版本 1.0.1 (2.0 KB) 作者: Elliot Layden
Enables fast computation of the intrinsic connectivity contrast (ICC), a measure of degree centrality for weighted networks, on large data.

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更新时间 2018/7/18


The intrinsic connectivity contrast (ICC) is a measure of degree centrality for weighted networks. The ICC for a given voxel i is the average of the squared correlation values of the voxel i time series with that of every other voxel (i.e., ICC = mean(r.^2)). This function enables rapid computation of the ICC on extremely large resting-state fMRI datasets, including cases in which explict calculation of the full correlation matrix is prohibitive, whether due to RAM or computation time limitations.

*Intrinsic Connectivity Contrast References:

Martuzzi, R., Ramani, R., Qiu, M., Shen, X., Papademetris, X., & Constable, R. T. (2011). A whole-brain voxel based measure of intrinsic connectivity contrast reveals local changes in tissue connectivity with anesthetic without a priori assumptions on thresholds or regions of interest. Neuroimage, 58(4), 1044-1050.

Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2012). Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain connectivity, 2(3), 125-141.

Note: for implementation details, see Whitfield-Gabrieli & Nieto-Castanon (2012) Appendix A.2: Computing Voxel-Wise Linear Functional Connectivity Measures Singular Value Decomposition


Elliot Layden (2023). intrinsic_connectivity_contrast (, MATLAB Central File Exchange. 检索来源 .

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