Freesurfer October 2017

freesurfer@nmr.mgh.harvard.edu

119 participants
179 discussions

Problem with mris_anatomical_stats on .label which is threshold under negative value on FS-FAST, using tksurfer
by stdp82＠virgilio.it 06 Oct '17

06 Oct '17

Hi list, aftermri_label2label --srcsubject Subj01 --srclabel ROI.label --trgsubject Subj01 --trglabel Subj01/label/ROI.label --hemi lh --regmethod surfaceandmris_anatomical_stats -l Subj01/label/ROI.label -b Subj01 I have run mris_anatomical_stats -l Subj01/ROI_neg.label -b Subj01 lh the following error has been produced: Subj01/mri/wm.mgz...reading input surface Subj01/surf/lh.white...Using TH3 vertex volume calcTotal face volume 211969Total vertex volume 209028 (mask=0)reading input pial surface Subj01/surf/lh.pial...reading input white surface Subj01/surf/lh.white...No such file or directorymris_anatomical_stats: could not open label file Subj01/label/ROI_neg.labelNo such file or directorySubj01: could not read label file Subj01/label/ROI_neg.label This error did not occur for another label (Red_positive.label) which is threshold over positive value. Please take in account that the Blue_negative.label is obtain from FS-FAST map using tksurfer.Blue_negative.label expresses the difference for FC of group B < FC of group A.Conversely, Red_positive cluster shows difference for FC of group A > FC of group BPlease also note that clusters were thresholded before to save the .label with tksurfer +at 1.3 for defining Red_positive.label and at for defining - 1.3. I do not know if this step could induce an error in label properties. Thanks Stefano

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TRACULA qc: forceps minor and major
by Linnea Marie Dramdal Borg 06 Oct '17

06 Oct '17

Hi, We have run into some issues with our forceps major and forceps minor tractographies. I have attached examples: In "fminor_bro_139.png", there is a "bridge" in forceps minor in the space between the hemispheres. We've also come across other cases of bridging in forceps minor, with somewhat unusual voxel intensity distribution, such as in "fminor_onestripe_otherwOK.png" and" fminor_litenbro_OKornot_210.png". Also, "fmajor_132_toolateral.png", fmajor brances out in the left hemisphere (right in the picture). All of these cases seem pretty bad to us. Do you agree? In contrast, "fminor_allslicesOKbutone_158.png" looks fine, but there is one slice where it branches out to some extent. Are we correct in assuming this won't affect the results too much, or is there something we can/should do about this? Thank you, Linnea Marie

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Postdoc and PhD student positions, TU Dresden, Germany
by Katharina von Kriegstein 06 Oct '17

06 Oct '17

We are seeking a postdoc and two PhD students to work in the Neural Mechanisms of Human Communication Research Group led by Katharina von Kriegstein at the TU Dresden, Germany. Postdoc Position The main research goal of the position is to investigate behavioural and neuroscience principles of perceptual learning and their translation to evidence-based teaching and training programmes. For more information on the position and application instructions see: http://tinyurl.com/y9396qdd PhD positions The main research goal of the two positions is to investigate behavioural and neuroscience principles of voice and face perception (identity and speech) in neurotypical populations as well as in populations with developmental person recognition deficits (i.e. phonagnosia and prosopagnosia). For more information on the position and application instructions see: http://tinyurl.com/ybvodeqo The Human Communication Research Group is currently based at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig (MPI-CBS; www.cbs.mpg.de/independent-research-groups/human-communication) and will be newly established at the TU Dresden. The TU Dresden offers an excellent, interdisciplinary scientific environment. Research will be carried out at the Department of Psychology of the TU Dresden, which houses a Neuroimaging Centre (http://www.nic-tud.de) The centre is equipped with a research-only 3-Tesla MRI machine, MRI-compatible eye tracking, EEG systems, and a neurostimulation unit including neuronavigaton, TMS and tDCS devices. All experimental facilities are supported by experienced physics and IT staff. For analyses with high computational demands, there is access to the TU Dresden high-performance computing clusters. There are also strong existing collaborations with the MPI-CBS in Leipzig involving 7 Tesla-MRI, Connectome scanner, and MEG data acquisitions. --- Prof. Dr. Katharina von Kriegstein Max Planck Institute for Human Cognitive and Brain Sciences Stephanstr. 1A, 04103 Leipzig, Germany Technische Universität Dresden Bamberger Str. 7, 01187 Dresden, Germany Phone +49 (0) 341-9940-2476 http://www.cbs.mpg.de/independent-research-groups/human-communication https://twitter.com/kvonkriegstein

