2) Did you subtract the row mean from each row? Peace,
Matt. From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>> Date: Wednesday, July 13, 2016 at 9:56 AM To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>> Cc: Stephen Smith <st...@fmrib.ox.ac.uk<mailto:st...@fmrib.ox.ac.uk>>, "Dierker, Donna" <do...@wustl.edu<mailto:do...@wustl.edu>>, hcp-users <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state data - 2400 data points instead of 1200 ? Hi Matthew, thank you for the help! I did the following: 1. I used the "clean" datasets now and extracted my ROI data from the LR and RL phase encodings (first two sessions) 2. I calculated the mean across time for every ROI and substracted it, i.e. I have a 1200 by 112 matrix and calculated the row mean (over time) and substracted it from each column (ROIs). 3. I did this for LR and RL seperately and then concatenated them together Can you confirm that this is the correct? thanks again! David 2016-07-13 0:55 GMT+02:00 Glasser, Matthew <glass...@wustl.edu<mailto:glass...@wustl.edu>>: I would recommend using the data with _hp2000_clean in the name. I a referring to taking the mean across time at each point in space and subtracting that from the data. Peace, Matt. From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>> Date: Tuesday, July 12, 2016 at 6:56 AM To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>> Cc: Stephen Smith <st...@fmrib.ox.ac.uk<mailto:st...@fmrib.ox.ac.uk>>, "Dierker, Donna" <do...@wustl.edu<mailto:do...@wustl.edu>>, hcp-users <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state data - 2400 data points instead of 1200 ? Hi all, Regarding Stephen's answer: I thought it is necessary to concatenate the LR/RL phase encoding directions together somehow or can I just treat every run seperately? What I basically want is the timecourse from a voxel or a region (from preprocessed data) which I can use for further analysis. Regarding Matthew's answer: I'm afraid I'm not exactly sure what you mean by cleaning or removing the mean image from the data. Mean centering? I used the preprocessed datasets: subjectcode_3T_rfMRI_REST1_preproc.zip \MNINonLinear\Results\rfMRI_REST1_LR \MNINonLinear\Results\rfMRI_REST1_RL Is this the correct data or is it necessary to use some different datasets for my specific purposes? (Normally I'd use the netmats datasets, but in I'm especially interested in the amygdala which I'm trying to extract from the Harvard-Oxford Atlas ROI). Thanks for your answers! David 2016-07-12 12:47 GMT+02:00 Glasser, Matthew <glass...@wustl.edu<mailto:glass...@wustl.edu>>: Also it appears you haven’t either cleaned or removed the mean image from the data. Matt. From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Stephen Smith <st...@fmrib.ox.ac.uk<mailto:st...@fmrib.ox.ac.uk>> Date: Tuesday, July 12, 2016 at 3:48 AM To: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>> Cc: "Dierker, Donna" <do...@wustl.edu<mailto:do...@wustl.edu>>, hcp-users <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state data - 2400 data points instead of 1200 ? Hi - no we do not (in general for resting-state) ever recommend temporal contatenation like this before further analyses - for the reason you're seeing here. For example, for the HCP released netmats, we take the 4 runs, one at a time, estimate the 4 (zstat) netmats, and average those. Cheers. On 12 Jul 2016, at 09:43, David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>> wrote: Hi Michael, thanks for the reply, using a different routine works and shows 1200 volumes. But now it seems that in some data (extracted ROI mean) there is a huge difference between LR and RL phase encoding in the signal (see attached picture). Is this "normal" and can I just concatenate LR and RL together or is this not possible? greetings David 2016-07-11 19:43 GMT+02:00 Harms, Michael <mha...@wustl.edu<mailto:mha...@wustl.edu>>: Hi, Can you check the number of volumes/frames of the unpacked REST1_{LR,RL}.nii.gz files using something other than your Matlab/SPM tools? e.g., FSL’s ‘fslhd’ or ‘fslnvols’ commands. 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<tel:314-747-6173> St. Louis, MO 63110 Email: mha...@wustl.edu<mailto:mha...@wustl.edu> From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>> Date: Monday, July 11, 2016 at 3:15 AM To: "Dierker, Donna" <do...@wustl.edu<mailto:do...