I’m not sure what you are looking for, beyond what is in the FAQ. For a given voxel/grayordinate/parcel, if M = mean_over_time S = std_over_time
and X(t) is your time-series then demeaning is just: X(t) - M and variance normalization is: (X(t) - M)/S 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: hercp <he...@uw.edu> Date: Thursday, October 5, 2017 at 3:39 PM To: "Harms, Michael" <mha...@wustl.edu> Subject: Re: [HCP-Users] Mean and variance normalization Hi Michael, Thanks for the input. Are you aware of any utility that does the demeaning, variance normalization and concatenation. Jenn Elam suggested FAQ #3 on the HCP-Users FAQ. Would this be also your preference. Is there a reference or mathematical definitions for these functions (other than the obvious ones), so I can do a mathematical comparison between the two approaches? Heracles Panagiotides, PhD From: Harms, Michael Sent: Thursday, October 05, 2017 12:13 PM To: Glasser, Matthew ; hercp ; HUMAN CONNECTOME Subject: Re: [HCP-Users] Mean and variance normalization Re (2) (expanding on Matt’s response): Demeaning and variance normalizing a parcellated timeseries (or equivalently the time series for a single ROI), and then concatenating those, is not the same as demeaning and variance normalizing the dense time series, concatenating those, and then parcellating. That’s not to say that the former isn’t sensible, but it *is* a different operation. If it was me, before I adopted the former, I’d run some analyses both ways, and compare the results to see if there are any appreciable differences. 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: <hcp-users-boun...@humanconnectome.org> on behalf of "Glasser, Matthew" <glass...@wustl.edu> Date: Thursday, October 5, 2017 at 1:19 PM To: hercp <he...@uw.edu>, HUMAN CONNECTOME <hcp-users@humanconnectome.org> Subject: Re: [HCP-Users] Mean and variance normalization 1. Yes 2. I haven’t tried it on parcellated timeseries, but suspect that would be fine too. Matt. From: <hcp-users-boun...@humanconnectome.org> on behalf of hercp <he...@uw.edu> Date: Thursday, October 5, 2017 at 2:12 PM To: HUMAN CONNECTOME <hcp-users@humanconnectome.org> Subject: [HCP-Users] Mean and variance normalization I am extracting time series from regions of interest. Matt Glasser suggested that I mean/variance-correct and concatenate the RL and LR phase encoded time series. I still have a couple of questions. 1. Is the concatenation over time? If so, doesn’t this introduce temporal discontinuity? Am I understanding the concatenation correctly? 2. Would the outcome be equivalent whether I do the preprocessing to the original rfMRI file OR to the ROI extracted time series and why? Thank you in advance for any suggestions you may offer. Heracles Panagiotides, PhD Heracles Panagiotides, PhD From: Elam, Jennifer Sent: Wednesday, October 04, 2017 2:50 PM To: hercp Subject: Re: [HCP-Users] Fw: rfMRI data files Hi Heracles, From what I've heard from others who have more experience, I would do the preprocessing and concatenating prior to extracting the ROI vector. The big caveat is that I don't actually do any processing, etc. myself as my expertise is in a different field. So, if you want to be sure you should ask your question on the list and get a real expert answer there. Cheers, Jenn Jennifer Elam, Ph.D. Scientific Outreach, Human Connectome Project Washington University School of Medicine Department of Neuroscience, Box 8108 660 South Euclid Avenue St. Louis, MO 63110 314-362-9387<tel:314-362-9387> e...@wustl.edu www.humanconnectome.org<http://www.humanconnectome.org/> ________________________________ From: hercp <he...@uw.edu> Sent: Wednesday, October 4, 2017 4:12:39 PM To: Elam, Jennifer Subject: Re: [HCP-Users] Fw: rfMRI data files Hi Jenn, Thank you so much the reply and pointing at FAQ #3. I am wondering if we are talking about the same thing when referring to “time series”. Perhaps, if I tell you what I have done so far, my question will be more clear: I have defined a ROI and extracted a time series from the original data file; the time series is a single vector corresponding to the mean lever of activity of that ROI . So, do I apply the mean and variance normalization to this vector and then concatenate the vectors, or do I do all this (preprocessing and concatenating) prior to extracting the ROI vector time series. (As a side note, I can do all this vector preprocessing in Matlab.) Would these two approaches be equivalent? Thank you very much for being so helpful, Heracles Panagiotides, PhD From: Elam, Jennifer Sent: Wednesday, October 04, 2017 1:30 PM To: hercp ; HUMAN CONNECTOME Subject: Re: [HCP-Users] Fw: rfMRI data files Hi Heracles, FAQ #3 on the HCP-Users FAQ<https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ> might help you do what Matt is suggesting. Best, Jenn Jennifer Elam, Ph.D. Scientific Outreach, Human Connectome Project Washington University School of Medicine Department of Neuroscience, Box 8108 660 South Euclid Avenue St. Louis, MO 63110 314-362-9387<tel:314-362-9387> e...@wustl.edu www.humanconnectome.org<http://www.humanconnectome.org/> ________________________________ From: hcp-users-boun...@humanconnectome.org <hcp-users-boun...@humanconnectome.org> on behalf of hercp <he...@uw.edu> Sent: Wednesday, October 4, 2017 1:32:38 PM To: HUMAN CONNECTOME Subject: [HCP-Users] Fw: rfMRI data files Does anyone know how the concatenation (see discussion below) of the ROI extracted time series needs to happen? Do I simply concatenate the time series as a temporal sequence, rfMRI_REST2_LR followed by rfMRI_REST2_RL ? Thanks again for the kind help. Heracles Panagiotides, PhD From: hercp Sent: Tuesday, October 03, 2017 5:15 AM To: Glasser, Matthew Subject: Re: [HCP-Users] rfMRI data files Thanks for the kind reply, Matt. Let me make sure that I understand the process. I should extract the time series from regions of interest from each phase encoded file. Then I should concatenate the time series demeaning and variance normalizing? Am I way off? Sorry about the naïve questions, but I am a couple of decades behind in MR work. [ile] Thanks, Heracles Panagiotides, PhD From: Glasser, Matthew Sent: Monday, October 02, 2017 5:11 PM To: hercp ; HUMAN CONNECTOME Subject: Re: [HCP-Users] rfMRI data files Yes you ideally would analyze all of the resting state fMRI runs per subject. They have different phase encoding directions, so you should always analyze an equal amount of each. Be sure to demean and perhaps variance normalize prior to concatenating. Peace. Matt. From: <hcp-users-boun...@humanconnectome.org> on behalf of hercp <he...@uw.edu> Date: Tuesday, October 3, 2017 at 9:09 AM To: HUMAN CONNECTOME <hcp-users@humanconnectome.org> Subject: [HCP-Users] rfMRI data files Pardon my ignorance, but could someone give me a brief explanation of the difference between the rfMRI_REST2_LR and rfMRI_REST2_RL rfMRI data. Should I be using both of them? 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