Freesurfer December 2013

freesurfer@nmr.mgh.harvard.edu

107 participants
197 discussions

Re: [Freesurfer] Fixed-Effects Analysis carried out by mri_glmfit
by Douglas N Greve 02 Dec '13

02 Dec '13

Hi Clark, I think Approach A should work ok. As you imply, there could be different scalings, so take that into account somehow. A slightly modified approach would be do define a different set of conditions for each subject in the paradigm file. They create a contrast with mkcontrast-sess that averages over subjects while testing the contrast you are interested in. Does that make sense? doug On 12/02/2013 12:27 PM, Clark Fisher wrote: > Hi Doug (and other Freesurfers), > > Hope you had a pleasant Thanksgiving. My thread last left off before > everyone left for the holidays. I just wanted to re-raise this > question, as it's still a pressing one for me. > > Thanks, > Clark > > > On Nov 27, 2013, at 11:06 AM, Clark Fisher <cfisher(a)rockefeller.edu > <mailto:cfisher@rockefeller.edu>> wrote: > >> Hmm, it looks like my formatting didn't survive the internet (at >> least in my e-mail program). . I'm going to try it one more time (I'm >> going to include the complete original message). >> >> Hi Doug, >> >> I sidestepped the registration issue because I am performing the >> analysis on 5 ROIs per subject (5x1x1 volumes), which are aligned by >> design. I'm doing this using the lab's semi-manual NHP processing >> stream, so usual assumptions you have about which FS-fast steps have >> been performed may not hold. >> >> Just to clarify things, I'll try to outline where I stand more >> completely. >> >> I have a block design study with 3 subjects, and ~30 runs per >> subject. Each run contains every condition occurs twice in each run. >> These runs have been collected over 2-3 days for each subject. Within >> each subject, I aligned all of the different sessions and combined >> them into a single metasession. Within these 3 metasessions, I >> defined ROIs, and created new ROI volumes by averaging the time >> courses within each ROI. From here I have taken 2 approaches. >> >> Approach A: Combine all of the ROI volumes (~30 runs X 3 subjects), >> which are pre-aligned with each other, into a single bold folder. >> Run selxavg3-sess on this data using my contrasts of interest. >> >> Approach B: Keep the ROI volumes from each subject in their own bold >> folder, and run selxavg3-sess 3 times (once for each subject). Then I >> used mri_glmfit to attempt fixed effects meta-analysis. Here there's >> another split. >> Approach B.1: I ran the contrasts for each individual subject, then >> used mri_glmfit --osgm on the ces and cesvar volumes of each contrast >> to test for significance of the contrast over the group. This does >> not work for F-tests. >> Approach B.2: I ran an omnibus contrast on each subject separately, >> and use the ces and cesvar for each condition in each subject. I >> assembled this for input to mri_glmfit. The fsgd file looks roughly >> like: >> >> GroupDescriptorFile 1 >> Class Subj1 >> Class Subj2 >> Class Subj3 >> Variables Condition1 Condition2 Condition3Condition4 >> Input Subj1-Cond1 Subj1 1 0 0 0 >> Input Subj1-Cond2 Subj1 0 1 0 0 >> Input Subj1-Cond3 Subj1 0 0 1 0 >> Input Subj1-Cond4 Subj1 0 0 0 1 >> Input Subj1-Cond00 Subj1 0 0 0 0 >> Input Subj2-Cond1 Subj2 1 0 0 0 >> Input Subj2-Cond2 Subj2 0 1 0 0 >> Input Subj2-Cond3 Subj2 0 0 1 0 >> Input Subj2-Cond4 Subj2 0 0 0 1 >> Input Subj2-Cond00 Subj2 0 0 0 0 >> Input Subj3-Cond1 Subj3 1 0 0 0 >> Input Subj3-Cond2 Subj3 0 1 0 0 >> Input Subj3-Cond3 Subj3 0 0 1 0 >> Input Subj3-Cond4 Subj3 0 0 0 1 >> Input Subj3-Cond00 Subj3 0 0 0 0 >> >> Approach B.2 (continued): I then define contrasts comparing >> conditions (Condition1 vs Condition2, etc.) and run these contrasts >> using mri_glmfit --C. With this method, I have no problem defining F >> contrasts (what they are actually testing is another question). >> >> My actual experiment is a 6 condition, 2x3 factorial design. The 2 >> contrasts of interest that I need an F test for are one of the main >> effects (these contrasts are shown without the 3 leading columns of >> zeros for the different subjects): >> 1 1 -1 -1 0 0 >> 1 1 0 0 -1 -1 >> >> and the interaction effect: >> 1 -1 -1 1 0 0 >> 1 -1 0 0 -1 1 >> >> I switched to Approach B because I want to scale the condition betas >> per-subject before running the analysis across all subjects (this is >> to correct for potentially different levels of a contrast agent). I >> was worried that if I scaled the raw time courses that are the input >> to Approach A, that the normalization step built into selxavg3-sess >> would interact with my manual normalization in ways that would be >> difficult to figure out. With approach B, I can directly scale the >> contrast ces and cesvars (B.1) or betas (B.2) for each subject. >> >> >> OK, given all of that background information, what is the best way to >> approach this? Should I: >> a) Try to scale the time courses that go into Approach A >> b) Work with Approach B.1, and live without knowing the significance >> of my main/interaction effects (not a nice thought) >> c) Work with Approach B.2 >> d) Take some other tack >> >> If I take Approach B.2, would any violation within-subject >> independence decrease my power, or artificially inflate my >> significance? Some loss of power could be acceptable. >> >> Thanks for reading all of the way