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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Aging Neurosci. | doi: 10.3389/fnagi.2019.00234

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

  • 1Columbia University, United States

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.

Keywords: Aging, Cognition, functional connectivity, Resting state – fMRI, graph theory

Received: 13 May 2019; Accepted: 14 Aug 2019.

Edited by:

Samba Reddy, Texas A&M Health Science Center, United States

Reviewed by:

Tarek Rajji, Centre for Addiction and Mental Health (CAMH), Canada
Laura Serra, Fondazione Santa Lucia (IRCCS), Italy  

Copyright: © 2019 Varangis, Habeck, Razlighi and Stern. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: PhD. Yaakov Stern, Columbia University, New York City, United States,