Confluence of Timing and Reward Biases in Perceptual Decision-Making Dynamics

Area of Science:

• Cognitive Neuroscience
• Computational Neuroscience
• Behavioral Economics

Background:

• Daily decisions integrate temporal and reward information, yet how these factors influence strategy is unclear.
• Understanding decision-making requires examining multiple factors simultaneously, not in isolation.

Purpose of the Study:

• To investigate how temporal and reward structures modulate decision-making strategies.
• To develop and apply a computational framework for analyzing complex decision behaviors.

Main Methods:

• Trained rhesus monkeys on a novel perceptual decision task with asymmetric rewards and time-varying evidence reliability.
• Developed a generalized drift-diffusion model to capture choice and response time patterns.
• Systematically manipulated temporal structure to assess its impact on urgency signals.

Main Results:

• Behavior was best explained by a dynamic urgency signal, leaky integration, and two independent reward biases.
• The temporal course of urgency was significantly affected by the temporal context of sensory evidence.
• The computational model successfully captured complex decision-making strategies.

Conclusions:

• Identified key cognitive mechanisms for integrating temporal and reward structures into decision-making.
• Demonstrated the necessity of multiple reward and timing mechanisms for explaining observed behavior.
• Provided insights into the neural underpinnings of adaptive decision strategies.