Freesurfer February 2010

freesurfer@nmr.mgh.harvard.edu

96 participants
153 discussions

inconsistencies in surface segmentation and aseg.mgz
by Joonkoo Park 27 Feb '10

27 Feb '10

Dear surfers, I was visually inspecting the results of the auto-recon process using tkmedit (e.g. tkmedit subject brainmask.mgz lh.white -aux T1.mgz -aux-surface rh.white -segmentation aseg.mgz /usr/local/freesurfer/FreeSurferColorLUT.txt) I noticed that often times the segmentation results from the surface files (pial, main and original surface represented by red, yellow, and green, respectively) are not consistent with the results from the aseg.mgz files. For instance, a piece of gray matter in the anterior temporal pole is colored pink and indicates Left-Cerebral-Cortex as the label, but this area is marked to be outside the red line (pial surface). Likewise, yellow line often cuts through the area indicated as white matter by aseg.mgz. >From a previous email thread, I noted that Bruce mentioned that "We usually trust the surfaces more than the aseg for cortical morphometry." Does this mean that aseg.mgz is not used in subsequent processing stream? What shall I do if I (after visually inspecting this) want to correct the surfaces more similar to the results given be aseg.mgz? Thanks for your help in advance. Joon -- Joonkoo Park Ph.D. Candidate, Cognition & Cognitive Neuroscience Department of Psychology, University of Michigan

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Surface very inaccurate after reprocessing for control points
by Laluz, Victor 26 Feb '10

26 Feb '10

Hello, Throughout most of Freesurfer's version history, I have noticed this problem pop up every 50 or so cases I do: I will have a pretty well-processed surface but with some inaccuracies in the WM surface, I will put control points down to correct it, and reprocess with autorecon2-cp as usual. The surface comes back with the areas I put CPs for accurate, but the rest of the cortex in a localized area will have a massive amount of the surface missing. An example is attached as a .png image. Now, if I go back and put down control points throughout the part of the surface that is missing after the first reprocessing and repeat autorecon2-cp, the end result at that point is usually a perfectly accurate surface. However, I was wondering if the massive loss in surface after the first autorecon2-cp is attributable to some kind of bug that I might be able to avoid. Any thoughts would be great, thanks! Victor Victor Laluz Imaging Coordinator UCSF Memory and Aging Center 350 Parnassus Avenue, Suite 905 Box 1207 San Francisco, CA 94143-1207 Phone: (415) 476.1680 Fax: (415) 476.1816 Email: vlaluz(a)memory.ucsf.edu<mailto:vlaluz@memory.ucsf.edu> memory.ucsf.edu<http://www.memory.ucsf.edu/> www.youtube.com/ucsfmemoryandaging<http://www.youtube.com/ucsfmemoryandaging>

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mri_glmfit reference
by Georg Homola 26 Feb '10

26 Feb '10

Hi, following these refs I've found on the list and the mri_glmfit help, I assume the cluster-wise probability of the permutation simulation is based on cluster mass inference, is that right? Thanks, Georg Statistical Science 2004, Vol. 19, No. 4, 676-685 Institute of Mathematical Statistics, 2004 Permutation Methods: A Basis for Exact Inference Michael D. Ernst Human Brain Mapping 15:1-25(2001) Nonparametric Permutation Tests For Functional Neuroimaging: A Primer with Examples Thomas E. Nichols and Andrew P. Holmes Validating cluster size inference: random field and permutation methods Satoru Hayasaka and Thomas E. Nichols, NI, 20 (2003) 2343-2356. Hagler and Sereno, NI, 2006, vol 33 1093-1103. Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data

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Optseq2 - Incorporate sequential order of trials as a factor
by Gaber, Tilman 26 Feb '10

