Re: [HCP-Users] Replicating "Resting-state fMRI in the Human Connectome Project"

FSLNets takes subjects x space x time. If what you want is the group average dense connectome (space x space), then a pre-computed version of that is available for download at db.humanconnectome.org. Note that it is 33 GB. If you just want to visualize the dense connectome, you can do that

Re: [HCP-Users] Replicating "Resting-state fMRI in the Human Connectome Project"

ICA+FIX precedes FSLNets and the appropriate data is distributed by the HCP. Peace, Matt. From: "Harms, Michael" > Date: Saturday, May 13, 2017 at 8:08 AM To: Sang-Yun Oh >, Matt Glasser

[HCP-Users] Datasets which have 7T?

Hello, I read that out of the 1200 subjects, 184 have 7T data also. I tried searching for more information on these 184 but couldn't find any regarding this. Is there any way to know the files numbers of these 184 subjects rather than manually searching each of them? Thank you. Regards, Shruti

Re: [HCP-Users] Multimodal parcellation atlas labels

We do not recommend making a group volume parcellation from the HCP MMP v1.0, please read this thread: https://www.mail-archive.com/hcp-users@humanconnectome.org/msg03078.html In short, volume registration aligns only structure, while the HCP MMP is a parcellation based on functional areas.

Re: [HCP-Users] Replicating "Resting-state fMRI in the Human Connectome Project"

Steve Smith would have generated that matrix. I would have been after running ICA+FIX, which would remove linear trends, 24 movement regressors and ICA noise component timeseries. The matrix would have been made with FSLNets. Peace, Matt. From:

[HCP-Users] Replicating "Resting-state fMRI in the Human Connectome Project"

Dear HCP users, I am new to this area and I would like to do a replication exercise to learn more about HCP dataset and neuroscience tools. What would be the simplest way to get my hands on matrix G (Figure 2) in this paper? https://doi.org/10.1016/j.neuroimage.2013.05.039 I would imagine G is

[HCP-Users] Error for gradient nonlinearity correction on Siemens Prisma data

Dear all: I’m running HCP pipeline script on our Siemens Prisma data. I would like to see whether gradient nonlinearity on Siemens Prisma scanner would cause visible error on segmentation result. I got the gradient coefficient file from the scanner. If I set the variable of

Re: [HCP-Users] Replicating "Resting-state fMRI in the Human Connectome Project"

No, ICA+FIX is data cleanup that is applied to the minimally preprocessed (MPP) data. I suggest you start here https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLNets and in particular the file “nets_examples.m” cheers, -MH -- Michael Harms, Ph.D.