First of all, again - thank you very much for your help. The support is really great.
Sorry for the ambiguity with the term “network” – let me try to be more specific in what I try to do. I meant a classic graph with a set of nodes and edges, where the nodes represent voxels (or other very fine brain regions) and the edges represent the connections between voxels. As I currently have the opportunity to analyze very large graphs, I would like to use a graph which is derived from brain imaging. Therefore I hoped that I could use the dense connectome files from your HC project to generate/extract my nodes and edges. Are there some steps you could recommend to get from the dense connectome files to a classic graph representation? And do you also offer tools to generate anatomical graphs of dMRI images? And when I use –cifti-correlation on the dtseries files, should I first combine the LR and RL dtseries files with some averaging functions or would I also get a “correct” output by just using one of them? Many thanks again for your help, Jürgen From: Timothy Coalson [mailto:[email protected]] Sent: Friday, June 06, 2014 6:41 PM To: Ommen, Jurgen Cc: [email protected] Subject: Re: [HCP-Users] Brain Connectivity Matrices First, a slight correction to my previous reply: the command is -cifti-correlation, but you seem to have figured that out. The HCP data is in Cifti files, and contain combined surface (for cortex) and voxel (for subcortical structures and cerebellum) data. The surfaces used have roughly equivalent spacing to the voxels used, so in some sense it is at the voxel "scale". However, two thirds of the data is not in voxels, but in surface vertices. Yes, it is a complete connectivity matrix, hence the large size. Connectome Workbench (http://www.humanconnectome.org/software/connectome-workbench.html) is the main tool we use with cifti files, you can visualize the data with the GUI, or do various operations on it (including extracting the data into other formats) with wb_command. Matt Glasser has written some matlab functions that use wb_command -cifti-convert and the matlab gifti toolbox to get the data into matlab, but I don't think we currently have a good way to do spatial operations on it in matlab. I don't know what you mean by "network", and might not be able to help you with it if I did, but others on the list might. Tim On Fri, Jun 6, 2014 at 12:33 PM, Ommen, Jurgen <[email protected]<mailto:[email protected]>> wrote: Hi Tim, Great, thanks for your fast answer. Generating the dense connectome files works good. However, I’m not quite sure about the content of the dense connectome files. As far as I understood it, it is the complete connectivity matrix on a voxel-based scale. Is this right? This would be exactly what I need. My question now would be: Which steps or tools are usually used to extract the information stored in the dense connectome files for further post-processing? It would be really great if you could just outline the steps roughly and the tools I could use to get the network. Is there maybe a Matlab library available which is able to read .dconn.nii files? Thanks again for your help, Jürgen From: Timothy Coalson [mailto:[email protected]<mailto:[email protected]>] Sent: Wednesday, June 04, 2014 7:42 PM To: Ommen, Jurgen Cc: [email protected]<mailto:[email protected]> Subject: Re: [HCP-Users] Brain Connectivity Matrices I believe we don't include those in the releases, because dense connectome files are very large (~30GB each). You should be able to generate them by running wb_command -cifti-correlate on a subject's rfMRI dtseries file. Tim On Tue, Jun 3, 2014 at 5:55 PM, Ommen, Jurgen <[email protected]<mailto:[email protected]>> wrote: Hello everyone, I’m working on graph theoretic analysis of the human’s brain network. After studying the documentation of the Q3 release, I’ve only found group average dense connectome files so far. I’d like to know if there are any connectivity matrices available for individual subjects with which I could generate the corresponding connectome networks. Do you provide this kind of data? Where could I find it? And if not, do you plan to include it in future releases? Thanks for your help in advance and my best regards, Jürgen _______________________________________________ HCP-Users mailing list [email protected]<mailto:[email protected]> http://lists.humanconnectome.org/mailman/listinfo/hcp-users _______________________________________________ HCP-Users mailing list [email protected] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
