help! >>>> >>>> Robert >>>> -- >>>> Robert Becker, PhD >>>> Universit?t Z?rich >>>> Psychologisches Institut >>>> Binzm?hlestrasse 14 >>>> 8050 Z?rich >>>> >>>> Tel: +41 44 63 57234 >>>> em...@robertbecker.info <mailto:em...@robertbecker.info> >>>> >>>> _______________________________________________ >>>> HCP-Users mailing list >>>> HCP-Users@humanconnectome.org >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>>> >>> >>> -- >>> Robert Becker, PhD >>> Universit?t Z?rich >>> Psychologisches Institut >>> Binzm?hlestrasse 14 >>> 8050 Z?rich >>> >>> Tel: +41 44 63 57234 >>> em...@robertbecker.info >>> >>> -------------- next part -------------- >>> An HTML attachment was scrubbed... >>> URL: >>> http://lists.humanconnectome.org/pipermail/hcp-users/attachments/20180302 >>> /ad320ef0/attachment-0001.html >>> >>> ------------------------------ >>> >>> Message: 11 >>> Date: Fri, 2 Mar 2018 13:47:12 +0100 >>> From: A R <aruls...@gmail.com> >>> Subject: [HCP-Users] Split dtseries >>> To: hcp-users@humanconnectome.org >>> Message-ID: <4e282581-45a1-47b5-a40d-a7cdf679a...@gmail.com> >>> Content-Type: text/plain; charset=us-ascii >>> >>> Dear HCP users, >>> >>> How to split/trim a dtseries or ptseries file by number of time points? >>> Basically an equivalent of fslroi... >>> >>> Thanks for any info >>> >>> >>> ------------------------------ >>> >>> Message: 12 >>> Date: Fri, 2 Mar 2018 14:39:40 +0000 >>> From: "Glasser, Matthew" <glass...@wustl.edu> >>> Subject: Re: [HCP-Users] Split dtseries >>> To: A R <aruls...@gmail.com>, "hcp-users@humanconnectome.org" >>> <hcp-users@humanconnectome.org> >>> Message-ID: <d6bebe37.163961%glass...@wustl.edu> >>> Content-Type: text/plain; charset="us-ascii" >>> >>> wb_command -cifti-merge contains this functionality, rather than a >>> separate command. >>> >>> Peace, >>> >>> Matt. >>> >>> On 3/2/18, 6:47 AM, "hcp-users-boun...@humanconnectome.org on behalf of >>> A >>> R" <hcp-users-boun...@humanconnectome.org on behalf of >>> aruls...@gmail.com> >>> wrote: >>> >>>> Dear HCP users, >>>> >>>> How to split/trim a dtseries or ptseries file by number of time points? >>>> Basically an equivalent of fslroi... >>>> >>>> Thanks for any info >>>> _______________________________________________ >>>> HCP-Users mailing list >>>> HCP-Users@humanconnectome.org >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>> >>> >>> >>> >>> ------------------------------ >>> >>> Message: 13 >>> Date: Fri, 2 Mar 2018 16:13:16 +0000 >>> From: Kwan-Jin Jung <kjj...@umass.edu> >>> Subject: [HCP-Users] Change of FreeSurferHiresPial.sh for MacBook IOS >>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> >>> Cc: Hae-Min Jung <hae-min.j...@austenriggs.net> >>> Message-ID: <df573886-ad6b-437e-9499-6a9c8283e...@umass.edu> >>> Content-Type: text/plain; charset="utf-8" >>> >>> Hi, >>> >>> After I failed to run FreeSurfer pipeline on both Ubuntu and Centos, I >>> tried it on MacBook. >>> >>> It runs without library issues, but it seems to have differences in >>> shell scripting commands. >>> >>> The first example is ?cp? which needs to be replaced into ?rsync? in >>> both FreeSurferHiresWhite.sh and FreeSurferHiresPial.sh. >>> >>> Then there was another issue in FreeSurferHiresPial.sh at the line #92 >>> of: >>> "${CARET7DIR}/wb_command -set-structure "$surfdir"/lh.white.surf.gii >>> CORTEX_LEFT" >>> >>> I converted this into: >>> "open -a ${CARET7DIR}/wb_command -set-structure >>> "$surfdir"/lh.white.surf.gii CORTEX_LEFT" >>> >>> However, I am getting an error of: >>> "The file /Users/kjjung/MRI/HCP/Practice/CORTEX_LEFT does not exist." >>> >>> Does any one know how to fix this issue? >>> >>> My MacBook is macOS High Sierra, v10.13.3. >>> >>> Kwan-Jin Jung >>> UMASS Amherst >>> >>> >>> >>> ------------------------------ >>> >>> Message: 14 >>> Date: Fri, 2 Mar 2018 16:16:02 +0000 >>> From: "Glasser, Matthew" <glass...@wustl.edu> >>> Subject: Re: [HCP-Users] Change of FreeSurferHiresPial.sh for MacBook >>> IOS >>> To: Kwan-Jin Jung <kjj...@umass.edu>, "hcp-users@humanconnectome.org" >>> <hcp-users@humanconnectome.org> >>> Cc: Hae-Min Jung <hae-min.j...@austenriggs.net> >>> Message-ID: <d6bed4a4.1639e4%glass...@wustl.edu> >>> Content-Type: text/plain; charset="Windows-1252" >>> >>> I?m not sure we support the HCP Pipelines on Mac OS X. You definitely >>> need to be using a bash interpreter. >>> >>> What issues were you having on Ubuntu? >>> >>> Peace, >>> >>> Matt. >>> >>> On 3/2/18, 10:13 AM, "hcp-users-boun...@humanconnectome.org on behalf of >>> Kwan-Jin Jung" <hcp-users-boun...@humanconnectome.org on behalf of >>> kjj...@umass.edu> wrote: >>> >>>> Hi, >>>> >>>> After I failed to run FreeSurfer pipeline on both Ubuntu and Centos, I >>>> tried it on MacBook. >>>> >>>> It runs without library issues, but it seems to have differences in >>> shell >>>> scripting commands. >>>> >>>> The first example is ?cp? which needs to be replaced into ?rsync? in >>> both >>>> FreeSurferHiresWhite.sh and FreeSurferHiresPial.sh. >>>> >>>> Then there was another issue in FreeSurferHiresPial.sh at the line #92 >>> of: >>>> "${CARET7DIR}/wb_command -set-structure "$surfdir"/lh.white.surf.gii >>>> CORTEX_LEFT" >>>> >>>> I converted this into: >>>> "open -a ${CARET7DIR}/wb_command -set-structure >>>> "$surfdir"/lh.white.surf.gii CORTEX_LEFT" >>>> >>>> However, I am getting an error of: >>>> "The file /Users/kjjung/MRI/HCP/Practice/CORTEX_LEFT does not exist." >>>> >>>> Does any one know how to fix this issue? >>>> >>>> My MacBook is macOS High Sierra, v10.13.3. >>>> >>>> Kwan-Jin Jung >>>> UMASS Amherst >>>> >>>> _______________________________________________ >>>> 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 >>> >>> >>> End of HCP-Users Digest, Vol 64, Issue 2 >>> **************************************** >>> >>> _______________________________________________ >>> 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
