Hi Freesurfer Experts,
I am trying to run mri_glmfit and while 90% of my files work, some of them display the error below. I have tried demeaning, and then tried multiplying this value by 100, and I still get the same error. Any feedback would be greatly appreciated.
mris_preproc done srcsubject = fsaverage srcval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00.mgh srctype = trgsubject = fsaverage trgval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh trgtype = srcsurfreg = sphere.reg trgsurfreg = sphere.reg srchemi = rh trghemi = rh frame = 0 fwhm-in = 0 fwhm-out = 0 label-src = (null) label-trg = (null) OKToRevFaceOrder = 1 Reading source surface reg /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.sphere.reg Loading source data INFO: trgsubject = srcsubject Saving target data Saving to rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh gdfReadHeader: reading /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 Age 19.5833 1.32025 1 eTIV 1.61645e+06 145343 2 EnglishParityRT 0.00012207 25139.1 Class Means of each Continuous Variable 1 Monolingual_male 19.7143 1678946.5893 -4197.2796 2 Monolingual_female 19.4000 1528966.6750 5876.1917 INFO: gd2mtx_method is dods Reading source surface /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.white Number of vertices 163842 Number of faces 327680 Total area 65020.765625 AvgVtxArea 0.396850 AvgVtxDist 0.717994 StdVtxDist 0.193566
$Id: mri_glmfit.c,v 1.196.2.8 2012/11/01 18:51:41 greve Exp $ cwd /gpfs/scratch/jtl190/Math_reconstruction cmdline mri_glmfit --y rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd --C /gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt --surf fsaverage rh --cortex --glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir sysname Linux hostname cyberstar129.hpc.rcc.psu.edu machine x86_64 user jtl190 FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh logyflag 0 usedti 0 FSGD /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd labelmask /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/label/rh.cortex.label maskinv 0 glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir Loading y from /gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh INFO: gd2mtx_method is dods Saving design matrix to rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir/Xg.dat Normalized matrix condition is 22568.9 Design matrix ------------------ 1.000 0.000 18.000 0.000 1865790.250 0.000 -8952.208 0.000; 0.000 1.000 0.000 19.000 0.000 1520429.625 0.000 -4605.208; 1.000 0.000 19.000 0.000 1749716.750 0.000 -39407.207 0.000; 0.000 1.000 0.000 18.000 0.000 1589109.250 0.000 -17967.209; 1.000 0.000 21.000 0.000 1472295.125 0.000 19531.791 0.000; 1.000 0.000 18.000 0.000 1580381.375 0.000 -17027.209 0.000; 1.000 0.000 20.000 0.000 1813373.500 0.000 16152.792 0.000; 1.000 0.000 21.000 0.000 1638616.500 0.000 -9074.208 0.000; 0.000 1.000 0.000 21.000 0.000 1297920.500 0.000 61860.793; 0.000 1.000 0.000 18.000 0.000 1634762.625 0.000 -22671.209; 0.000 1.000 0.000 21.000 0.000 1602611.375 0.000 12763.792; 1.000 0.000 21.000 0.000 1632452.625 0.000 9395.292 0.000; -------------------------------- ERROR: matrix is ill-conditioned or badly scaled, condno = 22568.9 -------------------------------- Possible problem with experimental design: Check for duplicate entries and/or lack of range of continuous variables within a class. If you seek help with this problem, make sure to send: 1. Your command line: mri_glmfit --y rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd --C /gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt --surf fsaverage rh --cortex --glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir 2. The FSGD file (if using one) 3. And the design matrix above
I am also attaching the FSGD file.
Best,
Jennifer Legault
This is almost surely a problem with scaling as your covariates are huge. Try subtracting the mean and dividing by the stddev before entering into the FSGD file. Compute the means and stddevs across all subjects. doug
On 07/11/2016 03:20 PM, Jennifer Legault wrote:
Hi Freesurfer Experts,
I am trying to run mri_glmfit and while 90% of my files work, some of them display the error below. I have tried demeaning, and then tried multiplying this value by 100, and I still get the same error. Any feedback would be greatly appreciated.
