Related Experiment Video
Updated: Feb 4, 2026

Acquisition of Resting-State Functional Magnetic Resonance Imaging Data in the Rat
Published on: August 28, 2021
Quantifying and Visualizing Intraregional Connectivity in Resting-State Functional Magnetic Resonance Imaging with
Alexander Petersen1, Chun-Jui Chen2, Hans-Georg Müller2
11 Department of Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara, California.
Abstract:
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.
Related Concept Videos
Magnetic Resonance Imaging
Imaging Studies IV: Magnetic Resonance Imaging
Functions of Connective Tissues
Hard connective tissues, such as bones and cartilage, provide structure and support to the body.
Atomic Nuclei: Magnetic Resonance
Correlations
Nuclear Magnetic Resonance (NMR): Overview
NMR spectroscopy generates a spectrum where the characteristic absorption frequencies of the sample are...

