Freesurfer June 2012

freesurfer@nmr.mgh.harvard.edu

124 participants
195 discussions

(no subject)
by mdkruepke＠uwalumni.com 13 Jun '12

13 Jun '12

Freesurfers A real real general question here: if i am running a glm_fit for cortical thickness with a fsgd with 2 groups (G1, G2) and 3 continues variables and have a matrix of 1 -1 0 0 0, red/yellow areas mean that G1 is thicker in this area than G2, correct? Best- Michael -- Michael D. Kruepke PhD - University of Illinois at Urbana-Champaign BA - Psych - University of Wisconsin-Madison mdkruepke(a)gmail.com (262)-483-7449

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aseg inaccuracy in cortex
by Nicole Senecal 13 Jun '12

13 Jun '12

Hi all, I'm noticing that when pulling up a brainmask volume with surfs and aseg on, the pial and white surfaces are (thankfully) very often correct, but the aseg in cortex is a bit off - often including parts of the skull/dura as gray matter - even though the pial surface does follow this boundary correctly. As long as the surfaces are correct, and my primary interest will be cortical thickness, do I need to worry about these inaccuracies in the aseg? Is checking the aseg primarily done for ensuring accuracy in subcortical structures rather than in cortex? thanks, Nicole -- Nicole Senecal Neuroscience Graduate Group Kable Lab 3720 Walnut St., Room C37 Philadelphia, PA 19104 Lab phone: 215-746-4371

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Correction for Multiple Comparisons
by mdkruepke＠uwalumni.com 13 Jun '12

13 Jun '12

Freesurfers- When correcting for multiple comparisons using: mri_glmfit-sim \ --glmdir lh.gender_age.glmdir \ --sim mc-z 5 4 mc-z.negative \ --sim-sign neg --cwpvalthresh 0.4\ --overwrite What does the sign mean (ie - the neg, pos, abs). Also for the mc-z simulation type do we no longer need to include the smoothness of our data (FWMH)? Michael D. Kruepke PhD - University of Illinois at Urbana-Champaign BA - Psych - University of Wisconsin-Madison mdkruepke(a)gmail.com (262)-483-7449

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cortical thickness with a continuous variable
by mdkruepke＠uwalumni.com 13 Jun '12

13 Jun '12

Freesurfers- I am looking to investigate the whether cortical thickness varies in regards to a continues variable, while controlling for other continues variables. I am having a little trouble wrapping my head around this as i am unsure how to compare thickness in regards to a continues variable, how the contrast would look, ect. Looking at this example FSGD ( http://surfer.nmr.mgh.harvard.edu/fswiki/Fsgdf2G1V) GroupDescriptorFile 1 Title OSGM Class Group1 Class Group2 Variables Age Input subject1 Group1 30 Input subject2 Group2 40 I am thinking i may need to randomly define two groups, and then use a contrast similar to 0 0 0.5 0.5 (contrast 4 on the same page). Which asks: Null Hypothesis: does mean of group age slope differ from 0? Is there an average affect of age regressing out the effect of group? Am i correct in thinking that if i use this contrast i would be able to determine whether there is a difference in cortical thickness based on any continuous variable (like age, IQ)? Michael -- Michael D. Kruepke PhD - University of Illinois at Urbana-Champaign BA - Psych - University of Wisconsin-Madison mdkruepke(a)gmail.com (262)-483-7449

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Re: [Freesurfer] specifying multiple contrasts
by Douglas N Greve 12 Jun '12

12 Jun '12

The FSGD file is incorrect. It has multiple subjects listed, and the string after the subject name is not the name of a class (Tract1_FA is not the same as Tract1). I would suggest working through the example on the wiki tutorial and/or looking at the slides on group analysis. doug On 06/12/2012 06:05 PM, Shantanu Ghosh wrote: > Hi Doug > > I set up my .fsgd file as follows (4 tracts of interest, 59 subjects > belonging to 2 different groups, CON and PAT): > > GroupDescriptorFile 1 > Title tract_fa > MeasurementName thickness > Class Tract1 > Class Tract2 > Class Tract3 > Class Tract4 > Input Subject1 Tract1_FA > Input Subject1 Tract2_FA > Input Subject1 Tract3_FA > Input Subject1 Tract4_FA > Input Subject2 Tract1_FA > Input Subject2 Tract2_FA > Input Subject3 Tract3_FA > Input Subject3 Tract4_FA > . > . > Input Subject59 Tract4_FA > > and set up the .mtx file for mri_glmfit as: > > C = [zeros(3) eye(4)] > > Is that correct? How do I define the contrast variables = -1 and 0 for the > test? > > I am a little confused. > > Thanks and regards, > shantanu > > On Tue, June 12, 2012 4:57 pm, Douglas N Greve wrote: >> Did you look at the FSGD examples on our wiki? Do a search for FSGD >> doug >> >> On 06/12/2012 04:46 PM, Shantanu Ghosh wrote: >>> Hello Freesurfer experts, >>> >>> How can I specify multiple contrasts for my thickness study with two >>> groups AA and BB, having different number of subjects in each group? My >>> variables are tract-wise FA values, age and IQ. >>> >>> Thanks in advance, >>> Shantanu >>> >>> >>> >> -- >> Douglas N. Greve, Ph.D. >> MGH-NMR Center >> greve(a)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 >> >> >> > -- Douglas N. Greve, Ph.D. MGH-NMR Center greve(a)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

