A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age

• Published in: Frontiers in neuroscience Vol. 15; p. 768418
• Main Authors: Li, Xia, Fischer, Håkan, Manzouri, Amirhossein, Månsson, Kristoffer N. T., Li, Tie-Qiang
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 20.10.2021; Frontiers Media S.A
• Subjects: adult age; Age; Aging; Brain; Brain mapping; Computer simulation; connectivity density index (CDI); connectivity strength index (CSI); Cortex (cingulate); Frontal gyrus; Functional magnetic resonance imaging; Magnetic resonance imaging; Neural networks; Neuroimaging; Neuroscience; Physiology; Psychology; psykologi; quantitative data-driven analysis (QDA); Regions; resting-state functional connectivity (RFC); resting-state functional magnetic resonance imaging (R-fMRI); Sensorimotor system

The objective of this study is to introduce a new quantitative data-driven analysis (QDA) framework for the analysis of resting-state fMRI (R-fMRI) and use it to investigate the effect of adult age on resting-state functional connectivity (RFC). Whole-brain R-fMRI measurements were conducted on a 3T...