mris_preproc done srcsubject = fsaverage srcval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00.mgh srctype = trgsubject = fsaverage trgval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh trgtype = srcsurfreg = sphere.reg trgsurfreg = sphere.reg srchemi = rh trghemi = rh frame = 0 fwhm-in = 0 fwhm-out = 0 label-src = (null) label-trg = (null) OKToRevFaceOrder = 1 Reading source surface reg /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.sphere.reg Loading source data INFO: trgsubject = srcsubject Saving target data Saving to rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh gdfReadHeader: reading /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 Age 19.5833 1.32025 1 eTIV 1.61645e+06 145343 2 EnglishParityRT 0.00012207 25139.1 Class Means of each Continuous Variable 1 Monolingual_male 19.7143 1678946.5893 -4197.2796 2 Monolingual_female 19.4000 1528966.6750 5876.1917 INFO: gd2mtx_method is dods Reading source surface /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.white Number of vertices 163842 Number of faces 327680 Total area 65020.765625 AvgVtxArea 0.396850 AvgVtxDist 0.717994 StdVtxDist 0.193566
$Id: mri_glmfit.c,v 1.196.2.8 2012/11/01 18:51:41 greve Exp $ cwd /gpfs/scratch/jtl190/Math_reconstruction cmdline mri_glmfit --y rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd --C /gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt --surf fsaverage rh --cortex --glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir sysname Linux hostname cyberstar129.hpc.rcc.psu.edu http://cyberstar129.hpc.rcc.psu.edu machine x86_64 user jtl190 FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh logyflag 0 usedti 0 FSGD /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd labelmask /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/label/rh.cortex.label maskinv 0 glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir Loading y from /gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh INFO: gd2mtx_method is dods Saving design matrix to rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir/Xg.dat Normalized matrix condition is 22568.9 Design matrix ------------------ 1.000 0.000 18.000 0.000 1865790.250 0.000 -8952.208 0.000; 0.000 1.000 0.000 19.000 0.000 1520429.625 0.000 -4605.208; 1.000 0.000 19.000 0.000 1749716.750 0.000 -39407.207 0.000; 0.000 1.000 0.000 18.000 0.000 1589109.250 0.000 -17967.209; 1.000 0.000 21.000 0.000 1472295.125 0.000 19531.791 0.000; 1.000 0.000 18.000 0.000 1580381.375 0.000 -17027.209 0.000; 1.000 0.000 20.000 0.000 1813373.500 0.000 16152.792 0.000; 1.000 0.000 21.000 0.000 1638616.500 0.000 -9074.208 0.000; 0.000 1.000 0.000 21.000 0.000 1297920.500 0.000 61860.793; 0.000 1.000 0.000 18.000 0.000 1634762.625 0.000 -22671.209; 0.000 1.000 0.000 21.000 0.000 1602611.375 0.000 12763.792;
1.000 0.000 21.000 0.000 1632452.625 0.000 9395.292 0.000;
ERROR: matrix is ill-conditioned or badly scaled, condno = 22568.9
Possible problem with experimental design: Check for duplicate entries and/or lack of range of continuous variables within a class. If you seek help with this problem, make sure to send:
- Your command line:
mri_glmfit --yrh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd --C /gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt --surf fsaverage rh --cortex --glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir 2. The FSGD file (if using one) 3. And the design matrix above
I am also attaching the FSGD file.
Best,
Jennifer Legault
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Doug,
Thank you for your response. The current fsgd file I sent you was with the covariates demeaned x 100, as I saw you recommend that to someone else. We previously tried doing just the demeaned values without multiplying by 100, and that still had the badly scaled error. Do you think we should take the demeaned x 100 covariates and divide them by the standard deviation? Or would it be better to take regular demeaned values and divide them by the standard deviation?
Best,
Jennifer Legault
On Mon, Jul 18, 2016 at 12:43 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu
wrote:
This is almost surely a problem with scaling as your covariates are huge. Try subtracting the mean and dividing by the stddev before entering into the FSGD file. Compute the means and stddevs across all subjects. doug
On 07/11/2016 03:20 PM, Jennifer Legault wrote:
Hi Freesurfer Experts,
I am trying to run mri_glmfit and while 90% of my files work, some of them display the error below. I have tried demeaning, and then tried multiplying this value by 100, and I still get the same error. Any feedback would be greatly appreciated.
