Learning and memory in humans rely upon several memory systems, which appear to have dissociable brain substrates. A fundamental question concerns whether, and how, these memory systems interact. Here we show using functional magnetic resonance imaging (FMRI) that these memory systems may compete with each other during classification learning in humans. The medial temporal lobe and basal ganglia were differently engaged across subjects during classification learning depending upon whether the task emphasized declarative or nondeclarative memory, even when the to-be-learned material and the level of performance did not differ. Consistent with competition between memory systems suggested by animal studies and neuroimaging, activity in these regions was negatively correlated across individuals. Further examination of classification learning using event-related FMRI showed rapid modulation of activity in these regions at the beginning of learning, suggesting that subjects relied upon the medial temporal lobe early in learning. However, this dependence rapidly declined with training, as predicted by previous computational models of associative learning.

The authors propose a computational theory of the hippocampal region's function in mediating stimulus representations. The theory assumes that the hippocampal region develops new stimulus representations that enhance the discriminability of differentially predictive cues while compressing the representation of redundant cues. Other brain regions, including cerebral and cerebellar cortices, are presumed to use these hippocampal representations to recode their own stimulus representations. In the absence of an intact hippocampal region, the theory implies that other brain regions will attempt to learn associations using previously established fixed representations. Instantiated as a connectionist network model, the theory provides a simple and unified interpretation of the functional role of the hippocampal region in a wide range of conditioning paradigms, including stimulus discrimination, reversal learning, stimulus generalization, latent inhibition, sensory preconditioning, and contextual sensitivity. The theory makes novel predictions regarding the effects of hippocampal lesions on easy-hard transfer and compound preexposure. Several prior qualitative characterizations of hippocampal function--including stimulus selection, chunking, cue configuration, and contextual coding--are identified as task-specific special cases derivable from this more general theory. The theory suggests that a profitable direction for future empirical and theoretical research will be the study of learning tasks in which both intact and lesioned animals exhibit similar initial learning behaviors but differ on subsequent transfer and generalization tasks.

Probabilistic category learning is often assumed to be an incrementally learned cognitive skill, dependent on nondeclarative memory systems. One paradigm in particular, the weather prediction task, has been used in over half a dozen neuropsychological and neuroimaging studies to date. Because of the growing interest in using this task and others like it as behavioral tools for studying the cognitive neuroscience of cognitive skill learning, it becomes especially important to understand how subjects solve this kind of task and whether all subjects learn it in the same way. We present here new experimental and theoretical analyses of the weather prediction task that indicate that there are at least three different strategies that describe how subjects learn this task. (1) An optimal multi-cue strategy, in which they respond to each pattern on the basis of associations of all four cues with each outcome; (2) a one-cue strategy, in which they respond on the basis of presence or absence of a single cue, disregarding all other cues; or (3) a singleton strategy, in which they learn only about the four patterns that have only one cue present and all others absent. This variability in how subjects approach this task may have important implications for interpreting how different brain regions are involved in probabilistic category learning.

Parkinson's disease is characterized by the degeneration of dopaminergic pathways projecting to the striatum. These pathways are implicated in reward prediction. In this study, we investigated reward and punishment processing in young, never-medicated Parkinson's disease patients, recently medicated patients receiving the dopamine receptor agonists pramipexole and ropinirole and healthy controls. The never-medicated patients were also re-evaluated after 12 weeks of treatment with dopamine agonists. Reward and punishment processing was assessed by a feedback-based probabilistic classification task. Personality characteristics were measured by the temperament and character inventory. Results revealed that never-medicated patients with Parkinson's disease showed selective deficits on reward processing and novelty seeking, which were remediated by dopamine agonists. These medications disrupted punishment processing. In addition, dopamine agonists increased the correlation between reward processing and novelty seeking, whereas these drugs decreased the correlation between punishment processing and harm avoidance. Our finding that dopamine agonist administration in young patients with Parkinson's disease resulted in increased novelty seeking, enhanced reward processing, and decreased punishment processing may shed light on the cognitive and personality bases of the impulse control disorders, which arise as side-effects of dopamine agonist therapy in some Parkinson's disease patients.

Based on prior animal and computational models, we propose a double dissociation between the associative learning deficits observed in patients with medial temporal (hippocampal) damage versus patients with Parkinson's disease (basal ganglia dysfunction). Specifically, we expect that basal ganglia dysfunction may result in slowed learning, while individuals with hippocampal damage may learn at normal speed. However, when challenged with a transfer task where previously learned information is presented in novel recombinations, we expect that hippocampal damage will impair generalization but basal ganglia dysfunction will not. We tested this prediction in a group of healthy elderly with mild-to-moderate hippocampal atrophy, a group of patients with mild Parkinson's disease, and healthy controls, using an "acquired equivalence" associative learning task. As predicted, Parkinson's patients were slower on the initial learning but then transferred well, while the hippocampal atrophy group showed the opposite pattern: good initial learning with impaired transfer. To our knowledge, this is the first time that a single task has been used to demonstrate a double dissociation between the associative learning impairments caused by hippocampal versus basal ganglia damage/dysfunction. This finding has implications for understanding the distinct contributions of the medial temporal lobe and basal ganglia to learning and memory.