Psilocybin increases optimistic engagement over time: computational modelling of behaviour in rats

Area of Science:

• Neuroscience
• Pharmacology
• Computational Psychiatry

Background:

• Psilocybin shows therapeutic potential for depression and psychiatric disorders.
• Mechanisms underlying psilocybin's effects on information processing remain unclear.

Purpose of the Study:

• To investigate the computational mechanisms of psilocybin's effects on learning and decision-making.
• To model rat behavior using active inference and reinforcement learning.

Main Methods:

• Developed a novel two-armed bandit reversal learning task for rats.
• Applied computational models (active inference, reinforcement learning) to analyze task performance.
• Assessed the impact of psilocybin administration on behavioral metrics.

Main Results:

• Psilocybin administration led to increased reward acquisition.
• Enhanced task engagement was observed post-psilocybin.
• Key computational changes included modified forgetting rates and reduced loss aversion.

Conclusions:

• Psilocybin may induce an optimism bias via altered belief updating mechanisms.
• Findings suggest potential translational applications for psychiatric populations.
• The study elucidates information processing changes associated with psilocybin treatment.