mris_preproc done srcsubject = fsaverage srcval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00.mgh srctype = trgsubject = fsaverage trgval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh trgtype = srcsurfreg = sphere.reg trgsurfreg = sphere.reg srchemi = rh trghemi = rh frame = 0 fwhm-in = 0 fwhm-out = 0 label-src = (null) label-trg = (null) OKToRevFaceOrder = 1 Reading source surface reg /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.sphere.reg Loading source data INFO: trgsubject = srcsubject Saving target data Saving to rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh gdfReadHeader: reading
/gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd
INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 Age 19.5833 1.32025 1 eTIV 1.61645e+06 145343 2 EnglishParityRT 0.00012207 25139.1 Class Means of each Continuous Variable 1 Monolingual_male 19.7143 1678946.5893 -4197.2796 2 Monolingual_female 19.4000 1528966.6750 5876.1917 INFO: gd2mtx_method is dods Reading source surface /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.white Number of vertices 163842 Number of faces 327680 Total area 65020.765625 AvgVtxArea 0.396850 AvgVtxDist 0.717994 StdVtxDist 0.193566
$Id: mri_glmfit.c,v 1.196.2.8 2012/11/01 18:51:41 greve Exp $ cwd /gpfs/scratch/jtl190/Math_reconstruction cmdline mri_glmfit --y rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd
/gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd
--C
/gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt
--surf fsaverage rh --cortex --glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir sysname Linux hostname cyberstar129.hpc.rcc.psu.edu http://cyberstar129.hpc.rcc.psu.edu machine x86_64 user jtl190 FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y
/gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh
logyflag 0 usedti 0 FSGD
/gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd
labelmask /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/label/rh.cortex.label maskinv 0 glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir Loading y from
/gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh
INFO: gd2mtx_method is dods Saving design matrix to rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir/Xg.dat Normalized matrix condition is 22568.9 Design matrix ------------------ 1.000 0.000 18.000 0.000 1865790.250 0.000 -8952.208 0.000; 0.000 1.000 0.000 19.000 0.000 1520429.625 0.000 -4605.208; 1.000 0.000 19.000 0.000 1749716.750 0.000 -39407.207
0.000;
0.000 1.000 0.000 18.000 0.000 1589109.250 0.000 -17967.209; 1.000 0.000 21.000 0.000 1472295.125 0.000 19531.791 0.000; 1.000 0.000 18.000 0.000 1580381.375 0.000 -17027.209
0.000;
1.000 0.000 20.000 0.000 1813373.500 0.000 16152.792 0.000; 1.000 0.000 21.000 0.000 1638616.500 0.000 -9074.208 0.000; 0.000 1.000 0.000 21.000 0.000 1297920.500 0.000 61860.793; 0.000 1.000 0.000 18.000 0.000 1634762.625 0.000 -22671.209; 0.000 1.000 0.000 21.000 0.000 1602611.375 0.000 12763.792;
1.000 0.000 21.000 0.000 1632452.625 0.000 9395.292 0.000;
ERROR: matrix is ill-conditioned or badly scaled, condno = 22568.9
Possible problem with experimental design: Check for duplicate entries and/or lack of range of continuous variables within a class. If you seek help with this problem, make sure to send:
- Your command line:
mri_glmfit --yrh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd
/gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd
--C
/gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt
--surf fsaverage rh --cortex --glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir 2. The FSGD file (if using one) 3. And the design matrix above
I am also attaching the FSGD file.
Best,
Jennifer Legault
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Douglas N. Greve, Ph.D. MGH-NMR Center 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 Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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.
It does not look like the variables are demeaned (your FSGD file below)
Variables Age eTIV EnglishParityRT Input Math_5001m Monolingual_male 18 1865790.30866 -8952.20833333333 Input Math_5002m Monolingual_female 19 1520429.68796 -4605.20833333333 Input Math_5003m Monolingual_male 19 1749716.72939 -39407.2083333333 Input Math_5004m Monolingual_female 18 1589109.27022 -17967.2083333333 Input Math_5005m Monolingual_male 21 1472295.15211 19531.7916666667 Input Math_5006m Monolingual_male 18 1580381.40566 -17027.2083333333 Input Math_5007m Monolingual_male 20 1813373.55024 16152.7916666667 Input Math_5008m Monolingual_male 21 1638616.48007 -9074.20833333333 Input Math_5009m Monolingual_female 21 1297920.49281 61860.7916666667 Input Math_5010m Monolingual_female 18 1634762.57845 -22671.2083333333 Input Math_5011m Monolingual_female 21 1602611.42141 12763.7916666667 Input Math_5014m Monolingual_male 21 1632452.66476 9395.29166666669
On 07/18/2016 01:31 PM, Jennifer Legault wrote:
Hi Doug,
Thank you for your response. The current fsgd file I sent you was with the covariates demeaned x 100, as I saw you recommend that to someone else. We previously tried doing just the demeaned values without multiplying by 100, and that still had the badly scaled error. Do you think we should take the demeaned x 100 covariates and divide them by the standard deviation? Or would it be better to take regular demeaned values and divide them by the standard deviation?
