In addition to their well-known role in skeletal movements, the basal ganglia control saccadic eye movements (saccades) by means of their connection to the superior colliculus (SC). The SC receives convergent inputs from cerebral cortical areas and the basal ganglia. To make a saccade to an object purposefully, appropriate signals must be selected out of the cortical inputs, in which the basal ganglia play a crucial role. This is done by the sustained inhibitory input from the substantia nigra pars reticulata (SNr) to the SC. This inhibition can be removed by another inhibition from the caudate nucleus (CD) to the SNr, which results in a disinhibition of the SC. The basal ganglia have another mechanism, involving the external segment of the globus pallidus and the subthalamic nucleus, with which the SNr-SC inhibition can further be enhanced. The sensorimotor signals carried by the basal ganglia neurons are strongly modulated depending on the behavioral context, which reflects working memory, expectation, and attention. Expectation of reward is a critical determinant in that the saccade that has been rewarded is facilitated subsequently. The interaction between cortical and dopaminergic inputs to CD neurons may underlie the behavioral adaptation toward purposeful saccades.

Action is controlled by both motivation and cognition. The basal ganglia may be the site where these kinds of information meet. Using a memory-guided saccade task with an asymmetric reward schedule, we show that visual and memory responses of caudate neurons are modulated by expectation of reward so profoundly that a neuron's preferred direction often changed with the change in the rewarded direction. The subsequent saccade to the target was earlier and faster for the rewarded direction. Our results indicate that the caudate contributes to the determination of oculomotor outputs by connecting motivational values (for example, expectation of reward) to visual information.

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Reward is a primary goal of behavior and is crucial for survival of animals. To explore the mechanisms underlying such reward-oriented behavior, we devised a memory-guided saccade task in which only one fixed direction out of four was rewarded, which was called the one-direction-rewarded task (1DR). As the rewarded direction was changed in four blocks, saccades in a given direction were rewarded in one block (constituting reward-oriented behavior), but non-rewarded in the other blocks (non-reward-oriented behavior). As a control, an all-directions-rewarded task (ADR) was used. Using these tasks, we found that the parameters of saccades changed depending on whether or not the saccade was followed by reward. (1) The mean saccadic peak velocity was higher and the mean saccade latency was shorter in the rewarded condition than in the non-rewarded condition. (2) The mean saccade amplitude showed no difference in two out of three monkeys. (3) The variations of saccadic velocity, latency and amplitude were smaller in the rewarded condition. (4) Within a block of 1DR, the saccade velocity remained high in the rewarded condition, but decreased gradually in the non-rewarded condition; it decreased only slightly in ADR. The saccade latency showed the opposite pattern of change, but less clearly. (5) The saccades in the non-rewarded condition tended to have slower velocities and longer latencies in the trials shortly after a rewarded trial. (6) The ratio of error trials was much higher in the non-rewarded condition than the rewarded condition. (7) The errors, which were due to premature or incorrect saccades, showed unique spatiotemporal patterns that would reflect the competition between the cognitive and motivational processes. These results provide important constraints to the neuronal mechanism underlying reward-oriented behavior because it must satisfy these rules.

Midbrain dopamine (DA) neurons are thought to encode reward prediction error. Reward prediction can be improved if any relevant context is taken into account. We found that monkey DA neurons can encode a context-dependent prediction error. In the first noncontextual task, a light stimulus was randomly followed by reward, with a fixed equal probability. The response of DA neurons was positively correlated with the number of preceding unrewarded trials and could be simulated by a conventional temporal difference (TD) model. In the second contextual task, a reward-indicating light stimulus was presented with the probability that, while fixed overall, was incremented as a function of the number of preceding unrewarded trials. The DA neuronal response then was negatively correlated with this number. This history effect corresponded to the prediction error based on the conditional probability of reward and could be simulated only by implementing the relevant context into the TD model.