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A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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Small-worldness and modularity of the resting-state functional brain network decrease with aging.

Keiichi Onoda1, Shuhei Yamaguchi

  • 1Department of Neurology, Shimane University, 89-1 Enyacho, Izumo, Shimane 693-8501, Japan.

Neuroscience Letters
|October 26, 2013
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Summary
This summary is machine-generated.

Normal aging slowly reduces brain network efficiency, specifically small-worldness and modularity. These key brain network properties show a gradual decline with increasing age.

Keywords:
AgingFunctional networkModularityResting-stateSmall-worldnessfMRI

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Area of Science:

  • Neuroscience
  • Network Science
  • Gerontology

Background:

  • Normal aging impacts the complex functional network of the human brain.
  • Graph-based analysis is a method for estimating functional brain network efficiency.
  • Previous studies reported age-related effects on small-worldness, a network property.

Purpose of the Study:

  • To investigate the relationship between normal aging and network modularity.
  • To further examine the effects of aging on small-worldness.
  • Hypothesized age-related declines in both small-worldness and modularity.

Main Methods:

  • Utilized graph-based analysis to assess functional brain networks.
  • Examined network small-worldness and modularity in relation to age.
  • Statistical analysis to determine correlations between age and network properties.

Main Results:

  • Found a negative correlation between increasing age and both small-worldness and modularity.
  • Observed that the age-related decline in these network properties is relatively slow.
  • Network modularity reflects the organization of densely interconnected nodes within a network.

Conclusions:

  • Both small-worldness and modularity exhibit age-related declines.
  • The observed decline in brain network efficiency with aging is gradual.
  • These findings contribute to understanding how normal aging affects brain network organization.