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Volume Version of ?h.sphere.reg and method to read it
by Daniel van de Velden 06 Oct '17

06 Oct '17

Dear Freesurfer Team, I am using your reconstruction pipeline for my study. Since I need to morph all my subjects to an average subject (using mne-python for this) for upcoming a Volume Source Analysis I deeply looked into the whole source-code of both software packages. Narowing down the problem, I think I will need a volume version of the ?h-sphere.reg files, which are created during the whole reconstruction process. Mne-python reads the subject specific 'sphere_tris' from this file. I can use the talairach.m3z, which is a nonlinear atlas warp. Or I can run CVS, which extends the surface warp into the volume. But how is it possible to read the warp map I got, e.g. CVS-based warp map, and use its information ? Yours sincerely, Daniel van de Velden .

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LGI error
by Nillo, Ryan Michael R 05 Oct '17

05 Oct '17

Hello FS users, I am using FreeSurfer version 5.3 to calculate local verification index and processing stopped at make_roi_paths. Here, I was given the error below. I searched in the archives and found a solution to the problem was to edit a few lines on SearchProjectionOnPial.m. The new script is included below the error. Any advice on how to fix this would be greatly appreciated. Make_roi_paths error ================= make_roi_paths('lh.pial','lh.pial-outer-smoothed',25,100,'/data/sugrue2/NF1_qdec/P0007/surf/tmp-mris_compute_lgi-lh.pial','/tmp/mrp_20907_.m'); exit ================= < M A T L A B (R) > Copyright 1984-2015 The MathWorks, Inc. R2015b (8.6.0.267246) 64-bit (glnxa64) August 20, 2015 For online documentation, see http://www.mathworks.com/support For product information, visit www.mathworks.com<http://www.mathworks.com>. modified_matlab = /working/sdl_analysis/software/freesufer_5.3_matlab Academic License >> loading datas ... FREESURFER_READ_SURF [v 1.2 ] ...reading surface file: lh.pial ...reading triangle file ...adding 1 to face indices for matlab compatibility. ...done ( 0.07 sec) FREESURFER_READ_SURF [v 1.2 ] ...reading surface file: lh.pial-outer-smoothed ...reading triangle file ...adding 1 to face indices for matlab compatibility. ...done ( 0.02 sec) preparing outer mesh structure ... face 5000 / 132292 face 10000 / 132292 face 15000 / 132292 face 20000 / 132292 face 25000 / 132292 face 30000 / 132292 face 35000 / 132292 face 40000 / 132292 face 45000 / 132292 face 50000 / 132292 face 55000 / 132292 face 60000 / 132292 face 65000 / 132292 face 70000 / 132292 face 75000 / 132292 face 80000 / 132292 face 85000 / 132292 face 90000 / 132292 face 95000 / 132292 face 100000 / 132292 face 105000 / 132292 face 110000 / 132292 face 115000 / 132292 face 120000 / 132292 face 125000 / 132292 face 130000 / 132292 mesh_outer = vertices: [66148x3 double] faces: [132292x3 double] facesOfVertex: [66148x1 struct] preparing pial mesh structure ... ...searching for mesh edges...done (140.10 sec). ... creating path file for vertex 1 / 66148 area file for outer ROIs saved at 1 In an assignment A(:) = B, the number of elements in A and B must be the same. Error in dsearchn (line 79) [d(i),t(i)] = min(sum((x-yi).^2,2)); Error in mesh_vertex_nearest (line 29) nearestIndex = dsearchn(vertices,points); Error in reorganize_verticeslist (line 28) [nextindex,nextvalue]=mesh_vertex_nearest(mesh_total.vertices(remaininglist,:),mesh_total.vertices(verticeslist(start_vertex),:)); Error in make_roi_paths (line 93) reorglist = reorganize_verticeslist (mesh_total, A, mesh_outer, perim, verticeslist, step); SearchProjectionOnPial.m Script function [verticeslist]=SearchProjectionOnPial(mesh_total,mesh_outer,perim, step) % step is typically set between 5 and 10. Default is 7, increasing it will % limit redundancies in the resulting path file. verticeslist=[]; si=max(size(perim)); for t=1:step:si [nearestIndexMT,nearestValuesMT]=mesh_vertex_nearest(mesh_total.vertices,mesh_outer.vertices(perim(t),:)); verticeslist= [verticeslist nearestIndexMT]; end verticeslist=unique(verticeslist); Sincerely, Ryan Nillo UCSF Center for Radiology and Biomedical Imaging Staff Research Associate

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mri_aparc2aseg creates black file
by Sara Nolin 05 Oct '17

