Freesurfer

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Postdoc Position in Neuromodulation and Neuroplasticity
by Xin Niu 24 Jan '23

24 Jan '23

External Email - Use Caution The Jiang Lab at the University of Iowa Carver College of Medicine (PI: Dr. Jing Jiang, https://secure-web.cisco.com/10vUzmjBRWrQ1Vub-YnhB7SPAxb-DAoT1MPQ0v4jSvBH4J…) is seeking a highly motivated postdoctoral fellow to join our team with a two-year term (and a possibility of extension) to work on projects related to neuromodulation and neuroplasticity. Research topics may include but not limited to emotion, language, and social cognition. The lab has a variety of unique datasets ready for immediate analyses, such as concurrent transcranial magnetic stimulation (TMS)-functional magnetic resonance imaging (fMRI), concurrent TMS-intracranial electroencephalography (iEEG), as well as brain lesion data from healthy, neuropsychiatric, and neurological populations. We are an interdisciplinary team situated in the Stead Family Department of Pediatrics and Department of Psychiatry. We maintain active collaborations with faculty and teams from the Departments of Neurology, Neurosurgery, Psychological and Brain Sciences, and Biomedical Engineering at the University of Iowa, the Iowa Neuroscience Institute, and the Intellectual and Developmental Disabilities Research Center. Our lab has access to the University of Iowa’s cutting-edge imaging facility ( https://secure-web.cisco.com/192mgb7jZPH5i5Ds18c_Lq95BFqyv8OB41Xvsq_HBr9KU2…) the world-renowned Iowa Neurological Patient Registry (https://secure-web.cisco.com/1qOPlXLuKPecg09RxBLKBWQ7BSAZwgBvTlGAKVig6-uoUX…) including neuroimaging and neuropsychological testing data from over 4,400 patients with focal brain lesions, and state-of-the-art portable fNIRS, concurrent TMS-fMRI, concurrent TMS-iEEG, and concurrent es-fMRI systems. The University of Iowa is an internationally recognized leader in neuropsychology and cognitive neuroscience. The Roy J. and Lucille A. Carver College of Medicine is consistently one of the nation’s top-ranked medical schools (#39 on research by the 2022 U.S. News & World Report). The Stead Family Children’s Hospital is listed among the nation’s best in seven specialties in the 2022-23 “Best Children’s Hospitals” rankings by U.S. News & World Report (#38 in pediatrics neurology). Iowa City ranks among one of the best places to live in America (e.g., #1 Best College Town by Reviews.org) Iowa City, Johnson County, and the state of Iowa all routinely appear on national “best of” lists <https://secure-web.cisco.com/1820NySo0132mIvD01EKSA8fbYnZMtV5Q2_otNeEyStvTS…> for low cost of living, safety, access to world-class health care, and more <https://secure-web.cisco.com/1UPyZvyZ1OHLRh_2ZA_AegJ56sxGn4jhaj0ypgucw582K1…>. *Responsibilities and what you will achieve* The goal of postdoctoral training in our lab is to help you become an independent researcher. To achieve this goal, you will work with Dr. Jiang to develop a plan (e.g., independent projects, mentorship experience, grant application, job hunts, networking) that meets your career development. You will receive theoretical and methodological training and resources through ongoing projects and independent projects, mentor students and research assistants, publish impactful papers, and apply for eligible research grants. You will also be provided with networking opportunities and professional guidance for job hunts. *Requirements* - PhD and/or MD degree in Neuroscience, Computer Science, Electrical or Biomedical Engineering, Psychology, Cognitive Science, Biology, or a related field - A track record of peer-reviewed scientific journal publications in human neuroscience - Experience with programming, e.g., in MATLAB, Python, R, and/or Shell - Experience with data analyses, e.g., in fMRI, (i)EEG, brain lesion, and/or, neural network - Self-motivated, able to work independently, strong written and interpersonal communication skills To apply, please email (1) a cover letter describing your research interests and (2) your CV to Dr. Jing Jiang (jing-jiang(a)uiowa.edu) Applications will be reviewed on a rolling basis until the position is filled. Start date is flexible depending on candidate availability.

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FSL on recon-all
by Aaron Tanenbaum 24 Jan '23

24 Jan '23

External Email - Use Caution Hello FreeSurfers, I just need to know if the FSL is used in the recon-all scripts. Basically if FSL_DIR is different will the recon-all produce different values. Thank you Aaron.

