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Tai Chi Practice Buffers Aging Effects in Functional Brain Connectivity.

Jonathan Cerna1, Prakhar Gupta2, Maxine He1

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Summary
This summary is machine-generated.

Tai Chi practice may counteract age-related brain network decline. This mind-body exercise enhances functional connectivity (FC) in older adults, promoting healthier brain aging.

Keywords:
Tai Chielectroencephalographyhealthy agingmind–body practicerecurrent neural network dynamicsresting statesource localization

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Area of Science:

  • Neuroscience
  • Gerontology
  • Cognitive Science

Background:

  • Tai Chi (TC) is known to improve cognitive and physical function in older adults.
  • The specific neural mechanisms driving these benefits are not fully understood.
  • Investigating age-related changes and TC's impact on brain networks is crucial for understanding healthy brain aging.

Purpose of the Study:

  • To explore age-related differences in brain network connectivity.
  • To investigate the effects of Tai Chi (TC) practice on neural network dynamics.
  • To identify whether TC practice mitigates age-associated declines in functional connectivity (FC).

Main Methods:

  • A cross-sectional study analyzing resting-state electroencephalography (EEG) data from younger adults, older adult controls, and Tai Chi practitioners.
  • Utilized an adaptive, data-driven thresholding approach for source-localized EEG data to analyze time-varying brain graphs.
  • Employed a hidden Markov model (HMM) to derive temporal and spatial features, with Mann-Whitney U tests comparing groups.

Main Results:

  • Aging was associated with reduced within-network and between-network functional connectivity (FC) across most brain networks.
  • Tai Chi (TC) practitioners showed increased FC within and between networks compared to non-practicing older adults.
  • These findings suggest TC practice may counteract age-related decreases in neural network efficiency and stability.

Conclusions:

  • Tai Chi (TC) practice may serve as a non-pharmacological intervention to promote healthy brain aging by preserving neural network integrity.
  • The study supports and extends the triple-network model, indicating TC may influence attentional reorientation through both top-down and bottom-up neural mechanisms.
  • Findings highlight the potential of TC to enhance neural network efficiency and stability in older adults, combating age-related cognitive decline.