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Circular inferences in schizophrenia.

Renaud Jardri1, Sophie Denève

  • 11 Group for Neural Theory, INSERM U960, Institute of Cognitive Studies, École Normale Supérieure, 75005 Paris, France.

Brain : a Journal of Neurology
|September 26, 2013
PubMed
Summary
This summary is machine-generated.

Schizophrenia involves an excitatory to inhibitory imbalance, leading to hallucinations and delusions. This imbalance causes faulty causal inference, where beliefs are mistaken for sensory data, explaining core psychotic symptoms.

Keywords:
Bayesianbeliefdelusionshallucinationsnetworkpredictive coding

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Computational Psychiatry

Background:

  • Subtle impairments in excitatory-inhibitory balance are implicated in neurological and psychiatric disorders.
  • Schizophrenia is characterized by complex psychotic symptoms, including hallucinations and delusions.

Purpose of the Study:

  • To quantitatively link excitatory-inhibitory imbalance to specific psychotic symptoms in schizophrenia.
  • To explore the neurobiological mechanisms underlying these symptoms using computational models.

Main Methods:

  • Computational modeling of hierarchical neural networks.
  • Analysis of causal inference processes in the brain.
  • Relating model predictions to known schizophrenia symptomatology.

Main Results:

  • Excitatory-inhibitory imbalance in hierarchical models leads to 'circular belief propagation'.
  • Circular belief propagation explains the misinterpretation of sensory information and predictions.
  • This mechanism accounts for hallucinations, delusions, and other schizophrenia-associated cognitive biases.

Conclusions:

  • Excitatory-inhibitory imbalance is a core mechanism driving psychotic symptoms in schizophrenia.
  • Circular belief propagation offers a quantitative explanation for the formation and persistence of delusions and hallucinations.
  • This framework advances our understanding of schizophrenia pathophysiology and potential therapeutic targets.