A Competition of Critics in Human Decision-Making

Area of Science:

• Neuroscience
• Computational Psychiatry
• Behavioral Economics

Background:

• Human decision-making involves complex processing of positive and negative errors.
• Serotonin and dopamine are implicated in decision-making, with serotonin potentially counteracting dopamine's pro-risk signals.

Purpose of the Study:

• To introduce a temporal difference (TD) model of human decision-making that incorporates differential error processing.
• To mathematically formalize serotonin's hypothesized role as an opponent to dopamine in decision-making.

Main Methods:

• Development of a TD model with two competing learning systems: an optimistic and a pessimistic critic.
• Integration of critic predictions to control decision selection.
• Simulation of a recent experiment to correlate model updates with neurochemical transients.

Main Results:

• The model predicts human decision-making can be characterized by sensitivity to risk and uncertainty.
• The model implicitly learns reward mean and standard deviation, and provides insights into reaction time.
• Simulations align model dynamics with dopamine and serotonin activity, supporting serotonin's inhibitory role.

Conclusions:

• The proposed TD model offers a novel framework for understanding human decision-making and the interplay of serotonin and dopamine.
• The model provides a mathematical basis for serotonin's role in mitigating risky choices.
• This computational approach can guide future experimental investigations into decision-making mechanisms.