Re: [Freesurfer] problem feeding design matrix to mri_glmfit
Thank you Doug, that worked a treat! I knew it must have been something simple I was missing. Best. LT On Tue, Nov 19, 2013 at 8:45 AM, Douglas N Greve wrote: > The problem is with the mat file, not the input. The matrix should be an > ascii text file. > doug > > > On 11/18/2013 12:09 PM, Laura M. Tully wrote: > > Hello freesurfers, > > > > I'm trying to run mri_glmfit between groups analysis (patients vs. > > controls) with gender, age, medication (continuous), and duration of > > illness as covariates. Because the control group have values of zeros > > for medication and duration of illness (which results in an > > illconditioned matrix), I have created my own design matrix so that > > controls do not have a column for medication or duration of illness > > and am feeding this matrix into mri_glmfit instead of the fsgd file. > > However, this seems to cause a problem with the --y input; when I try > > to run mri_glmfit, i get an error message "error in uncompressing" - > > I'm not quite sure what this means, perhaps I did something wrong in > > creating the design matrix? > > > > See the full output below. I've also attached the design matrix, > > contrast file, and the original fsgd (which results in the ill > > conditioned matrix). > > > > Best, > > Laura. > > > > *Command line: * > > mri_glmfit --y lh_grpDiffs_thickness10.mgh --X > > new_mat_files/X_lh_grp_thick_med_dur.mat --C > > Contrast1B_grp_Diffs_HCvsSZ_Med_Dur.mtx --surf fsaverage lh --cortex > > --glmdir lh.grp_diffs_thickness_med_dur_112013.glmdir --illcond > > > > *Output:* > > Reading source surface > > /ncf/snp/04/SCORE/freesurfer_analysis/fsaverage/surf/lh.white > > Number of vertices 163842 > > Number of faces327680 > > Total area 65416.648438 > > AvgVtxArea 0.399267 > > AvgVtxDist 0.721953 > > StdVtxDist 0.195470 > > > > $Id: mri_glmfit.c,v 1.196.2.6 2011/05/05 20:54:25 greve Exp $ > > cwd /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis > > cmdline mri_glmfit --y lh_grpDiffs_thickness10.mgh --X > > new_mat_files/X_lh_grp_thick_med_dur.mat --C > > Contrast1B_grp_Diffs_HCvsSZ_Med_Dur.mtx --surf fsaverage lh --cortex > > --glmdir lh.grp_diffs_thickness_med_dur_112013.glmdir --illcond > > sysname Linux > > hostname ncfws13.rc.fas.harvard.edu <http://ncfws13.rc.fas.harvard.edu> > > machine x86_64 > > user ltully > > FixVertexAreaFlag = 1 > > UseMaskWithSmoothing 1 > > OneSampleGroupMean 0 > > y > > > > /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis/lh_grpDiffs_thickness10.mgh > > logyflag 0 > > Xnew_mat_files/X_lh_grp_thick_med_dur.mat > > usedti 0 > > labelmask > > /ncf/snp/04/SCORE/freesurfer_analysis/fsaverage/label/lh.cortex.label > > maskinv 0 > > glmdir lh.grp_diffs_thickness_med_dur_112013.glmdir > > IllCondOK 1 > > ReScaleX 1 > > DoFFx 0 > > Creating output directory lh.grp_diffs_thickness_med_dur_112013.glmdir > > Loading y from > > > /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis/lh_grpDiffs_thickness10.mgh > > MatrixReadTxT: could not scan value [1][1] > > > > File exists > > ERROR: in uncompressing > > MATFILE5: 0 x 0, type 0, imagf 0, name '' > > > > File exists > > unsupported matlab format 0 (unknown) > > > > File exists > > Saving design matrix to > > lh.grp_diffs_thickness_med_dur_112013.glmdir/Xg.dat > > *** glibc detected *** mri_glmfit: double free or corruption (out): > > 0x3b1279c0 *** > > === Backtrace: = > > /lib64/libc.so.6[0x3229470d7f] > > /lib64/libc.so.6(cfree+0x4b)[0x32294711db] > > mri_glmfit[0x99fea2] > > mri_glmfit[0x5bcbe3] > > mri_glmfit[0x433608] > > mri_glmfit[0x433802] > > mri_glmfit[0x40f2f7] > > /lib64/libc.so.6(__libc_start_main+0xf4)[0x322941d994] > > mri_glmfit(__gxx_personality_v0+0x172)[0x40b2ba] > > === Memory map: > > 0040-00b86000 r-xp 0040 00:00 0 > > 00b86000-00c86000 ---p 00b86000 00:00 0 > > 00c86000-26a08000 rwxp 00c86000 00:00 0 > > 35b4b000-3d4fa000 rwxp 35b4b000 00:00 0 [heap] > > 322900-322901c000 r-xp fd:00 557272 > > /lib64/ld-2.5.so <http://ld-2.5.so> > > 322901c000-322921c000 ---p 322901c000 00:00 0 > > 322921c000-322921d000 r-xp 0001c000 fd:00 557272 > > /lib64/ld-2.5.so <http://ld-2.5.so> > > 322921d000-322921e000 rwxp 0001d000 fd:00 557272 > > /lib64/ld-2.5.so <http:/
[Freesurfer] problem feeding design matrix to mri_glmfit
/lib64/libgcc_s-4.1.2-20080825.so.1 322f00d000-322f20d000 ---p d000 fd:00 557370 /lib64/libgcc_s-4.1.2-20080825.so.1 322f20d000-322f20e000 rwxp d000 fd:00 557370 /lib64/libgcc_s-4.1.2-20080825.so.1 323720-32372e6000 r-xp fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32372e6000-32374e5000 ---p 000e6000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374e5000-32374eb000 r-xp 000e5000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374eb000-32374ee000 rwxp 000eb000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374ee000-323750 rwxp 32374ee000 00:00 0 323960-3239609000 r-xp fd:00 557404 /lib64/libcrypt-2.5.so 3239609000-3239808000 ---p 9000 fd:00 557404 /lib64/libcrypt-2.5.so 3239808000-3239809000 r-xp 8000 fd:00 557404 /lib64/libcrypt-2.5.so 3239809000-323980a000 rwxp 9000 fd:00 557404 /lib64/libcrypt-2.5.so 323980a000-3239838000 rwxp 323980a000 00:00 0 2b1225c45000-2b1225c48000 rwxp 2b1225c45000 00:00 0 2b1225c69000-2b1225c6d000 rwxp 2b1225c69000 00:00 0 2b1225c6d000-2b1225ca2000 r-xs fd:00 3703836 /var/run/nscd/dbC3ggnz (deleted) 2b1225d6d000-2b12952bb000 rwxp 2b1225d6d000 00:00 0 7fff44349000-7fff44362000 rwxp 7ffe5000 00:00 0 [stack] 7fff443cb000-7fff443ce000 r-xp 7fff443cb000 00:00 0 [vdso] ff60-ffe0 ---p 00:00 0 [vsyscall] Aborted -- -- Laura M. Tully, PhD Post-Doctoral Fellow in Psychiatry UC Davis Imaging Research Center 4701 X Street, Sacramento, CA 95817 Phone: (916) 734-7927 Fax: (916) 734-8750 Alumnus of Social Neuroscience & Psychopathology Lab, Harvard University ltu...@fas.harvard.edu Follow me on twitter: @tully_laura -- *Confidentiality Notice:* This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. -- -- Laura M. Tully, PhD Post-Doctoral Fellow in Psychiatry UC Davis Imaging Research Center 4701 X Street, Sacramento, CA 95817 Phone: (916) 734-7927 Fax: (916) 734-8750 Alumnus of Social Neuroscience & Psychopathology Lab, Harvard University ltu...@fas.harvard.edu Follow me on twitter: @tully_laura -- *Confidentiality Notice:* This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. X_lh_grp_thick_med_dur.mat Description: Binary data grpdiffs_thickness_lh_Med_Dur.fsgd Description: Binary data Contrast1B_grp_Diffs_HCvsSZ_Med_Dur.mtx Description: Binary data ___ 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.
[Freesurfer] problem feeding design matrix to mri_glmfit
/lib64/libgcc_s-4.1.2-20080825.so.1 322f00d000-322f20d000 ---p d000 fd:00 557370 /lib64/libgcc_s-4.1.2-20080825.so.1 322f20d000-322f20e000 rwxp d000 fd:00 557370 /lib64/libgcc_s-4.1.2-20080825.so.1 323720-32372e6000 r-xp fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32372e6000-32374e5000 ---p 000e6000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374e5000-32374eb000 r-xp 000e5000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374eb000-32374ee000 rwxp 000eb000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374ee000-323750 rwxp 32374ee000 00:00 0 323960-3239609000 r-xp fd:00 557404 /lib64/libcrypt-2.5.so 3239609000-3239808000 ---p 9000 fd:00 557404 /lib64/libcrypt-2.5.so 3239808000-3239809000 r-xp 8000 fd:00 557404 /lib64/libcrypt-2.5.so 3239809000-323980a000 rwxp 9000 fd:00 557404 /lib64/libcrypt-2.5.so 323980a000-3239838000 rwxp 323980a000 00:00 0 2b1225c45000-2b1225c48000 rwxp 2b1225c45000 00:00 0 2b1225c69000-2b1225c6d000 rwxp 2b1225c69000 00:00 0 2b1225c6d000-2b1225ca2000 r-xs fd:00 3703836 /var/run/nscd/dbC3ggnz (deleted) 2b1225d6d000-2b12952bb000 rwxp 2b1225d6d000 00:00 0 7fff44349000-7fff44362000 rwxp 7ffe5000 00:00 0 [stack] 7fff443cb000-7fff443ce000 r-xp 7fff443cb000 00:00 0 [vdso] ff60-ffe0 ---p 00:00 0 [vsyscall] Aborted -- -- Laura M. Tully, PhD Post-Doctoral Fellow in Psychiatry UC Davis Imaging Research Center 4701 X Street, Sacramento, CA 95817 Phone: (916) 734-7927 Fax: (916) 734-8750 Alumnus of Social Neuroscience & Psychopathology Lab, Harvard University ltu...@fas.harvard.edu Follow me on twitter: @tully_laura -- *Confidentiality Notice:* This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. X_lh_grp_thick_med_dur.mat Description: Binary data grpdiffs_thickness_lh_Med_Dur.fsgd Description: Binary data Contrast1B_grp_Diffs_HCvsSZ_Med_Dur.mtx Description: Binary data ___ 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.