05 Oct '17

Freesurfer people, *I have a label file that I want to make into a volume file only in the white matter to use in diffusion tractography.* *I was told to use mri_aparc2aseg to put the labels onto the WM surface and make them into a volume. I made the label files into annotation files using the following commands:* mris_label2annot --ctab clut.2lhV1.ctab --s 100206 --h lh --l /data/user/snolin/subjects_reconall/100206/label/2_LH_V1.label --a 2V1 mris_label2annot --ctab clut.2rhV1.ctab --s 100206 --h rh --l /data/user/snolin/subjects_reconall/100206/label/2_RH_V1.label --a 2V1 *These ran with no errors and made annotation files. Then I ran mri_aparc2aseg using the following command:* mri_aparc2aseg --s 100206 --annot 2V1 --new-ribbon *This is my log file:* SUBJECTS_DIR /data/user/snolin/subjects_reconall subject 100206 outvol /data/user/snolin/subjects_reconall/100206/mri/2V1+aseg.mgz useribbon 0 baseoffset 0 RipUnknown 0 Reading lh white surface /data/user/snolin/subjects_reconall/100206/surf/lh.white Reading lh pial surface /data/user/snolin/subjects_reconall/100206/surf/lh.pial Loading lh annotations from /data/user/snolin/subjects_reconall/100206/label/lh.2V1.annot reading colortable from annotation file... colortable with 2 entries read (originally clut.2lhV1.ctab) Reading rh white surface /data/user/snolin/subjects_reconall/100206/surf/rh.white Reading rh pial surface /data/user/snolin/subjects_reconall/100206/surf/rh.pial Loading rh annotations from /data/user/snolin/subjects_reconall/100206/label/rh.2V1.annot reading colortable from annotation file... colortable with 2 entries read (originally clut.2rhV1.ctab) Have color table for lh white annotation Have color table for rh white annotation Loading ribbon segmentation from /data/user/snolin/subjects_reconall/100206/mri/ribbon.mgz Building hash of lh white Building hash of lh pial Building hash of rh white Building hash of rh pial Loading aseg from /data/user/snolin/subjects_reconall/100206/mri/aseg.mgz ASeg Vox2RAS: ----------- -1.00000 0.00000 0.00000 128.00000; 0.00000 0.00000 1.00000 -128.00000; 0.00000 -1.00000 0.00000 128.00000; 0.00000 0.00000 0.00000 1.00000; ------------------------- Labeling Slice 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 nctx = 1764 Used brute-force search on 0 voxels Writing output aseg to /data/user/snolin/subjects_reconall/100206/mri/2V1+aseg.mgz *It creates the 2V1+aseg.mgz file and I tried opening it in freeview with the color lookup table that I used when I made it into an annotation file and there is nothing there. The file is 401KB, but its all black. * *Clicking around it comes up 41, 0, or 2000, but I can’t visually see anything. What have I done wrong here?* *As I mentioned before, I just want to use these label file for diffusion tractography, so if I am heading down the wrong path, I would appreciate advice.* Freesurfer version: freesurfer-Linux-centos6_x86_64-stable-pub-v6.0.0-2beb96c Platform: linux based cluster Thank you! Sara Sims

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Extracting values via mri_segstats from middle of the cortex
by Yash Patel 05 Oct '17

05 Oct '17

Hi, I have a MT and T1W volume (processed through recon-all). I would like to extract all MT values that lie in the middle surface of the cortex, and run that through mri_segstats so I get average MT values for each cortical region in the DK-atlas. My workflow is as follows: 1. mri_vol2suf --mov <MT_vol> --hemi lh --projfrac 0.5 -- regheader <id> --reg <MT_reg_to_T1W.dat> --o <vol2surf.output.mgh> --interp nearest 2. mri_surf2vol --surfval <vol2surf.output.mgh> --hemi lh --fillribbon --identity <id> --template <T1W> --o <surf2vol.output.mgh. 3. mri_segstats --seg <aparc+aseg for subid.mgz> --i <surf2vol.output.mgh> --ctab --id <list of regions> --o <output.stats> Is this the correct way of going about it? In essence I extract all the values of MT found in the middle of the cortex (#1), then I fill the cortex ribbon with these values in the subject's T1W vol (#2), and then run mri_segstats on that output so both aparc+aseg and the output from #2 are in the same space. Is there any other (more efficient) method to do this? Thank you, Yash RRI, Baycrest Health Sciences University of Toronto

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Extract pcc.nii.gz stats using aparc parcellations
by Tori Williams 05 Oct '17

