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Updated: May 29, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Microvascular structure variability explains variance in fMRI functional connectivity
François Gaudreault1,2, Michèle Desjardins3,4
1Département de physique, de génie physique et d'optique, Université Laval, 2325 Rue de l'Université, Quebec, QC, G1V 0A6, Canada.
Abstract:
The influence of regional brain vasculature on resting-state fMRI BOLD signals is well documented. However, the role of brain vasculature is often overlooked in functional connectivity research. In the present report, utilizing publicly available whole-brain vasculature data in the mouse, we investigate the relationship between functional connectivity and brain vasculature. This is done by assessing interregional variations in vasculature through a novel metric termed vascular similarity. First, we identify features to describe the regional vasculature. Then, we employ multiple linear regression models to predict functional connectivity, incorporating vascular similarity alongside metrics from structural connectivity and spatial topology. Our findings reveal a significant correlation between functional connectivity strength and regional vasculature similarity, especially in anesthetized mice. We also show that multiple linear regression models of functional connectivity using standard predictors are improved by including vascular similarity. We perform this analysis at the cerebrum and whole-brain levels using data from both male and female mice. Our findings regarding the relation between functional connectivity and the underlying vascular anatomy may enhance our understanding of functional connectivity based on fMRI and provide insights into its disruption in neurological disorders.

