Freesurfer June 2014

freesurfer@nmr.mgh.harvard.edu

155 participants
234 discussions

Using QDEC for 3 groups x 2 time-points
by Tudor Popescu 23 Jun '14

23 Jun '14

Dear FS list, I have a data set with 3 groups (2 treatments, 1 control), each with equally-spaced time-points (pre and post structural scan). I've done the 3 longitudinal pre-processing steps, and stage#1 of the two-stage model, and I would prefer to run stage#2 (cross-sectional analysis of the difference) with QDEC as opposed to with mri_glmfit. I know that QDEC is meant for 2 groups, but I see that designs with 4 or 6 groups can be analysed with QDEC (as per this <https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples> FSGD examples page) whereas designs with 3 groups cannot be. It seems to me that an even number of groups is QDEC-able while an odd number isn't, but is there any workaround so that I can still use QDEC? Perhaps if I only do pairwise comparisons one at a time, i.e. treatment1 vs control and treatment2 vs control? Many thanks! Tudor

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low polygon count like fsaverage3
by Kai Schlamp 23 Jun '14

23 Jun '14

Hello again, I am still looking for a way to create a low polygon surface during recon-all (where labels still fit). Is there any (expert) option where I can specify the number of vertices or distance between vertices? How was fsaverage3 (very low polygon count) was created? Best regards, Kai

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Alzheimer's Disease Sage/DREAM Challenge
by Arno Klein 22 Jun '14

22 Jun '14

The Alzheimer's Disease Sage/DREAM Challenge #1 (AD#1) launched earlier this month! The goal of the AD#1 is to apply an open science approach to rapidly identify accurate predictive AD biomarkers that can be used by the scientific, industrial and regulatory communities to improve AD diagnosis and treatment. AD#1 will be the first in a series of AD Data Challenges to leverage genetics and brain imaging in combination with cognitive assessments, biomarkers and demographic information from cohorts ranging from cognitively normal to mild cognitively impaired to individuals with AD. FreeSurfer was instrumental in the processing of the image data. For challenge details, please see: https://www.synapse.org/#!Synapse:syn2290704 Cheers, @rno

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Postdoc opening in multimodal human brain mapping/modulation & epilepsy
by David Groppe 22 Jun '14

22 Jun '14

Post doctoral position available for research using a multimodal approach to investigate brain organization and function at the Hofstra University-North Shore LIJ School of Medicine in partnership with the Feinstein Institute for Medical Research. Studies involve surgical epilepsy patients undergoing intracranial electrophysiological monitoring for seizure detection and functional electrical stimulation mapping. Ongoing research projects include: 1) Validation of task-based and resting state fMRI and DTI using electrical stimulation mapping, electrocorticography and corticocortical evoked potentials; 2) Investigation of the neuronal dynamics underlying selective attention and active sensing, language, object identification and auditory stream analysis; 3) Modulation of neuronal function by direct cortical stimulation and investigation of the mechanisms of TMS, tDCS and tACS; 4) Prediction of seizure spread using electrophysiological and MRI markers. Responsibilities will include designing fMRI, ECoG and neurostimulation experiments and data analysis and the coordination of access to patients for research studies. Located in Long Island, 10 miles from Manhattan, there is tremendous opportunity for involvement with collaborative effort with multiple research groups the area with similar interests. Candidates should have M.D. and/or Ph.D. degrees and have some background in fMRI, electrophysiology, and/or data analysis (Matlab). Ideal start date would be between 9/2014-1/2015. For more information about the lab see: http://www.feinsteininstitute.org/faculty/ashesh-mehta-md-phd/ If interested, please submit CV and short statement of interest to Dr. Ashesh Mehta at amehta(a)nshs.edu for more information. -- David Groppe, Ph.D. Institute Scientist Laboratory for Multimodal Human Brain Mapping Feinstein Institute for Medical Research Manhasset, New York http://www.cogsci.ucsd.edu/~dgroppe/

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Why the result was not same for the same subject
by wangkangcheng_gmail 21 Jun '14

21 Jun '14

Dear experts I used freesurfer (Version 5.3) to calculate one subject for ten times and extract the number of each index. However, I found that the number was different each time. Is this normal? Why the result was not same for the same subject? Thank you Wang Kangcheng

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MatLab Version and Hardware and Freesurfer Statistics
by Pedro Rosa 20 Jun '14

20 Jun '14

Dear list, Does the OS version, hardware or MatLab version (i.e., 2013a vs. 2014a) impacts in the results from the LME processing (Bernal-Rusiel et al.), employed after the Freesurfer 5.1/5.3 longitudinal pipeline? Regards, Pedro Rosa.

