Freesurfer

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30097 discussions

CORTICAL Thicknesses
by amirhossein manzouri 23 Sep '13

23 Sep '13

Hi, In the attached Slice image of a processed brain, there is a yellow line which defines the WM and red line for the cortex but in segmentation some WM have been segmented as cortex and some part of cortex have not been segmented ! Would you please let me know how to handle the situation while I am reporting cortical thicknesses of my data? -- Best regards, Amirhossein Manzouri

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Re: [Freesurfer] qdec analysis and covariates
by Anita van Loenhoud 23 Sep '13

23 Sep '13

Oh, I meant to reply to an older post, but that didn't work apparently. Below the original post. This person does a group analysis, with gender and age as covariates.You adviced to first do a DODS and look for a age-by-group interaction. If there's no interaction, he/she could continue with DOSS. My questions is (since I'm doing a similar analysis) whether it's also necesary to check for a age-by-gender interaction? Or is this not important since gender is a covariate instead of an independent variable? Thanks! Anita Douglas N Greve Mon, 29 Nov 2010 07:27:30 -0800 Yes, that looks fine. The only other thing to decide is whether to use DODS (different offset different slope) or DOSS (different offset same slope). The default is DODS, but if you don't think that there is an age-by-group interaction, then you can get more power using DOSS. If you use DODS, then you should probably de-mean the ages (ie, subtract the grand mean age over all subjects from the age of each individual). doug Roser Sala wrote: Hi, We are doing a group analysis using qdec with two groups, and we would like to include gender and age as covariates. Which is the best option in order to perform a simple t-test (group1>group2 and group2>group1) and including the two covariates? (we would like them to have 'zero' weighting in the contrast matrix) We realized that if we include 'age' as a continous factor in the dialog, qdec is performing rather an interaction analysis than a covariate. So, would it be ok to include group and gender as fixed factors and age as nuisance, and then select the output as 'Does the average thickness accounting for gender differ between group1 and group2' (age as nuisance variable)? By checking all the possibilities this seemed the best option for us, but we would like to get a confirmation that we are doing it right. Many thanks Roser

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Re: [Freesurfer] qdec analysis and covariates
by Anita van Loenhoud 23 Sep '13

23 Sep '13

Hi, I have a question related to this post. Besides an age-group interaction, wouldn't it also be neccesary to check for an age-gender interaction?

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dilate a label?
by Yang, Daniel 22 Sep '13

22 Sep '13

Hi FreeSurfer Experts, Is it possible to dilate a label using command line? Thanks! Daniel -- Yung-Jui "Daniel" Yang, PhD Postdoctoral Researcher Yale Child Study Center New Haven, CT (203) 737-5454

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break down a label?
by Yang, Daniel 22 Sep '13

22 Sep '13

Dear FreeSurfer Experts, If I have a label that spans across multiple anatomical regions, is it possible to automatically break it down according to aparc.annot? Thanks! Daniel -- Yung-Jui "Daniel" Yang, PhD Postdoctoral Researcher Yale Child Study Center New Haven, CT (203) 737-5454

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Sulcal depth variations
by Damien MARIE 21 Sep '13

21 Sep '13

Hello everyone, I'm working on a group analysis of cortical thickness, surface area, curvature and sulcal depth with FreeSurfer 5.3. However I'm in trouble concerning the interpretation or the meaning of my results, especially concerning curvature and sulcal depth. I understood that curvature can be positive when it concerns sulcus or positive in case of gyrus. According to my result it would be almost the same for sulcal depth. The value of sulcal depth is positive on a sulcus while it is negative on a gyrus. Am I correct? All the best, Damien Marie

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Qdec analysis with one group and two covariates (1 dichotomic, 1 continuous)
by E. Scariati 21 Sep '13

21 Sep '13

Dear Freesurfer experts, I would like to study the relationship between cortical thickness and one clinical variable with qdec, but correcting for age and gender. Given that I have only one group and 2 covariates (one continuous, one dichotomic) I don't know how I should set the design of my analysis in qdec, especially for the gender variable. I have tried two different ways (both DOSS design): 1) selecting Discrete = gender; Continuous = clinical measure; Nuisance factor = age and looking at the contrast called : "Does the correlation between thickness and clinical measure accounting for gender differ from 0? nuisance factor : age" 2) selecting : continuous = clinical measure; Nuisance Factor = age, gender (coded as 1 and 2) and looking at the contrast called : "Does the correlation between thickness and clinical measure differ from 0, nuisance factor : age, gender" But the two contrasts give very different results, which I find very surprising. I exported cortical thickness at the peak significance of the clusters and tried to run a GLM myself in SPSS and it seems that coding gender as a continuous variable with two values (1 and 2) provides the most realistic results. However, I saw many times on the mailing list that you recommend to use gender as a discrete variable, so I am very confused. Could you explain me the difference between these contrasts and help me to identify which one will accurately identify the correlation between cortical thickness and my clinical variable correcting for the effect of age and gender. Thank you in advance for your answer, Best regards Elisa

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postdoc opening
by Thomas Yeo 20 Sep '13

20 Sep '13

Hi, I am looking to hire talented postdocs to develop novel image analysis and machine learning algorithms for the Human Connectome Project data. This is my research webpage: https://sites.google.com/site/yeoyeo02/. See more information below. Regards, Thomas Requirements: Ph.D. in computer science, electrical engineering, statistics or related fields. Candidates should have previously published research in image processing or statistical analysis, preferably in biomedical applications. Compensation: Competitive and commensurate with experience Institutes: Perform ground-breaking research at the National University of Singapore (NUS), while enjoying the beautiful sceneries and cultures of South-East Asia. NUS is a research-intensive university consistently ranked among the top 30 universities in the world (http://en.wikipedia.org/wiki/National_University_of_Singapore#University_ra…) Successful candidates may be required to travel between Singapore and the U.S. for certain projects. Contact: Interested candidates should email Thomas (ythomas(a)csail.mit.edu) with CV and/or questions. To apply, please send cover letter, CV and names/contact information of 3 people who can provide letters of reference.

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Ph.D. student openings
by Thomas Yeo 20 Sep '13

20 Sep '13

Hi, I am looking to recruit talented students to develop novel image analysis and machine learning algorithms for the Human Connectome Project data. This is my research webpage: https://sites.google.com/site/yeoyeo02/. See more information below. Regards, Thomas Application Deadline: Nov 1st, 2013 in order to start in Fall 2014 Requirements: Bachelor's or Master's degree in computer science, electrical engineering, statistics or related fields. Ideal candidates should be highly motivated, and have research experience and/or excellent grades. Compensation: Graduate Student Fellowship Institutes: Perform ground-breaking research at the National University of Singapore (NUS), while enjoying the beautiful sceneries and cultures of South-East Asia. NUS is a research-intensive university consistently ranked among the top 30 universities in the world (http://en.wikipedia.org/wiki/National_University_of_Singapore#University_ra…) Successful candidates may be required to travel between Singapore and the U.S. for certain projects. Contact: Interested candidates should email Thomas (ythomas(a)csail.mit.edu) with CV and/or questions.

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ACFFWHM for surface-based analyses in FSFAST?
by Caspar M. Schwiedrzik 20 Sep '13

20 Sep '13

Hi Freesurfer Experts, mkanalysis-sess seems to default to a FWHM of 20 for the smooting of the ACF (in version 5.1). I was wondering whether it makes sense to use the same FWHM for volume and surface based analyses of functional data in FSFAST? I seem to remember that the autocorrelations differ between, e.g., grey and white matter, which might be a reason to use a different FWHM on the surface? Thank you very much, Caspar

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