Best,
Jennifer Legault
On Mon, Jul 18, 2016 at 12:43 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu mailto:greve@nmr.mgh.harvard.edu> wrote:
This is almost surely a problem with scaling as your covariates are huge. Try subtracting the mean and dividing by the stddev before entering into the FSGD file. Compute the means and stddevs across all subjects. doug On 07/11/2016 03:20 PM, Jennifer Legault wrote: > Hi Freesurfer Experts, > > I am trying to run mri_glmfit and while 90% of my files work, some of > them display the error below. I have tried demeaning, and then tried > multiplying this value by 100, and I still get the same error. Any > feedback would be greatly appreciated. > > mris_preproc done > srcsubject = fsaverage > srcval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00.mgh > srctype = > trgsubject = fsaverage > trgval = rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh > trgtype = > srcsurfreg = sphere.reg > trgsurfreg = sphere.reg > srchemi = rh > trghemi = rh > frame = 0 > fwhm-in = 0 > fwhm-out = 0 > label-src = (null) > label-trg = (null) > OKToRevFaceOrder = 1 > Reading source surface reg > /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.sphere.reg > Loading source data > INFO: trgsubject = srcsubject > Saving target data > Saving to rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh > gdfReadHeader: reading > /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd > INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. > Continuous Variable Means (all subjects) > 0 Age 19.5833 1.32025 > 1 eTIV 1.61645e+06 145343 > 2 EnglishParityRT 0.00012207 25139.1 > Class Means of each Continuous Variable > 1 Monolingual_male 19.7143 1678946.5893 -4197.2796 > 2 Monolingual_female 19.4000 1528966.6750 5876.1917 > INFO: gd2mtx_method is dods > Reading source surface > /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/surf/rh.white > Number of vertices 163842 > Number of faces 327680 > Total area 65020.765625 > AvgVtxArea 0.396850 > AvgVtxDist 0.717994 > StdVtxDist 0.193566 > > $Id: mri_glmfit.c,v 1.196.2.8 2012/11/01 18:51:41 greve Exp $ > cwd /gpfs/scratch/jtl190/Math_reconstruction > cmdline mri_glmfit --y > rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd > /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd > --C > /gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt > --surf fsaverage rh --cortex --glmdir > rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir > sysname Linux > hostname cyberstar129.hpc.rcc.psu.edu <http://cyberstar129.hpc.rcc.psu.edu> > <http://cyberstar129.hpc.rcc.psu.edu> > machine x86_64 > user jtl190 > FixVertexAreaFlag = 1 > UseMaskWithSmoothing 1 > OneSampleGroupMean 0 > y > /gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh > logyflag 0 > usedti 0 > FSGD > /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd > labelmask > /gpfs/scratch/jtl190/Math_reconstruction/fsaverage/label/rh.cortex.label > maskinv 0 > glmdir rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir > IllCondOK 0 > ReScaleX 1 > DoFFx 0 > Creating output directory > rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir > Loading y from > /gpfs/scratch/jtl190/Math_reconstruction/rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh > INFO: gd2mtx_method is dods > Saving design matrix to > rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir/Xg.dat > Normalized matrix condition is 22568.9 > Design matrix ------------------ > 1.000 0.000 18.000 0.000 1865790.250 0.000 -8952.208 0.000; > 0.000 1.000 0.000 19.000 0.000 1520429.625 0.000 -4605.208; > 1.000 0.000 19.000 0.000 1749716.750 0.000 -39407.207 0.000; > 0.000 1.000 0.000 18.000 0.000 1589109.250 0.000 -17967.209; > 1.000 0.000 21.000 0.000 1472295.125 0.000 19531.791 0.000; > 1.000 0.000 18.000 0.000 1580381.375 0.000 -17027.209 0.000; > 1.000 0.000 20.000 0.000 1813373.500 0.000 16152.792 0.000; > 1.000 0.000 21.000 0.000 1638616.500 0.000 -9074.208 0.000; > 0.000 1.000 0.000 21.000 0.000 1297920.500 0.000 61860.793; > 0.000 1.000 0.000 18.000 0.000 1634762.625 0.000 -22671.209; > 0.000 1.000 0.000 21.000 0.000 1602611.375 0.000 12763.792; > 1.000 0.000 21.000 0.000 1632452.625 0.000 9395.292 0.000; > -------------------------------- > ERROR: matrix is ill-conditioned or badly scaled, condno = 22568.9 > -------------------------------- > Possible problem with experimental design: > Check for duplicate entries and/or lack of range of > continuous variables within a class. > If you seek help with this problem, make sure to send: > 1. Your command line: > mri_glmfit --y > rh.mono_EnglishParityRT_age_gender_TIV.volume.00B.mgh --fsgd > /gpfs/scratch/jtl190/FSGD_files/fsgd_math_mono_EnglishParityRT_age_gender_TIV_demean100.fsgd > --C > /gpfs/scratch/jtl190/Contrast_files/Contrast_math_monly_EnglishParityRT_a_g_TIV.txt > --surf fsaverage rh --cortex --glmdir > rh.mono_EnglishParityRT_age_gender_TIV_100.glmdir > 2. The FSGD file (if using one) > 3. And the design matrix above > > > I am also attaching the FSGD file. > > Best, > > Jennifer Legault > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu> Phone Number: 617-724-2358 <tel:617-724-2358> Fax: 617-726-7422 <tel:617-726-7422> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting <http://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/ _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer 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.-- Jennifer Legault Ph.D candidate, Neuroscience Brain, Language, and Computation Lab The Pennsylvania State University
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