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Humans show consistent differences in the extent to which their behavior reflects a bias toward appetitive approach-related behavior or avoidance of aversive stimuli [Elliot, A. J. Approach and avoidance motivation. In A. J. Elliot (Ed.), Handbook of approach and avoidance motivation (pp. 3-14). New York: Psychology Press, 2008]. We examined the hypothesis that in healthy participants this motivational bias (assessed by self-report and by a probabilistic learning task that allows direct comparison of the relative sensitivity to reward and punishment) reflects lateralization of dopamine signaling. Using [F-18]fallypride to measure D2/D3 binding, we found that self-reported motivational bias was predicted by the asymmetry of frontal D2 binding. Similarly, striatal and frontal asymmetries in D2 dopamine receptor binding, rather than absolute binding levels, predicted individual differences in learning from reward versus punishment. These results suggest that normal variation in asymmetry of dopamine signaling may, in part, underlie human personality and cognition.

Most existing models of dopamine and learning in Parkinson 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.