Casey L. Roark

This study combines pupillometry and drift-diffusion models to analyze auditory category learning dynamics, showing that delayed trials reveal distinct learning markers and DDM parameters.

The paper investigates how neural dynamics differ based on auditory category structures during learning, showing distinct spatiotemporal patterns for rule-based and information-integration tasks.

This study examines how individual differences in working memory affect non-native speech category learning through computational modeling and pupillometry, finding that higher working memory correlates with faster and more effective learning.