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mri_glmfit
by James Brown 24 Jan '23

24 Jan '23

External Email - Use Caution Dear FS experts, I am working on a surface based analysis using FS 7.1.1 and I would like to run mri_glmfit between two groups using the flag "--label" to restrict analysis within lobes. I ran these commands on fsaverage mri_annotation2label --subject fsaverage --hemi lh --lobesStrict lobes mri_annotation2label --subject fsaverage --hemi rh --lobesStrict lobes This created annotation files within the "labels" folder of fsaverage, then I ran mri_glmfit using the flag --label lh.lobes from fsaverage I got this error message mri_glmfit: could not scan # of lines from label file I am ot sure what I am doing wrong. Thanks for guidance James

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segmentation of phantoms with own defined PVE priors
by Nederpelt, D.R. van (David) 24 Jan '23

24 Jan '23

External Email - Use Caution Hi Freesurfer developers, I am trying to segment phantoms, but I would like to base the principle of the segmentation on a "freesurfer-like" pipeline/segmentation. This is to minimize differences between the segmentation pipeline of the phantoms compared to the patient/subject segmentation. I have predefined priors of the phantoms. Would you be able to provide me with some advice regarding this or maybe a collaboration? Thank you very much in advance. Best regards, David [cid:image002.png@01D40E30.3E299A80] David R. van Nederpelt, MSc | PhD Candidate Radiology and Nuclear Medicine Amsterdam UMC, Location VUmc | PK -1 X 004 | De Boelelaan 1118, 1081 HZ Amsterdam, the Netherlands T: +31 20 444 6480 | E: d.vannederpelt(a)amsterdamumc.nl<mailto:d.vannederpelt@amsterdamumc.nl> http://secure-web.cisco.com/1at1mrWf46TOdtPx5xS0xcPHtKcjjqhnoJwny2mJmnGu4hm…<http://secure-web.cisco.com/1yt8mKzBEytW00FvP7R2l1fvv0p1Pks7wPNSutSj2uehWVn…> | http://secure-web.cisco.com/1y-o8iz8BJklocrN5kNtjdaY9roEiw9EV6YPN1Wwf9vH14d…<http://secure-web.cisco.com/1E1k3KMRyxkEmAcnW_-WFns2RvcM9ov9xv6I3gxiqAnetJC…> / http://secure-web.cisco.com/1GkQSxDF48gjZk9fcvs_RSxxTrrn8aVzrQUNoTHAGIapFGV…<http://secure-web.cisco.com/1goc8A86juC4VvHujbtKqV3uicP70Yt2xy7J6aiTJF2W-mb…> ______________________________________________________ ______________________________________________________ AmsterdamUMC disclaimer : http://secure-web.cisco.com/19CYr4N6KMaTAvugEDoUiopxGZ9zOlXs-WAapNPiU40Nisk…

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Two basic questions: brainmask file versions and qcache
by Harriott, Emily M 23 Jan '23

23 Jan '23

External Email - Use Caution Dear FreeSurfer experts, I hope this email finds you all well. I have two relatively basic questions that I am hoping to get some help with. My basic planned processing pipeline is: Run initial recon-all with gcut and ws flags Edit white matter/pial voxels and add control points (as needed) Run second recon-all with autorecon2 and autorecon3 flags Run LGI I have two questions about this: When I run the initial recon-all, I end up with three versions of the brainmask within the /mri/ folder: brainmask.auto.mgz, brainmask.gcuts.mgz, brainmask.mgz. Which brainmask version do I edit, so that my edits are incorporated into the second recon-all run and thus the second attempt at wm/gm segmentation is better? Exactly when and with what command(s) do I use the qcache flag? I apologize that these are quite basic, but sincerely appreciate any input anyone might be able to provide. Thank you so very much in advance! All the best, Emily Harriott Doctoral student at Vanderbilt University

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Dijk.m - Freesurfer Dijkstra MATLAB function
by Sarah Lavelle 23 Jan '23

