Kéri , S., Moustafa, A. A., Myers, C. E., Benedek, G., & Gluck, M. A. (2010). Alpha-synuclein gene duplication impairs reward learning. Proceedings of the National Academy of Sciences.

• Alpha-synuclein plays an important role in the regulation of dopaminergic neurotransmission and neurodegeneration in Parkinson disease. We investigated reward and punishment learning in asymptomatic carriers of a rare alpha-synuclein gene duplication who were healthy siblings of patients with Parkinson disease. Results revealed that healthy gene duplication carriers displayed impaired reward and intact punishment learning compared with noncarriers. These results demonstrate that a copy number variation of the alpha-synuclein gene is associated with selective impairments on reinforcement learning in asymptomatic carriers without the motor symptoms of Parkinson disease.

In a study of acquired equivalence in Parkinson disease (PD), in which patients were tested on normal dopaminergic medication, we found that comorbid clinical depression impairs initial acquisition, whereas the use of anticholinergic therapy impairs subsequent transfer generalization. In addition, this study provides a replication of the basic finding of Myers et al (2003) that patients with PD on dopaminergic therapy are impaired at initial acquisition, but normal at subsequent transfer generalization, generalizing these results to an Arabic-speaking population including many participants with no formal education. These results are consistent with our past computational modeling, which argues that acquisition of incrementally acquired, feedback-based learning tasks is dependent on cortico-striatal circuits, whereas transfer generalization is dependent on medial temporal (MT) structures. They are also consistent with prior computational modeling, and with empiric work in humans and animals, suggesting that anticholinergic drugs may particularly impair cognitive abilities that depend on the MT lobe.

Moustafa, A. A., & Gluck, M. A. (2010). A Neurocomputational Model of Dopamine and Prefrontal-Striatal Interactions during Multicue Category Learning by Parkinson's Patients. J Cogn Neurosci.

Most existing models of dopamine and learning in Parkinson's disease (PD) focus on simulating the role of basal ganglia dopamine in reinforcement learning. Much data argue, however, for a critical role for prefrontal cortex (PFC) dopamine in stimulus selection in attentional learning. Here, we present a new computational model that simulates performance in multicue category learning, such as the “weather prediction” task. The model addresses how PD and dopamine medications affect stimulus selection processes, which mediate reinforcement learning. In this model, PFC dopamine is key for attentional learning, whereas basal ganglia dopamine, consistent with other models, is key for reinforcement and motor learning. The model assumes that competitive dynamics among PFC neurons is the neural mechanism underlying stimulus selection with limited attentional resources, whereas competitive dynamics among striatal neurons is the neural mechanism underlying action selection. According to our model, PD is associated with decreased phasic and tonic dopamine levels in both PFC and basal ganglia. We assume that dopamine medications increase dopamine levels in both the basal ganglia and PFC, which, in turn, increase tonic dopamine levels but decrease the magnitude of phasic dopamine signaling in these brain structures. Increase of tonic dopamine levels in the simulated PFC enhances attentional shifting performance. The model provides a mechanistic account for several phenomena, including (a) medicated PD patients are more impaired at multicue probabilistic category learning than unmedicated patients and (b) medicated PD patients opt out of reversal when there are alternative and redundant cue dimensions.

Although previous studies have shown that Parkinson’s patients are impaired in tasks involving learning from feedback, they have not directly tested the widely held hypothesis that dopamine neuron activity specifically encodes the reward prediction error signal used in reinforcement learning models. To test a key prediction of this hypothesis, we fit choice behavior from a dynamic foraging task with reinforcement learning models and show that treatment with dopaminergic drugs alters choice behavior in a manner consistent with the theory. More specifically,we found that dopaminergic drugs selectively modulate learning from positive outcomes.We observed no effect of dopaminergic drugs on learning from negative outcomes. We also found a novel dopamine-dependent effect on decision making that is not accounted for by reinforcement learning models: perseveration in choice, independent of reward history, increases with Parkinson’s disease and decreases with dopamine therapy.

N. Bodi, S. Keri, H. Nagy, A. Moustafa, C. E. Myers, N. Daw, G. Dibo, A. Takats, D. Bereczki, and M. A. Gluck Reward-learning and the novelty-seeking personality: a between- and within-subjects study of the effects of dopamine agonists on young Parkinson's patients. Brain, September 1, 2009; 132(9): 2385 - 2395.

In this study, we investigated reward and punishment processing in three groups: 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. 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 personality traits, whereas these drugs decreased the correlation between punishment processing and harm-avoidance personality traits. 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.

Guthrie, M., Myers, C. E., & Gluck, M. A. (2009/In press). A neurocomputational model of tonic and phasic dopamine in action selection: A comparison with cognitive deficits in Parkinson’s disease. Behavioral Brain Research.

The striatal dopamine signal has multiple facets; tonic level, phasic rise and fall, and variation of the phasic rise/fall depending on the expectation of reward/punishment.We have developed a network model of the striatal direct pathway using an ionic current level model of the medium spiny neuron that incorporates currents sensitive to changes in the tonic level of dopamine. The model neurons in the network learn action selection based on a novel set of mathematical rules that incorporate the phasic change in the dopamine signal. This network model is capable of learning to perform a sequence learning task that in humans is thought to be dependent on the basal ganglia. When both tonic and phasic levels of dopamine are decreased, as would be expected in unmedicated Parkinson's disease (PD), the model reproduces the deficits seen in a human PD group off medication. When the tonic level is increased to normal, but with reduced phasic increases and decreases in response to reward and punishment, respectively, as would be expected in PD medicated with L-Dopa, the model again reproduces the human data. These findings support the view that the cognitive dysfunctions seen in Parkinson's disease are not solely either due to the decreased tonic level of dopamine or to the decreased responsiveness of the phasic dopamine signal to reward and punishment, but to a combination of the two factors that varies dependent on disease stage and medication status.

Kéri, S., Nagy, H., Myers, C. E., Benedek, G., Shohamy, D., & Gluck, M. A. (2008). Risk and protective haplotypes of the alpha-synuclein gene associated with Parkinson's disease differentially affect cognitive sequence learning. Genes, Brain, and Behavior. 7 (1). 31-36

Alpha-synuclein (SNCA) is a key factor in the regulation of dopaminergic transmission and related to Parkinson's disease. In this study, we investigated the effects of risk and protective SNCA haplotypes associated with Parkinson's disease on cognitive sequence learning in 204 healthy volunteers. We found that the risk haplotypes are associated with less effective stimulus-reward learning of sequences and with superior context representation of sequences. In contrast, participants with protective haplotypes exhibit better stimulus-reward learning and worse context representation, which suggests that these functions are inversely affected by risk and protective haplotypes. Since stimulus-reward learning may be mediated by the basal ganglia, and context learning may be related to the medial temporal lobe, our data raise the possibility that dopaminergic signals regulated by SNCA inversely affect these memory systems.