Abstract
Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, “bi-modal comparison plots” show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using “worm plots”. Group differences in connections are examined with an existing visualization, the “connectogram”. These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the “Statistical Analysis of Minimum cost path based Structural Connectivity” method and the average fractional anisotropy along the fiber. The functional measures were Pearson’s correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.
Highlights
Brain connectivity is an area of research receiving increasing attention
In the Rotterdam Scan Study (RSS) study, group differences are visible in the mean network histograms of DMC, which is reflected in the t-statistic distributions
This study presents a framework for comparison of regions of interest (ROIs)-based functional and structural connectivity to identify group differences
Summary
Brain connectivity is an area of research receiving increasing attention. Regions communicate through networks of structural and functional links, which is termed connectivity. Connectivity can be studied non-invasively using advanced imaging techniques such as magnetic resonance imaging (MRI). Relationships between regions of interest (ROIs) are extracted from MRI’s and used to define a network. Variations in MRI acquisition and analysis have resulted in several types of connectivity. With ever increasing choices, comparing connectivity types becomes an important first step in addressing a given research question
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