A NOVEL METHOD FOR VISUALIZING FUNCTIONAL CONNECTIVITY USING PRINCIPAL COMPONENT ANALYSIS

Abstract

Functional connectivity is a useful measure of voxel-wise functional magnetic resonance imaging signals that allows for the identification of functionally related brain areas and distributed networks. However, the high dimensionality of functional connectivity makes it difficult to visualize. In most studies, a small percentage of the total functional connectivity is visualized through diagrams that are constructed using individual seed voxels. In the present study describes a new method for visualizing most of the functional connectivity through a single diagram. This method does not rely on seed voxels, but rather employs a reduction of the high-dimensionality of the functional connectivity via a projection onto a three-dimensional color space using principal components analysis. With this new method, most of the information contained in a functional connectivity matrix can be represented through a single color-coded functional connectivity map, thereby facilitating a greater visual appreciation of functional connectivity.

keywords:

• fMRI
• functional connectivity
• principal component analysis
• subspace
• visualization
• whole-brain