26 Feb '10

Dear mailinglist recipients, I am currently planning an optimized experiment using optseq2 and a 2x2 factors behavioral response task (Simon-task). The task consists of a pseudo-randomized series of two kinds of trials (congruent and incongruent). In addition there is a sequential factor, i.e. it is of interest whether a trial follows a trial of the same or the opposite kind. In other words there are (2x2) four different conditions where trials relate to precedent trials (AA,AB,BB,BA). Would it be possible to incorporate this sequential factor into the optseq2? I am aware that null events will fall between trials and thus interrupt trial sequences. Trials following null events would therefore be treated separately (i.e. for data analysis). In order to obtain an equal number of trials per condition, this would require increasing the number of trials depending on the number and order of null events. Currently I am able to produce a randomized order of equally balanced trials regarding trial type and sequential order (AA,AB,BB,BA). Any thoughts or suggestions are more than welcome! Best, Tilman

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Gaussian Curvature Calculation
by Lisa Ronan 26 Feb '10

26 Feb '10

Hi All I wonder could you tell me how Gaussian curvature values are computed at a vertex, i.e. Gauss_Bonnet scheme? Is there any way to vary the neighborhood over which the vertex curvature values are computed? Thanks for your help, Lisa Ronan - - - - - - - - - - Research Associate Brain Mapping Unit Sir William Hardy Building Department of Psychiatry University of Cambridge

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how to use time points
by Guang Zeng 26 Feb '10

26 Feb '10

Hi, there, I have scans from two time points, and they have been cross-sectionally processed. But both of they missed some white matter in some slices, so I manually add control points to them, and re-run it. Both of them look fine now. Then, I send them to longitudinal stream. After the -base step is finished. I load the output in the based folder, those white matter are misclassified at the same place again. Is a method which can use the control points I added to the two time point when I called recon-all -base to build the base template. Or I need add control points to the built base subject again? Thanks! Guang _________________________________________________________________ Hotmail: Powerful Free email with security by Microsoft. http://clk.atdmt.com/GBL/go/201469230/direct/01/

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can't change common-space subject in qdec
by Danielian, Laura (NIH/NINDS) [E] 25 Feb '10

25 Feb '10

Hi, I've created an average brain and would like to use that as the "common-space subject" in my qdec analysis. However, the program does not seem to allow editing of that box - I can't seem to delete or type over the default fsaverage. Is there a trick to changing this information or another way to load it at the command line? Thanks in advance for your help, Laura

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LGN label or ROI....
by Ritobrato Datta 25 Feb '10

25 Feb '10

Hi All, Is there a method for obtaining an ROI for the lateral geniculate nucleus in freesurfer ? Thanks, Ri

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correction of pial surface...
by Gonzalo Rojas 24 Feb '10

24 Feb '10

Hi: How can I correct the pial surface in the image that I am sending attached ?... Sincerely, -- Gonzalo Rojas Costa Advanced Medical Image Processing Laboratory Department of Radiology Las Condes Clinic Lo Fontecilla 441, Las Condes, Santiago, Chile. Tel: 56-2-2105170 Cel: 56-9-97771785 www.clc.cl

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QDEC covariate question
by lordowen 24 Feb '10

24 Feb '10

Dear freesurfer experts: We are using freesurfer to preform a cortical thickness analysis between patients and controls. We plan to use the mean_thickness and subject age as covariates. It's fine to analysis as group x age or group x mean_thickness, respectively. But when we set design as group x age x mean_thickness, an error report appeared in the terminal: -------- Matrix condition is 11355.6 ERROR: matrix is ill-conditioned or bad scaled, condno = 11355.6 Possible problem with experimental design: Check for duplicate entries and /or lack of range of continuous variables within a class. (continuous with values in Xg.dat) ------ Does the problem course by the different "range" from age value (between 18-28) and mean_thickness (between 2-4) with in the same subject? if so, how can we solve it? Does proportional scaling on age or mean_thickness help? Any comments are welcome and very appreciate. -- Best regards -- 杜政昊 Cheng-Hao Tu, PhD Student Laboratory of Integrated Brain Research Department of Medical Research and Education Taipei Veterans General Hospital No.201, Sect.2, Shih-Pai Rd. Taipei Taiwan Email: lordowen(a)ms10.hinet.net or lordowentu(a)gmail.com Tel: +886-2-28712121 ext 3474 Fax: +886-2-28745182

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Freesurfer February 2010