Re: [Freesurfer] ill conditioned matrix with covariates that are unequal between groups
Thanks for the suggestions Doug, I have a few clarifying questions below, to make sure I understand everything. On Tue, Oct 22, 2013 at 8:02 AM, Douglas N Greve wrote: > > The duration of illnessis always 0 for your healthy controls(which is > obviously reasonable). The problem is that mri_glmfit is creating a > regressor of all 0s to model this duration and this is causing the > ill-conditionedness. There are several things you can do: > > 1. Create your own design matrix so that HCs do not have a column for > duration. You can edit the one created by mri_glmfit from the fsgd. You > can then feed this matrix into mri_glmfit instead of the fsgd file. > Would I do this for both medication and duration columns? What is the flag for feeding mri_glmfit an .mtx instead of an fsgd? > > 2. Run mri_glmfit with DOSS instead of DODS. This is appropriateif all > four groupshave the same slope with age, mean thickness, medication, and > duration. > i.e. if there are no group differences on age, mean thickness, medication, or duration of illness I can run DOSS? My groups are matched on age and ,mean thickness, but there are obviously group differences in medications and illness duration... thus wouldn't I expect them to have different slopes? > > 3. Recode the HCs be SZs with 0 duration illness. This maynot make sense > with your other variables (like medication). > i.e. collapse them into one group? But, the analysis I am interested in is detecting group differences in thickness whilst controlling for confounds such as age, medication, and duration of illness... if I recoded the HC group wouldn't this change the analysis from between group to within? > > doug > > On 10/21/2013 11:01 PM, Laura M. Tully wrote: > > Hello freesurfers, > > > > I'm trying to run mri_glmfit between groups analysis (patients vs. > > controls) with gender, age, medication (continuous), and duration of > > illness as covariates. The problem is, only the patients have > > medication and duration of illness values - by virtue of being control > > participants, the control group have values of zero for medication and > > duration of illness. This causes issues with the matrix and I'm trying > > to figure out how to get around it. Suggestions would be most > > appreciated. See output and details below, plus attached files. > > > > Thanks! > > > > Laura. > > > > *Command line: * > > mri_glmfit --y lh_grpDiffs_thickness10.mgh --fsgd > > grpdiffs_thickness_lh_Med_Dur.fsgd --fsgd-rescale --C > > Contrast1A_grp_Diffs_HCvsSZ_Med_Dur.mtx --surf fsaverage lh --cortex > > --glmdir lh_grpdiffs_lh_thickness_Med_Dur.glmdir > > * > > * > > *Output:* > > gdfReadHeader: reading grpdiffs_thickness_lh_Med_Dur.fsgd > > INFO: demeaning continuous variables > > Continuous Variable Means (all subjects) > > 0 Age 36.0909 11.4927 > > 1 LH_Mean_Thick 2.34931 0.118499 > > 2 medication 204.545 330.217 > > 3 duration_illness 7.74545 11.4005 > > Class Means of each Continuous Variable > > 1 HCmale 34.3000 2.3799 0. 0. > > 2 HCfemale 32.5556 2.3723 0. 0. > > 3 SZmale 36.5000 2.3124 391.2500 14.6875 > > 4 SZfemale 42.2000 2.3265 499. 19.1000 > > INFO: gd2mtx_method is dods > > Reading source surface > > /ncf/snp/04/SCORE/freesurfer_analysis/fsaverage/surf/lh.white > > Number of vertices 163842 > > Number of faces327680 > > Total area 65416.648438 > > AvgVtxArea 0.399267 > > AvgVtxDist 0.721953 > > StdVtxDist 0.195470 > > > > $Id: mri_glmfit.c,v 1.196.2.6 2011/05/05 20:54:25 greve Exp $ > > cwd /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis > > cmdline mri_glmfit --y lh_grpDiffs_thickness10.mgh --fsgd > > grpdiffs_thickness_lh_Med_Dur.fsgd --fsgd-rescale --C > > Contrast1A_grp_Diffs_HCvsSZ_Med_Dur.mtx --surf fsaverage lh --cortex > > --glmdir lh_grpdiffs_lh_thickness_Med_Dur.glmdir > > sysname Linux > > hostname ncfws14.rc.fas.harvard.edu <http://ncfws14.rc.fas.harvard.edu> > > machine x86_64 > > user ltully > > FixVertexAreaFlag = 1 > > UseMaskWithSmoothing 1 > > OneSampleGroupMean 0 > > y > > > > /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis/lh_grpDiffs_thickness10.mgh > > logyflag 0 > > usedti 0 > > FSGD grpdiffs_thickness_lh_Med_Dur.fsgd > > labelmask > > /ncf/snp/04/SCORE/freesurfer_analysis/fsaverage/label/lh.cortex.label > > maskinv 0 > > glmdir lh_grpdiffs_lh_thickness_Med_Dur.glmdir > > IllCondOK 0 > > ReScaleX 1 > > DoFFx 0 > > Creating output director
[Freesurfer] ill conditioned matrix with covariates that are unequal between groups
00 1.790 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000; 1.000 0.000 0.000 0.000 -0.983 0.000 0.000 0.000 0.558 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000; 1.000 0.000 0.000 0.000 -1.157 0.000 0.000 0.000 0.254 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000; 1.000 0.000 0.000 0.000 -1.157 0.000 0.000 0.000 0.752 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000; 0.000 1.000 0.000 0.000 0.000 -0.918 0.000 0.000 0.000 0.841 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000; 0.000 0.000 1.000 0.000 0.000 0.000 1.088 0.000 0.000 0.000 -1.354 0.000 0.000 0.000 3.660 0.000 0.000 0.000 1.343 0.000; 0.000 0.000 1.000 0.000 0.000 0.000 -0.305 0.000 0.000 0.000 1.819 0.000 0.000 0.000 -1.185 0.000 0.000 0.000 -1.025 0.000; 1.000 0.000 0.000 0.000 -0.461 0.000 0.000 0.000 0.870 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000; 1.000 0.000 0.000 0.000 -1.418 0.000 0.000 0.000 -0.336 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000; ERROR: matrix is ill-conditioned or badly scaled, condno = 1e+08 -- -- Laura M. Tully, PhD Post-Doctoral Fellow in Psychiatry UC Davis Imaging Research Center 4701 X Street, Sacramento, CA 95817 Phone: (916) 734-7927 Fax: (916) 734-8750 Alumnus of Social Neuroscience & Psychopathology Lab, Harvard University ltu...@fas.harvard.edu Follow me on twitter: @tully_laura -- grpdiffs_thickness_lh_Med_Dur.fsgd Description: Binary data ___ 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.
Re: [Freesurfer] Merging PArcellation labels
it sounds like you want a different parcellation of the lateral prefrontal cortex than what is offered by the default atlas (aparc, AKA the desikan atlas) - I suggest you load in ?h.aparc.a2009s.annot (aka the destrieux atlas) as your annotation in tksurfer and select the annotations of the PFC that you want from there and save as labels. The aparc.a2009 annotation offers a more fine grained parcellation of the PFC - e.g. you can get the DLPFC by merging the middle frontal gyrus & middle frontal sulcus parcellations. On Mon, Mar 25, 2013 at 3:19 AM, Anupa AV wrote: > Dear Laura, > Thank you so much. > It worked well. > Do you know how to make cuts on the merged label, for eg. if I need to > seperate DLPFC from premotor cortex. > > >---------- > *From:* Laura M. Tully > *To:* Anupa AV > *Cc:* "freesurfer@nmr.mgh.harvard.edu" > *Sent:* Sunday, March 24, 2013 12:20 AM > *Subject:* Re: [Freesurfer] Merging PArcellation labels > > First save each parcellation that you want as its own separate label by > selecting it in tksurfer (simply click on it with your mouse and its > boarder will be highlighted in yellow) and then file -> label -> save > selected label... Then you can merge these separate labels into one label > at the command line using mri_mergelabels -i [labelfile1] -i [labelfile2] > -o [newlabelfile.label] > > If doing glms from the command line you can then feed mri_glmfit the label > with the --label option. This will conduct the glm in the region specified > in the label only (i.e. an roi analysis) > > There is also a quick way to turn all of the desikan parcellations into > individual label files at the command line using mri_annotation2label I > think, but I can't remember precisely. This is a lot faster than using > tksurfer as it simply dumps *all* the individual parcellations into a > specified output directory. But I don't know if you can do it with the > Destrieux atlas parcellations (if you were interested in doing that.) > > Laura. > > > > > > On Sat, Mar 23, 2013 at 2:36 AM, Anupa AV wrote: > > Dear All, > > Can anyone tell me how to merge the parcellation labels using tksurfer.? > For eg. How can I merge, Superior frontal gyrus, middle frontal gyrus and > caudal middle frontal gyrus. > > ___ > 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. > > > > > -- > -- > Laura M. Tully, MA > Social Neuroscience & Psychopathology, Harvard University > Center for the Assessment and Prevention of Prodromal States, UCLA Semel > Institute of Neuroscience > ltu...@mednet.ucla.edu > ltu...@fas.harvard.edu > 310-267-0170 > -- > My musings as a young clinical scientist: > http://theclinicalbrain.blogspot.com/ > Follow me on Twitter: @tully_laura > > ___ > 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. > > > -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
Re: [Freesurfer] Merging PArcellation labels
First save each parcellation that you want as its own separate label by selecting it in tksurfer (simply click on it with your mouse and its boarder will be highlighted in yellow) and then file -> label -> save selected label... Then you can merge these separate labels into one label at the command line using mri_mergelabels -i [labelfile1] -i [labelfile2] -o [newlabelfile.label] If doing glms from the command line you can then feed mri_glmfit the label with the --label option. This will conduct the glm in the region specified in the label only (i.e. an roi analysis) There is also a quick way to turn all of the desikan parcellations into individual label files at the command line using mri_annotation2label I think, but I can't remember precisely. This is a lot faster than using tksurfer as it simply dumps *all* the individual parcellations into a specified output directory. But I don't know if you can do it with the Destrieux atlas parcellations (if you were interested in doing that.) Laura. On Sat, Mar 23, 2013 at 2:36 AM, Anupa AV wrote: > Dear All, > > Can anyone tell me how to merge the parcellation labels using tksurfer.? > For eg. How can I merge, Superior frontal gyrus, middle frontal gyrus and > caudal middle frontal gyrus. > > ___ > 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. > > -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
Re: [Freesurfer] help with contrasts