@wustl.edu>> Cc: hcp-users <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state data - 2400 data points instead of 1200 ? Hi Donna and others, thanks for your answer. I'm facing a difficulty with extracting data from the preprocessed files, that is they seems to each contain 2400 data points rather than 1200 like described in the documentation. I downloaded the 10 subjects data set and used the following files: subjectcode_3T_rfMRI_REST1_preproc.zip, from which I assume that these are the preprocessed files. It contains two datasets LR and RL: \MNINonLinear\Results\rfMRI_REST1_LR \MNINonLinear\Results\rfMRI_REST1_RL I unpacked these files: rfMRI_REST1_LR.nii.gz rfMRI_REST1_RL.nii.gz and read them as 4D NIFTI with Matlab and an SPM function. Afterwards they each contain 2400 data points (dimension: 91 109 91 2400), but in the documention it says they each should contain only 1200 data points. So I'm not sure if I did something wrong. greetings David 2016-06-30 18:30 GMT+02:00 Dierker, Donna <do...@wustl.edu<mailto:do...@wustl.edu>>: Hi David, I hope this publication answers your questions about HCP rfMRI preprocessing: Resting-state fMRI in the Human Connectome Project. Smith SM1, Beckmann CF, Andersson J, Auerbach EJ, Bijsterbosch J, Douaud G, Duff E, Feinberg DA, Griffanti L, Harms MP, Kelly M, Laumann T, Miller KL, Moeller S, Petersen S, Power J, Salimi-Khorshidi G, Snyder AZ, Vu AT, Woolrich MW, Xu J, Yacoub E, Uğurbil K, Van Essen DC, Glasser MF; WU-Minn HCP Consortium. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720828/ I am only used to seeing what it is in the fix extended packages, so I'm not sure all these volumes are in the basic fix packages, but here are NIFTI volumes in a sample subject's rfMRI subdirectories: 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000_clean.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000.ica/filtered_func_data.ica/mask.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000_clean.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000.ica/filtered_func_data.ica/mask.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000_clean.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000.ica/filtered_func_data.ica/mask.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000_clean.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000.ica/filtered_func_data.ica/mask.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL.nii.gz Maybe this page will help explain those: http://fsl.fmrib.ox.ac.uk/fslcourse/lectures/practicals/rfMRIconnectivity/ But keep in mind that for neocortex, you can take advantage of the surface data the HCP provides (e.g., fsaverage_32k/*surf.gii, *dscalar.nii and *dtseries.nii). You can get better inter-subject registration/alignment on the surface, if that will be a factor in your study. Donna On Jun 28, 2016, at 6:30 PM, David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>> wrote: > Hi all, > > I would like to extract ROI data (only neocortex) 'manually' e.g. using a ROI > from Harvard-Oxford atlas from HCP resting state data, but I'm not sure which > (nifti) files to use and where to find them. I'm also looking for some > information about the preprocessing steps applied to the resting state data > that is, if some additional steps (e.g. filtering) have to be carried out > before ROI extraction or if this has already been done. > > Any help on this appreciated! > > Thanks > > David > _______________________________________________ > HCP-Users mailing list > HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> http://lists.humanconnectome.org/mailman/listinfo/hcp-users ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> http://lists.humanconnectome.org/mailman/listinfo/hcp-users <timecourse.png> --------------------------------------------------------------------------- Stephen M. Smith, Professor of Biomedical Engineering Head of Analysis, Oxford University FMRIB Centre FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK +44 (0) 1865 222726<tel:%2B44%20%280%29%201865%20222726> (fax 222717) st...@fmrib.ox.ac.uk<mailto:st...@fmrib.ox.ac.uk> http://www.fmrib.ox.ac.uk/~steve --------------------------------------------------------------------------- Stop the cultural destruction of Tibet<http://smithinks.net> _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> http://lists.humanconnectome.org/mailman/listinfo/hcp-users ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
