Dissociation of Category-Learning Systems via Brain Potentials

• Main Authors: Robert G Morrison, Paul J Reber, Krishna L Bharani, Ken A Paller
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2015-07-01
• Series: Frontiers in Human Neuroscience
• Subjects: EEG; modeling; ERP; category learning; Implicit; explicit
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00389/full

Behavioral, neuropsychological, and neuroimaging evidence has suggested that categories can often be learned via either an explicit rule-based mechanism critically dependent on medial temporal and prefrontal brain regions, or via an implicit information-integration mechanism relying on the basal ganglia. In this study, participants viewed sine-wave gratings (i.e., Gabor patches) that varied on two dimensions and learned to categorize them via trial-by-trial feedback. Two different stimulus distributions were used; one was intended to encourage an explicit rule-based process and the other an implicit information-integration process. We monitored brain activity with scalp electroencephalography (EEG) while each participant (1) passively observed stimuli represented of both distributions, (2) categorized stimuli from one distribution, and, one week later, (3) categorized stimuli from the other distribution. Categorization accuracy was similar for the two distributions. Subtractions of Event-Related Potentials (ERPs) for correct and incorrect trials were used to identify neural differences in rule-based and information-integration categorization processes. We identified an occipital brain potential that was differentially modulated by categorization condition accuracy at an early latency (150 - 250 ms), likely reflecting the degree of holistic processing. A stimulus-locked late positive complex associated with explicit memory updating was modulated by accuracy in the rule-based, but not the information-integration task. Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the rule-based, but not the information-integration condition. These results provide additional evidence for distinct brain mechanisms supporting rule-based versus implicit information-integration category learning and use.