Freesurfer

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30076 discussions

qdec question
by Yaakub, Siti Nurbaya 28 Nov '16

28 Nov '16

Dear Experts, I'm looking at differences in area between two groups of subjects in FreeSurfer using qdec. I've delineated an ROI based on a cluster that showed significant differences in surface area between the two groups (taking gender into account, and with age and ICV as nuisance covariates). As a sanity check, I extracted the total surface area values for that ROI for each subject in native space (using mri_label2label and mris_anatomical_stats) When I plot these values (and do an ANCOVA with the same covariates, or even just a simple t-test) there is almost no difference between the groups. Did I do something wrong? How do I get the average surface area values for each subject (in that ROI that shows a difference) so I can see the spread of values in each group? Thanks, Siti

2 1

Multiple Frames Error
by James Wilks 28 Nov '16

28 Nov '16

Hello, I’ve been having a problem with recon-all lately. I’m relatively new to FreeSurfer and the processes that I have done in the past have been done on sample individualized scans in my lab and I ran into an issue once I started trying to run FreeSurfer on fMRI data provided by our lab. Whenever I try to run the command this is the generated output: #@# MotionCor Wed Nov 23 11:01:54 EST 2016 Found 1 runs /export/home/jawilks/Desktop/freesurfer/subjects/run_02/mri/orig/001.mgz Checking for (invalid) multi-frame inputs... ERROR: input(s) cannot have multiple frames! /export/home/jawilks/Desktop/freesurfer/subjects/run_02/mri/orig/001.mgz has 160 frames Linux tykwer.engin.umich.edu 2.6.18-416.el5 #1 SMP Wed Oct 26 12:04:18 EDT 2016 x86_64 x86_64 x86_64 GNU/Linux recon-all -s run_02 exited with ERRORS at Wed Nov 23 11:01:57 EST 2016 The archives have not been of any help and I would greatly appreciate it if someone would be able to help point me in the right direction. Thank You

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QDEC versus R
by Lisa Delalande 28 Nov '16

28 Nov '16

Hello, As a PhD student, I send you this mail because i am meeting a misunderstanding with QDEC. In a few words : I made an analysis thanks to the QDEC tool : * I tested a correlation between an inhibition score and cortical thickness, corrected for age (continuous = inhibition score ; nuisance = age ; smoothing = 25 and FDR corrected) *** ***** ** *********** * *********** ******* *** ********** ***** *** ******** ********* ** ***** ****** ************** ***** * then, I realised a ROI analysis. I extracted different statistic values from this orbito-frontal region following your wiki (aparcstat2table). Thus, I obtained for each participant, the average value of medial orbitofrontal cortical thickness. Finally, I made a multiple linear regression analysis on R software which is a statistical software. Surprisingly, « R », indicated that it doesn't exist any correlation between the right medialorbito frontal thickness values and the inhibition scores. I don't understand why. Can you help shed some light on this issue ? Yours sincerely Marine Moyon

2 1

Re: [Freesurfer] ASL processing in Freesurfer?
by Elijah Mak 28 Nov '16

28 Nov '16

Apologies, please ignore the other email response. I believe this should be tagged to the right thread (hopefully!) ----- Many thanks for the information, Doug! I will give it a go. Actually, I would like to carry out the following analyses: Get regional estimates of perfusion within a region of interest as defined by a significant cluster after mri_glmfit-sim. as well as other cortical regions that are connected to that cluster in terms of WM paths. Is it possible to do that in Freesurfer environment? How can I do PVC for perfusion in ROIs? Will the -pv ppvol flag be crucial during the mri_segstats stage? Thanks again for help. Best Wishes, Elijah Re: [Freesurfer] ASL processing in Freesurfer? <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=subje…> Douglas Greve <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=from:…> Mon, 21 Nov 2016 12:31:41 -0800 <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=date:…> No, not really. If you're not doing anything fancy (eg, just computing mean of tag-control) and mapping to the surface, it is easy enough to do (mri_concat --paired-diff --sum, then bbregister to register to the anat, then mri_vol2surf or mris_preproc to map to fsaverage, then mri_glmfit and mri_glmfti-sim. If you're trying to correct for decay, intensity gradients, etc, then no. On 11/21/16 1:40 PM, Foo Keat Mak wrote: > Hi Freesurfer Team, > > Is there an ASL-friendly processing pipeline embedded in Freesurfer? > Something like an equivalent to that of PetSurfer? Thanks. > > Best Wishes, > Elijah > > Sent from my iPad > _______________________________________________ > Freesurfer mailing list > Freesurfer(a)nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > _______________________________________________ Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://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 athttp://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.

