It should be 10^-abs(sig)
On 02/06/2015 12:53 AM, Bronwyn Overs wrote: > Hi Doug, > > Thanks for all of your help. I am investigating the differences > between the design matrices now. > > I have one more query about the sig.table.dat file put out by the GLM > using the parcellated ROIs. When I transform each of the values in > this file to p values using 10^"value", some of the resulting p-value > are >1. Do you know why this would be happening? Here is an example of > one of my sig.table.dat files, where 10^.799 = 6.295: > > lh.aparc.thickness me_gender_ageRem me_group_ageRem > lh_bankssts_thickness 0.107 -2.752 > lh_caudalanteriorcingulate_thickness -2.616 -0.190 > lh_caudalmiddlefrontal_thickness -0.701 -4.258 > lh_cuneus_thickness 0.799 -1.178 > lh_entorhinal_thickness 1.669 -4.129 > lh_fusiform_thickness -0.088 -6.808 > lh_inferiorparietal_thickness -0.665 -1.477 > lh_inferiortemporal_thickness 0.149 -7.985 > lh_isthmuscingulate_thickness -0.476 -2.393 > lh_lateraloccipital_thickness 0.212 -1.189 > lh_lateralorbitofrontal_thickness 0.288 -7.657 > lh_lingual_thickness 1.148 -1.594 > lh_medialorbitofrontal_thickness 1.405 -4.461 > lh_middletemporal_thickness 0.727 -7.215 > lh_parahippocampal_thickness -1.059 -2.854 > lh_paracentral_thickness -0.514 -0.282 > lh_parsopercularis_thickness 0.444 -3.541 > lh_parsorbitalis_thickness -0.110 -7.075 > lh_parstriangularis_thickness 0.244 -4.769 > lh_pericalcarine_thickness 0.376 -0.218 > lh_postcentral_thickness -0.485 -0.832 > lh_posteriorcingulate_thickness -0.135 -1.241 > lh_precentral_thickness 0.196 -2.102 > lh_precuneus_thickness 0.018 -1.361 > lh_rostralanteriorcingulate_thickness -1.208 -2.073 > lh_rostralmiddlefrontal_thickness 0.437 -4.470 > lh_superiorfrontal_thickness -0.141 -2.743 > lh_superiorparietal_thickness -0.288 -0.365 > lh_superiortemporal_thickness 0.227 -4.646 > lh_supramarginal_thickness -1.185 -1.354 > lh_frontalpole_thickness -0.325 -0.521 > lh_temporalpole_thickness -0.067 -4.074 > lh_transversetemporal_thickness -0.009 -1.618 > lh_insula_thickness 0.553 -6.063 > > Kind regards, > > Bronwyn Overs > Research Assistant > > Neuroscience Research Australia > > Neuroscience Research Australia > Margarete Ainsworth Building > Barker Street Randwick Sydney NSW 2031 Australia > *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 > > neura.edu.au <http://neura.edu.au> > > Follow @neuraustralia on twitter > <https://twitter.com/neuraustralia>Follow NeuRA on facebook > <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to > the NeuRA Magazine <http://www.neura.edu.au/help-research/subscribe> > > On 5/02/2015 10:46 am, Douglas N Greve wrote: >> How sure are you that you are using the exact same model? Can you output >> the design matrix from SPSS? Can you input the FS design matrix into >> SPSS? Are you sure you are using the exact same input data? >> >> On 02/04/2015 06:32 PM, Bronwyn Overs wrote: >>> Ahh right. I have just understood which part of the output I needed to >>> look at. However, for the ROI GLM there are only 1-2 regions that were >>> significantly different between groups, while the SPSS ANCOVA showed >>> significant group differences for the majority of parcellated regions. >>> I have confirmed that I am using the exact same model for each, so it >>> is only the analysis method that differs. Do you know why these two >>> methods would produce such disparate results? >>> >>> >>> Kind regards, >>> >>> Bronwyn Overs >>> Research Assistant >>> >>> Neuroscience Research Australia >>> >>> Neuroscience Research Australia >>> Margarete Ainsworth Building >>> Barker Street Randwick Sydney NSW 2031 Australia >>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>> >>> neura.edu.au<http://neura.edu.au> >>> >>> Follow @neuraustralia on twitter >>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to >>> the NeuRA Magazine<http://www.neura.edu.au/help-research/subscribe> >>> >>> On 