Interrogating brain engagement as a function of exception learning performance

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC
Also presenting in Data Blitz Session 2 - Saturday, April 13, 2024, 1:00 – 2:30 pm EDT, Ballroom Center.

Emily Heffernan¹ (emily.heffernan@mail.utoronto.ca), Michael Mack¹; ¹University of Toronto

Navigating a dynamic environment requires a balance of efficiency and adaptability. Category learning, the process of generalizing past knowledge to novel experiences, is an integral part of efficient learning. However, what happens when the learner encounters “exceptions” that violate what has already been learned? Here we explore learning-related activation in the brain during rule-plus-exception learning. Participants (N = 41) underwent fMRI scanning during a category learning task. Stimuli were cartoon flower images sorted into two categories according to a rule-plus-exception structure. Notably, exceptions were introduced later in learning, after participants had become familiar with category prototypes and rule-following stimuli. Participants were divided into “high” and “low” performance groups based on the median split of end-of-learning exception categorization performance. When exceptions were introduced, we found higher activation in hippocampus for all stimulus types that was associated with improved exception learning. In medial prefrontal cortex (MPFC), engagement differed for prototype versus exception stimuli, with higher activation in high versus low learners specific to prototype stimuli; the opposite effect occurred for exception stimuli. A stimulus-specific effect was also found in parietal regions: better exception learning performance was associated with increased activation to exceptions but decreased activation to prototypes. These findings are consistent with theoretical accounts of these regions’ roles in learning. Hippocampus plays a broad role in integrating rule-violating information, whereas MPFC and parietal regions respectively engage to encode regularities and details. The complementary role of these regions enables the learner to successfully integrate exceptional information while preserving existing knowledge.

Topic Area: LONG-TERM MEMORY: Semantic