Fixation patterns in simple choice reflect optimal information sampling

Area of Science:

• Cognitive Science
• Neuroscience
• Decision Science

Background:

• Simple choices involve integrating noisy evidence over time.
• Visual attention fluctuations can significantly impact decision-making outcomes.
• The determinants of visual fixation patterns during choice remain unclear.

Purpose of the Study:

• To model the decision process for simple choices as an information sampling problem.
• To determine the optimal policy for sampling information during choice.
• To investigate how value estimates influence fixation and choice behavior.

Main Methods:

• Developed an information sampling model for simple choice tasks.
• Approximated the optimal sampling policy within this model.
• Analyzed fixation and choice data in binary and trinary choice scenarios.

Main Results:

• Optimal information sampling involves focusing on options with high value and high uncertainty.
• The derived optimal policy accurately predicts fixation patterns in simple choices.
• The model accounts for differences in choice behavior between binary and trinary options.

Conclusions:

• Fixation during simple choice is dynamically driven by evolving value estimates.
• Decision-making processes align with principles of optimal information sampling.
• Understanding attention-value dynamics is key to explaining choice behavior.