thanks for the clarification - I'll look into using other methods for model fitting. LT On Fri, Mar 22, 2013 at 8:46 AM, MCLAREN, Donald wrote: > You'd want an F test with 2 rows. One for the F-test of var 1 and one for > the F-test of var2. A significant F-test won't tell you if your > significantly better though than the F-test of var 1 only in the model. > > However, this sounds more like a model fitting question, which would be > best addressed using AIC, BIC, etc. metrics of the overall model fit. > > Best Regards, Donald McLaren > = > D.G. McLaren, Ph.D. > Research Fellow, Department of Neurology, Massachusetts General Hospital > and > Harvard Medical School > Postdoctoral Research Fellow, GRECC, Bedford VA > Website: http://www.martinos.org/~mclaren > Office: (773) 406-2464 > = > This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED > HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is > intended only for the use of the individual or entity named above. If the > reader of the e-mail is not the intended recipient or the employee or agent > responsible for delivering it to the intended recipient, you are hereby > notified that you are in possession of confidential and privileged > information. Any unauthorized use, disclosure, copying or the taking of any > action in reliance on the contents of this information is strictly > prohibited and may be unlawful. If you have received this e-mail > unintentionally, please immediately notify the sender via telephone at > (773) > 406-2464 or email. > > > On Fri, Mar 22, 2013 at 11:38 AM, Laura M. Tully < > tully.la...@googlemail.com> wrote: > >> Thanks Donald for your help. One final question - putting the "does the >> amount of variance explained vary by group?" question aside, if I wanted to >> run a multiple regression style model within one group looking at the >> contribution of the two behavioral variables together, does it make sense >> to weight the two variables as part of the same chunk of variance e.g. 0 0 >> 0 0 .125 .125 .125 .125 .125 .125 .125 .125 (which I think will run a >> model looking at the contribution of variables 1 & 2 together regardless of >> group or gender). If so, I'm assuming I could adjust the model and run >> separate GLMs within each group, as you suggested - I just want to make >> sure I am understanding the weights correctly first... >> >> LT >> >> >> On Fri, Mar 22, 2013 at 8:23 AM, MCLAREN, Donald < >> mclaren.don...@gmail.com> wrote: >> >>> >>> On Thu, Mar 21, 2013 at 8:59 PM, Laura M. Tully < >>> tully.la...@googlemail.com> wrote: >>> >>>> oops sorry! (I also miscalculated the # of regressors - there's >>>> actually 12 (not 10 as previously noted). Here is the list of column >>>> labels: >>>> Grp1male Grp1female Grp2male Grp2female Grp1maleVar1 Grp1femaleVar1 >>>> Grp1maleVar2 Grp1femaleVar2 Grp2maleVar1 Grp2femaleVar1 Grp2maleVar2 >>>> Grp2femaleVar2 >>>> >>>> And what I think is actually an F test looking for group x var 1 >>>> interaction OR group x variable 2 interaction whilst accounting for gender. >>>> .5 .5 -.5 -.5 0 0 0 0 0 0 >>>> 0 0 0 0 0 0 .5 .5 -.5 -.5 >>>> >>> >>> The Contrast for group*var1 would be: 0 0 0 0 .5 .5 0 0 -.5 -.5 0 0 >>> The Contrast for group*var2 would be: 0 0 0 0 0 0 .5 .5 0 0 -.5 -.5 >>> >>> >>> >>>> >>>> But what I actually WANT to test is a multiple regression style model >>>> - i.e. if I put var 1 AND 2 into the model together do they explain more >>>> variance than either variable alone, AND does this vary by group (is this >>>> even a sensible contrast to make?). Which I *think* would look something >>>> like this... >>>> >>>> 0 0 0 0 .125 .125 .125 .125 .125 .125 .125 .125 >>>> >>> >>> People generally don't ask that question. The answer is when you add >>> more variables, you will explain more variance. Tests about overall model >>> fits are generally assessed with the AIC, BIC, etc. metrics. I'm not sure >>> if there is anyway in regression to say that the amount of variance >>> explained is different by group unless you run 2 separate models. If you >>> think this might be a valid question, I'd consult a statistician - which I >>> am not. >>> >>> >>>> >>>> Laura. >>>&g
Re: [Freesurfer] help with contrasts
Thanks Donald for your help. One final question - putting the "does the amount of variance explained vary by group?" question aside, if I wanted to run a multiple regression style model within one group looking at the contribution of the two behavioral variables together, does it make sense to weight the two variables as part of the same chunk of variance e.g. 0 0 0 0 .125 .125 .125 .125 .125 .125 .125 .125 (which I think will run a model looking at the contribution of variables 1 & 2 together regardless of group or gender). If so, I'm assuming I could adjust the model and run separate GLMs within each group, as you suggested - I just want to make sure I am understanding the weights correctly first... LT On Fri, Mar 22, 2013 at 8:23 AM, MCLAREN, Donald wrote: > > On Thu, Mar 21, 2013 at 8:59 PM, Laura M. Tully < > tully.la...@googlemail.com> wrote: > >> oops sorry! (I also miscalculated the # of regressors - there's actually >> 12 (not 10 as previously noted). Here is the list of column labels: >> Grp1male Grp1female Grp2male Grp2female Grp1maleVar1 Grp1femaleVar1 >> Grp1maleVar2 Grp1femaleVar2 Grp2maleVar1 Grp2femaleVar1 Grp2maleVar2 >> Grp2femaleVar2 >> >> And what I think is actually an F test looking for group x var 1 >> interaction OR group x variable 2 interaction whilst accounting for gender. >> .5 .5 -.5 -.5 0 0 0 0 0 0 >> 0 0 0 0 0 0 .5 .5 -.5 -.5 >> > > The Contrast for group*var1 would be: 0 0 0 0 .5 .5 0 0 -.5 -.5 0 0 > The Contrast for group*var2 would be: 0 0 0 0 0 0 .5 .5 0 0 -.5 -.5 > > > >> >> But what I actually WANT to test is a multiple regression style model - >> i.e. if I put var 1 AND 2 into the model together do they explain more >> variance than either variable alone, AND does this vary by group (is this >> even a sensible contrast to make?). Which I *think* would look something >> like this... >> >> 0 0 0 0 .125 .125 .125 .125 .125 .125 .125 .125 >> > > People generally don't ask that question. The answer is when you add > more variables, you will explain more variance. Tests about overall model > fits are generally assessed with the AIC, BIC, etc. metrics. I'm not sure > if there is anyway in regression to say that the amount of variance > explained is different by group unless you run 2 separate models. If you > think this might be a valid question, I'd consult a statistician - which I > am not. > > >> >> Laura. >> >> >> >> On Thu, Mar 21, 2013 at 5:51 PM, MCLAREN, Donald < >> mclaren.don...@gmail.com> wrote: >> >>> Please include the list of the column labels. >>> >>> Best Regards, Donald McLaren >>> = >>> D.G. McLaren, Ph.D. >>> Research Fellow, Department of Neurology, Massachusetts General Hospital >>> and >>> Harvard Medical School >>> Postdoctoral Research Fellow, GRECC, Bedford VA >>> Website: http://www.martinos.org/~mclaren >>> Office: (773) 406-2464 >>> = >>> This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED >>> HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is >>> intended only for the use of the individual or entity named above. If the >>> reader of the e-mail is not the intended recipient or the employee or >>> agent >>> responsible for delivering it to the intended recipient, you are hereby >>> notified that you are in possession of confidential and privileged >>> information. Any unauthorized use, disclosure, copying or the taking of >>> any >>> action in reliance on the contents of this information is strictly >>> prohibited and may be unlawful. If you have received this e-mail >>> unintentionally, please immediately notify the sender via telephone at >>> (773) >>> 406-2464 or email. >>> >>> >>> On Thu, Mar 21, 2013 at 6:43 PM, Laura M. Tully < >>> tully.la...@googlemail.com> wrote: >>> >>>> hi Experts, >>>> >>>> I'm struggling to conceptualize the appropriate contrasts for my >>>> cortical thickness analysis. I have four classes [two groups; two levels >>>> (patients,controls; male,female) and two behavioral variables. I want to >>>> see if together the two variables account significant proportion of the >>>> variance in y (thickness) and if this differs by group whilst regressing >>>> out gender. - i.e. if I enter both behavioral variables into the model does >>>> it account fo
Re: [Freesurfer] help with contrasts
oops sorry! (I also miscalculated the # of regressors - there's actually 12 (not 10 as previously noted). Here is the list of column labels: Grp1male Grp1female Grp2male Grp2female Grp1maleVar1 Grp1femaleVar1 Grp1maleVar2 Grp1femaleVar2 Grp2maleVar1 Grp2femaleVar1 Grp2maleVar2 Grp2femaleVar2 And what I think is actually an F test looking for group x var 1 interaction OR group x variable 2 interaction whilst accounting for gender. .5 .5 -.5 -.5 0 0 0 0 0 0 0 0 0 0 0 0 .5 .5 -.5 -.5 But what I actually WANT to test is a multiple regression style model - i.e. if I put var 1 AND 2 into the model together do they explain more variance than either variable alone, AND does this vary by group (is this even a sensible contrast to make?). Which I *think* would look something like this... 0 0 0 0 .125 .125 .125 .125 .125 .125 .125 .125 Laura. On Thu, Mar 21, 2013 at 5:51 PM, MCLAREN, Donald wrote: > Please include the list of the column labels. > > Best Regards, Donald McLaren > = > D.G. McLaren, Ph.D. > Research Fellow, Department of Neurology, Massachusetts General Hospital > and > Harvard Medical School > Postdoctoral Research Fellow, GRECC, Bedford VA > Website: http://www.martinos.org/~mclaren > Office: (773) 406-2464 > = > This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED > HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is > intended only for the use of the individual or entity named above. If the > reader of the e-mail is not the intended recipient or the employee or agent > responsible for delivering it to the intended recipient, you are hereby > notified that you are in possession of confidential and privileged > information. Any unauthorized use, disclosure, copying or the taking of any > action in reliance on the contents of this information is strictly > prohibited and may be unlawful. If you have received this e-mail > unintentionally, please immediately notify the sender via telephone at > (773) > 406-2464 or email. > > > On Thu, Mar 21, 2013 at 6:43 PM, Laura M. Tully < > tully.la...@googlemail.com> wrote: > >> hi Experts, >> >> I'm struggling to conceptualize the appropriate contrasts for my cortical >> thickness analysis. I have four classes [two groups; two levels >> (patients,controls; male,female) and two behavioral variables. I want to >> see if together the two variables account significant proportion of the >> variance in y (thickness) and if this differs by group whilst regressing >> out gender. - i.e. if I enter both behavioral variables into the model does >> it account for more variance than either variable on their own (after >> controlling for gender)? What I have is this: >> >> .5 .5 -.5 -.5 0 0 0 0 >> 0 0 0 0 .5 .5 -.5 -.5 >> >> Does this look right? >> >> Thanks! >> >> Laura. >> >> >> >> >> -- >> -- >> Laura M. Tully, MA >> Social Neuroscience & Psychopathology, Harvard University >> Center for the Assessment and Prevention of Prodromal States, UCLA Semel >> Institute of Neuroscience >> ltu...@mednet.ucla.edu >> ltu...@fas.harvard.edu >> 310-267-0170 >> -- >> My musings as a young clinical scientist: >> http://theclinicalbrain.blogspot.com/ >> Follow me on Twitter: @tully_laura >> >> ___ >> 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. >> >> > -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
[Freesurfer] help with contrasts
hi Experts, I'm struggling to conceptualize the appropriate contrasts for my cortical thickness analysis. I have four classes [two groups; two levels (patients,controls; male,female) and two behavioral variables. I want to see if together the two variables account significant proportion of the variance in y (thickness) and if this differs by group whilst regressing out gender. - i.e. if I enter both behavioral variables into the model does it account for more variance than either variable on their own (after controlling for gender)? What I have is this: .5 .5 -.5 -.5 0 0 0 0 0 0 0 0 .5 .5 -.5 -.5 Does this look right? Thanks! Laura. -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
Re: [Freesurfer] Stat doubts
So this instead?
