Deep brain stimulation (DBS) of the subthalamic nucleus markedly improves the motor symptoms of Parkinson's disease, but causes cognitive side effects such as impulsivity. We showed that DBS selectively interferes with the normal ability to slow down when faced with decision conflict. While on DBS, patients actually sped up their decisions under high-conflict conditions. This form of impulsivity was not affected by dopaminergic medication status. Instead, medication impaired patients' ability to learn from negative decision outcomes. These findings implicate independent mechanisms leading to impulsivity in treated Parkinson's patients and were predicted by a single neurocomputational model of the basal ganglia.

What are the genetic and neural components that support adaptive learning from positive and negative outcomes? Here, we show with genetic analyses that three independent dopaminergic mechanisms contribute to reward and avoidance learning in humans. A polymorphism in the DARPP-32 gene, associated with striatal dopamine function, predicted relatively better probabilistic reward learning. Conversely, the C957T polymorphism of the DRD2 gene, associated with striatal D2 receptor function, predicted the degree to which participants learned to avoid choices that had been probabilistically associated with negative outcomes. The Val/Met polymorphism of the COMT gene, associated with prefrontal cortical dopamine function, predicted participants' ability to rapidly adapt behavior on a trial-to-trial basis. These findings support a neurocomputational dissociation between striatal and prefrontal dopaminergic mechanisms in reinforcement learning. Computational maximum likelihood analyses reveal independent gene effects on three reinforcement learning parameters that can explain the observed dissociations.basal ganglia ͉ prefrontal cortex ͉ computational model

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.

Recent neuroimaging evidence has led to the proposal that freezing of gait in Parkinson's disease is due to dysfunctional interactions between frontoparietal cortical regions and subcortical structures, such as the striatum. However, to date, no study has employed task-based functional connectivity analyses to explore this hypothesis. In this study, we used a data-driven multivariate approach to explore the impaired communication between distributed neuronal networks in 10 patients with Parkinson's disease and freezing of gait, and 10 matched patients with no clinical history of freezing behaviour. Patients performed a virtual reality gait task on two separate occasions (once ON and once OFF their regular dopaminergic medication) while functional magnetic resonance imaging data were collected. Group-level independent component analysis was used to extract the subject-specific time courses associated with five well-known neuronal networks: the motor network, the right- and left cognitive control networks, the ventral attention network and the basal ganglia network. We subsequently analysed both the activation and connectivity of these neuronal networks between the two groups with respect to dopaminergic state and cognitive load while performing the virtual reality gait task. During task performance, all patients used the left cognitive control network and the ventral attention network and in addition, showed increased connectivity between the bilateral cognitive control networks. However, patients with freezing demonstrated functional decoupling between the basal ganglia network and the cognitive control network in each hemisphere. This decoupling was also associated with paroxysmal motor arrests. These results support the hypothesis that freezing behaviour in Parkinson's disease is because of impaired communication between complimentary yet competing neural networks.