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matrix error
by mdkruepke＠uwalumni.com 12 Jun '12

12 Jun '12

Hello- I am trying to analyze the cortical thickness between two groups of subjects Cl1 and CL2. When i run the GLM i receive the error: matrix is ill-conditioned or badly scaled, condno = 1e+08 I am under the impression the error could be due to the non-uniformity in the range/scale of the regressors. here is my information: contrast is 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1) mri_glmfit --y lh.PvNPeverything.10.mgh --fsgd PvNPeverything.fsgd dods --C PvNP_everything.mtx --surf UNM_ALLGOOD lh --cortex --glmdir lh.PvNPeverything.glmdir 2) (sample of my fsgd) - there are no columns with all 0's in them GroupDescriptorFile 1 Title Methedone Comparison Class Cl1 Class Cl2 Variables WAISIQ trait_anxiety alcohol_year heroin_year cocaine_year cannabis_year meth_year amphetamines_year meth_amphet_year hallucinogens_year inhalants_year methodne_year opiates_year pills_year opitates_pills_year other_year total_years Input M87160505 Cl1 86 33 10 3 9 11 0 1 1 1 8 0 0 6 6 0 49 Input M87161888 Cl1 109 59 0 0 7 22 0 0 0 0 0 0 0 0 0 0 32 Input M87107477 Cl1 89 34 12 0 9 13 0 9 9 6 10 0 1 9 10 0 57 Input M87199897 Cl1 117 44 0 23 0 10 0 0 0 0 0 9 15 0 15 3 60 Input M87146570 Cl1 94 42 26 0 3 8 0 0 0 0 0 0 0 0 0 6 37 Input M87189755 Cl1 111 59 11 0.5 2 15 0 3 3 1.5 0 0 0 0 0 0 36 Input M87169696 Cl1 86 22 2 0 11 14 0 0 0 0 0 0 0 0 0 0 25 Input M87187366 Cl1 106 51 28 0 27 0 0 20 20 0 0 0 0 0 0 0 75 Input M87178857 Cl2 117 48 0 4 4 8 0 5 5 7 0 4 0 0.08 0.08 0 42.08 Input M87165923 Cl2 103 40 5 2 0 15 0 0 0 0 0 0 0 1 1 0 23 Input M87110556 Cl2 134 60 4 0 1 15 0 0 0 0 0 0 0 0 0 0 20 Input M87183811 Cl2 97 43 15 0 8 3 0 0 0 0 0 0 0 0 0 0 26 3) design matrix 1 0 86 0 33 0 10 0 3 0 9 0 11 0 0 0 1 0 1 0 1 0 8 0 0 0 0 0 6 0 6 0 0 0 49 0 1 0 109 0 59 0 0 0 0 0 7 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 1 0 89 0 34 0 12 0 0 0 9 0 13 0 0 0 9 0 9 0 6 0 10 0 0 0 1 0 9 0 10 0 0 0 57 0 1 0 89 0 40 0 15 0 5 0 2 0 30 0 10 0 0 0 10 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 59 0 1 0 77 0 44 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 91 0 22 0 6 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 1 0 103 0 29 0 20 0 3 0 11 0 27 0 0 0 11 0 11 0 5 0 0 0 0 0 0 0 1 0 1 0 0 0 78 0 1 0 117 0 44 0 0 0 23 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 9 0 15 0 0 0 15 0 3 0 60 0 1 0 94 0 42 0 26 0 0 0 3 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 37 0 1 0 91 0 38 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 1 0 86 0 45 0 3 0 1 0 2 0 7 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 0 14 0 1 0 114 0 50 0 5 0 1 0 3 0 10 0 0 0 0.08 0 0.08 0 0 0 0 0 0.33 0 1 0 0 0 1 0 0 0 20.42 0 1 0 109 0 27 0 5 0 5 0 4 0 14 0 0 0 0 0 0 0 5 0 0 0 0 0 1 0 4 0 5 0 0 0 38 0 1 0 97 0 29 0 23 0 1 0 22 0 24 0 0 0 15 0 15 0 12 0 0 0 0 0 14 0 0 0 14 0 0 0 111 0 1 0 106 0 23 0 7 0 0 0 4 0 6 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 1 0 131 0 25 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 74 0 54 0 12 0 0 0 0 0 16 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 0 6 0 0 0 32 0 1 0 123 0 41 0 0 0 0.17 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5.17 0 1 0 100 0 27 0 4 0 0 0 2 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0 86 0 37 0 7 0 3 0 1 0 7 0 0 0 5 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 1 0 91 0 40 0 12 0 0 0 0 0 12 0 8 0 0 0 8 0 0 0 0 0 0 0 0.5 0 0 0 0.5 0 0 0 32.5 0 1 0 97 0 42 0 1.5 0 0 0 2 0 6 0 4 0 0 0 4 0 0.5 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 1 0 91 0 37 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 0 91 0 48 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0.25 0 0 0 0 0 0 0 0 0 0 0 0 0 4.25 0 1 0 94 0 58 0 1 0 0 0 0.67 0 4 0 5 0 0 0 5 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 13.67 0 1 0 114 0 48 0 17 0 0 0 6 0 17 0 0 0 7 0 7 0 5 0 0 0 0 0 0 0 2 0 2 0 0 0 50 0 1 0 106 0 54 0 15 0 0 0 7 0 15 0 0 0 15 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 44 0 1 0 74 0 46 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 91 0 43 0 0 0 0 0 0 0 0 0 0 0 0.33 0 0.33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.33 0 1 0 80 0 27 0 3 0 30 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 60 0 1 0 97 0 33 0 0.5 0 0 0 0.25 0 2 0 2 0 0 0 2 0 0 0 0.17 0 0 0 0 0 0 0 0 0 0 0 4.92 0 1 0 100 0 31 0 6 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 1 0 109 0 29 0 0 0 0 0 0 0 13 0 0 0 10 0 10 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0 1 0 80 0 37 0 0 0 0 0 8 0 8 0 0.5 0 0 0 0.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16.5 0 1 0 72 0 55 0 10 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 1 0 103 0 40 0 0 0 0.5 0 1 0 8 0 0.67 0 0 0 0.67 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10.17 0 1 0 77 0 32 0 0 0 0.5 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12.5 0 1 0 120 0 28 0 0 0 0 0 4 0 12 0 0 0 7 0 7 0 4 0 0 0 0 0 0 0 0 0 0 0 7 0 34 0 1 0 86 0 32 0 11 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 1 0 91 0 44 0 2 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 1 0 94 0 50 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 100 0 29 0 5 0 0 0 0 0 16 0 17 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 38 0 1 0 94 0 25 0 4 0 0 0 0.5 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12.5 0 1 0 74 0 51 0 10 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 0 1 0 97 0 36 0 30 0 0 0 20 0 33 0 5 0 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0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 1 0 77 0 49 0 0 0 0 0 10 0 12 0 0 0 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 42 0 1 0 89 0 42 0 0 0 0 0 4 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 1 0 117 0 34 0 25 0 0 0 2 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52 0 1 0 83 0 56 0 12 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 1 0 91 0 33 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 106 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 120 0 50 0 1 0 0 0 0 0 2 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 -- Michael D. Kruepke PhD - University of Illinois at Urbana-Champaign BA - Psych - University of Wisconsin-Madison mdkruepke(a)gmail.com (262)-483-7449