y = load('contrast/cache.th13.abs.**y.ocn.dat');
X = load('Xg.dat');
beta = inv(X'*X)*X'*y;
C = load('contrast/C.dat');
rvar = MRIread('rvar.mgh');
betamat = fast_vol2mat(beta);
rvarmat = fast_vol2mat(rvar);
[betamat rvarmat] = fast_glmfit(y,X);
rhomat = fast_glm_pcc(betamat,X,C,**rvarmat);
rho = beta;
rho.vol = fast_mat2vol(rhomat,rho.**volsize);
MRIwrite(rho,'contrast/pcc.**mgh')
On Thu, Mar 21, 2013 at 3:14 PM, Douglas N Greve
wrote:
> oh, sorry, you'll need to recompute rvarmat (don't load rvar or beta)
>
> [betamat rvarmat] = fast_glmfit(y,X);
>
> Make sure you have $FREESURFER_HOME/fsfast/**toolbox in your matlab path
>
> doug
>
>
>
> On 03/21/2013 05:04 PM, Laura M. Tully wrote:
>
>> Hi Doug,
>>
>> I gave that a try but got a matrix error - below is the command line and
>> error output from matlab, can you spot what I'm doing wrong? (I'm a matlab
>> newbie I'm afraid...)
>>
>> y = load('contrast/cache.th13.abs.**y.ocn.dat');
>> X = load('Xg.dat');
>> beta = inv(X'*X)*X'*y;
>> C = load('contrast/C.dat');
>> rvar = MRIread('rvar.mgh');
>> betamat = fast_vol2mat(beta);
>> rvarmat = fast_vol2mat(rvar);
>> rhomat = fast_glm_pcc(betamat,X,C,**rvarmat);
>> rho = beta;
>> rho.vol = fast_mat2vol(rhomat,rho.**volsize);
>> MRIwrite(rho,'contrast/pcc.**mgh')
>>
>> ??? Error using ==> mtimes
>> Inner matrix dimensions must agree.
>>
>> Error in ==> fast_glm_pcc at 39
>> yhatd = Rd*(X*beta);
>>
>>
>> Thanks!
>>
>> Laura
>>
>>
>> On Thu, Mar 21, 2013 at 10:56 AM, Douglas N Greve <
>> gr...@nmr.mgh.harvard.edu
>> <mailto:gr...@nmr.mgh.harvard.**edu>>
>> wrote:
>>
>> It does it across the whole brain (on a voxel-by-voxel basis) but
>> it is specific to the contrasts that you specify. You can run the
>> same commands on the cluster averaged data (xxx.y.ocn...). To do
>> this, don't load in the beta file. Instead
>>
>> y = load('xxx.y.ocn...');
>> beta = inv(X'*X)*X'*y;
>> then proceed with the rest of the code
>>
>> doug
>>
>>
>>
>> On 03/21/2013 01:49 PM, Laura M. Tully wrote:
>>
>> I had this exact question yesterday :-) The functions
>> necessary to run it are in $FREESURFER_HOME/matlab and
>> $FREESURFER_HOME/fsfast/**toolbox
>> Just add the path to these directories in your matlab (file ->
>> setpath) and you can run the function from your matlab command
>> window
>>
>> *Doug -* I had a follow up question about using this function
>> on clusters identified in mri_glmfit-sim. Is the function as
>> written below calculating the pcc across the whole brain or is
>> it just calculating the rho using the betas specific to the
>> cluster found in mri_glmfit-sim by only taking those betas
>> from beta.mgh that are specific to the contrast and cluster
>> results in C.dat? The reason I ask is that I have a cluster
>> showing a significant relationship between thickness and a
>> continuous behavioral variable (a positive relationship as
>> denoted by a positive log10p of the Maxvertex in the cluster)
>> and I'd like to get the correlation coefficient for it but
>> when I run the PCC function I get zero so I'm wondering if
>> this is because it is calculating across the whole brain
>> rather than just within the cluster? (btw I get the same issue
>> with a similar relationship showing positive corr between
>> thickness and two behav variables).
>> Thanks,
>>
>> Laura.
>>
>>
>>
>> On Thu, Mar 21, 2013 at 10:37 AM, Gabriel Gonzalez Escamilla
>> mailto:ggon...@upo.es> <mailto:ggon...@upo.es
>>
>> <mailto:ggon...@upo.es>>> wrote:
>>
>> Thanks Doug for your quick answer,
>>
>> Sorry for so late answer.
>>
>> One question about this, is about the fast_vol2mat, is this a
>> function? if so, where can I get it?
>>
>> As the PCC is the R value, I'm guessing that I can just
>> squ
Re: [Freesurfer] Stat doubts
Hi Doug,
I gave that a try but got a matrix error - below is the command line and
error output from matlab, can you spot what I'm doing wrong? (I'm a matlab
newbie I'm afraid...)
y = load('contrast/cache.th13.abs.y.ocn.dat');
X = load('Xg.dat');
beta = inv(X'*X)*X'*y;
C = load('contrast/C.dat');
rvar = MRIread('rvar.mgh');
betamat = fast_vol2mat(beta);
rvarmat = fast_vol2mat(rvar);
rhomat = fast_glm_pcc(betamat,X,C,rvarmat);
rho = beta;
rho.vol = fast_mat2vol(rhomat,rho.volsize);
MRIwrite(rho,'contrast/pcc.mgh')
??? Error using ==> mtimes
Inner matrix dimensions must agree.
Error in ==> fast_glm_pcc at 39
yhatd = Rd*(X*beta);
Thanks!
Laura
On Thu, Mar 21, 2013 at 10:56 AM, Douglas N Greve wrote:
> It does it across the whole brain (on a voxel-by-voxel basis) but it is
> specific to the contrasts that you specify. You can run the same commands
> on the cluster averaged data (xxx.y.ocn...). To do this, don't load in the
> beta file. Instead
>
> y = load('xxx.y.ocn...');
> beta = inv(X'*X)*X'*y;
> then proceed with the rest of the code
>
> doug
>
>
>
> On 03/21/2013 01:49 PM, Laura M. Tully wrote:
>
>> I had this exact question yesterday :-) The functions necessary to run it
>> are in $FREESURFER_HOME/matlab and $FREESURFER_HOME/fsfast/**toolbox
>> Just add the path to these directories in your matlab (file -> setpath)
>> and you can run the function from your matlab command window
>>
>> *Doug -* I had a follow up question about using this function on clusters
>> identified in mri_glmfit-sim. Is the function as written below calculating
>> the pcc across the whole brain or is it just calculating the rho using the
>> betas specific to the cluster found in mri_glmfit-sim by only taking those
>> betas from beta.mgh that are specific to the contrast and cluster results
>> in C.dat? The reason I ask is that I have a cluster showing a significant
>> relationship between thickness and a continuous behavioral variable (a
>> positive relationship as denoted by a positive log10p of the Maxvertex in
>> the cluster) and I'd like to get the correlation coefficient for it but
>> when I run the PCC function I get zero so I'm wondering if this is because
>> it is calculating across the whole brain rather than just within the
>> cluster? (btw I get the same issue with a similar relationship showing
>> positive corr between thickness and two behav variables).
>> Thanks,
>>
>> Laura.
>>
>>
>>
>> On Thu, Mar 21, 2013 at 10:37 AM, Gabriel Gonzalez Escamilla <
>> ggon...@upo.es <mailto:ggon...@upo.es>> wrote:
>>
>> Thanks Doug for your quick answer,
>>
>> Sorry for so late answer.
>>
>> One question about this, is about the fast_vol2mat, is this a
>> function? if so, where can I get it?
>>
>> As the PCC is the R value, I'm guessing that I can just square at
>> it, to obtain R2.
>>
>> When you asked me to divide the beta by sqrt(rvar), is there any
>> place where I can find is this is the correct way to get the
>> standardized beta?
