Literature DB >> 30312808

The age-dependent relationship between resting heart rate variability and functional brain connectivity.

D Kumral1, H L Schaare2, F Beyer3, J Reinelt4, M Uhlig2, F Liem4, L Lampe4, A Babayan4, A Reiter5, M Erbey6, J Roebbig4, M Loeffler7, M L Schroeter8, D Husser9, A V Witte4, A Villringer10, M Gaebler11.   

Abstract

Resting heart rate variability (HRV), an index of parasympathetic cardioregulation and an individual trait marker related to mental and physical health, decreases with age. Previous studies have associated resting HRV with structural and functional properties of the brain - mainly in cortical midline and limbic structures. We hypothesized that aging affects the relationship between resting HRV and brain structure and function. In 388 healthy subjects of three age groups (140 younger: 26.0 ± 4.2 years, 119 middle-aged: 46.3 ± 6.2 years, 129 older: 66.9 ± 4.7 years), gray matter volume (GMV, voxel-based morphometry) and resting state functional connectivity (eigenvector centrality mapping and exploratory seed-based functional connectivity) were related to resting HRV, measured as the root mean square of successive differences (RMSSD). Confirming previous findings, resting HRV decreased with age. For HRV-related GMV, there were no statistically significant differences between the age groups, nor similarities across all age groups. In whole-brain functional connectivity analyses, we found an age-dependent association between resting HRV and eigenvector centrality in the bilateral ventromedial prefrontal cortex (vmPFC), driven by the younger adults. Across all age groups, HRV was positively correlated with network centrality in the bilateral posterior cingulate cortex. Seed-based functional connectivity analysis using the vmPFC cluster revealed an HRV-related cortico-cerebellar network in younger but not in middle-aged or older adults. Our results indicate that the decrease of HRV with age is accompanied by changes in functional connectivity along the cortical midline. This extends our knowledge of brain-body interactions and their changes over the lifespan.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aging; Brain structure; Default mode network; Eigenvector centrality mapping; Heart rate variability; Voxel-based morphometry

Mesh:

Year:  2018        PMID: 30312808     DOI: 10.1016/j.neuroimage.2018.10.027

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  11 in total

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