05 Oct '17

Hi Doug, I was wondering if anyone could offer some insight into a freesurfer challenge I've encountered. I have run a resting connectivity analysis using the fsfast stream and now have a pcc.nii.gz map for each subject that is in fsaverage space (and loads just fine using tksurfer with fsaverage). Without mapping back to each subject's native space, is there a way to just use the fsaverage aparc to extract the mean pcc value for each subject by parcellation? I initially tried the following: `mris_anatomical_stats -a fsaverage/label/lh.aparc.annot -t fsaverage/surf/<subject pcc map in fsaverage space> -b fsaverage lh' and got an error that fsaverage/mri/wm.mgz could not be found. I followed an old post on the listerv and just put in a random wm.mgz file from a subject, assuming that anatomical stats wouldn't be calculating any distances if I specified a surface file. After I tried the same command again, I got this error: "ERROR: subject fsaverage is an average subject. mris_anatomical_stats cannot currently be used with an average subject. " Is there a better way to do this that I might be missing? I don't know if it complicates things given that the pcc files are saved as .nii.gz, even though they are surface overlays? Any suggestions would be greatly appreciated! Sincerely, Tori -- Victoria J. Williams, PhD Clinical Research Fellow Interdisciplinary Brain Center Massachusetts General Hospital Harvard Medical School Department of Neurology 149 13th Street Charlestown, MA 02129

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Error feeding design matrix into mri_glmfit
by Dowling, Kevin Francis 04 Oct '17

04 Oct '17

Dear Freesurfer experts, I'm trying to run a between groups analysis for two groups with a matrix set up for DOSS regressing out 5 covariates (contrast is 1 -1 0 0 0 0 0). I am trying to run this with DOSS as one of the covariates is an interaction term that would lead to colinearity issues in DODS. However, I am having some difficulty reading in my matrix. When I send in a standard matlab matrix (attached as a .mat) I get the following, "MatrixReadTXT: could not scan value [1][1] \ ERROR:in uncompressing," which I assume means that my matrix isn't being read properly (full output below under Output 1). I noticed a similar issue was discussed on the forum previously (https://mail.nmr.mgh.harvard.edu/pipermail//freesurfer/2013-November/034582…) and using an ASCII file seemed to resolve the issue. When I convert my matlab file into an ASCII text file (using dlmwrite in matlab, also attached as a .txt file) I get the following error (full output below under Output 2), "MatrixReadTxt: could not scan value [2][1] \ Invalid argument \ WARNING:matlab elment type is 758132281, which is not a matrix." I'm running Freesurfer version 5.3 on a CentOs 7 system. I suspect this is probably a simple mistake on my part, but I would greatly appreciate any guidance or further troubleshooting suggestions you might have! ~~~ Output 1: [dauntless:RPDR_Manual_Edits] (nmr-stable53-env) mri_glmfit --y /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh --X /cluster/roffman/users/fsgd/matrix/RPDR/99PostFortification_Minus_100PreFortification_DOSS_Nuisance_ZAgeGST_ZAgeXGrp_Matrix.mat --C /cluster/roffman/users/fsgd/RPDR_083115/Test_TwoGroups_RegressOutFiveCovariates_OddSyntax.mtx --glmdir /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS --surf fsaverage rh --fwhm 22 --no-prune Reading source surface /cluster/roffman2/users/RPDR_Manual_Edits//fsaverage/surf/rh.white FWHM = 22.000000 Number of vertices 163842 Number of faces 327680 Total area 65020.765625 AvgVtxArea 0.396850 AvgVtxDist 0.717994 StdVtxDist 0.193566 Surface smoothing by fwhm=22.000000, niters=356.000000 $Id: mri_glmfit.c,v 1.196.2.8 2012/11/01 18:51:41 greve Exp $ cwd /autofs/cluster/roffman2/users/RPDR_Manual_Edits cmdline mri_glmfit --y /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh --X /cluster/roffman/users/fsgd/matrix/RPDR/99PostFortification_Minus_100PreFortification_DOSS_Nuisance_ZAgeGST_ZAgeXGrp_Matrix.mat --C /cluster/roffman/users/fsgd/RPDR_083115/Test_TwoGroups_RegressOutFiveCovariates_OddSyntax.mtx --glmdir /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS --surf fsaverage rh --fwhm 22 --no-prune sysname Linux hostname dauntless.nmr.mgh.harvard.edu machine x86_64 user kfd11 FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 fwhm 22.000000 niters 356.000000 OneSampleGroupMean 0 y /autofs/cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh logyflag 0 X /cluster/roffman/users/fsgd/matrix/RPDR/99PostFortification_Minus_100PreFortification_DOSS_Nuisance_ZAgeGST_ZAgeXGrp_Matrix.mat usedti 0 labelmask /cluster/roffman2/users/RPDR_Manual_Edits//fsaverage/label/rh.cortex.label maskinv 0 glmdir /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS Loading y from /autofs/cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh MatrixReadTxT: could not scan value [1][1] Invalid argument ERROR: in uncompressing not enough memory in buffer Cannot allocate memory Segmentation fault (core dumped) ~~~ Output 2: [dauntless:RPDR_Manual_Edits] (nmr-stable53-env) mri_glmfit --y /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh --X /cluster/roffman/users/fsgd/matrix/RPDR/99PostFortification_Minus_100PreFortification_DOSS_Nuisance_ZAgeGST_ZAgeXGrp_Matrix_ASCII.txt --C /cluster/roffman/users/fsgd/RPDR_083115/Test_TwoGroups_RegressOutFiveCovariates_OddSyntax.mtx --glmdir /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS --surf fsaverage rh --fwhm 22 --no-prune Reading source surface /cluster/roffman2/users/RPDR_Manual_Edits//fsaverage/surf/rh.white FWHM = 22.000000 Number of vertices 163842 Number of faces 327680 Total area 65020.765625 AvgVtxArea 0.396850 AvgVtxDist 0.717994 StdVtxDist 0.193566 Surface smoothing by fwhm=22.000000, niters=356.000000 $Id: mri_glmfit.c,v 1.196.2.8 2012/11/01 18:51:41 greve Exp $ cwd /autofs/cluster/roffman2/users/RPDR_Manual_Edits cmdline mri_glmfit --y /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh --X /cluster/roffman/users/fsgd/matrix/RPDR/99PostFortification_Minus_100PreFortification_DOSS_Nuisance_ZAgeGST_ZAgeXGrp_Matrix_ASCII.txt --C /cluster/roffman/users/fsgd/RPDR_083115/Test_TwoGroups_RegressOutFiveCovariates_OddSyntax --glmdir /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS --surf fsaverage rh --fwhm 22 --no-prune sysname Linux hostname dauntless.nmr.mgh.harvard.edu machine x86_64 user kfd11 FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 fwhm 22.000000 niters 356.000000 OneSampleGroupMean 0 y /autofs/cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh logyflag 0 X /cluster/roffman/users/fsgd/matrix/RPDR/99PostFortification_Minus_100PreFortification_DOSS_Nuisance_ZAgeGST_ZAgeXGrp_Matrix_ASCII.txt usedti 0 labelmask /cluster/roffman2/users/RPDR_Manual_Edits//fsaverage/label/rh.cortex.label maskinv 0 glmdir /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory /cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_fwhm22/FS53Test_TopMinusBottomRegressoutZAgeGST_ZAgeXGrp_DOSS Loading y from /autofs/cluster/roffman2/users/RPDR_Manual_Edits/Analyses_Thickness/199_PrePostFort/RH/rh_thickness_map_usingfsgd.mgh MatrixReadTxT: could not scan value [2][1] Invalid argument WARNING: matlab elment type is 758132281, which is not a matrix. Kind regards, Kevin Kevin F. Dowling Clinical Research Coordinator Brain Genomics Laboratory Division of Psychiatric Neuroimaging Martinos Center for Biomedical Imaging Massachusetts General Hospital 149 13th Street Charlestown, MA, 02129 (p) 617.643.2479