>>
>> Best regards,
>> Gabriel
>>
>>
>>
>> El 14/03/13, *Douglas Greve * > <mailto:gr...@nmr.mgh.harvard.**edu >>
>> escribió:
>>
>>>
>>> Hi Gabriel, I've attached a matlab routine which will compute the
>>> PCC. If you cd into the GLM dir, then
>>>
>>> X = load('Xg.dat');
>>> beta = MRIread('beta.mgh');
>>> C = load('yourcontrast/C.dat');
>>> rvar = MRIread('rvar.mgh');
>>>
>>> betamat = fast_vol2mat(beta);
>>> rvarmat = fast_vol2mat(rvar);
>>>
>>> rhomat = fast_glm_pcc(betamat,X,C,**rvarmat);
>>>
>>> rho = beta;
>>> rho.vol = fast_mat2vol(rhomat,rho.**volsize);
>>> MRIwrite(rho,'yourcontrast/**pcc.mgh')
>>>
>>> The R2 should just be the square of the PCC, right?
>>>
>>> For the standardized beta, do you just divide the beta by sqrt(rvar)?
>>>
>>> doug
>>>
>>>
>>> On 3/14/13 1:39 PM, Gabriel Gonzalez Escamilla wrote:
>>>
>>>>
>>>> Dear Freesurfers
>>>>
>>>> I'm performing regression analyses including confounding
>>>> variables, and I would like to know how to obtain the following
>>>> information:
>&
Re: [Freesurfer] y values from glmfit-sim
Thank you! On Thu, Mar 21, 2013 at 10:56 AM, Douglas N Greve wrote: > Yes, the average thickness over the cluster for each subject. > doug > > On 03/21/2013 01:54 PM, Laura M. Tully wrote: > >> Thanks - one last clarification: just to confirm - the values of >> thickness.ocn.y.dat (i.e. analyses with thickness as input) are avg >> thickness over the whole cluster for each subject? If not, how would I get >> the avg thickness value for that cluster for each subject? >> >> LT >> >> >> On Thu, Mar 21, 2013 at 10:49 AM, Douglas N Greve < >> gr...@nmr.mgh.harvard.edu >> <mailto:gr...@nmr.mgh.harvard.**edu>> >> wrote: >> >> >> On 03/21/2013 01:11 PM, Laura M. Tully wrote: >> >> yes the input is area - so to clarify, in order to get the >> average area for each subject in that cluster I would multiply >> each subject's values in the xxx.ocn.y.dat file by the number >> of vertices in the cluster (denoted as NVtxs in the cluster >> summary?) e.g. 0.761374 * 998 = 759.85mmsq? >> >> Yes, correct >> >> >> Does the same hold for the y values in a thickness analysis, >> i.e. when thickness is the input, does each value in the >> xxx.ocn.y.dat file (e.g. 2.54) represent the average thickness >> of each vertex and so I must multiply that by the number of >> vertices to get the average thickness for each subject for >> that cluster? >> >> No, you probably just want to report the average thickness, not >> the sum of the thicknesses within the cluster >> >> >> I'm using 5.1.0 - I have no idea if I have the patch for area >> and volume analyses because I run all my analyses remotely on >> the harvard imaging server (ncf) - how would I know? And what >> are the bugs in area/volume analyses in 5.1.0(how could I >> detect them)? >> >> You will need a new version of mris_preproc which you can get from >> here: >> ftp://surfer.nmr.mgh.harvard.**edu/transfer/outgoing/flat/** >> greve/mris_preproc<ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/mris_preproc> >> You can compare this version against the one you have. If they are >> different, then copy this version into $FREESURFER_HOME/bin. If >> you are using QDEC, then rerun qcache (recon-all -qcache ...). If >> you are using the command-line stream, re-run it starting at >> mris_preproc. >> >> doug >> >> >> >> LT >> >> >> >> On Thu, Mar 21, 2013 at 10:02 AM, Douglas N Greve >> > <mailto:gr...@nmr.mgh.harvard.**edu >> > >> <mailto:gr...@nmr.mgh.harvard.**edu >> <mailto:gr...@nmr.mgh.harvard.**edu >>> >> wrote: >> >> Hi Laura, I assume the input is area? Then this will >> compute the >> average area of each vertex. The area of a vertex is the >> average >> area of the triangles around it. To get total area, you can >> multiple the number that you get from xxx.ocn.y.dat by the >> number >> of vertices in the cluster. >> >> doug >> >> ps. What version of FS are you using? If not 5.2, do you >> have the >> patch to fix the area and volume analysis? >> >> >> >> On 03/21/2013 12:52 PM, Laura M. Tully wrote: >> >> hi Doug, >> A follow up question: when I look at the >> xxx.ocn.y.dat for a >> cluster where group differences in surface area have been >> identified the values are all less than 1 (e.g. >> 0.761374) even >> though the cluster size is reported as 680 mmsq. does >> the y >> value correspond to .76 mmsq average area for that >> subject in >> that cluster or does the y value in the context of surface >> area analyses represent something else? (or does it >> need to be >> multiplied by some factor?) >> >> Thanks! >> >> >> On Wed, Mar 20, 2013 at 2:39 PM, Douglas N Greve >> > <mailto:gr...@nmr.mgh.harvard.**edu > >> <mailto:gr...@nmr.mgh.harvard.**e
Re: [Freesurfer] Stat doubts
I had this exact question yesterday :-) The functions necessary to run it
are in $FREESURFER_HOME/matlab and $FREESURFER_HOME/fsfast/**toolbox
Just add the path to these directories in your matlab (file -> setpath) and
you can run the function from your matlab command window
*Doug -* I had a follow up question about using this function on clusters
identified in mri_glmfit-sim. Is the function as written below calculating
the pcc across the whole brain or is it just calculating the rho using the
betas specific to the cluster found in mri_glmfit-sim by only taking those
betas from beta.mgh that are specific to the contrast and cluster results
in C.dat? The reason I ask is that I have a cluster showing a significant
relationship between thickness and a continuous behavioral variable (a
positive relationship as denoted by a positive log10p of the Maxvertex in
the cluster) and I'd like to get the correlation coefficient for it but
when I run the PCC function I get zero so I'm wondering if this is because
it is calculating across the whole brain rather than just within the
cluster? (btw I get the same issue with a similar relationship showing
positive corr between thickness and two behav variables).
Thanks,
Laura.
On Thu, Mar 21, 2013 at 10:37 AM, Gabriel Gonzalez Escamilla wrote:
> Thanks Doug for your quick answer,
>
> Sorry for so late answer.
>
> One question about this, is about the fast_vol2mat, is this a function? if
> so, where can I get it?
>
> As the PCC is the R value, I'm guessing that I can just square at it, to
> obtain R2.
>
> When you asked me to divide the beta by sqrt(rvar), is there any place
> where I can find is this is the correct way to get the standardized beta?
>
> Best regards,
> Gabriel
>
>
>
> El 14/03/13, *Douglas Greve * escribió:
>
> Hi Gabriel, I've attached a matlab routine which will compute the PCC.
> If you cd into the GLM dir, then
>
> X = load('Xg.dat');
> beta = MRIread('beta.mgh');
> C = load('yourcontrast/C.dat');
> rvar = MRIread('rvar.mgh');
>
> betamat = fast_vol2mat(beta);
> rvarmat = fast_vol2mat(rvar);
>
> rhomat = fast_glm_pcc(betamat,X,C,rvarmat);
>
> rho = beta;
> rho.vol = fast_mat2vol(rhomat,rho.volsize);
> MRIwrite(rho,'yourcontrast/pcc.mgh')
>
> The R2 should just be the square of the PCC, right?
>
> For the standardized beta, do you just divide the beta by sqrt(rvar)?
>
> doug
>
>
> On 3/14/13 1:39 PM, Gabriel Gonzalez Escamilla wrote:
>
>
> Dear Freesurfers
>
> I'm performing regression analyses including confounding variables, and I
> would like to know how to obtain the following information:
>
> A) The squre R
>
> and
>
> B) The standarized beta coefficient of an independient variable; and the
> partial correlation with its p-values
>
>
> Many thanks in advanced,
> Gabriel
>
>
>
> ___
> Freesurfer mailing listfreesur...@nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
>
>
> --
> --
> PhD. student Gabriel González-Escamilla
> Laboratory of Functional Neuroscience
> Department of Physiology, Anatomy, and Cell Biology
> University Pablo de Olavide
> Ctra. de Utrera, Km.1
> 41013 - Seville
> - Spain -
>
> Email: ggon...@upo.es
> http://www.upo.es/neuroaging/es/
> ___
> 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.
>
>
--
--
Laura M. Tully, MA
Social Neuroscience & Psychopathology, Harvard University
Center for the Assessment and Prevention of Prodromal States, UCLA Semel
Institute of Neuroscience
ltu...@mednet.ucla.edu
ltu...@fas.harvard.edu
310-267-0170
--
My musings as a young clinical scientist:
http://theclinicalbrain.blogspot.com/
Follow me on Twitter: @tully_laura
___
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.
