[Freesurfer] Measuring the cortical thickness

-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html ------------------------------ Message: 2 Date: Wed, 03 Nov 2010 19:05:03 -0400 From: Douglas N Greve greve@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] Questions about event related processing and selxavg-sess and selxavg3-sess To: Katie Bettencourt kcrum@bu.edu Cc: freesurfer maillist freesurfer@nmr.mgh.harvard.edu Message-ID: 4CD1EA9F.2060403@nmr.mgh.harvard.edu Content-Type: text/plain; charset=ISO-8859-1; format=flowed The FIR does not assume a shape to the HRF but fits each point within the given time window. You might not be seeing activation for several reasons. FIRs are much less efficient than gamma functions. Also, by default, the FIR analysis gives you a sig map at each time point in the FIR, so you might be looking at the activation 1.5 sec *before* stimulus onset (so it would be a good thing not to see any activation!). Try advancing the time point from the overlay config window. You can see the map from the gamma and the timecourse from the FIR with something like tksurfer-sess -analysis fir-analysis -map-analysis gamma-analysis ... I'm not sure about the diffs with version 3. Why are you using such an old version? doug Katie Bettencourt wrote: > Hi all, > > I've been trying to analyses both an event related and block design > experiments and have noticed a couple things that are confusing me and > I would appreciate any help anyone could give me. > > 1. In trying do the event-related analysis, I'm am a bit confused by > the FIR vs Gamma analysis and the use of the time window and tprestim > in the FIR analysis. I have an experiment with 6 set size conditions > and 1 fixation condition. each trial is 6s long with a TR of 1.5 > > I have run both of these commands: > > mkanalysis-sess.new -analysis supIPS_loc -TR 1.5 -paradigm supIPS.dat > -designtype event-related -funcstem fmc -motioncor -runlistfile > supIPSruns.txt -inorm -nskip 2 -nconditions 6 -gammafit 2.25 1.25 > > mkanalysis-sess.new -analysis supIPS_loc -TR 1.5 -paradigm supIPS.dat > -designtype event-related -funcstem fmc -motioncor -runlistfile > supIPSruns.txt -inorm -nskip 2 -nconditions 6 -tprestim 2 -timewindow 20 > > > The FIR gives me a time course window, which makes me think that > perhaps that is the one I want to use, but it shows very little > activation. This data has been previously analyzed in Brain Voyager, > so I know it's not a case of the conditions not actually causing > activation, but for some reason, the FIR analysis doesn't show any. > I'm not sure if this is due to a bad time window/tprestim settings, or > something else. However the gamma fit analysis shows a bunch of > activity where I expect to see it, but no time course window. > (attached are pngs of the differences for the act_vs_fixation > comparison). > > > 2. In addition, in both the event related (gamma) and a normal block > design (different experiment) I get very different results (at least > for certain comparisons) depending on whether I use selxavg-sess (with > stxgrinder-sess for each contrast) or selxavg3-sess. The differences > are shown in the attached pngs (act_vs_fix-gamma.png (which is the > selxavg-sess and stxgrinder-sess analysis and > act_vs_fix-gamma-selxavg3). In the block design, both selxavg3 and > selxavg (+stxgrinder) give me very similar activation when comparing > two non-null conditions (ie. shape_vs_noise) but very different (and > similar to the differences in the attached pictures) activations when > comparing against the null (ie shape_vs_fix or noise_vs_fix). What am > I doing wrong here? > > Thanks for your help! > > Katie > > ------------------------------------------------------------------------ > > > ------------------------------------------------------------------------ > > > ------------------------------------------------------------------------ > > ------------------------------------------------------------------------ > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html ------------------------------ Message: 3 Date: Wed, 03 Nov 2010 19:28:11 -0400 From: Douglas N Greve greve@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] read data mri_vol2surf To: "Oya, Hiroyuki (UI Health Care)" oyah@healthcare.uiowa.edu Cc: freesurfer@nmr.mgh.harvard.edu Message-ID: 4CD1F00B.9060505@nmr.mgh.harvard.edu Content-Type: text/plain; charset=ISO-8859-1; format=flowed yes, use the FreeSurfer MRIread matlab command Oya, Hiroyuki (UI Health Care) wrote: > > Hello > > > > Is it possible to load the outputs of mri_vol2surf with matlab? > > > > Thank you. > > > > Hiroyuki > > ------------------------------------------------------------------------ > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html ------------------------------ Message: 4 Date: Wed, 03 Nov 2010 19:59:52 -0400 From: Douglas N Greve greve@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] Binary masks and mri_vol2vol To: Andrew Ward award@nmr.mgh.harvard.edu Cc: freesurfer@nmr.mgh.harvard.edu Message-ID: 