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Longitudinal functional brain network reconfiguration in healthy aging.

Brigitta Malagurski1, Franziskus Liem1, Jessica Oschwald1

  • 1University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.

Human Brain Mapping
|August 29, 2020
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Summary
This summary is machine-generated.

Healthy aging shows increased brain network flexibility over time. Older adults exhibit greater variability in brain module organization, linked to baseline age but not immediate cognitive changes.

Keywords:
brain networkshealthy agingmultilayer modularitynetwork flexibilityresting-state fMRI

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Area of Science:

  • Neuroscience
  • Cognitive Aging
  • Network Science

Background:

  • Healthy aging involves cognitive and brain organization changes.
  • Previous studies suggest reduced brain modularity and increased heterogeneity in older adults.
  • Longitudinal studies are needed to understand dynamic brain network changes in aging.

Purpose of the Study:

  • To investigate the time-evolving modular structure of the whole-brain network in healthy older adults using longitudinal data.
  • To examine the relationship between brain network flexibility and age.
  • To explore associations between temporal network metrics and cognitive performance.

Main Methods:

  • Utilized a longitudinal dataset of resting-state functional magnetic resonance imaging (fMRI) and cognitive testing from 150 healthy older adults over 4 years.
  • Applied graph theory and multilayer modularity maximization to analyze the dynamic modular organization of brain networks across four time points.
  • Calculated global flexibility and network-specific flexibility metrics.

Main Results:

  • Global flexibility of the whole-brain network was significantly higher in healthy older adults compared to a null model.
  • Higher global flexibility and network-specific flexibility (default mode, frontoparietal control, somatomotor networks) were associated with older age at baseline.
  • Temporal network metrics did not correlate with concurrent changes in processing speed or memory encoding performance.

Conclusions:

  • Older age is associated with increased variability and flexibility in brain modular organization.
  • Brain network dynamics offer insights into healthy aging, distinct from immediate cognitive function.
  • This longitudinal approach can reveal patterns of modular variability in aging populations, potentially aiding in clinical aging research.