Re: [Freesurfer] y values from glmfit-sim
yes the input is area - so to clarify, in order to get the average area for each subject in that cluster I would multiply each subject's values in the xxx.ocn.y.dat file by the number of vertices in the cluster (denoted as NVtxs in the cluster summary?) e.g. 0.761374 * 998 = 759.85mmsq? Does the same hold for the y values in a thickness analysis, i.e. when thickness is the input, does each value in the xxx.ocn.y.dat file (e.g. 2.54) represent the average thickness of each vertex and so I must multiply that by the number of vertices to get the average thickness for each subject for that cluster? I'm using 5.1.0 - I have no idea if I have the patch for area and volume analyses because I run all my analyses remotely on the harvard imaging server (ncf) - how would I know? And what are the bugs in area/volume analyses in 5.1.0(how could I detect them)? LT On Thu, Mar 21, 2013 at 10:02 AM, Douglas N Greve wrote: > Hi Laura, I assume the input is area? Then this will compute the average > area of each vertex. The area of a vertex is the average area of the > triangles around it. To get total area, you can multiple the number that > you get from xxx.ocn.y.dat by the number of vertices in the cluster. > > doug > > ps. What version of FS are you using? If not 5.2, do you have the patch to > fix the area and volume analysis? > > > > On 03/21/2013 12:52 PM, Laura M. Tully wrote: > >> hi Doug, >> A follow up question: when I look at the xxx.ocn.y.dat for a cluster >> where group differences in surface area have been identified the values are >> all less than 1 (e.g. 0.761374) even though the cluster size is reported as >> 680 mmsq. does the y value correspond to .76 mmsq average area for that >> subject in that cluster or does the y value in the context of surface area >> analyses represent something else? (or does it need to be multiplied by >> some factor?) >> >> Thanks! >> >> >> On Wed, Mar 20, 2013 at 2:39 PM, Douglas N Greve < >> gr...@nmr.mgh.harvard.edu >> <mailto:gr...@nmr.mgh.harvard.**edu>> >> wrote: >> >> They are the input (mri_glmfit --y y.mgh) averaged over the clusters. >> They are raw input, no detrending. >> doug >> On 03/20/2013 05:16 PM, Laura M. Tully wrote: >> > Hello experts, >> > >> > could someone clarify for me what the y values in the xxx.ocn.y.dat >> > files represent following glmfit-sim? are they the residualized y >> > values of avg cortical thickness in that specific cluster after >> > regressing out the effect of any predictor variables in the glm? >> > >> > Thanks! >> > >> > Laura. >> > -- >> > -- >> > Laura M. Tully, MA >> > Social Neuroscience & Psychopathology, Harvard University >> > Center for the Assessment and Prevention of Prodromal States, UCLA >> > Semel Institute of Neuroscience >> > ltu...@mednet.ucla.edu <mailto:ltu...@mednet.ucla.edu**> >> <mailto:ltu...@mednet.ucla.edu <mailto:ltu...@mednet.ucla.edu**>> >> > ltu...@fas.harvard.edu <mailto:ltu...@fas.harvard.edu**> >> <mailto:ltu...@fas.harvard.edu <mailto:ltu...@fas.harvard.edu**>> >> > 310-267-0170 >> >> > -- >> > My musings as a young clinical scientist: >> > >> http://theclinicalbrain.**blogspot.com/<http://theclinicalbrain.blogspot.com/> >> > Follow me on Twitter: @tully_laura >> > >> > >> > __**_ >> > Freesurfer mailing list >> > Freesurfer@nmr.mgh.harvard.edu >> <mailto:freesur...@nmr.mgh.**harvard.edu >> > >> >> > >> https://mail.nmr.mgh.harvard.**edu/mailman/listinfo/**freesurfer<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> >> >> -- >> Douglas N. Greve, Ph.D. >> MGH-NMR Center >> gr...@nmr.mgh.harvard.edu >> <mailto:gr...@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> >>
Re: [Freesurfer] y values from glmfit-sim
hi Doug, A follow up question: when I look at the xxx.ocn.y.dat for a cluster where group differences in surface area have been identified the values are all less than 1 (e.g. 0.761374) even though the cluster size is reported as 680 mmsq. does the y value correspond to .76 mmsq average area for that subject in that cluster or does the y value in the context of surface area analyses represent something else? (or does it need to be multiplied by some factor?) Thanks! On Wed, Mar 20, 2013 at 2:39 PM, Douglas N Greve wrote: > They are the input (mri_glmfit --y y.mgh) averaged over the clusters. > They are raw input, no detrending. > doug > On 03/20/2013 05:16 PM, Laura M. Tully wrote: > > Hello experts, > > > > could someone clarify for me what the y values in the xxx.ocn.y.dat > > files represent following glmfit-sim? are they the residualized y > > values of avg cortical thickness in that specific cluster after > > regressing out the effect of any predictor variables in the glm? > > > > Thanks! > > > > Laura. > > -- > > -- > > Laura M. Tully, MA > > Social Neuroscience & Psychopathology, Harvard University > > Center for the Assessment and Prevention of Prodromal States, UCLA > > Semel Institute of Neuroscience > > ltu...@mednet.ucla.edu <mailto:ltu...@mednet.ucla.edu> > > ltu...@fas.harvard.edu <mailto:ltu...@fas.harvard.edu> > > 310-267-0170 > > -- > > My musings as a young clinical scientist: > > http://theclinicalbrain.blogspot.com/ > > Follow me on Twitter: @tully_laura > > > > > > ___ > > 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 > gr...@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 > 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. > > -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
[Freesurfer] y values from glmfit-sim
Hello experts, could someone clarify for me what the y values in the xxx.ocn.y.dat files represent following glmfit-sim? are they the residualized y values of avg cortical thickness in that specific cluster after regressing out the effect of any predictor variables in the glm? Thanks! Laura. -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
Re: [Freesurfer] Reposting: interpreting clusters from 2 and 3 way interactions
the mri_segstats command did not work - below is the command and output. It looks like it is searching for the .annot file in fsaverage directory. How do I tell it to use fsaverage and to look for the .annot elsewhere? cd glmdir mri_segstats --i beta.mgh --annot fsaverage lh ./SZcontrast_oneGrp_oneBehVar_4CVs/cache.th13.abs.sig.ocn.annot --avgwf lh.SZ_CPT_area_betas.dat --excludeid 0 $Id: mri_segstats.c,v 1.75.2.2 2011/04/27 22:18:58 nicks Exp $ cwd cmdline mri_segstats --i beta.mgh --annot fsaverage lh ./SZcontrast_oneGrp_oneBehVar_4CVs/cache.th13.abs.sig.ocn.annot --avgwf lh.SZ_CPT_area_betas.dat --excludeid 0 sysname Linux hostname ncfws12.rc.fas.harvard.edu machine x86_64 user ltully Constructing seg from annotation could not read annot file /ncf/snp/04/SCORE/freesurfer_analysis/fsaverage/label/lh../SZcontrast_oneGrp_oneBehVar_4CVs/cache.th13.abs.sig.ocn.annot.annot No such file or directory Thanks! LT On Wed, Mar 20, 2013 at 9:54 AM, Douglas N Greve wrote: > > On 03/20/2013 12:09 PM, Laura M. Tully wrote: > >> Sorry - meant to respond to list. >> >> Thanks for the response Doug - I have a few follow up questions I hope >> you can clarify: >> >> * is the xxx.ocn.annot file created by mri_glmfit-sim considered >> a "label" by freesurfer? >> >> It is an annotation > > >> * or does it need to be converted to a label before I can use >> mri_segstats to extract the betas from the cluster(s) in the >> xxx.ocn.annot? >> >> No > >> * I tried using the following command line to attempt to extract >> the betas from the cluster annotation file created by >> mri_glmfit-sim, but received an error: >> >> mri_segstats --i beta.mgh --annot fsaverage hemi >> contrast/xxx.ocn.annot --avgwf avgwf.dat >> >> That looks correct. Did it work? Add --excludeid 0 to keep it from > reporting on non-clusters > >> >> >> * how does one convert an xxx.ocn.annot file to a label? >> >> If needed, use mri_annotation2label > >> >> * If I have run 3 different glms looking at the relationship >> >> between thickness and 3 different behavioral variables, and >> found 1 (or more) cluster in each glm using mri_glmfit-sim can >> I create 1 annotation/label with all the clusters from the >> separate glms and then extract the betas from that one >> annotation using mri_segstats? Or do I need to treat each glm >> separately? >> >> It is probably easiest if you treat each glm separately. You can break > the annotations into separate labels, then recombine the labels into > another annotation (mris_label2annot), but it is a lot of work. > >> >> * >> >> >> * I saw on the listserv some references to matlab functions that >> >> can calculate r square and partial correlations for glms with >> more than one predictor variable (e.g pcc between thickness >> and behavioral variable 1; pcc between thickness and >> behavioral variable2; Rsq for overall model) but I could not >> find the .m scripts for the functions (MRIread >> or fast_glm_pcc?) - would these functions be appropriate and >> if so where might I find them? >> >> Yes. They are in $FREESURFER_HOME/matlab and $FREESURFER_HOME/fsfast/** > toolbox > doug > >> >> * >> >> >> Thanks in advance for your help! >> >> Laura. >> >> >> On Wed, Mar 20, 2013 at 8:29 AM, Douglas N Greve >> > <mailto:gr...@nmr.mgh.harvard.**edu>> >> wrote: >> >> >> On 03/20/2013 10:17 AM, Laura M. Tully wrote: >> > Hi, >> > >> > I wanted to re-post my questions from a couple of days ago >> below, but >> > with some more specific questions following a search through the >> > archives. >> > >> > I want to be able to extract the beta values from a cluster >> identified >> > using mc-z in a group by behavioral variable interaction so >> that I can >> > 1) plot the relationship of thickness to behavioral variable >> data by >> > group in that cluster, 2) conduct post hoc tests to examine the >> > interaction, and 3) calculate the Rsquare and partial >> correlations for >> > each variable in the glm (i.e. how much variation in >>
Re: [Freesurfer] Reposting: interpreting clusters from 2 and 3 way interactions
Sorry - meant to respond to list. Thanks for the response Doug - I have a few follow up questions I hope you can clarify: > >- is the xxx.ocn.annot file created by mri_glmfit-sim considered a >"label" by freesurfer? or does it need to be converted to a label before I >can use mri_segstats to extract the betas from the cluster(s) in the >xxx.ocn.annot? I tried using the following command line to attempt to >extract the betas from the cluster annotation file created by >mri_glmfit-sim, but received an error: > > mri_segstats --i beta.mgh --annot fsaverage hemi contrast/xxx.ocn.annot > --avgwf avgwf.dat > > >- how does one convert an xxx.ocn.annot file to a label? > > >- If I have run 3 different glms looking at the relationship between >thickness and 3 different behavioral variables, and found 1 (or more) >cluster in each glm using mri_glmfit-sim can I create 1 annotation/label >with all the clusters from the separate glms and then extract the betas >from that one annotation using mri_segstats? Or do I need to treat each glm >separately? > > >- I saw on the listserv some references to matlab functions that >can calculate r square and partial correlations for glms with more than one >predictor variable (e.g pcc between thickness and behavioral variable 1; >pcc between thickness and behavioral variable2; Rsq for overall model) but >I could not find the .m scripts for the functions (MRIread >or fast_glm_pcc?) - would these functions be appropriate and if so where >might I find them? > > Thanks in advance for your help! > > Laura. > > > On Wed, Mar 20, 2013 at 8:29 AM, Douglas N Greve < > gr...