Sensorimotor network segregation declines with age and is linked to GABA and to sensorimotor performance.


Journal

NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515

Informations de publication

Date de publication:
01 02 2019
Historique:
received: 04 07 2018
revised: 03 11 2018
accepted: 07 11 2018
pubmed: 12 11 2018
medline: 16 7 2019
entrez: 12 11 2018
Statut: ppublish

Résumé

Aging is typically associated with declines in sensorimotor performance. Previous studies have linked some age-related behavioral declines to reductions in network segregation. For example, compared to young adults, older adults typically exhibit weaker functional connectivity within the same functional network but stronger functional connectivity between different networks. Based on previous animal studies, we hypothesized that such reductions of network segregation are linked to age-related reductions in the brain's major inhibitory transmitter, gamma aminobutyric acid (GABA). To investigate this hypothesis, we conducted graph theoretical analyses of resting state functional MRI data to measure sensorimotor network segregation in both young and old adults. We also used magnetic resonance spectroscopy to measure GABA levels in the sensorimotor cortex and collected a battery of sensorimotor behavioral measures. We report four main findings. First, relative to young adults, old adults exhibit both less segregated sensorimotor brain networks and reduced sensorimotor GABA levels. Second, less segregated networks are associated with lower GABA levels. Third, less segregated networks and lower GABA levels are associated with worse sensorimotor performance. Fourth, network segregation mediates the relationship between GABA and performance. These findings link age-related differences in network segregation to age-related differences in GABA levels and sensorimotor performance. More broadly, they suggest a neurochemical substrate of age-related dedifferentiation at the level of large-scale brain networks.

Identifiants

pubmed: 30414983
pii: S1053-8119(18)32078-0
doi: 10.1016/j.neuroimage.2018.11.008
pmc: PMC6338503
mid: NIHMS997139
pii:
doi:

Substances chimiques

gamma-Aminobutyric Acid 56-12-2

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

234-244

Subventions

Organisme : NIA NIH HHS
ID : R01 AG050523
Pays : United States
Organisme : NIA NIH HHS
ID : RF1 AG006265
Pays : United States

Informations de copyright

Copyright © 2018. Published by Elsevier Inc.

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Auteurs

Kaitlin Cassady (K)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA.

Holly Gagnon (H)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA.

Poortata Lalwani (P)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA.

Molly Simmonite (M)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA.

Bradley Foerster (B)

Department of Radiology, University of Michigan, Ann Arbor, MI, USA.

Denise Park (D)

Research of the Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA.

Scott J Peltier (SJ)

Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.

Myria Petrou (M)

Department of Radiology, University of Michigan, Ann Arbor, MI, USA.

Stephan F Taylor (SF)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA; Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.

Daniel H Weissman (DH)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA.

Rachael D Seidler (RD)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA; School of Kinesiology, University of Michigan, Ann Arbor, MI, USA; Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, USA.

Thad A Polk (TA)

Department of Psychology, University of Michigan, Ann Arbor, MI, USA. Electronic address: tpolk@umich.edu.

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