Age-Related Changes in Resting-State Networks of A Large Sample Size of Healthy Elderly

Chun Chao Huang, Wen Jin Hsieh, Pei Lin Lee, Li Ning Peng, Li Kuo Liu, Wei Ju Lee, Jon Kway Huang, Liang Kung Chen*, Ching Po Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

82 Scopus citations

Abstract

Aims: Population aging is burdening the society globally, and the evaluation of functional networks is the key toward understanding cognitive changes in normal aging. However, the effect of age on default mode subnetworks has not been documented well, and age-related changes in many resting-state networks remain debatable. The purpose of this study was to propose more precise results for these issues using a large sample size. Methods: We used group-level meta-ICA analysis and dual regression approach for identifying resting-state networks from functional magnetic resonance imaging data of 430 healthy elderly participants. Partial correlation was used to observe age-related correlations within and between resting-state networks. Results: In the default mode network, only the ventral subnetwork negatively correlated with age. Age-related decrease in functional connectivity was also noted in the auditory, right frontoparietal, sensorimotor, and visual medial networks. Further, some age-related increases and decreases were observed for between-network correlations. Conclusion: The results of this study suggest that only the ventral default mode subnetwork had age-related decline in functional connectivity and several reverse patterns of resting-state networks for network development. Understanding age-related network changes may provide solutions for the impact of population aging and diagnosis of neurodegenerative diseases.

Original languageEnglish
Pages (from-to)817-825
Number of pages9
JournalCNS Neuroscience and Therapeutics
Volume21
Issue number10
DOIs
StatePublished - 1 Oct 2015

Keywords

  • Aging
  • Default mode subnetwork
  • Resting-state network

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