Prediction error, ketamine and psychosis: An updated model.

Area of Science:

• Neuroscience
• Psychiatry
• Computational Neuroscience

Background:

• Delusion formation was previously proposed as aberrant prediction error-driven associative learning.
• Ketamine was identified as a model for this process, with validation in psychosis patients.

Purpose of the Study:

• To review and expand upon the prediction error model of psychosis.
• To explain the heterogeneity of psychotic illness and psychotomimetic drug effects.
• To incorporate precision of predictions and prior expectations into the model.

Main Methods:

• Review of the prediction error minimization principle in brain function.
• Analysis of how prediction errors and their precision can be perturbed.
• Examination of the role of expectation and prediction error uncertainty in psychosis.

Main Results:

• The expanded model explains hallucinations via altered uncertainty balance between expectation and prediction error.
• Negative symptoms may result from unreliable predictions affecting action.
• The model provides a biological basis for belief and perception in psychosis.

Conclusions:

• The refined prediction error model offers novel explanations for psychosis, including hallucinations and negative symptoms.
• The model accounts for the heterogeneity of psychotic disorders and diverse drug effects.
• Future research directions include incorporating more symptoms and refining the biological mapping.