5/02/2015 3:16 am, Douglas N Greve wrote: >>>> I'm not sure that I understand what I'm looking at. If it is an ROI >>>> analysis, then there is no surface, it should be about 40 numbers, one >>>> for each ROI. >>>> >>>> On 02/03/2015 06:26 PM, Bronwyn Overs wrote: >>>>> Hi Doug, >>>>> >>>>> Thanks for your correction. >>>>> >>>>> I have now completed the FDR for my case-control comparisons, and it >>>>> appears that none of the regions survived. This is again quite >>>>> confusing given the large number of parcellated regions that survived >>>>> FDR in the SPSS ANCOVA. Can you confirm that this screenshot of the >>>>> sig.mgh file from ROI analysis looks as you would expect (it looks >>>>> very strange to me): >>>>> >>>>> >>>>> >>>>> Kind regards, >>>>> >>>>> Bronwyn Overs >>>>> Research Assistant >>>>> >>>>> Neuroscience Research Australia >>>>> >>>>> Neuroscience Research Australia >>>>> Margarete Ainsworth Building >>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>> >>>>> neura.edu.au<http://neura.edu.au> >>>>> >>>>> Follow @neuraustralia on twitter >>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to >>>>> the NeuRA Magazine<http://www.neura.edu.au/help-research/subscribe> >>>>> >>>>> On 4/02/2015 9:35 am, Douglas Greve wrote: >>>>>> Yes, it should be .^ >>>>>> >>>>>> On 2/3/15 5:33 PM, Bronwyn Overs wrote: >>>>>>> Hi Doug, >>>>>>> >>>>>>> I am having a problem with the line in Matlab 2014b: >>>>>>> p = 10^-abs(sigmat); >>>>>>> I keep getting the following error: >>>>>>> Error using ^ >>>>>>> Inputs must be a scalar and a square matrix. >>>>>>> To compute elementwise POWER, use POWER (.^) >>>>>>> instead. >>>>>>> >>>>>>> Do you know why this would be? >>>>>>> >>>>>>> Kind regards, >>>>>>> >>>>>>> Bronwyn Overs >>>>>>> Research Assistant >>>>>>> >>>>>>> Neuroscience Research Australia >>>>>>> >>>>>>> Neuroscience Research Australia >>>>>>> Margarete Ainsworth Building >>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>> >>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>> >>>>>>> Follow @neuraustralia on twitter >>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to >>>>>>> the NeuRA Magazine<http://www.neura.edu.au/help-research/subscribe> >>>>>>> >>>>>>> On 4/02/2015 2:22 am, Douglas Greve wrote: >>>>>>>> There is not a way to do it from the command line. You can do it in >>>>>>>> matlab, something like >>>>>>>> >>>>>>>> sig = MRIread('sig.mgh'); >>>>>>>> sigmat = fast_vol2mat(sig); >>>>>>>> p = 10^-abs(sigmat); >>>>>>>> fdr = .05; >>>>>>>> pthresh = fast_fdrthresh(p,fdr); >>>>>>>> ind = find(p < pthresh); % This will be a list of ROI indices that >>>>>>>> survive FDR >>>>>>>> >>>>>>>> doug >>>>>>>> >>>>>>>> On 2/2/15 10:26 PM, Bronwyn Overs wrote: >>>>>>>>> Hi Doug, >>>>>>>>> >>>>>>>>> That makes perfect sense. Just one more thing then, how do you >>>>>>>>> conduct an FDR via the command line for an ROI mri_glmfit analysis? >>>>>>>>> >>>>>>>>> Kind regards, >>>>>>>>> >>>>>>>>> Bronwyn Overs >>>>>>>>> Research Assistant >>>>>>>>> >>>>>>>>> Neuroscience Research Australia >>>>>>>>> >>>>>>>>> Neuroscience Research Australia >>>>>>>>> Margarete Ainsworth Building >>>>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>>>> >>>>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>>>> >>>>>>>>> Follow @neuraustralia on twitter >>>>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe >>>>>>>>> to the NeuRA Magazine >>>>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>>>> >>>>>>>>> On 3/02/2015 2:00 pm, Douglas Greve wrote: >>>>>>>>>> This is not something you would run the MC sim on because there >>>>>>>>>> is no clustering, it is just a list of ROIs with their p-values. >>>>>>>>>> The p-values are uncorrected. You can do bonferoni correction >>>>>>>>>> across all the ROIs (or just the ones you are interested in). You >>>>>>>>>> could do FDR too. >>>>>>>>>> >>>>>>>>>> doug >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On 2/2/15 9:39 PM, Bronwyn Overs wrote: >>>>>>>>>>> Thanks Doug, that worked well. >>>>>>>>>>> >>>>>>>>>>> However, is it possible to run a monte-carlo simulation with >>>>>>>>>>> this GLM ROI analysis? I attempted to run it using the following >>>>>>>>>>> command... >>>>>>>>>>> mri_glmfit-sim --glmdir >>>>>>>>>>> DesikanROIAnal_case-control.thick.lh.glmdir --cache 1.3 abs >>>>>>>>>>> --cwpvalthresh 0.05 --2spaces >>>>>>>>>>> and received the following error: >>>>>>>>>>> ERROR: could not determine file for >>>>>>>>>>> DesikanROIAnal_case-control.thick.lh.glmdir/mask >>>>>>>>>>> >>>>>>>>>>> Kind regards, >>>>>>>>>>> >>>>>>>>>>> Bronwyn Overs >>>>>>>>>>> Research Assistant >>>>>>>>>>> >>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>> >>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>> Margarete Ainsworth Building >>>>>>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>>>>>> >>>>>>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>>>>>> >>>>>>>>>>> Follow @neuraustralia on twitter >>>>>>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to >>>>>>>>>>> the NeuRA Magazine >>>>>>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>>>>>> >>>>>>>>>>> On 3/02/2015 11:03 am, Douglas Greve wrote: >>>>>>>>>>>> Even easier. Run aparcstats2table, then run mri_glmfit passing >>>>>>>>>>>> the output of aparcstats2table with --table (instead of --y). >>>>>>>>>>>> There's something on the wiki about it, also look for the ROI >>>>>>>>>>>> tutorial. >>>>>>>>>>>> doug >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On 2/2/15 6:20 PM, Bronwyn Overs wrote: >>>>>>>>>>>>> Hi Doug, >>>>>>>>>>>>> >>>>>>>>>>>>> I am not sure how to run an ROI analysis using mri_glmfit. Is >>>>>>>>>>>>> there a wiki page detailing this method (I was unable to find >>>>>>>>>>>>> one)? Is the first step to map lh.aparc.label and >>>>>>>>>>>>> rh.aparc.label from fsaverage to each of my individual >>>>>>>>>>>>> subjects using mri_label2label? When I do so and then view the >>>>>>>>>>>>> mapped label for an individual subject in freeview, it appears >>>>>>>>>>>>> to be a continuous label for all of the parcellated regions >>>>>>>>>>>>> combined. Is this correct? >>>>>>>>>>>>> >>>>>>>>>>>>> Kind regards, >>>>>>>>>>>>> >>>>>>>>>>>>> Bronwyn Overs >>>>>>>>>>>>> Research Assistant >>>>>>>>>>>>> >>>>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>>>> >>>>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>>>> Margarete Ainsworth Building >>>>>>>>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>>>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>>>>>>>> >>>>>>>>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>>>>>>>> >>>>>>>>>>>>> Follow @neuraustralia on twitter >>>>>>>>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>>>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe >>>>>>>>>>>>> to the NeuRA Magazine >>>>>>>>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>>>>>>>> >>>>>>>>>>>>> On 3/02/2015 3:31 am, Douglas Greve wrote: >>>>>>>>>>>>>> First, I would run the ROI analysis in mri_glmfit to see if >>>>>>>>>>>>>> you get the same results as in SPSS. In the handfull of these >>>>>>>>>>>>>> cases, no one has been able to correctly replicate the FS >>>>>>>>>>>>>> design matrix in SPSS, so I suspect that is part of the >>>>>>>>>>>>>> discrepancy. The other thing is that ROI and vertex-wise >>>>>>>>>>>>>> analyses are simply different. As an extreme example, if some >>>>>>>>>>>>>> of the vertices are pos and some are neg then they would >>>>>>>>>>>>>> cancel out when you average them in an ROI but individually >>>>>>>>>>>>>> could be significant at the vertex level. If you analyze the >>>>>>>>>>>>>> average over the cluster then that should come out as >>>>>>>>>>>>>> significant. >>>>>>>>>>>>>> >>>>>>>>>>>>>> doug >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> On 2/1/15 11:36 PM, Bronwyn