Freesurfer

freesurfer@nmr.mgh.harvard.edu

30132 discussions

folding index to table
by Chris Hyatt 01 Mar '11

01 Mar '11

Hi all, I'm trying to extract the folding index for each subject/hemisphere/roi from ?h.aparc.stats into a single table with all subjects. It appears though that aparcstats2table will only extract area, volume, thickness, thicknessstd and meancurv, not folding index, even though these values are in the ?h.aparc.stats file. Is there a way of extracting folding index for each subject and importing into a file? Thanks, Chris

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Re: [Freesurfer] -normalization2 does not run mri_mask
by Y. Mohammed 01 Mar '11

01 Mar '11

Dear Freesurfer team, is mri_mask actually a part of normalization2 as stated here http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg02175.html? while trying to run freesurfer stepwise, the normalization2 step "recon-all -subjid subject -normalization2" is not executing "mri_mask" when it is called separately (while running "recon-all -subjid subject -all" executes indeed mri_mask). This is preventing "recon-all -subjid subject -finalsurfs" later from running successfully. Do you have any suggestion/idea/workaround how to solve/fix this? is there something like "recon-all -s subject -mri_mask" or shall I run mri_mask directly from the command line? Thanking you in advance for your reply Yassene

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laterality analysis
by Ritobrato Datta 01 Mar '11

01 Mar '11

Hello All, I am trying to do a laterality analysis for a cortical reorganization project in blind patients. Since each hemisphere has slightly different gyral and sulcal patterns, in theory, one hemisphere could be mirrored and compared; in the surface space this amounts to turning one of the spheres inside-out (so to speak). Are there are any extant tools available to do this for freesurfer ? I remember seeing something in the discussion boards in the past. Please let me know. Thank you very much Ri

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load individuel a2009s labels
by LAOUCHEDI MAKHLOUF 28 Feb '11

28 Feb '11

hi i am new to freesurfer, i want to load somme specific (individuel) labels on a brain.mgz thanks

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RFT_FDR tool for Random Field Theory-based multiple comparison correction
by jorge luis 28 Feb '11

28 Feb '11

I have updated the tool RFT_FDR in the NITRC software database (http://www.nitrc.org/projects/rft_fdr/).Remember that this tool allows you to perform Random Field Theory-based multiple comparison correction specific for freesurfer surface data. I have now considered the fact that SurfStat toolbox performs a one-sided test-based RFT correction for multiple comparisons. I have then modified the functions RFT, RFT_FDR_Opt, RFT_FDR and fdr_two_stage to made that fact explicit and to engage well with the Fresurfer visualization tools (tksurfer).

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NIFTI-2 public announcement
by Douglas N Greve 28 Feb '11

