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Embodying addiction: A predictive processing account.

Mark Miller1, Julian Kiverstein2, Erik Rietveld3

  • 1Department of Informatics, University of Sussex, Sussex House, Falmer, Brighton BN1 9RH, United Kingdom.

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This summary is machine-generated.

Addiction arises from learning processes gone awry, reframed by predictive processing theory. It

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Philosophy of Mind

Background:

  • Addiction is often viewed as a brain disease or mental illness.
  • Existing models struggle to fully explain the persistent nature of addictive behaviors.

Purpose of the Study:

  • To reframe addiction through the lens of predictive processing theory.
  • To propose that addiction is a breakdown in the agent-environment system, not solely a brain disease.

Main Methods:

  • Utilizing predictive processing theory to analyze learning mechanisms in addiction.
  • Examining the role of environmental organization around drug-seeking behaviors.

Main Results:

  • Predictive processing suggests addiction involves a failure of the agent-environment system's dynamics.
  • Addiction leads to a predictive model of the environment that poorly attunes individuals to dynamic surroundings.
  • Substance use provides illusory attunement, masking a detrimental lack of environmental awareness.

Conclusions:

  • Addiction is better understood as a systemic issue within the agent-environment interaction, rather than a localized brain disease.
  • The harm of addiction lies in the maladaptive "way of life" it fosters, neglecting alternative possibilities.
  • Predictive processing offers a novel framework for understanding and potentially intervening in addiction.