A new framework for modeling decisions about changing information: The Piecewise Linear Ballistic Accumulator model

Area of Science:

• Cognitive Psychology
• Neuroscience
• Decision Science

Background:

• Real-world decision-making requires integrating non-stationary information that changes during the process.
• Traditional decision-making theories often assume stationary information, but non-stationary stimuli are gaining theoretical importance.

Purpose of the Study:

• To investigate how decision processes update when faced with changing stimuli.
• To quantify the delay in integrating new information during decision-making.

Main Methods:

• Utilized a random-dot motion paradigm where stimulus direction switched midway.
• Employed cognitive modeling, specifically a Piecewise Linear Ballistic Accumulator (PLBA) model.
• Fitted the PLBA model to participant choice and response-time data using a hierarchical Bayesian framework.

Main Results:

• Behavioral data showed a significant delay effect in integrating updated motion information.
• PLBA model fits confirmed a substantial delay between stimulus change presentation and information integration.
• The decision process demonstrated an asymmetric effect of stimulus change on evidence accumulation, and did not show increased response caution.

Conclusions:

• The perceptual decision process is slow to react to new, contrary motion information.
• New evidence is underestimated, leading to a non-veridical integration process.
• Findings highlight the challenges in dynamic decision-making and the need for models that account for non-stationarity.