The Effect of Aging on Resting State Connectivity of Predefined Networks in the Brain

• Published in: Frontiers in aging neuroscience Vol. 11; p. 234
• Main Authors: Varangis, Eleanna, Habeck, Christian G., Razlighi, Qolamreza R., Stern, Yaakov
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 04.09.2019; Frontiers Media S.A
• Subjects: Adults; Aging; Brain; cognition; Cognition & reasoning; Cognitive ability; fMRI; functional connectivity; graph theory; Life span; Memory; Middle age; Neural networks; Neuroscience; Older people; fMRI; functional connectivity; aging; cognition; graph theory
• ISSN: 1663-4365; 1663-4365
• DOI: 10.3389/fnagi.2019.00234

Recent studies have found a deleterious effect of age on a wide variety of measures of functional connectivity, and some hints at a relationship between connectivity at rest and cognitive functioning. However, few studies have combined multiple functional connectivity methods, or examined them over a wide range of adult ages, to try to uncover which metrics and networks seem to be particularly sensitive to age-related decline across the adult lifespan. The present study utilized multiple resting state functional connectivity methods in a sample of adults from 20-80 years old to gain a more complete understanding of the effect of aging on network function and integrity. Whole-brain results showed that aging results in weakening average within-network connectivity, lower system segregation and local efficiency, and higher participation coefficient. Network-level results suggested that nearly every primary sensory and cognitive network faces some degree of age-related decline, including reduced within-network connectivity, higher network-based participation coefficient, and reduced network-level local efficiency. Further, some of these connectivity metrics showed relationships with cognitive performance. Thus, these results suggest that a multi-method analysis of functional connectivity data may be critical to capture the full effect of aging on the health of brain networks.