@nmr.mgh.harvard.edu> wrote: > >> >> On 03/20/2013 10:17 AM, Laura M. Tully wrote: >> > Hi, >> > >> > I wanted to re-post my questions from a couple of days ago below, but >> > with some more specific questions following a search through the >> > archives. >> > >> > I want to be able to extract the beta values from a cluster identified >> > using mc-z in a group by behavioral variable interaction so that I can >> > 1) plot the relationship of thickness to behavioral variable data by >> > group in that cluster, 2) conduct post hoc tests to examine the >> > interaction, and 3) calculate the Rsquare and partial correlations for >> > each variable in the glm (i.e. how much variation in thickness is >> > explained by my behavioral variable). >> > >> > To extract the beta values from a cluster identified by mc-z would I >> > treat the cluster like a label and use mri_segstats to extract the >> > beta weights from the cluster? Would I need to make a label of all the >> > clusters that I want to do this for first? >> You can do it label by label. Or, if the annotation created by >> mri_glmfit-sim has all the clusters you want, you can use that (also in >> mri_segstats). You can also create an annotation from individual labels >> with mris_label2annot. >> > >> > Is there a way to calculate the basic statistics for the glm and >> > extract in table form? i.e. Fs and ps for peaks of each cluster? What >> > about Rsquare, or the correlation between thickness and my behavioral >> > variable in the clusters? or would I need to compute these outside of >> > freesurfer using the extracted betas? >> You will need to do it outside of FS. What are Fs and ps? >> doug >> >> > >> > Thank you! >> > >> > Laura. >> > >> > >> > >> > >> > >> > >> > On Mon, Mar 18, 2013 at 5:05 PM, Laura M. Tully >> > mailto:tully.la...@googlemail.com>> wrote: >> > >> > Hi Freesurfer experts, >> > >> > I'm hoping you can help me understand how to interpret >> > interactions in clusters identified in whole brain analysis using >> > glmfit and glmfit-sim. Below I describe what I've done and what >> > I'd like to be able to do. Any suggestions would be most >> appreciated! >> > >> > * I have two groups (patients, controls) and a behavioral >> > variable of interest (social functioning). I am interested in >> > cortical thickness differences between groups (main effect of >> > group), whether cortical thickness relate to social >> > functioning across the group (main effect of social >> > functioning), and whether this relationship differs by group >> >
[Freesurfer] Reposting: interpreting clusters from 2 and 3 way interactions
Hi, I wanted to re-post my questions from a couple of days ago below, but with some more specific questions following a search through the archives. I want to be able to extract the beta values from a cluster identified using mc-z in a group by behavioral variable interaction so that I can 1) plot the relationship of thickness to behavioral variable data by group in that cluster, 2) conduct post hoc tests to examine the interaction, and 3) calculate the Rsquare and partial correlations for each variable in the glm (i.e. how much variation in thickness is explained by my behavioral variable). To extract the beta values from a cluster identified by mc-z would I treat the cluster like a label and use mri_segstats to extract the beta weights from the cluster? Would I need to make a label of all the clusters that I want to do this for first? Is there a way to calculate the basic statistics for the glm and extract in table form? i.e. Fs and ps for peaks of each cluster? What about Rsquare, or the correlation between thickness and my behavioral variable in the clusters? or would I need to compute these outside of freesurfer using the extracted betas? Thank you! Laura. On Mon, Mar 18, 2013 at 5:05 PM, Laura M. Tully wrote: > Hi Freesurfer experts, > > I'm hoping you can help me understand how to interpret interactions in > clusters identified in whole brain analysis using glmfit and glmfit-sim. > Below I describe what I've done and what I'd like to be able to do. Any > suggestions would be most appreciated! > > >- I have two groups (patients, controls) and a behavioral variable of >interest (social functioning). I am interested in cortical thickness >differences between groups (main effect of group), whether cortical >thickness relate to social functioning across the group (main effect of >social functioning), and whether this relationship differs by group (group >x social functioning interaction). >- I ran whole brain analysis using mri_glmfit with group and >functioning as variables of interest whilst controlling for/regressing out >gender, age, and mean thickness. i.e. 4 classes (conmale,confemale, ptmale, >ptfemale) and 3 continuous variables (age, AvgThickness, Functioning) = 16 >regressors. >- I tested the group x functioning interaction with the following >contrast - is it correct? > > 0 0 0 0 0 0 0 0 0 0 0 0 0.5 0.5 -0.5 -0.5 > >- I then ran mri_glmfit-sim to identify clusters that survive multiple >comparisons. This revealed 4 clusters (3 in LH; 1 in RH) that represent >regions showing significant group x functioning interaction. >- I visualized the clusters in tksurfer, and by loading the y.fsgd >file was able to visualize the plotted data to get a sense of the >interaction, but this is as much as I know in terms of how to examine >interactions in the cluster data.. > > My specifc questions include: > >- I understand that the values in xxx.sig.cluster.mgh overlay reflect >log10 p values, the signs of which indicate the direction of the >relationship (i.e. -3 = negative correlation between thickness & variable) >but I'm not sure how to interpret this in the context of an interaction >with group? >- I understand that the values in xxx.y.ocn.dat contain the average >thickness value for each subject in that cluster and that in a simple >between groups test this data could be used to conduct post hoc t-tests to >show the direction of the difference, but again I'm not sure how to use >this data in the context of the interaction. What do the values represent >in a group x variable interaction? > > Ideally, I'd like to extract the contrast estimates for each subject in > the group x functioning contrast and plot it in another program and > conduct pairwise comparisons (t-tests) in order to get a better > understanding of the interaction). I'm not sure how to do this - is it > possible? My thinking is that I do something similar in fMRI analysis in > spm where I can plot the contrasts in a significant cluster and then > extract both the average contrast estimates for each group and the contrast > estimates for each individual subject. > > Thanks in advance! > > Laura. > > > -- > -- > Laura M. Tully, MA > Social Neuroscience & Psychopathology, Harvard University > Center for the Assessment and Prevention of Prodromal States, UCLA Semel > Institute of Neuroscience > ltu...@mednet.ucla.edu > ltu...@fas.harvard.edu > 310-267-0170 > -- > My musings as a young clinical scientist: > http://theclinicalbrain.blogspot.com/ > Follow me on Twitter: @tully_laura > -- -- Laura M. Tully, MA Social Neuroscience & Psycho
[Freesurfer] interpreting clusters from 2 and 3 way interactions
Hi Freesurfer experts, I'm hoping you can help me understand how to interpret interactions in clusters identified in whole brain analysis using glmfit and glmfit-sim. Below I describe what I've done and what I'd like to be able to do. Any suggestions would be most appreciated! - I have two groups (patients, controls) and a behavioral variable of interest (social functioning). I am interested in cortical thickness differences between groups (main effect of group), whether cortical thickness relate to social functioning across the group (main effect of social functioning), and whether this relationship differs by group (group x social functioning interaction). - I ran whole brain analysis using mri_glmfit with group and functioning as variables of interest whilst controlling for/regressing out gender, age, and mean thickness. i.e. 4 classes (conmale,confemale, ptmale, ptfemale) and 3 continuous variables (age, AvgThickness, Functioning) = 16 regressors. - I tested the group x functioning interaction with the following contrast - is it correct? 0 0 0 0 0 0 0 0 0 0 0 0 0.5 0.5 -0.5 -0.5 - I then ran mri_glmfit-sim to identify clusters that survive multiple comparisons. This revealed 4 clusters (3 in LH; 1 in RH) that represent regions showing significant group x functioning interaction. - I visualized the clusters in tksurfer, and by loading the y.fsgd file was able to visualize the plotted data to get a sense of the interaction, but this is as much as I know in terms of how to examine interactions in the cluster data.. My specifc questions include: - I understand that the values in xxx.sig.cluster.mgh overlay reflect log10 p values, the signs of which indicate the direction of the relationship (i.e. -3 = negative correlation between thickness & variable) but I'm not sure how to interpret this in the context of an interaction with group? - I understand that the values in xxx.y.ocn.dat contain the average thickness value for each subject in that cluster and that in a simple between groups test this data could be used to conduct post hoc t-tests to show the direction of the difference, but again I'm not sure how to use this data in the context of the interaction. What do the values represent in a group x variable interaction? Ideally, I'd like to extract the contrast estimates for each subject in the group x functioning contrast and plot it in another program and conduct pairwise comparisons (t-tests) in order to get a better understanding of the interaction). I'm not sure how to do this - is it possible? My thinking is that I do something similar in fMRI analysis in spm where I can plot the contrasts in a significant cluster and then extract both the average contrast estimates for each group and the contrast estimates for each individual subject. Thanks in advance! Laura. -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
Re: [Freesurfer] running mris_preproc for each glm?
Thanks Doug. just to be clear - I'd need to run it once per surface measure correct? i.e. once for thickness analyses on each hemi, and once for area analyses on each hemi? On Fri, Mar 15, 2013 at 11:05 AM, Douglas Greve wrote: > Hi Laura, you would only need to run preproc multiple times if the > subjects changed between analyses. If it is the same subjects in the same > order, then you only need to run it once. > doug > > > > On 3/15/13 4:42 PM, Laura M. Tully wrote: > > Hi freesurfer experts, > > I'm planning to run a few different glms on surface data using glm_fit > e.g. diagnosis * age; diagnosis * age * symptoms; diagnosis * age * > somebehavioral variable etc.. > > Do I have to run mris_preproc using the specific fsgd file for each glm? > My data are already qcached, and it seems that there may be an option > (-cache--in?) that I can use on just one mris_preproc but I'm not sure if > this is correct, or what the -cache--in option does. > > Thanks! > > Laura. > > -- > -- > Laura M. Tully, MA > Social Neuroscience & Psychopathology, Harvard University > Center for the Assessment and Prevention of Prodromal States, UCLA Semel > Institute of Neuroscience > ltu...@mednet.ucla.edu > ltu...@fas.harvard.edu > 310-267-0170 > -- > Follow me on Twitter: @tully_laura > > > ___ > Freesurfer mailing > listfreesur...@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > > ___ > 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. > > -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
[Freesurfer] running mris_preproc for each glm?
Hi freesurfer experts, I'm planning to run a few different glms on surface data using glm_fit e.g. diagnosis * age; diagnosis * age * symptoms; diagnosis * age * somebehavioral variable etc.. Do I have to run mris_preproc using the specific fsgd file for each glm? My data are already qcached, and it seems that there may be an option (-cache--in?) that I can use on just one mris_preproc but I'm not sure if this is correct, or what the -cache--in option does. Thanks! Laura. -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- Follow me on Twitter: @tully_laura ___ 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.
