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Brain Structure and Function Predict Adherence to an Exercise Intervention in Older Adults.

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Brain structure and function, along with psychosocial factors, can predict exercise adherence in older adults. A multimodal approach combining these measures offers the strongest prediction for personalized exercise interventions.

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Area of Science:

  • Neuroscience
  • Gerontology
  • Exercise Science

Background:

  • Individual differences in brain structure and function in older adults may reflect brain reserve or maintenance.
  • These differences could mechanistically predict adherence to exercise interventions.

Purpose of the Study:

  • To investigate whether multimodal neuroimaging features, alone and combined with psychosocial, cognitive, and health measures, can predict adherence to a 6-month exercise intervention in older adults.
  • To explore the utility of brain-based measures for predicting exercise adherence.

Main Methods:

  • A 6-month randomized controlled trial of exercise involving 131 older adults (mean age ~66 years, 63% female).
  • Regularized elastic net regression within a nested cross-validation framework was used to predict adherence.
  • Three models were tested: brain structure/function only, psychosocial/health/demographic data only, and a multimodal model.

Main Results:

  • Higher cortical thickness and lower surface area in specific brain regions predicted adherence.
  • Increased nodal functional connectivity in certain brain networks and decreased nodal strength in others also predicted adherence (r = 0.24, P = 0.004).
  • A combined multimodal model demonstrated the highest predictive power for exercise adherence (r = 0.28, P = 0.001).

Conclusions:

  • Brain-based measures show significant utility in predicting exercise adherence in older adults.
  • These findings support the use of neuroimaging for developing precision and individualized exercise interventions for the aging population.