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Activity and connectivity differences underlying inhibitory control across the adult life span

Tsvetanov, Kamen A., Ye, Zheng, Hughes, Laura, Samu, David, Treder, Matthias ORCID: https://orcid.org/0000-0001-5955-2326, Wolpe, Noham, Tyler, Lorraine K. and Rowe, James B. 2018. Activity and connectivity differences underlying inhibitory control across the adult life span. Journal of Neuroscience 38 (36) , pp. 7887-7900. 10.1523/JNEUROSCI.2919-17.2018

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Abstract

Inhibitory control requires precise regulation of activity and connectivity within multiple brain networks. Previous studies have typically evaluated age-related changes in regional activity or changes in interregional interactions. Instead, we test the hypothesis that activity and connectivity make distinct, complementary contributions to performance across the life span and the maintenance of successful inhibitory control systems. A representative sample of healthy human adults in a large, population-based life span cohort performed an integrated Stop-Signal (SS)/No-Go task during functional magnetic resonance imaging (n = 119; age range, 18–88 years). Individual differences in inhibitory control were measured in terms of the SS reaction time (SSRT), using the blocked integration method. Linear models and independent components analysis revealed that individual differences in SSRT correlated with both activity and connectivity in a distributed inhibition network, comprising prefrontal, premotor, and motor regions. Importantly, this pattern was moderated by age, such that the association between inhibitory control and connectivity, but not activity, differed with age. Multivariate statistics and out-of-sample validation tests of multifactorial functional organization identified differential roles of activity and connectivity in determining an individual's SSRT across the life span. We propose that age-related differences in adaptive cognitive control are best characterized by the joint consideration of multifocal activity and connectivity within distributed brain networks. These insights may facilitate the development of new strategies to support cognitive ability in old age.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
ISSN: 0270-6474
Date of First Compliant Deposit: 10 October 2018
Date of Acceptance: 18 June 2018
Last Modified: 17 May 2023 02:26
URI: https://orca.cardiff.ac.uk/id/eprint/115680

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