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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(More)
Making appropriate choices often requires the ability to learn the value of available options from experience. Parkinson's disease is characterized by a loss of dopamine neurons in the substantia nigra, neurons hypothesized to play a role in reinforcement learning. Although previous studies have shown that Parkinson's patients are impaired in tasks(More)
Probabilistic category learning engages neural circuitry that includes the prefrontal cortex and caudate nucleus, two regions that show prominent changes with normal aging. However, the specific contributions of these brain regions are uncertain, and the effects of normal aging have not been examined previously in probabilistic category learning. In the(More)
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(More)
Specific reductions in hippocampal volume in nondemented elderly individuals with mild cognitive impairment have been shown to correlate with future development of Alzheimer's disease (AD). Hippocampal atrophy (HA) is also correlated with cognitive impairments, leading to the promise of behavioral markers for early AD. Prior theoretical work has suggested(More)
The learning of an association between a CS and a US can be retarded by unreinforced presentations of the CS alone (termed latent inhibition or LI) or by un-correlated presentations of the CS and US (termed learned irrelevance or LIRR). In rabbit eyeblink conditioning, there have been some recent failures to replicate LI. LIRR has been hypothesized as(More)
We present a simple computational model of the dentate gyrus to evaluate the hypothesis that pattern separation, defined as the ability to transform a set of similar input patterns into a less-similar set of output patterns, is dynamically regulated by hilar neurons. Prior models of the dentate gyrus have generally fallen into two categories: simplified(More)
Previous research has suggested that a probabilistic category learning task (e.g. weather prediction task) can be used to elucidate brain substrates of learning. We tested amnesic subjects with bilateral hippocampal damage due to hypoxia and matched controls on the weather prediction task and a variant, the "ice cream" task, which maintains a similar(More)
The purpose of this study was to investigate basal ganglia (BG) and medial temporal lobe (MTL) dependent learning in patients with schizophrenia. Acquired equivalence is a phenomenon in which prior training to treat two stimuli as equivalent (if two stimuli are associated with the same response) increases generalization between them. The learning of(More)
Building on our previous neurocomputational models of basal ganglia and hippocampal region function (and their modulation by dopamine and acetylcholine, respectively), we show here how an integration of these models can inform our understanding of the interaction between the basal ganglia and hippocampal region in associative learning and transfer(More)