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Predictive Processing, Source Monitoring, and Psychosis.

Juliet D Griffin1, Paul C Fletcher1

  • 1Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, United Kingdom; email: jdg48@cam.ac.uk , pcf22@cam.ac.uk.

Annual Review of Clinical Psychology
|April 5, 2017
PubMed
Summary

The predictive processing framework offers a unified model for understanding psychosis, linking neurobiology to subjective experiences like delusions and hallucinations. This approach complements existing source monitoring theories, providing deeper insights into psychosis mechanisms.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Psychiatry

Background:

  • Understanding psychosis requires integrating neurobiological, cognitive, subjective, and social factors.
  • Gaps exist in explaining how brain changes cause psychosis symptoms or how adversity affects brain processes.

Purpose of the Study:

  • To propose the predictive processing framework as a unifying model for psychosis.
  • To demonstrate how predictive processing can explain delusions and hallucinations.
  • To model key clinical features of psychosis using a hierarchical predictive system.

Main Methods:

  • Conceptual integration of predictive processing with source monitoring theories.
  • Application of predictive processing to explain psychosis phenomena.
  • Modeling psychosis through a dynamic, hierarchical predictive system.
Keywords:
predictive codingpsychosisschizophreniasource monitoring

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Main Results:

  • Predictive processing provides a framework to bridge explanatory gaps in psychosis.
  • The framework complements source monitoring theories of delusions and hallucinations.
  • A hierarchical predictive system models key clinical features of psychosis.

Conclusions:

  • The predictive processing framework offers a robust model for understanding psychosis.
  • It integrates diverse levels of explanation, from neurobiology to subjective experience.
  • It reconciles and deepens understanding offered by source monitoring theories.