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FreeSurfer Question
by Shazia Dharssi 20 Jun '14

20 Jun '14

Hi, I was wondering if you happened to know why the origin of the rawavg.mgz image is slightly different than the origin of my original structural image that I "recon"ed to obtain processed FreeSurfer data. Am I doing something wrong or is this expected? Is there an image that FreeSurfer creates that is has the exact dimensions and origin as my original data? Thank you in advance for all of your time and help! Best, Shazia -- *Shazia Dharssi* Columbia University Medical Center Department of Neurology Taub Institute P: (212) 305-8921 C: (319) 431-5060

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FLASH and MPRAGE sequences for segmentation on a GE 3.0T
by Sherwood, Matt 20 Jun '14

20 Jun '14

Freesurfer, We recently gained access to a new GE Discovery MR750w 3.0T GEM MRI with a 24 channel headcoil. Because this system is located at a nearby hospital and is used clinically, we do not have a research agreement with GE in place and, therefore, cannot edit the default pulse sequences. We were wondering what scans/parameters would give us optimal segmentation (similar to MPRAGE and/or FLASH at https://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferWiki?action=AttachFile&…) Thanks, Matthew Sherwood Medical Research Engineer Wright State Research Institute 4035 Colonel Glenn Hwy. Dayton, OH 45431 PH: 937.705.1025 FAX: 937.705.1095 EMAIL: matt.sherwood(a)wright.edu<mailto:matt.sherwood@wright.edu>

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Re: [Freesurfer] Fwd: Improving translation of Choi striatal ROIs to original domain
by Paul Beach 20 Jun '14

