An Improved RV Based Fuzzy Cluster Analysis (IRVFCA) Method for Task-Related Functional MRI Data Analysis

Abstract:

Functional magnetic resonance imaging (fMRI) has become one of the important tools of functional connectivity studies of the human brain. Fuzzy clustering method (FCM) is a common method for analysis of FMRI data. Traditional FCA methods measure the similarity between the BOLD time course of a centroid and the ones of all other voxels in the brain on the basis of Pearson correlation coefficient. This article puts forward a multi-voxel-based similarity measure, an improved RV (IRV) measure, which takes the hypothesis into account that the function homogeneous voxels of brain volume are spatially clustered within a local region. Experimental validation is presented through four visual fMRI data sets which shows that the IRVFCA method not only has improved the speed of FCA, but has comparatively raised the accuracy of the method.

• Periodical: Applied Mechanics and Materials (Volumes 427-429)
• Pages: 1570-1573
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.427-429.1570
• Online since: September 2013
• Authors: Han Wang*, Wei Ming Zeng
• Keywords: FCA, fMRI, Improved Rv, Pearson Coefficient, Rv Coefficient

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