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PCA and v.gmh
by Florence Campana 04 Oct '17

04 Oct '17

Dear freesurfers, I contact you since I ran a PCA with mri_glmfit. I do not manage to load the output v.mgh as an overlay as suggested in the documentation, which makes me wonder what is wrong. The output file or me loading it? For clarification, I ran the command: mri_glmfit --surf fsaverage lh --y fmcpr.siemens.sm4.fsaverage.lh.nii.gz --pca --osgm --glmdir /Users/Florence/Documents/test_glm_pca to run the PCA in surface. v.mgh is of size 1*163842(nb of vertices)*1*300 (number of components). On the one hand, the output seems to make sense (its size, and the values are centered around 0), on the other hand I do not understand why I do not see anything when I load it as an overlay in tksurfer, despite modifying the thresholds and color parameters etc. Or should I then save separately each spatial component contained in v.mgh, and load each of them as one overlay? I would also like to specify that my input data (fmcpr.siemens.sm4.fsaverage.lh.nii.gz) are of size 1*163842(nb of vertices)*1*300 (time points). This is the data from a single subject for now (before getting group data via mris_preproc) and I am not sure of whether it has the proper format. Indeed, it is specified that —y is the “path to input file with each frame being a separate input”. I do not understand what it means: does frame refer to one time point, and should I then have 300 input files (which seems a lot!)? Thank you very much, Florence

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Freesurfer October 2017