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Author Notes:

Yuhui Du, duyugui@sxu.edu.cn

YD applied for the application of the use of the UK Biobank data, designed the whole analysis framework, and proposed the original NeuroMark method. YD and YG performed the analyses and wrote the original draft. All authors contributed to the article and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Subjects:

Research Funding:

This work was supported by National Natural Science Foundation of China (Grant nos. 62076157 and 61703253 to YD), Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province (to YD), the 1,331 Engineering Project of Shanxi Province of China, the National Institutes of Health (Grant nos. R01MH118695 and R01MH123610 to VC), and the National Science Foundation (Grant no. 2112455 to VC).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Geriatrics & Gerontology
  • Neurosciences
  • Neurosciences & Neurology
  • brain functional network
  • functional network connectivity
  • normal brain aging
  • joint changes
  • NeuroMark
  • AGE-RELATED-CHANGES
  • FUNCTIONAL CONNECTIVITY
  • OLDER-ADULTS
  • MEMORY
  • PERFORMANCE
  • FRAMEWORK
  • CINGULATE
  • DEFAULT
  • DISEASE
  • CORTEX

Aging brain shows joint declines in brain within-network connectivity and between-network connectivity: a large-sample study (N > 6,000)

Tools:

Journal Title:

FRONTIERS IN AGING NEUROSCIENCE

Volume:

Volume 15

Publisher:

, Pages 1159054-1159054

Type of Work:

Article | Final Publisher PDF

Abstract:

Introduction: Numerous studies have shown that aging has important effects on specific functional networks of the brain and leads to brain functional connectivity decline. However, no studies have addressed the effect of aging at the whole-brain level by studying both brain functional networks (i.e., within-network connectivity) and their interaction (i.e., between-network connectivity) as well as their joint changes. Methods: In this work, based on a large sample size of neuroimaging data including 6300 healthy adults aged between 49 and 73 years from the UK Biobank project, we first use our previously proposed priori-driven independent component analysis (ICA) method, called NeuroMark, to extract the whole-brain functional networks (FNs) and the functional network connectivity (FNC) matrix. Next, we perform a two-level statistical analysis method to identify robust aging-related changes in FNs and FNCs, respectively. Finally, we propose a combined approach to explore the synergistic and paradoxical changes between FNs and FNCs. Results: Results showed that the enhanced FNCs mainly occur between different functional domains, involving the default mode and cognitive control networks, while the reduced FNCs come from not only between different domains but also within the same domain, primarily relating to the visual network, cognitive control network, and cerebellum. Aging also greatly affects the connectivity within FNs, and the increased within-network connectivity along with aging are mainly within the sensorimotor network, while the decreased within-network connectivity significantly involves the default mode network. More importantly, many significant joint changes between FNs and FNCs involve default mode and sub-cortical networks. Furthermore, most synergistic changes are present between the FNCs with reduced amplitude and their linked FNs, and most paradoxical changes are present in the FNCs with enhanced amplitude and their linked FNs. Discussion: In summary, our study emphasizes the diversity of brain aging and provides new evidence via novel exploratory perspectives for non-pathological aging of the whole brain.

Copyright information:

© 2023 Du, Guo and Calhoun.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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