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This code processes data from the 1000 Functional Connectomes Project

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Octocat-spinner-32 centrality
Octocat-spinner-32 corr_mat
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Octocat-spinner-32 README.md
README.md

This code was all written by Xi-Nian Zuo , Ph.D. for the analysis of the 1000 Functional Connectome Project data, while in the lab of Michael Milham, M.D., Ph.D. The code relies on some parcellations developed by others, including the Neuro Bureau. Note that the raw data is available for download from the 1000FCP NITRIC downloads page, and the processed data is available for download as well.

Mission

The purpose of this code is to take NIFTI files of whole brains and estimate functional connectivity. The main functions are called 'IPN_doSingleSubject_regionCENT_X.m' where X indicates which of four possible parcellation schemes were used: (i) aal, (ii) cameron, (iii) dosenbach2010, or (iv) hoa25. Each of the main functions behaves as follows:

Input:

  • filename: name of NIFTI file to be processed
  • maskname: name of mask to use to exclude non-brain
  • template: which of the 4 templates will be used
  • outfprefix: name of the output files
  • threshold: threshold for binarizing each correlation matrix

Output:

no array's are output to the workspace, but several data derivatives are saved, including:

  • ts: N-by-T matrix containing the time-series of each region
  • rsfc: N-by-N matrix of correlations across regions, as well some transformed versions
  • cent: the thresholds for binarizing the adjacency matrices computed in a variety of possible ways

Data Derivatives

All the data downloads are freely available from the OCP 1000 Functional Connectome page (here is the link directly to the data derivates)

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