through this (twice now), >> Clark >> >> >> >> On Nov 26, 2013, at 11:13 PM, Douglas Greve >> <greve(a)nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote: >> >>> >>> Clark, it sounds like what you did (ie, combine different subjects >>> into one folder) would be tricky to analyze correctly because FSFAST >>> will try to register them to the same subject. I could think of a >>> way to do it, but it would be complicated. What is the test that you >>> want to do? An F test is usually something like a logical "or" >>> between two conditions. The RM ANOVA won't do this, but a simple >>> ANOVA would. The problem is that the DOF would be off because it >>> would assume that each data point came from a different subject, and >>> it would not take into account the covariance in the measurements >>> from a single subject. Another approach would be to do separate >>> tests for each condition at the group level, then do a type of >>> conjunction analysis to implement the OR. Let me know if you want to >>> pursue that approach. >>> >>> doug >>> >>> >>> >>> On 11/26/13 4:02 PM, Clark Fisher wrote: >>>> Thanks again, >>>> >>>> I have 3 subjects, and want to tests for effects using data >>>> collected across all 3 subjects. The multiple sessions for each >>>> subject have already been concatenated into a single BOLD folder (3 >>>> folders total: 1 for each subject). I have actually already >>>> performed the fixed effects analysis by concatenating all 3 >>>> subjects into a single bold folder and re-running the first level >>>> analysis. While that works, I now want to try to normalize the >>>> data for each subject to minimize the variability introduced by the >>>> contrast agent we use, and that would be easier to do by >>>> normalizing the outputs of the first level analysis. If I wanted to >>>> normalize per-subject and then combine them into a first level >>>> analysis, what would be the best way to do this? >>>> >>>> My naive assumption would have been that using glmfit for this >>>> should be very similar to the repeated measures ANOVA example that >>>> is on the wiki >>>> (http://ftp.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova) >>>> Rather than time points for each subject, I will have the beta from >>>> each condition for each subject. In both cases (multiple time >>>> points from a single subject and multiple conditions from a single >>>> subject/set of runs), the within-subject measurements are not >>>> independent. How is my situation different? >>>> >>>> Cheers, >>>> Clark >>>> >>>> >>>> On Nov 26, 2013, at 1:41 PM, Douglas N Greve >>>> <greve(a)nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote: >>>> >>>>> Are the different input to glmfit different runs within a session >>>>> or across sessions? Either way, for within subject analysis, can >>>>> you put all of the runs into a single "bold" folder? Then it >>>>> automatically does the FFX analysis across runs, which can include >>>>> an F-test. The problem is that glmfit expects all the inputs to be >>>>> independent, which conditions within a run will not be. >>>>> doug >>>>> >>>>> >>>>> On 11/25/2013 01:35 PM, Clark Fisher wrote: >>>>>> Thanks Doug, >>>>>> >>>>>> I had forgotten that my roadblock was actually in isxconcat_sess, >>>>>> not mri_glmfit. This worked out great. >>>>>> >>>>>> Following this up, how would you recommend calculating the >>>>>> fixed-effects significance of a complex (within subject) contrast >>>>>> with mri_glmfit? For simple contrasts, I have been calculating >>>>>> the contrast at the single subject level, then performing an osgm >>>>>> fixed-effects analysis on the output ces and cesvar volumes for >>>>>> each subject. However, I have some 2D F-contrasts that don't >>>>>> output ces volumes (naturally). >>>>>> >>>>>> One possibility would be to concatenate the ces and cesvar from >>>>>> the omnibus contrasts of each subject, set up an appropriate fsgd >>>>>> (as in >>>>>> http://ftp.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova) and >>>>>> then define the contrasts at the level of mri_glmfit with .mtx >>>>>> files. Would that be the way to go? >>>>>> >>>>>> Thanks, >>>>>> Clark >>>>> -- >>>>> Douglas N. Greve, Ph.D. >>>>> MGH-NMR Center >>>>> greve(a)nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu> >>>>> Phone Number: 617-724-2358 >>>>> Fax: 617-726-7422 >>>>> >>>>> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting >>>>> FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 >>>>> www.nmr.mgh.harvard.edu/facility/filedrop/index.html >>>>> <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> >>>>> Outgoing: >>>>> ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ >>>>> >>>>> >>>>> >>>>> The information in this e-mail is intended only for the person to >>>>> whom it is >>>>> addressed. If you believe this e-mail was sent to you in error and >>>>> the e-mail >>>>> contains patient information, please contact the Partners >>>>> Compliance HelpLine at >>>>> http://www.partners.org/complianceline . If the e-mail was sent to >>>>> you in error >>>>> but does not contain patient information, please contact the >>>>> sender and properly >>>>> dispose of the e-mail. >>>>> >>>> >>>> >>> >> > -- 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: https://gate.nmr.mgh.harvard.edu/filedrop2 www.nmr.mgh.harvard.edu/facility/filedrop/index.html Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/

