Quantifying and Visualizing Intraregional Connectivity in Resting-State Functional Magnetic Resonance Imaging with Correlation Densities

• Published in: Brain connectivity Vol. 9; no. 1; pp. 37 - 47
• Main Authors: Petersen, Alexander, Chen, Chun-Jui, Müller, Hans-Georg
• Format: Journal Article
• Language: English
• Published: United States Mary Ann Liebert, Inc 01.02.2019
• Subjects: Alzheimer's disease; Brain mapping; Brain research; Cognition; Cognitive ability; Functional magnetic resonance imaging; Memory; Methods; Neural networks; Neuroimaging; NMR; Nuclear magnetic resonance; Semantics; Studies; Substantia grisea; United States > US; Santa Barbara California; California; density functions; functional linear model; functional connectivity; correlation; cognitive performance; transformation
• ISSN: 2158-0014; 2158-0022; 2158-0022
• DOI: 10.1089/brain.2018.0591

The use of correlation densities is introduced to quantify and provide visual interpretation for intraregional functional connectivity in the brain. For each brain region, pairwise correlations are computed between a seed voxel and other gray matter voxels within the region, and the distribution of the ensemble of these correlation values is represented as a probability density, the correlation density. The correlation density can be estimated by kernel smoothing. It provides an intuitive and comprehensive representation of subject-specific functional connectivity strength at the local level for each region. To address the challenge of interpreting and utilizing this rich connectivity information when multiple regions are considered, methods from functional data analysis are implemented, including a recently developed method of dimensionality reduction specifically tailored to the analysis of probability distributions. To illustrate the utility of these methods in neuroimaging, experiments were carried out to identify the associations between local functional connectivity and a battery of neurocognitive scores. These experiments demonstrate that correlation densities facilitate the discovery and interpretation of specific region-score associations.