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Reward-based decision-making and aging.

A Marschner1, T Mell, I Wartenburger

  • 1Berlin NeuroImaging Center, Charité, Campus Mitte, Schumannstr. 20/21, 10117 Berlin, Germany. hauke.heekeren@charite.de

Brain Research Bulletin
|October 12, 2005
PubMed
Summary
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Aging impairs behavioral flexibility due to changes in the brain's reward system. This affects decision-making, learning, and processing, impacting cognitive functions like memory and speed.

Area of Science:

  • Neuroscience
  • Cognitive Aging
  • Neurobiology

Background:

  • Healthy aging involves neuroanatomical and neurobiological changes impacting cognition.
  • Dopaminergic and serotonergic systems, prefrontal cortex (PFC), and striatum undergo age-related alterations.
  • Cognitive functions like episodic memory, working memory, and processing speed decline with age.

Purpose of the Study:

  • To hypothesize that age-related behavioral inflexibility stems from reward system alterations.
  • To investigate impairments in reward processing, learning, and decision-making due to aging.
  • To review neural correlates, age-related changes, and behavioral/neuroimaging data on reward-based decision-making.

Main Methods:

  • Review of neural substrates of reward processing in young individuals.

Related Experiment Videos

  • Examination of age-related functional and structural changes in the reward system.
  • Analysis of behavioral and neuroimaging studies on aging and reward-based decision-making.

    • Main Results:

    • Aging affects dopaminergic and serotonergic systems, with structural changes in PFC and striatum.
    • Cognitive decline in aging includes deficits in memory, processing speed, and task adaptation.
    • Alterations in the reward system are linked to impaired reward processing and decision-making.

    Conclusions:

    • Age-related structural and functional changes in the reward system cause behavioral inflexibility.
    • Impaired reward processing and decision-making contribute to cognitive deficits in aging.
    • Findings have implications for neuroeconomics and understanding neurodegenerative diseases.