28 Feb '11

FYI _* _* _* _* _*A 64-bit update to the NIfTI format*_ *_ *_ *_ *_ The NIfTI committee are proposing the creation of a NIfTI-2 format that is a very simple extension of the current NIfTI-1 format, but updated to allow 64-bit storage and addressing for large images and matrices. _ _ It is intended that this format: - will enable the storage of large images and matrices, with all dimensions being coded by 64-bit integers rather than the current limitation of 16-bit signed integers (which currently gives a restrictive 32767 size limit in each dimension) - will be very simple to implement and update software (a couple of hours coding or less generally) - contains the same information as a NIfTI-1 file (no new fields and all current fields still retained) - will support the existing file formats and naming: a .nii single-file, a .hdr/.img file-pair and their gzipped versions - has a very simple test (see below) to determine if the file is NIfTI-1 or NIfTI-2 - does not replace NIfTI-1 in the short term but is supported alongside it *_Comments_* This announcement is intended for public comment. Please post any comments on this NIfTI-2 proposal to the NITRC discussion list (www.nitrc.org/forum/forum.php?forum_id=1941 <http://www.nitrc.org/forum/forum.php?forum_id=1941>) We ask that comments relating to larger-scale changes and requests for other types of format change be posted instead to a separate NITRC discussion list for more advanced neuroimaging formats (www.nitrc.org/forum/forum.php?forum_id=1942 <http://www.nitrc.org/forum/forum.php?forum_id=1942>) _* *_ _*Supporting software*_ - AFNI, BrainVoyager, Caret, Fiswidgets, FreeSurfer, FSL, ITK, LONI-DIRAC, MRIcron, NiBabel and SPM have all agreed to support the NIfTI-2 version in their upcoming releases, but that NIfTI-1 will remain a default output, or a configurable default, in the short-term - the sourceforge supporting libraries in niftilib will be updated so that they seemlessly support both NIfTI-1 and NIfTI-2 - conversion utilities to and from NIfTI-1 will be made available via sourceforge as well as in some of the software packages mentioned above _*Changes to the header *_The changes to the NIfTI header structure are the following: - short dim[8] becomes int64_t dim[8] - float intent_p1 becomes double intent_p1 - float intent_p2 becomes double intent_p2 - float intent_p3 becomes double intent_p3 - float pixdim[8] becomes double pixdim[8] - float vox_offset becomes int64_t vox_offset - float scl_slope becomes double scl_slope - float scl_inter becomes double scl_inter - float cal_max becomes double cal_max - float cal_min becomes double cal_min - float slice_duration becomes double slice_duration - float toffset becomes double toffset - float quatern_b becomes double quatern_b and similarly for quatern_c, quatern_d, qoffset_x, qoffset_y, qoffset_z - float srow_x[4] becomes double srow_x[4] and similarly for srow_y[4], srow_z[4] - char magic[4] becomes char magic[8] - char unused_str[12] is added after char magic[8] The order, size and type of all other fields remains unchanged. The sizeof_hdr must store 556 for a NIfTI-2 file instead of 348 for NIfTI-1. Extension information is still held in the first 4 bytes after this header (bytes 557-560) in the same way as in NIfTI-1. Note that the total block size of 560 (header + 4 bytes) retains the 16-byte alignment in NIfTI-1 (348+4=352), as needed for convenient memory-mapping. The changes of float to double are generally made to allow for more accurate mapping of intensities or indices when dealing with very large arrays, and unused_str is added to ensure the 16-byte alignment holds. _*Compatibility*_ This format is not, and cannot be, bit-wise compatible with the previous NIfTI-1 (or ANALYZE) formats and so will not work with existing NIfTI-1 software directly. In the short term this can be solved via conversion utilities. A NIfTI-2 image will not be recognised as a valid NIfTI-1 image by existing software and so no incorrect processing or analyses should occur. In the longer term most code should be very easily converted to work with both NIfTI-2 and NIfTI-1 by using the updated sourceforge libraries or making equivalent changes internally. The change in format is intentionally very minimal and should be very easy to code. *_Determining the NIfTI version_* The following pseudo-code shows how a file can be tested to see: (a) if it is a NIfTI image file, (b) what version of NIfTI it is, and (c) whether byte-swapping is required. read in the first 4 bytes from the file let d = the content of these bytes, formatted as a 32-bit int if (d==348) then it is a NIfTI-1 file, no byte-swapping required else if (swap_4bytes(d)==348) then it is a NIfTI-1 file, but with byte-swapping required else if (d==556) then it is a NIfTI-2 file, no byte-swapping required else if (swap_4bytes(d)==556) then it is a NIfTI-2 file, but with byte-swapping required else it is not a valid NIfTI file if it passed the above then read in the remaining 344 or 552 bytes of the header into the appropriate NIfTI-1 or NIfTI-2 struct double-check this is truly a valid NIfTI file by looking at dim[0] (should be between 0 and 7) and magic[] which should contain "ni1" or "n+1" followed by \0 for NIfTI-1, and "ni2" or "n+2" followed by \0 and 4 extra signature bytes for NIfTI-2 *_Magic Signature_* The magic string is expanded to 8 bytes with the first 4 bytes containing ones of the strings "ni2" or "n+2", terminated with \0. The next four bytes form a magic signature much the same as used by the PNG format (http://www.libpng.org/pub/png/pngintro.html) to detect for file transfer errors involving newline characters. The extra four bytes are the same as the last four in the PNG format - that is: |\r| |\n| |\032| |\n (||0D| |0A| |1A| |0A|) The magic string will have a different offset from the start of the file in NIfTI-1 and NIfTI-2 (344 and 536 bytes respectively). *_Timeline_* Barring any unknown unknowns or unforseeable unforseen problems, it is intended to begin rolling out this format in practice in March-April 2011. Example datasets will also be provided soon.

