Visual Analysis of Integrated Resting State Functional Brain Connectivity and Anatomy

Abstract

Resting state functional magnetic resonance imaging (rs-fMRI) is an important modality in the study of the functional architecture of the human brain. The correlation between the resting state fMRI activity traces of different brain regions indicates to what extent they are functionally connected. rs-fMRI data typically consists of a matrix of correlations, also denoted as functional correlations, between regions in the brain. Visualization is required for a good understanding of the data. Several well-known representations have been used to visualize this type of data, including multi-dimensional scaling, spring embedding, scatter plots and network visualization. None of these methods provide the ability to show the functional correlation in relation to the anatomical distance and position of the regions, while preserving the ability to quickly identify outliers in the data. In this paper, a visual analysis application is presented that overcomes this limitation by combining the strengths of the two-dimensional representations with three dimensional network and iso-surfacing visualizations. We show how the application facilitates rs-fMRI connectivity research by means of a case study evaluation.