Overs wrote: >>>>>>>>>>>>>>> Dear FreeSurfer Mailing List, >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> I have a sample of schizophrenia and control subjects for >>>>>>>>>>>>>>> whom I have run a case-control analysis of cortical >>>>>>>>>>>>>>> thickness using two separate methods (GLM vertex-wise >>>>>>>>>>>>>>> analysis in freesurfer, repeated measures ANCOVA analysis of >>>>>>>>>>>>>>> parcellated data in SPSS). However, for each methods of >>>>>>>>>>>>>>> analysis I am getting extremely different results. For the >>>>>>>>>>>>>>> GLM in Freesurfer I have only 1 small cluster in the frontal >>>>>>>>>>>>>>> lobe that differs between cases and controls (controlling >>>>>>>>>>>>>>> for all other IVs, FWMH = 10mm, cluster-forming threshold= >>>>>>>>>>>>>>> .05, cluster-wise pval=.05), while for the ANCOVA method all >>>>>>>>>>>>>>> but 8 of the parcellated regions differ significantly >>>>>>>>>>>>>>> between groups (p<.05). For both methods I have used the >>>>>>>>>>>>>>> same model of predictors (independent variables = gender, >>>>>>>>>>>>>>> group, scanning site; covariate = age) and exactly the same >>>>>>>>>>>>>>> sample of participants. I have also replicated the GLM >>>>>>>>>>>>>>> analysis using the QDEC GUI to ensure that I had no made any >>>>>>>>>>>>>>> mistakes. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Can you provide any insight into why I would be seeing such >>>>>>>>>>>>>>> different results for each method using the same data set? >>>>>>>>>>>>>>> My findings using the ANCOVA analysis make much more sense >>>>>>>>>>>>>>> to me, given previous findings of reduced cortical thickness >>>>>>>>>>>>>>> in schizophrenia subjects. I was surprised not to find the >>>>>>>>>>>>>>> same pattern of effects using the GLM analysis. >>>>>>>>>>>>>>> -- >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Kind regards, >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Bronwyn Overs >>>>>>>>>>>>>>> Research Assistant >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>>>>>> Margarete Ainsworth Building >>>>>>>>>>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>>>>>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Follow @neuraustralia on twitter >>>>>>>>>>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>>>>>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe >>>>>>>>>>>>>>> to the NeuRA Magazine >>>>>>>>>>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>> Freesurfer mailing list >>>>>>>>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>>>>>>>> https://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. >>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>> Freesurfer mailing list >>>>>>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>>>>>> https://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. >>>>>>>>>>> _______________________________________________ >>>>>>>>>>> Freesurfer mailing list >>>>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>>>> https://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. >>>>>>>>> _______________________________________________ >>>>>>>>> Freesurfer mailing list >>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>> https://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. >>>>>>> _______________________________________________ >>>>>>> Freesurfer mailing list >>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>> https://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. >>>>> _______________________________________________ >>>>> Freesurfer mailing list >>>>> Freesurfer@nmr.mgh.harvard.edu >>>>> https://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 > > > > _______________________________________________ > 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: https://gate.nmr.mgh.harvard.edu/filedrop2 www.nmr.mgh.harvard.edu/facility/filedrop/index.html Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