1 0

Re: [Freesurfer] glmfit error on v5.1
by Gabriel Gonzalez Escamilla 02 Dec '13

02 Dec '13

2 1

nuisance factors in QDEC
by Yolanda Vives 02 Dec '13

02 Dec '13

Dear FreeSurfer experts, I am performing a DODS analysis with QDEC to compare cortical thickness of patients and controls and I have some questions regarding the nuisance factors age and global cortical thickness. 1.- Should I demean both variables or only the age? 2.- Which of the following options do you think that would be better? - To include the global mean thickness of the left hemisphere for the QDEC analysis of the left hemisphere and the right global mean thickness for the QDEC analysis of the right hemisphere. - To include mean cortical thickness calculated like that: bh.thickness = (lh.thickness*lh.surfarea + rh.thickness*rh.surfarea) / (lh.surfarea + rh.surfarea) If you think that this is the best option, which surfarea should I use? Would it be correct to use the WhiteSurfArea? Thank you for your help, Yolanda

1 0

glmfit error on v5.1
by Gabriel Gonzalez Escamilla 02 Dec '13

02 Dec '13

1 0

Fwd: Minimum Dti directions and odf
by Salil Soman 02 Dec '13

02 Dec '13

Hi, I hope all is well. Was wondering if any of had heard of an explicit minimum number of DTI directions necessary for using odf / hardi modeling ? I have run a couple of data sets of 30 directions (+ 5 b0) through TRACULA, and have run this same data through diffusion toolkit using the hardi / odf model, with reasonable looking results. I was wondering if there was any specific reason why using these models with 30 directions would be considered in appropriate? Thanks! Sal

2 1

Re: [Freesurfer] Cortical thickness/surface area in volume-defined ROIs
by Anita van Loenhoud 02 Dec '13

02 Dec '13

Hi Bruce, Thank you for your response. Now at least I know what went wrong; I'll try your solution. Thanks! Anita

1 0

Volume differences after corrections
by Garikoitz Lerma-Usabiaga 01 Dec '13

01 Dec '13

Hi list, I obtained cortical thickness and volumetric results before and after correcting them for defects. I just did some wm edits and mostly controls points in the top of the head (some subjects had less signal so I put control points in order to allow for a good surface reconstructions). When comparing the values: EXPECTED - Same volume values for subcortical structures, i.e.: same thalamic volume before and after - Different CT values in the edited areas and only for the edited subjects, i.e.: lh_paracentral_thickness - Different volumetric values only for the edited subjects in, for example: lhCortexVol, CortexVol, CorticalWhiteMatterVol NOT EXPECTED - Same values for EstimatedTotalIntraCranialVol. I was controlling thalamic values with the eTIV, (using Raz 2005's formula)*, but before and after correcting almost half of the subjects, obviously, I obtain the same results. - Should I use a different value other than the eTIV? - Is normal that the eTIV doesn't change but the rest of the values are changing? The brain is definitely different after the control points, it grows a little bit upwards. any information on this will be appreciated! thanks, Gari PS: * Volume (adj) = Vol(rawi)-b*(ICV(i)-mean ICV), where b is the slope of regression of an ROI volume on ICV

2 1

Jump to page:

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Freesurfer December 2013