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Proceedings Paper

RV-coefficient and its significance test in mapping brain functional connectivity
Author(s): Hui Zhang; Jie Tian; Jun Li; Jizheng Zhao
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Paper Abstract

The statistic of RV-coefficient is a good substitute for the Pearson correlation coefficient to measure the temporal similarity of two local brain regions. However, the hypothesis test of RV-coefficient is a hard problem which limits its application. This paper discussed the problem in details. Since the distribution of RV-coefficient is unknown, we do not know a critical p-value to statistically test its significance. We proposed a new strategy to test the significance of RV calculated from fMRI. In order to approximate the p-value, we elicited the first two moments of the population permutation distribution of RV; we then derived a formula to more closely approximate the normal distribution with these transformed statistics. These transformations of statistics are suggested for a precise approximation to the permutational p-value even under large number of observations. This strategy of test can greatly reduce the computational complexity and avoid "calculation catastrophe", we then use the statistic of RV to extract the map of functional connectivity from fMRI and test its significance with the strategy proposed here.

Paper Details

Date Published: 27 February 2009
PDF: 9 pages
Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 726222 (27 February 2009); doi: 10.1117/12.811369
Show Author Affiliations
Hui Zhang, Institute of Automation (China)
Jie Tian, Institute of Automation (China)
Xidian Univ. (China)
Jun Li, Xidian Univ. (China)
Jizheng Zhao, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 7262:
Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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