23 Jan '23

External Email - Use Caution Hi there, I'm looking to use the *Dijkstra matlab code* provided by freesurfer, titled 'dijk.m'. It calculates the *shortest path* from node 's' to node 't'. I want to use this to calculate the distance from 1 vertex to another on an inflated cortical surface( in matlab.) I currently have the surface imported into matlab in terms of 2 matrices: *vertices(V) and edges(E)*. (this was done using the 'freesurfer_read_surf' function. ) However, the input used to describe the cortical surface/graph in dijk.m is 'A'. After researching, I believe that 'A' the *weighted adjacency matrix* of the graph? Is that right? And if so, do you know how I can get 'A' using 'V' and 'E', so I can use it as an input in dijk.m? Thanks, Sarah DIJK.M: function [D,P] = dijk(A,s,t) %DIJK Shortest paths from nodes 's' to nodes 't' using Dijkstra algorithm. % [D,P] = dijk(A,s,t) % % (Note: A(i,j) = 0 => Arc (i,j) does not exist; % A(i,j) = NaN => Arc (i,j) exists with 0 weight) % s = FROM node indices % = [] (default), paths from all nodes % t = TO node indices % = [] (default), paths to all nodes % D = |s| x |t| matrix of shortest path distances from 's' to 't' % = [D(i,j)], where D(i,j) = distance from node 'i' to node 'j' % = Inf, if no path from 'i' to 'j' % P = |s| x n matrix of predecessor indices, where P(i,j) is the % index of the predecessor to node 'j' on the path from 's(i)' to % 'j',where P(i,i) = 0 and P(i,j) = NaN is 'j' not on path to % 's(i)' (use PRED2PATH to convert P to paths) % = path from 's' to 't', if |s| = |t| = 1 % % Example: % A = [0 1 3 0 % 0 0 0 2 % 0 0 0 4 % 0 0 0 0] % [d,p] = dijk(A,1,4) % (Single path) d = 3 % % p = 1 2 4 % % [D,P] = dijk(A) % (All paths) D = 0 1 3 3 % % Inf 0 Inf 2 % % Inf Inf 0 4 % % Inf Inf Inf 0 % % P = 0 1 1 2 % % NaN 0 NaN 2 % % NaN NaN 0 3 % % NaN NaN NaN 0 % p = pred2path(P,1,4) % p = 1 2 4 % % (If A is a triangular matrix, then computationally intensive node % selection step not needed since graph is acyclic (triangularity is a % sufficient, but not a necessary, condition for a graph to be acyclic) % and A can have non-negative elements) % % (If |s| >> |t|, then DIJK is faster if DIJK(A',t,s) used, where D is now % transposed and P now represents successor indices) % % (Based on Fig. 4.6 in Ahuja, Magnanti, and Orlin, Network Flows, % Prentice-Hall, 1993, p. 109.) % Copyright (c) 1994-2006 by Michael G. Kay % Matlog Version 9 13-Jan-2006 (http://secure-web.cisco.com/1cRs4G5kkiqFfc2Vy9yVEtcMD7rwIzApZJZ4z6EgLjvr3DL…) % Input Error Checking **************************************************** error(nargchk(1,3,nargin)) [n,cA] = size(A); if nargin < 2 || isempty(s), s = (1:n)'; else s = s(:); end if nargin < 3 || isempty(t), t = (1:n)'; else t = t(:); end if ~any(any(tril(A) ~= 0)) % A is upper triangular isAcyclic = 1; elseif ~any(any(triu(A) ~= 0)) % A is lower triangular isAcyclic = 2; else % Graph may not be acyclic isAcyclic = 0; end if n ~= cA error('A must be a square matrix'); elseif ~isAcyclic && any(any(A < 0)) error('A must be non-negative'); elseif any(s < 1 | s > n) error(['"s" must be an integer between 1 and ',num2str(n)]); elseif any(t < 1 | t > n) error(['"t" must be an integer between 1 and ',num2str(n)]); end % End (Input Error Checking) ********************************************** A = A'; % Use transpose to speed-up FIND for sparse A D = zeros(length(s),length(t)); if nargout > 1, P = NaN*ones(length(s),n); end for i = 1:length(s) j = s(i); Di = Inf*ones(n,1); Di(j) = 0; isLab = false(length(t),1); if isAcyclic == 1 nLab = j - 1; elseif isAcyclic == 2 nLab = n - j; else nLab = 0; UnLab = 1:n; isUnLab = true(n,1); end if nargout > 1, P(i,s(i)) = 0; end %Change from NaN to indicate no pred while nLab < n && ~all(isLab) if isAcyclic Dj = Di(j); else % Node selection [Dj,jj] = min(Di(isUnLab)); j = UnLab(jj); UnLab(jj) = []; isUnLab(j) = 0; end nLab = nLab + 1; if length(t) < n, isLab = isLab | (j == t); end [jA,kA,Aj] = find(A(:,j)); Aj(isnan(Aj)) = 0; if isempty(Aj), Dk = Inf; else Dk = Dj + Aj; end if nargout > 1, P(i,jA(Dk < Di(jA))) = j; end Di(jA) = min(Di(jA),Dk); if isAcyclic == 1 % Increment node index for upper triangular A j = j + 1; elseif isAcyclic == 2 % Decrement node index for lower triangular A j = j - 1; end end D(i,:) = Di(t)'; end if nargout > 1 && length(s) == 1 && length(t) == 1 P = pred2path(P,s,t); end