20 Jun '14

Thomas, Thank you so much for this input. I tried out both the striatum and the general MNI152 template. For the striatum the match is *SO* much better. The MNI152 template also looks alright - though it's a little fuzzy. I'm pretty happy with this now and I'll definitely have more confidence in any striatum-based connectivity differences I see now. Thanks again. Paul On Thu, Jun 19, 2014 at 11:07 AM, Thomas Yeo <thomas.yeo(a)nus.edu.sg> wrote: > Sorry for the slow reply. Here's a (non-ideal) suggestion: > > 1) Assuming you are quite happy with the freesurfer striatal parcellation > in your AD subjects, then I am assuming freesurfer nonlinear registration > (talairach.m3z) is working quite well. Talairach.m3z warps your subject to > an internal freesurfer space (kinda like MNI305, but not quite). Let's say > the freesurfer recon-all output is at <something>/AD_SUBJECT_FS/ > > 2) Run the MNI152 1mm template (the one from FSL) through recon-all. > Recon-all will give you a Talairach.m3z that allows you to map the MNI152 > 1mm template to the internal freesurfer space. Let's say the freesurfer > recon-all output is at <something>/MNI152_FS/ > > 3) Then do the following: > > a) Use mri_vol2vol to upsample the Choi striatal atlas which is 2mm > resolution to the 1mm MNI152 template: > > >> mri_vol2vol --mov Choi_atlas.nii.gz --targ MNI152/mri/norm.mgz > --regheader --o Choi_atlas1mm.nii.gz --no-save-reg --interp nearest > > Notice that I use norm.mgz of the MNI template rather than the original > MNI template? norm.mgz is the 256 x 256 x 256 conformed version of the MNI > template that recon-all puts through. > > b) warp the Choi_atlas1mm.nii.gz to freesurfer nonlinear volumetric space: > > >> setenv SUBJECTS_DIR <something> > >> mri_vol2vol_used --mov Choi_atlas1mm.nii.gz --s MNI152_FS --targ > $FREESURFER_HOME/average/mni305.cor.mgz --m3z talairach.m3z --o > Choi_atlas_freesurfer_internal_space.nii.gz --interp nearest > > c) warp the Choi_atlas_freesurfer_internal_space.nii.gz to your subject: > > >> setenv SUBJECTS_DIR <something> > >> mri_vol2vol --mov $SUBJECTS_DIR/AD_SUBJECT_FS/mri/norm.mgz --s > AD_SUBJECT_FS --targ Choi_atlas_freesurfer_internal_space.nii.gz --m3z > talairach.m3z --o Choi_atlas_AD_subject.nii.gz --interp nearest --inv-morph > > > This is not optimal because of the double interpolation. You might want to > use the MNI template instead of the Choi_atlas to test the above, so you > can check the goodness of the warp. The final warped MNI template should > hopefully look identical to your AD subject. If that works, then use the > Choi_atlas. Note that mri_vol2vol does not work properly for talairach.m3z > below version 5, so you should use version 5x mri_vol2vol. > > --Thomas > > > > > > > > > > On Wed, Jun 18, 2014 at 10:04 PM, Harms, Michael <mharms(a)wustl.edu> wrote: > >> >> Hi, >> The recon-all based striatal parcellations are based on the anatomy of >> each particular subject, guided by a probabilistic atlas. That is >> inherently likely to be more accurate that just taking a set of >> ROIs/parcellations defined in some (non-probabilistic) atlas and warping >> them to each subject via an affine transformation, which is what it sounds >> like you are doing with the "Choi ROIs". >> >> 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: mharms(a)wustl.edu >> >> From: Paul Beach <pabeach1(a)gmail.com> >> Reply-To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> >> Date: Wednesday, June 18, 2014 8:52 AM >> To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> >> Cc: Thomas Yeo <thomas.yeo(a)nus.edu.sg>, "Yeo, Boon Thye Thomas -- Boon >> Thye Thomas Yeo" <ythomas(a)csail.mit.edu> >> Subject: Re: [Freesurfer] Fwd: Improving translation of Choi striatal >> ROIs to original domain >> >> Hi Bruce, >> >> Thanks for the response. >> >> I actually got this pipeline partly from Thomas a few months back. >> However, I wasn't sure if anyone had suggestions perhaps for a recon-all >> based command for going from the MNI152 1mm template-based fit to >> individual subjects. The recon-all/Freesurfer inherent striatal >> parcellations are so well fitted to even my severe AD patients, so I was >> hoping I could somehow adapt this to the Choi ROIs. >> >> >> On Wed, Jun 18, 2014 at 8:45 AM, Bruce Fischl <fischl(a)nmr.mgh.harvard.edu >> > wrote: >> >>> Hi Paul >>> >>> Thomas Yeo (ccd) would be the best person to help you, but he may not be >>> reading email for a while.... >>> >>> cheers >>> Bruce >>> >>> >>> >>> On Wed, 18 Jun 2014, Paul Beach wrote: >>> >>> Hi Freesurfers, >>>> My processing stream involves moving the parcellated functional >>>> networks of >>>> Yeo and Choi to original subject domain to do connectivity analyses. >>>> While >>>> my process works very well for the Yeo networks I'm rather unsatisfied >>>> by >>>> the results of the Choi translations. >>>> >>>> I'm hoping someone has some suggestions for improving things so that the >>>> Choi ROIs map onto individual subjects nearly as well as the general >>>> Freesurfer striatal segmentations. >>>> >>>> NB - I work with AD patients, so I'm sure part of the problem is >>>> atrophy-based. However, I'm sure there are ways to improve things... >>>> >>>> My current pipeline involves two steps: >>>> mri_vol2vol \ >>>> --mov Choi2012_17Networks_MNI152_FreeSurferConformed1mm_TightMask.nii.gz >>>> \ >>>> --targ $FSLDIR/data/standard/MNI152_T1_2mm_brain.nii.gz --regheader \ >>>> --o FSL_choi_17Net_MNI152_tight_parcellation.nii.gz --no-save-reg >>>> --interp >>>> nearest >>>> >>>> mri_label2vol \ >>>> --seg FSL_choi_17Net_MNI152_tight_parcellation.nii.gz \ >>>> --reg $SUBJECTS_DIR/{$subj}/mri/transforms/reg.mni152.2mm.dat \ >>>> --invertmtx \ >>>> --o Choi_17Network_tight_striatum_orig.nii.gz \ >>>> --temp $SUBJECTS_DIR/{$subj}/mri/orig.mgz >>>> >>>> I suspect one way to improve things would be to do a recon-all based >>>> procedure, but I have no clue what commands within the recon-all domain >>>> that >>>> would involve. >>>> >>>> >>>> Thanks for your suggestions. >>>> -- >>>> Paul Beach >>>> DO/PhD candidate - Year VI >>>> Michigan State University >>>> - College of Osteopathic Medicine >>>> - Neuroscience Program - MSU Cognitive and Geriatric Neurology Team >>>> (CoGeNT) >>>> >>>> >>> _______________________________________________ >>> Freesurfer mailing list >>> Freesurfer(a)nmr.mgh.harvard.edu >>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>> >>> >>> 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. >>> >>> >> >> >> -- >> Paul Beach >> DO/PhD candidate - Year VI >> Michigan State University >> - College of Osteopathic Medicine >> - Neuroscience Program >> - MSU *Co*gnitive and *Ge*riatric *N*eurology *T*eam (*CoGeNT*) >> >> >> ------------------------------ >> >> 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. >> > > -- Paul Beach DO/PhD candidate - Year VI Michigan State University - College of Osteopathic Medicine - Neuroscience Program - MSU *Co*gnitive and *Ge*riatric *N*eurology *T*eam (*CoGeNT*)

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Reducing Used Disk Space?
by Jamie Hanson 20 Jun '14

20 Jun '14

Hi Freesurfer List, Do folks have any recommendations on reducing the amount of space used by each subject? I looked a bit in the list archives but didn't see any recent tips. I had a large potential sample size (n=~750) and didn't know if I would have the estimated 375GBs processing would require. It looked as though there was potentially some space to trim (i.e., deleting some files in the mdi directory like nu.mgz, nu_noneck.mgz) once processing had completed). I wondered if anyone had a more exhaustive list (or suggestions) regarding files that could be deleted? Any help is greatly appreciated! Thanks much! Best, jamie. -- Jamie L. Hanson Postdoctoral Fellow, Laboratory of NeuroGenetics Duke University 417 Chapel Drive Duke West Campus Sociology-Psychology Building, Room 07A Durham, NC 27710 Email: jamielarshanson(a)gmail.com Website: http://jamiehanson.org/

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Freesurfer June 2014