Re: [Freesurfer] mean thickness covariate, mean area covariate, & mri_anatomical_stats for multiple subjects
Thank you Michael! LT On Mon, Mar 11, 2013 at 8:54 AM, Michael Harms wrote: > > Hi Laura, > If you're looking for another reference that has used this approach, you > could see our 2010 paper: > http://www.ncbi.nlm.nih.gov/pubmed/20118463 > > cheers, > -MH > > -- > Michael Harms, Ph.D. > --- > Conte Center for the Neuroscience of Mental Disorders > Washington University School of Medicine > Department of Psychiatry, Box 8134 > 660 South Euclid Ave. Tel: 314-747-6173 > St. Louis, MO 63110 Email: mha...@wustl.edu > > From: "Laura M. Tully" > Date: Saturday, March 9, 2013 5:58 PM > To: "Anderson M. Winkler" > Cc: free > Subject: Re: [Freesurfer] mean thickness covariate, mean area covariate, > & mri_anatomical_stats for multiple subjects > > Hi Anderson, > > Thanks, that reference is particularly helpful. > > Re: the usage of the white versus pial area question - I believe that the > default area calculation in freesurfer is the white surface area, so unless > one specifies the pial in calculations, the standard surface area output > for surface area by parcellation will be white. This suggests the use of > the global measurement of white surface area as a covariate would be an > appropriate, whereas if one was specifically using pial surface area in the > aparc calculations, it may make more sense to use the global measure of > pial surface area as a covariate, correct? As for which one to use in > analysis, I'm not sure - conceptually it might be that the pial surface > area is more sensitive to atrophy but I don't know if that is born out in > the data... > > Laura. > > > On Sat, Mar 9, 2013 at 11:49 AM, Anderson M. Winkler < > wink...@fmrib.ox.ac.uk> wrote: > >> Hi Laura, >> >> >> >>>1. Is there a paper that I could cite that recommends using mean >>>cortical thickness rather than ICV? >>> >>> >> If it helps, we used cortical thickness and area as covariate for the >> respective analysis of regional thickness and area. Brain volume, which is >> more closely related to ICV, correlates well with area, but not with >> thickness. We computed a global thickness average by weighting the >> thickness of each region by their respective areas. The paper is this: >> http://surfer.nmr.mgh.harvard.edu/ftp/articles/Winkler2010_Neuroimage.pdf >> >> >>> >>>1. Would the same logic be applied to surface area analyses? i.e. >>>would it make more sense to use mean surface area as a covariate in >>> surface >>>area analyses? If so, which mean surface area calculation should be used? >>>mri_anatomical_stats can produce both pial and white matter mean surface >>>area stats. >>> >>> >> Yes, I think so. It seems more logical to have a global measurement of >> area in the model than a measurement of brain volume. On the other hand, >> area and thickness are not correlated one to another (as shown in the paper >> above and also in Panizzon et al, 2009, in Cereb Cortex). I don't think >> there is a clear answer on which, pial or white, should be used. I'd >> probably go with the white, as I think it may be more robust to image >> quality, but I admit this is a rather weak justification and if the images >> are good, perhaps the pial could be just as good, despite the fact that it >> somewhat depends on the white for its construction. >> >> >> >>> >>>1. Is there a way to run mri_anatomical_stats on multiple subjects >>>at once and write to a tablefile (similar to asegstats2table output)? >>> >>> >> I think you can use aparcstats2table, then add up all regions in a >> spreadsheet (or even with awk/gawk). Alternatively, you can use "grep" to >> pick the WhiteSurfArea for each hemisphere from the ?h.aparc.stats file for >> each subject. >> >> Hope this helps! >> >> All the best, >> >> Anderson >> >> > > > -- > -- > Laura M. Tully, MA > Social Neuroscience & Psychopathology, Harvard University > Center for the Assessment and Prevention of Prodromal States, UCLA Semel > Institute of Neuroscience > ltu...@mednet.ucla.edu > ltu...@fas.harvard.edu > 310-267-0170 > -- > My musings as a young clinical scientist: > http://theclinicalbrain.blogspot.com/ > Follow me on Twitter: @tully_laura > ___ Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail
Re: [Freesurfer] mean thickness covariate, mean area covariate, & mri_anatomical_stats for multiple subjects
Hi Anderson, Thanks, that reference is particularly helpful. Re: the usage of the white versus pial area question - I believe that the default area calculation in freesurfer is the white surface area, so unless one specifies the pial in calculations, the standard surface area output for surface area by parcellation will be white. This suggests the use of the global measurement of white surface area as a covariate would be an appropriate, whereas if one was specifically using pial surface area in the aparc calculations, it may make more sense to use the global measure of pial surface area as a covariate, correct? As for which one to use in analysis, I'm not sure - conceptually it might be that the pial surface area is more sensitive to atrophy but I don't know if that is born out in the data... Laura. On Sat, Mar 9, 2013 at 11:49 AM, Anderson M. Winkler wrote: > Hi Laura, > > > >>1. Is there a paper that I could cite that recommends using mean >>cortical thickness rather than ICV? >> >> > If it helps, we used cortical thickness and area as covariate for the > respective analysis of regional thickness and area. Brain volume, which is > more closely related to ICV, correlates well with area, but not with > thickness. We computed a global thickness average by weighting the > thickness of each region by their respective areas. The paper is this: > http://surfer.nmr.mgh.harvard.edu/ftp/articles/Winkler2010_Neuroimage.pdf > > >> >>1. Would the same logic be applied to surface area analyses? i.e. >>would it make more sense to use mean surface area as a covariate in >> surface >>area analyses? If so, which mean surface area calculation should be used? >>mri_anatomical_stats can produce both pial and white matter mean surface >>area stats. >> >> > Yes, I think so. It seems more logical to have a global measurement of > area in the model than a measurement of brain volume. On the other hand, > area and thickness are not correlated one to another (as shown in the paper > above and also in Panizzon et al, 2009, in Cereb Cortex). I don't think > there is a clear answer on which, pial or white, should be used. I'd > probably go with the white, as I think it may be more robust to image > quality, but I admit this is a rather weak justification and if the images > are good, perhaps the pial could be just as good, despite the fact that it > somewhat depends on the white for its construction. > > > >> >>1. Is there a way to run mri_anatomical_stats on multiple subjects at >>once and write to a tablefile (similar to asegstats2table output)? >> >> > I think you can use aparcstats2table, then add up all regions in a > spreadsheet (or even with awk/gawk). Alternatively, you can use "grep" to > pick the WhiteSurfArea for each hemisphere from the ?h.aparc.stats file for > each subject. > > Hope this helps! > > All the best, > > Anderson > > -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
[Freesurfer] mean thickness covariate, mean area covariate, & mri_anatomical_stats for multiple subjects
Hello freesurfers, It appears that prior discussions on the listserv have recommended using mean cortical thickness (rather than ICV) as a covariate for thickness analyses (predominantly recommended by Michael Harms). I have three questions about this: 1. Is there a paper that I could cite that recommends using mean cortical thickness rather than ICV? 2. Would the same logic be applied to surface area analyses? i.e. would it make more sense to use mean surface area as a covariate in surface area analyses? If so, which mean surface area calculation should be used? mri_anatomical_stats can produce both pial and white matter mean surface area stats. 3. Is there a way to run mri_anatomical_stats on multiple subjects at once and write to a tablefile (similar to asegstats2table output)? Thanks! Laura. -- -- Laura M. Tully, MA Social Neuroscience & Psychopathology, Harvard University Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience ltu...@mednet.ucla.edu ltu...@fas.harvard.edu 310-267-0170 -- Follow me on Twitter: @tully_laura ___ 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.
Re: [Freesurfer] qdec table
Thanks Doug - Nick, do you have any idea what might be happening here? Why might qdec stop allowing me to select more than one continuous variable? Thanks! Laura. Message: 24 Date: Mon, 04 Jun 2012 11:19:57 -0400 From: Douglas N Greve Subject: Re: [Freesurfer] qdec table file To: freesurfer@nmr.mgh.harvard.edu Message-ID: <4fccd21d.4040...@nmr.mgh.harvard.edu> Content-Type: text/plain; charset=ISO-8859-1; format=flowed OK, I've replicated that this is happening, but Nick will have to take a look. doug On 06/04/2012 11:05 AM, Laura M. Tully wrote: > > > > Hi Doug, > > Attached is the qdec table file and associated levels files. It's > strange that qdec won't let me select more than one continuous > variable. What's even more strange is that I have been able to do that > last month when I originally looked at these data before doing manual > edits and quality control. I don't think that I have changed anything > since then, but I'm not sure what to look for. Any help you have would > be most appreciated! > > Best, > > Laura. -- Laura Tully Social Neuroscience & Psychopathology Harvard University 840 William James Hall 33 Kirkland St Cambridge, MA 02138 ltu...@fas.harvard.edu -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
[Freesurfer] qdec table file
Hi Doug, Attached is the qdec table file and associated levels files. It's strange that qdec won't let me select more than one continuous variable. What's even more strange is that I have been able to do that last month when I originally looked at these data before doing manual edits and quality control. I don't think that I have changed anything since then, but I'm not sure what to look for. Any help you have would be most appreciated! Best, Laura. -- Laura Tully Social Neuroscience & Psychopathology Harvard University 840 William James Hall 33 Kirkland St Cambridge, MA 02138 ltu...@fas.harvard.edu -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura -- Laura Tully Social Neuroscience & Psychopathology Harvard University 840 William James Hall 33 Kirkland St Cambridge, MA 02138 ltu...@fas.harvard.edu -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura betweenGroup.qdec.table.dat Description: Binary data Gender.levels Description: Binary data Group.levels Description: Binary data ___ 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.
[Freesurfer] qdec: selecting multiple continuous variables
Hi, I am using freesurfer 5.1.0 and qdec 1.4. I'm interested in looking at between group differences in thickness in relation to two other continuous measures whilst controlling for ICV. However, qdec doesn't seem to let me select more that one continuous variable even though I only have group selected (discrete) and ICV (nuisance) as additional variables (i.e. a total of three selected) - it's my understanding that qdec allows up to 4 variables, is there a method to selecting multiple continuous variables that I am missing (e.g. hold down shift and select)? Thanks! Laura. -- Laura Tully Social Neuroscience & Psychopathology Harvard University 840 William James Hall 33 Kirkland St Cambridge, MA 02138 ltu...@fas.harvard.edu -- My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/ Follow me on Twitter: @tully_laura ___ 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.