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Cohen's D = gamma.mgh / rstd.mgh?
by Elijah Mak 28 Nov '16

28 Nov '16

Hi there, What is the correct way to plot, at each vertex, the Cohen's *D* after a *mri_glmfit* comparison? I've seen a few variations posted on the mailing list. Is gamma.mgh / rstd.mgh is the correct formula? Does rstd.mgh represent pooled SD across both groups (patients and controls)? Secondly, after plotting the effect size across the whole brain, is it feasible to test whether there are regional differences in effect size by using *mri_segstats* and *aparc* to extract the ROI-averaged effect size in *fsaverage* space, and then perform a paired t-test between say, frontal vs occipital ROIs? Thank you. Best Wishes, Elijah

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Re: [Freesurfer] how does the content of the curv files compare to that of smoothwm.H.crv
by Bernardoni, Fabio 28 Nov '16

28 Nov '16

Dear Bruce, thanks a lot for your answer. I am still a bit confused. I followed your suggestion to use msris_curvature to compute the curvature on the white surface (unsmoothed) instead of on smoothwm: mris_curvature -w -a 10 $subj/surf/lh.white mris_preproc -s $subj --target fsaverage --hemi lh --meas white.H --out ./measures/lh.white.H.mgh mri_surf2surf --hemi lh --s fsaverage --sval ./measures/lh.white.H.mgh --tval ./measures/lh.white.H_sm10.mgh --fwhm-trg 10 --cortex --noreshape (mri_surf2surf smoothing was applied also to other curvatures) If I understood right, mris_curvature uses a hessian method to compute the curvature, while mris_curvature_stats uses the Gauss-Bonnet theorem (I extracted this information from your email to this mailing list from: Fri, 26 Feb 2010 05:54:32 -0800). In an email from Wed, 30 Mar 2011 12:40:58 -0700, Rudolph says that gauss-bonnet procedure is more robust against noise. Does this also hold for the mean/extrinsic curvature? I ask because in the Gauss-Bonnet theorem only the gaussian curvature is mentioned. For the extrinsic/mean curvature (see attachment) I obtain that actually the smoothwm.H.crv seems to be the noisiest quantity (red in the histogram), followed by the classical method applied on the unsmoothed white matter surface (blu) and by the classical method applied on the smoothed wm surface (green, corresponds to the ?h.curv files produced by recon-all). This observation also holds when comparing the curvature in ?h.curv.pial and ?h.pial.H.crv (histogram sent in my previous email). In that case, on many vertices the mean curvature computed with the gauss-Bonnet method was ~1/mm which makes me think to unrealistically small 'hollows' on the pial surface. Finally, to compare curvature vertexwise between a group of patients and controls, which should be the right numerical quantity to look at: 1- curv.pial (classic method on smoothed pial surface - from recon-all) 2- pial.H (classic method on smoothed pial surface - from mris_curvature) 3- pial.H.crv (gauss-bonnet method on the pial surface - from mris_curvature_stats)? Thank you very much for any help, Fabio Dr. Fabio Bernardoni wiss. Mitarbeiter Psychosoziale Medizin und Entwicklungsneurowissenschaften Tel. +49 (0)351 458-5245 Fax +49 (0)351 458-7206 URL http://www.uniklinikum-dresden.de/psm; www.transdenlab.de Universitätsklinikum Carl Gustav Carus & Medizinische Fakultät an der Technischen Universität Dresden Anstalt des öffentlichen Rechts des Freistaates Sachsen Fetscherstraße 74, 01307 Dresden http://www.uniklinikum-dresden.de Vorstand: Prof. Dr. med. D. M. Albrecht (Sprecher), Wilfried E. B. Winzer Vorsitzender des Aufsichtsrates: Prof. Dr. med. Peter C. Scriba USt.-IDNr.: DE 140 135 217, St.-Nr.: 203 145 03113

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Re: [Freesurfer] LME: contrast questions
by jorge luis 28 Nov '16

28 Nov '16

Hi Jordi You have implicitlyincluded the reference group in your statistical model by includingan intercept term and a time variable: group0 intercept: ß1group0 time: ß2group1 intercept:ß1+ß3group1 time: ß2+ß4group2 intercept:ß1+ß5group2 time: ß2+ß6 >From here you canquickly see that your proposed contrast for the differences inthe mean response over time between group1 and group2 is correct. Finally the regiongrowing estimation method should yield more precise (lower variance)estimates for the ßs but I think it’s (might be) too complicatedto setup with the current scripts. The vw method will produce goodestimates too. So I recommend the vw estimation method if things gettoo complicated for you with the region-wise method. Cheers-Jorge De: Jordi Pegueroles <jordi(a)pegueroles.cat> Para: Freesurfer <freesurfer(a)nmr.mgh.harvard.edu>; jbernal0019(a)yahoo.es Enviado: Lunes 28 de noviembre de 2016 5:11 Asunto: LME: contrast questions Dear FS experts, I am trying to run a LME model for three groups (group0, group1 and group2) and (almost all) with three time points, all processed using the Longitudinal FS stream. Our intention is to compare the differences between group0 against group1 and group0 against group2. I have followed the online LME tutorial and I have adapted your code to my data. However, I think I have not well understood the steps and I have few questions that you will be able to answer me... i) In the X matrix I put the following columns: 1) intercept 2) time (years from baseline) 3) group1 (binary variable: 1 if belongs to group1) 4) group1.*time 5) group2 (binary variable: 1 if belongs to group2) 6) group2.*time I don't understand why I do not have to include the reference group (in my case group0 and group0.*time) in the design matrix. How I can see the progresion of the reference group if I did not include it in the design matrix? How I can compare both progressions if the time of the group0 subjects is not taking into account? ii) Linked to the previous question, if I want to compare the differences in time between group1 and group2... Should the contrast be C = [0 0 0 1 0 -1]? iii) Finally, between the vw method and the region growing method which one is more accurate? In other words, which one do you recommend to use? Thank you, -- Jordi.

