Schedule of Events | Symposia

Swinging into faster learning: Larger motor movements can enhance category learning

Poster Session F - Tuesday, April 1, 2025, 8:00 – 10:00 am EDT, Back Bay Ballroom/Republic Ballroom

Luke Rosedahl¹ (luke_rosedahl@brown.edu), Takeo Watanabe¹; ¹Brown University

Category learning has traditionally been viewed as a primarily cognitive process, with popular models like the generalized context model, ALCOVE, and SUSTAIN treating it as largely independent from motor systems. Our research challenges this perspective by demonstrating that the magnitude of motor response in categorization tasks significantly impacts learning performance. Using a virtual reality paradigm, participants (N=72) categorized Gabor discs using either controller triggers or virtual lightsaber swings. We tested two category structures: Rule-Based (RB), requiring binary decisions along feature dimensions, and Information-Integration (II), requiring integration of multiple feature dimensions. Based on evidence that II structures engage basal ganglia motor learning systems while RB structures involve prefrontal areas (Ashby & Valentin, 2017), we hypothesized that larger motor movements might specifically enhance II category learning. Participants were evenly divided across four conditions: RB-Button, RB-Lightsaber, II-Button, and II-Lightsaber. While RB performance remained consistent across response types (t = -.12, p = .91), II category learning significantly improved with lightsaber swings (t = 2.7, p = .006). Notably, II participants using lightsaber swings achieved 82% accuracy after just 150 trials - a level that exceeded the maximum accuracy (81%) that II button-pressing participants reached after 600 trials. These findings challenge the purely cognitive view of category learning and highlight the importance of motor engagement, particularly for complex categories. This suggests the need to revise existing theories to account for motor system involvement, possibly through enhanced engagement of basal ganglia circuits in procedural learning.

Topic Area: PERCEPTION & ACTION: Vision