4CD1F778.60606@nmr.mgh.harvard.edu Content-Type: text/plain; charset=ISO-8859-1; format=flowed It is better to use mri_label2vol using the registration matrix for the functional. You can set the "fill threshold" to control the percent of a segmentation that must be present in a voxel to declare that voxel to be in that segment. I would not set this to 1 (ie, 100%) as this can lead to some artifacts since it just counts the number of anat voxels that land in the functional voxel. Set it to something like .85 or .9. doug Andrew Ward wrote: > Hi Freesurfers, > > I have created a binary mask of the ventricles using mri_binarize > using data from aparc+aseg.mgz. I want to resample this mask into > native functional space, but I want to include only functional voxels > that are 100% covered by by the structural mask. Because the > anatomical mask is written with voxels that are 1x1x1 and our > functional data is re-sliced at 3x3x3, there are functional voxels > that are more than 50% covered by the anatomical mask that I want to > exclude. I used the command: > > mri_vol2vol --mov brainmask.mgz --targ ventmask.nii --ing --reg > register.dat --interp nearest --o func.ventmask.nii > > This properly resampled the mask into functional space, and maintained > its binary character, but it looks to be a bit too permissive -- > although I could just be seeing things. > > Any ideas? > > Thanks for your help, > > Andrew Ward > Brigham and Women's Hospital (BBNG) > Massachusetts General Hospital (GRU) > Athinoula A. Martinos Center for Biomedical Imaging > 149 13th St., Rm 2689C > Charlestown, MA 02129 > Phone: 617-726-6211 > Fax: 617-726-5760 > > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html ------------------------------ Message: 5 Date: Thu, 4 Nov 2010 04:55:56 +0100 From: "Hasson, Uri" uri.hasson@unitn.it Subject: [Freesurfer] Post-doctoral and data analyst positions (fMRI, MEG) To: "freesurfer@nmr.mgh.harvard.edu" freesurfer@nmr.mgh.harvard.edu Message-ID: C8F77CDC.2B72%uri.hasson@unitn.it Content-Type: text/plain; charset="utf-8" Applications are invited for two postdoctoral positions and one data analyst position funded by an ERC (European Research Council) Starting Grant. The research program examines the cognitive mechanisms and neural systems by which the human brain codes the recent past and predicts the immediate future. It uses neuroimaging, behavioral studies, and eye tracking methods. The ideal candidates for all positions are highlymotivated and creative individuals, capable of working independently and ingroups, who will thrive in a dynamic startup-like work environment. Prior experience with computational modeling of complex systems would be helpful. The research takes place at the Center for Mind/Brain Sciences at the University of Trento, Italy. Salaries are comparable to those offered by research institutions in the US and Europe, include benefits and health insurance, and are commensurate with training and experience. Expected starting date for all positions is Feb 1st, 2011. Interested candidates should Email a CV and a description of research interests to: Dr. Uri Hasson uri.hasson@unitn.itmailto:uri.hasson@unitn.it Center for Mind/Brain Sciences via delle Regole, 101 I-38060 Mattarello (TN) Italy Positions offered: a. Post-doctoral position (2-4 years) for fMRI research. The person will beresponsible for the design of several fMRI studies, conducting data analysis and leading the write-up of scientific work. The person will have access to the center?s onsite 4T fMRI scanner. REQUIREMENTS: expertise with fMRI design and analysis methods and a solid background in cognitive neuroscience. HELPFUL:knowledge of functional connectivity methods including those applicable to resting state data, analysis of perfusion (ASL) data, R/Matlab programming,good understanding of UNIX. Interest in MEG methods. b. Post-doctoral position (2-4 years) for Magnetoencephalography (MEG) research. The person will be responsible for the design of several MEG studies, conducting data analysis and leading the write-up of scientific work. The person will have access to the center?s onsite MEG apparatus and 4T fMRI scanner. REQUIREMENTS: expertise with MEG techniques and a solid background in cognitive neuroscience. HELPFUL: Knowledge of coherence analysis and pattern classifier methods; knowledge of fMRI analysis techniques and the integration of fMRI and MEG data. c. Data Analyst (2 years): The data analyst will be responsible for analysis of fMRI datasets, algorithm development, programming and conducting fMRI studies, and monitoring computer hardware. This position is ideal for college graduates who are technically inclined and are considering future graduate studies in cognitive neuroscience. REQUIREMENTS: Prior experience with fMRI analysis. HELPFUL: a bachelor's degree in psychology, computer science, math, cognitive science, neuroscience, or computer science, knowledge of Italian. Experience with diverse computing environments (Linux/OSX/Windows), programming (python/perl/shell scripting, or R) and relational databases.