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Re: [Freesurfer] win xp shared drives
by Saad Ramadan 28 Feb '11

28 Feb '11

Hi, I have recently installed freesurfer 5.0.0 on top of a Xubuntu Linux distribution on an virtualBox/WIN XP computer. I can run freesurfer without a problem. My problem is with accessing Host drives from linux system. How am I going to get the image data to my linux virtual system if I cannot access host USB drives from my guest linux system? I looked on your archives and found nothing on "shared drives". Your help is appreciated. Thanks

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question about weighted regression analysis
by Katie Bettencourt 28 Feb '11

28 Feb '11

Still looking for an answer to this question: So in doing a more complicated version of the analysis with paradigm weighting, I had another experiment where I wanted to test out two different models, 1) that BOLD activity was related to my behavioral measure alone or 2) that BOLD activity was related to my behavioral activity plus a factor that represented the number of distractors present (which is constant across set size) (had a high and low distractor condition, so that this factor was effectively 0 for the low distractor condition and something like 1 for the high distractor condition). I modelled the second my simply adding the behavior measure and the distractor factor together (which means that in practicality, nothing changed for the low distractor conditions between model 1 and model 2, but that the weight was increased by a constant factor in the high distractor conditions between model 1 and model 2). When I ran this analysis, what I got (shown in the attached picture in a group average) was an increase in the amount of activity and area of activity for model 2 (targets & distractors) compared with model 1 (targets only). Am I right in interpreting this as model 2 being a better fit? Or is can these maps be compared to show areas that are a better fit for model 1 and other areas that are a better fit for model 2? I have ROI data on the unweighted analyses that goes along with the idea of model 2 being better, but I wanted to make sure I was intrepreting the activity in this weighted analysis correctly. Thanks, Katie On Tue, Feb 22, 2011 at 1:35 PM, Douglas N Greve <greve(a)nmr.mgh.harvard.edu>wrote: > Yes, your understanding is correct. People might choose Version 1 because > they strongly feel that it accurately represents the underlying mechanism. > It saves one DoF, but that's not going to change much. I think the problem > with Version 1 is that, for most designs, it forces you to extrapolate > outside of your data range. Few things are truly linear, but they are often > well modeled by straight lines over a limited range. For your data, you > might really expect the response to be 0 at x=0, but it become a very > non-linear curve in that region. > > doug > > Katie Bettencourt wrote: > >> Ok, so just so that I understand (I realize I'm being a bit dense, and I >> appreciate you walking me through this). If I am weighting my paradigm by >> my behavioral measure, then the activity I see with this weighted analysis, >> is areas where we are seeing a linear relationship between BOLD activity and >> my behavioral measure. In version 1:1vs0, this assumes that my linear fit >> passes through xy=0. However, in version 2:2vs0, we put an offset (or a >> sort of y intercept?) into the model so that the data doesn't have to pass >> through xy=0. And you are saying that the larger amount of activated area >> that I am getting in Version 1:1vs0, is because I'm seeing areas activated >> for the fact that there's an increase from baseline but not exactly the >> linear fit between BOLD and behavioral measures, but for Version 2:2vs0, I >> see only the areas that show this linear correlation? Does that sound about >> right? >> >> And if I am right, why would anyone do Verison1? Is it just because if >> your fit does pass through xy=0, you get more power this way compared with >> Version 2? >> >> Katie >> >> On Tue, Feb 22, 2011 at 1:00 PM, Douglas N Greve < >> greve(a)nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote: >> >> >> >> Katie Bettencourt wrote: >> >> >> You should also look at Version2:1v0. I bet a lot of the areas >> from Version1:1v0 will also show up. You can also create a >> Version3 in which you divide your presentations into a >> low-weight >> and a high-weight (but set the weight=1). Then create >> contrasts of >> low+high and high-low. The low+high should look like >> Version2:1v0 >> and the high-low should look like Version2:2v0. >> >> >> >> So, what would this say? That the extra activity I'm getting >> in Version 1 is just the slope/offset, and isn't actually load >> related data that I am trying to get at (ie. isn't activity >> that is increasing as the number of items the subjects is >> remembering increases, but is just baseline visual stimulation >> activity or something?) >> >> Yes. It's easier to explain if I can draw it out. But imagine an >> xy plot with your weight on the x axis and the fMRI response on >> the y axis. If there is an offset but no change in fMRI with >> weight, then the data points will be on a horizontal line. Now >> what happens if you try to fit that data with a line that is >> forced to pass through xy=0? You'll get some positive slope, but >> overall it won't fit very well. >> >> >> And What exactly to do you mean by divide my presentations >> into low and high weight? What exactly would this be >> comparing? Sorry if I'm being dense. >> >> I mean create a new paradigm file with two non-null conditions. >> Condition 1 would be all presentations with weight < 0.5 (low >> weight); Condition 2 would be all those with weight>0.5. You >> should pick your own weight threshold of course. >> >> doug >> >> >> Katie >> >> >> doug >> >> >> >> >> Katie Bettencourt wrote: >> >> Yes, those are the maps I"ve been comparing. I've been >> comparing it to BV sort of, but that analysis is not >> surface >> based and I"m not used to it, so I can't quite tell >> which is >> more accurate, though Version 2 gives a much smaller >> area of >> activity, which fits with the description of what I've been >> given about what to expect in BV. Attached is two >> pictures of >> the difference I get for Version 1:1v0 (labeled with >> "single" >> in the image name) and Version 2:2v0 (labeled with >> "double" in >> the name). As you can see, Version1 activates a much >> larger >> area than Version 2. >> >> I guess part of my problem is that I'm having trouble >> understanding exactly what these two versions are >> telling me >> about the data and what the differences is. Can you try to >> give me a sort of layman's explanation? >> >> Katie >> >> >> On Tue, Feb 22, 2011 at 11:45 AM, Douglas N Greve >> <greve(a)nmr.mgh.harvard.edu >> <mailto:greve@nmr.mgh.harvard.edu> >> <mailto:greve@nmr.mgh.harvard.edu >> <mailto:greve@nmr.mgh.harvard.edu>> >> <mailto:greve@nmr.mgh.harvard.edu >> <mailto:greve@nmr.mgh.harvard.edu> >> <mailto:greve@nmr.mgh.harvard.edu >> <mailto:greve@nmr.mgh.harvard.edu>>>> wrote: >> >> I assume that you are comparing maps of Version1:1v0 and >> Version2:2v0 ? I could imagine it going either way. >> If the true >> slope is 0 but the offset is non-0, then Version1 >> will give >> you an >> artificially high slope (and Verion2 will give you >> the correct >> slope at 0, and so no activation). Are you comparing >> this >> to a BV >> analysis? >> >> doug >> >> >> Katie Bettencourt wrote: >> >> So I created a weighted regression analysis to >> look at the >> effect of memory load in a particular brain region. >> Basically, >> I weighted the paradigms by a behavioral measure >> that >> reflected the number of items actually >> remembered (as >> set size >> was increased). As far as Doug told me there are >> basically 2 >> ways to weight your paradigm files. >> >> Version 1: >> Have 2 conditions, baseline (condition 0) and >> all the set >> sizes (condition 1). Condition 1 would then be >> weighted by >> the behavioral measure. >> >> Version 2: >> Have 3 conditions, baseline (condition 0), and >> then I >> represented each presentation as two different >> conditions, one >> with a weight that is always 1 (condition 1), >> the other >> weighted according to the behavioral measure >> (condition 2). >> >> >> The difference, as far as I understand it, in >> version >> 1, it is >> assumed that the response amplitude is ) when the >> weight is 0 >> (ie. that when you are attending to 0 items, brain >> activity = >> 0). Whereas, version 2, tests the slope of the HRF >> amplitude >> vs weight without the assumption above. >> >> However, I'm a bit confused as to the results I got. >> When I >> looked at the data from both versions, version 1 >> provided a >> much higher amount of activation and more areas >> activated than >> version 2. However, I believe version 2 better fits >> with the >> multiple regression analysis that is done in >> Brain Voyager. >> Can anyone give me a better explanation of what the >> difference >> between these analysis models is? >> >> Katie >> >> >> >> >> -- Douglas N. Greve, Ph.D. >> MGH-NMR Center >> greve(a)nmr.mgh.harvard.edu >> <mailto:greve@nmr.mgh.harvard.edu> >> <mailto:greve@nmr.mgh.harvard.edu >> <mailto:greve@nmr.mgh.harvard.edu>> >> <mailto:greve@nmr.mgh.harvard.edu >> <mailto:greve@nmr.mgh.harvard.edu> >> <mailto:greve@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 >> <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> >> <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> >> <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> >> >> FileDrop: >> www.nmr.mgh.harvard.edu/facility/filedrop/index.html >> <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> >> < >> http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> >> < >> http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> >> >> >> >> >> 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 >> <mailto:greve@nmr.mgh.harvard.edu> >> <mailto:greve@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 >> <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> >> <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> >> FileDrop: >> www.nmr.mgh.harvard.edu/facility/filedrop/index.html >> <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> >> <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> >> >> >> >> -- 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 >> <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> >> FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html >> <http://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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thickness analyse
by 汪贵宏 28 Feb '11