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specifying multiple contrasts
by Shantanu Ghosh 12 Jun '12

12 Jun '12

Hello Freesurfer experts, How can I specify multiple contrasts for my thickness study with two groups AA and BB, having different number of subjects in each group? My variables are tract-wise FA values, age and IQ. Thanks in advance, Shantanu -- Shantanu Ghosh, Ph.D. Martinos Center for Biomedical Imaging Harvard-MIT Program in Health Sciences & Technology

1 0

(no subject)
by Shantanu Ghosh 12 Jun '12

12 Jun '12

1 0

Correction for Multiple Comparisons
by mdkruepke＠uwalumni.com 12 Jun '12

12 Jun '12

Hey all- This may be a simple question to answer, but in an analysis looking at say cortical thickness between Group 1 and Group 2 with say 3 continues variables (age, anxiety, IQ) there would be a contrast matrix of 1 -1 0 0 0 . How does free surfer correctly remove the effects of the continues variables? -- Michael D. Kruepke PhD - University of Illinois at Urbana-Champaign BA - Psych - University of Wisconsin-Madison mdkruepke(a)gmail.com (262)-483-7449

2 1

urgent help with cortical areas
by Rashmi Singh 12 Jun '12

12 Jun '12

Hello experts, I have the aparcstat files for corticla thickness. I would want to know is there any information on how may I group these regions more broadly ex frontal , temporal lobe areas. Thanks Rashmi. ________________________________ This document may contain information covered under the Privacy Act, 5 USC 552(a), and/or the Health Insurance Portability and Accountability Act (PL 104-191) and its various implementing regulations and must be protected in accordance with those provisions. Healthcare information is personal and sensitive and must be treated accordingly. If this correspondence contains healthcare information it is being provided to you after appropriate authorization from the patient or under circumstances that don't require patient authorization. You, the recipient, are obligated to maintain it in a safe, secure and confidential manner. Redisclosure without additional patient consent or as permitted by law is prohibited. Unauthorized redisclosure or failure to maintain confidentiality subjects you to application of appropriate sanction. If you have received this correspondence in error, please notify the sender at once and destroy any copies you have made.

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Freesurfer June 2012