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surface based analysis for subcortical structures
by John Anderson 28 Nov '16

28 Nov '16

3 11

OPPORTUNITY OF FULL-TIME POSTDOCTORAL FELLOWSHIP AT THE UNIVERSITY OF SÃO PAULO, BRAZIL
by Neuroimagem IPQHCFMUSP - LIM21 28 Nov '16

28 Nov '16

One postdoctoral position is available within the Laboratory of Psychiatric Neuroimaging (LIM21) (www.neuroimagem.org.br/) at the University of São Paulo Medical School, Brazil, directed by Geraldo F. Busatto, Ph.D. Candidates should send a message to neuroimagem.ipq(a)hc.fm.usp.br with his/her CV and a letter of support. Deadline: 06 Dec 2016 *JOB DESCRIPTION* We are looking for a full-time researcher with previous experience in the use of software for the analysis of neuroimaging data. This post-doctoral fellow will be requested to work mainly with data acquired using resting-state functional magnetic resonance imaging methods (rs-fMRI) to evaluate patterns of functional connectivity in the brain. In our project, funded by the *FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO, BRAZIL* (FAPESP), such brain imaging data is being acquired in groups of cognitively-intact elderly individuals, patients with Alzheimer´s disease (AD), and patients with mild cognitive impairment (MCI). Pre-processing steps will be carried out using the software Analysis of Functional NeuroImages (AFNI), while the actual processing of data will be conducted using Matlab-based programs. The work will also involve use of software to evaluate the diagnostic accuracy to distinguish between AD, MCI and healthy elderlies, generating multivariate classifiers based on machine-learning methods (support vector machine). With such strategy, we aim to identify which are the functional connectivity characteristics in the brain that are most critical for the progression from normal cognition to MCI and then to AD. The post-doctoral fellow should have knowledge about the acquisition and analysis of fMRI data and other neuroimaging modalities. We aim to bring an individual with abilities to carry out, independently, analyses and organization of computational brain imaging data, interaction with other researchers involved in the same project, and participating in the writing up of scientific papers. These characteristics are expected to boost the scientific productivity from the funded project, both quantitatively and qualitatively. The professional will also have the opportunity to interact with scientists who are at the forefront of technologies for amyloid imaging in the brain, and data will be combined with fMRI analyses in the same elderly subjects evaluated with those two imaging technologies. The post-doctoral fellow will have the opportunity to practice abilities in analysing data of a challenging scientifc project, and he/she will be expected to establish and use optimized processing pipelines for the analysis of rs-fMRI data and other neuroimaging modalities. *REQUIREMENTS* - Completed PhD in areas related to computer sciences, neuroscience, neurology or psychiatry - Research interest and brain imaging applied to research studies of brain aging - Previous experience in the usage of processing and statistical analysis methods for research studies applied to magnetic resonance imaging studies of the brain. best regard *Laboratory of Psychiatric Neuroimaging - HCFMUSP*

1 0

(no subject)
by Lisa Delalande 28 Nov '16

28 Nov '16

Hello, I made an analysis thanks to the QDEC tool : I tested a correlation between an inhibition score and cortical thickness, corrected for age (continuous = inhibition score ; nuisance = age ; smoothing = 25 and FDR corrected) *** ***** ** *********** * *********** ******* *** ********** ***** *** ******** ********* ** ***** ****** ************** ***** then, I realised a ROI analysis. I extracted different statistic values from this orbito-frontal region following your wiki (aparcstat2table). Thus, I obtained for each participant, the average value of medial orbitofrontal cortical thickness. Finally, I made a multiple linear regression analysis on R software which is a statistical software. Surprisingly, « R », indicated that it doesn't exist any correlation between the right medialorbito frontal thickness values and the inhibition scores. I don't understand why. Can you help shed some light on this issue ? Yours sincerely Marine Moyon

1 0

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