The Integrative Role of Frontopolar Cortex in Rule-Based Category Learning

Abstract

Category learning is a critical neurobiological function that allows organisms to simplify a complex world. Rostrolateral prefrontal cortex (rlPFC) is often active in neurobiological studies of category learning; however, the specific role this region serves in category learning remains uncertain. Previous category learning studies have hypothesized that the rlPFC is involved in switching between rules, whereas others have emphasized rule abstraction and evaluation. We aimed to clarify the role of rlPFC in category learning and dissociate switching and evaluation accounts using two common types of category learning tasks: matching and classification. The matching task involved matching a reference stimulus to one of four target stimuli. In the classification task, participants were shown a single stimulus and learned to classify it into one of two categories. Matching and classification are similar but place different demands on switching and evaluation. In matching, a rule can be known with certainty after a single correct answer. In classification, participants may need to evaluate evidence for a rule even after an initial correct response. This critical difference allows isolation of evaluative functions from switching functions. If the rlPFC is primarily involved in switching between representations, it should cease to be active once participants settle on a given rule in both tasks. If the rlPFC is involved in rule evaluation, its activation should persist in the classification task, but not matching. The results revealed that rlPFC activation persisted into correct trials in classification, but not matching, suggesting that it continues to be involved in the evaluations of evidence for a rule even after participants have arrived at the correct rule.\n\nHighlightsO_LIDifferences between rule-based matching and classification tasks were highlighted.\nC_LIO_LIRostrolateral prefrontal cortex is involved in evaluation of evidence for a rule in rule-based category learning tasks.\nC_LI