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Prediction in the Aging Brain: Merging Cognitive, Neurological, and Evolutionary Perspectives.

Rachel M Brown1, Stefan L K Gruijters2, Sonja A Kotz3

  • 1Institute of Psychology, RWTH Aachen University, Aachen, Germany.

The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences
|April 16, 2022
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As people age, their brains shift from learning new information to effectively using existing knowledge for prediction. This cognitive shift may optimize resource allocation and knowledge transfer in later life.

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Area of Science:

  • Cognitive Neuroscience
  • Neurobiology of Aging
  • Evolutionary Psychology

Background:

  • Aging is often associated with cognitive decline, but some functions may remain stable or improve.
  • A growing body of research suggests a shift in cognitive priorities over the lifespan.

Purpose of the Study:

  • To propose and explore the hypothesis of a lifespan shift from learning to prediction in the aging brain.
  • To offer neurocognitive and evolutionary explanations for this observed shift.

Main Methods:

  • Integration of evidence from behavioral, computational, and neurological studies.
  • Application of evolutionary models and principles of senescence and plasticity.

Main Results:

  • The aging brain may become more efficient at prediction (utilizing existing knowledge) than at learning new information.
  • Potential explanations include optimized resource allocation and enhanced late-life social learning.

Conclusions:

  • The learning-to-prediction shift offers a framework for understanding cognitive aging.
  • Further theoretical and empirical research is needed to explore this neurocognitive-evolutionary perspective.