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PetSurfer - MG coregister
by Marina Fernández 23 Jan '23

23 Jan '23

External Email - Use Caution Dear experts, I am trying to do PVC on FBB-PET images using the following commands: " mri_coreg --s s_001 --mov s_001_pet_fbb.nii.gz --reg s_001_pet_fbb.reg.lta mri_gtmpvc --i s_001_pet_fbb.nii.gz --reg s_001_pet_fbb.reg.lta --psf 6 --seg gtmseg.mgz --rescale 174 --default-seg-merge --auto-mask --mgx .1 --o s_001_pet_fbb " The problem is that when overlaying the mgx.ctxgm.nii.gz file with the T1.mgz of the corresponding subject, they don't match, since the resulting MG-image is in the space of the original PET (without PVC) instead of in the space of the freesurfer subject. How can I make the MG image be in the freesurfer's subject space? Where is the error? Thank you very much in advance. Best regards, Marina

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mri_segstats question: --avgwf for cross hemisphere ROI
by Bram Diamond 23 Jan '23

23 Jan '23

External Email - Use Caution Hello FreeSurfer Team, I've made a New Year's resolution to stop bothering Andrew Hoopes and instead send my questions to the FreeSurfer Mailing List. I would like to calculate a single average waveform for two surface labels on contralateral hemispheres. In essence, I would like to treat these contralateral labels as a single label. Is there a way to use freesurfer binaries (e.g., mri_segstats) with, lh.func.mgz, rh.fun.mgz, lh.ROI.label, and rh.ROI.label to write a text file with a single average waveform column? Thanks! I hope all is well in Boston! Cheers, Bram Bram R. Diamond, BSc Clinical Neuropsychology Doctoral Student Northwestern University Feinberg School of Medicine Mesulam Center for Cognitive Neurology & Alzheimer’s Disease 300 E. Superior Street | Tarry 8 | Chicago, IL 60611 http://secure-web.cisco.com/1rd9CGB1epEqWboZc37JDhl3-uOBS_KFp5wmeeP-n7zZWCM… <https://secure-web.cisco.com/1l1WxoIUCeqChdzdCLmFK4W0BM6NBQUq7Q-yena2Oie4hv…>

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Quantification of regional volume using external atlas
by Beatriz Cavendish 23 Jan '23

23 Jan '23

External Email - Use Caution Hi all, I would like to know how to quantify the regional volume using an external atlas. I already ran the recon all command and now I want to quantify the volume not with the default Freesurfer atlases, but a specific atlas that is in the MNI space. Should I transform the atlas to each subject's native space before quantifying? How should I do it? Then how do I quantify it and make sure it was done correctly? Could you provide me with command line suggestions? And if I wanted to work with everything on the MNI space, how would the code be like? Also, Best, -- Beatriz Araújo Cavendish, MSc PhD student | Psychologist University of São Paulo São Paulo/SP - Brazil

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freesufer
by David 23 Jan '23

23 Jan '23

External Email - Use Caution Hi Freesurfer experts, I'm very sorry to bother you, but I am very confused with the following questions: My experimental design includes two discrete factors: with three levels (d,m,h); gender (f, m), and two Nvariables So I can get 6 classes: df, dm,mf, mm,hf,hm. I want to perform the difference between any of the classes leves analysis with regressing out the effect of gender and two Nvariables, but I don't know the rules for setting the contrasts for the F-test. The contrast matrix I used is: 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 My orders are as follows： mris_preproc --fsgd glmteach3.fsgd --target fsaverage --hemi lh --meas thickness --out lh_teach3.mgh mris_preproc --fsgd glmteach3.fsgd --target fsaverage --hemi rh --meas thickness --out rh_teach3.mgh mri_glmfit --y lh_teach3.mgh --fsgd glmteach3.fsgd --C glmteach3.mtx --glmdir group3.testA1_10sm.lh --fwhm 10 --surface fsaverage lh --eres-save mri_glmfit --y rh_teach3.mgh --fsgd glmteach3.fsgd --C glmteach3.mtx --glmdir group3.testA1_10sm.rh --fwhm 10 --surface fsaverage rh --eres-save mri_glmfit-sim --glmdir group3.testA1_10sm.lh --cache 3 abs --cwp .05 --2spaces mri_glmfit-sim --glmdir group3.testA1_10sm.rh --cache 3 abs --cwp .05 --2spaces We obtained five differential brain regions and extracted their cortical thickness. And then put the extracted cortical thickness into SPSS for general linear model analysis, but two of the brain regions were not statistically significant. Why? Is the contrast matrix I used wrong? Or other errors? Any help will be very appreciated. Best wishes

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