28 Feb '11

Dear all, I try to analysis the thickness difference between the patient vs. control for several days, but I fail to explain the results.Although I had read the wiki on the website,it not works for me. Here,I list the procedures which I took for my study,I really hope somebody can help me. My research is to analysis the thickness difference between the control vs.patient which are addicted on the internet. Firstly,as the papers says,FREESURFER divided eachcortexhemisphere into 33 areas,but why did there has only one thickness value per area?there is the thickness information for all of controls and patients in the first file which I add in theappendix. Secondly,why did the thicknesses are not in the same value for the same area between the qdec.table.dat (in the first appendix)and which in the first picture in the appendix below? Thirdly,the detail steps I took in the qdec are also list in the appendix pictures,is it right? Thanks a lot. Sincerely, wang

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Baseline Offset in Stable 5 funcroi
by Adam Nitenson 28 Feb '11

28 Feb '11

Hi Freesurfers, When conducting ROI analyses in Stable 5, is there a way to generate a mean functional baseline offset value within the ROI which can be used to help calculate percent signal change? This would correspond to the value from row 4 in the output file generated by roisummary-sess in Stable 4. Thanks, Adam PS: Here are examples of the commands I've used in Stable 5 to generate ROI Data: funcroi-config -analysis SIRP_Stable5 -label LH_16MTH_7v1_DLPFC -roi MTH_7vFix_DLPFC.roicfg -contrast Cond7vFix -sign abs -thresh 1.3 funcroi-sess -roi MTH_7vFix_DLPFC.roicfg -sf /cluster/roffman/users/Stable5_PerRun/Subject_Files/16_PreScan_Genotyped_MTH funcroi-table-sess -roi MTH_7vFix_DLPFC.roicfg -sf /cluster/roffman/users/Stable5_PerRun/Subject_Files/16_PreScan_Genotyped_MTH -c Cond7vFix -o /cluster/roffman/users/Stable5_PerRun/DLPFC_ROI_7vFix_MTH Adam Nitenson, B.S. Brain Genomics Lab Massachusetts General Hospital nitenson(a)nmr.mgh.harvard.edu Phone: 617-643-3215

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