@article{oai:repo.qst.go.jp:00047318,
 author = {Hori, Yukiko and Minamimoto, Takafumi and Kimura, Minoru and 堀 由紀子 and 南本 敬史},
 issue = {6},
 journal = {Journal of Neurophysiology},
 month = {Dec},
 note = {Decision making and action selection are influenced by the values of benefit, reward, cost, and punishment. Mapping of the positive and negative values of external events and actions occurs mainly via the discharge rates of neurons in the cerebral cortex, the amygdala, and the basal ganglia. However, it remains unclear how the reward values of external events and actions encoded in the basal ganglia are integrated into reward value-based control of limb-movement actions through the corticobasal ganglia loops. To address this issue, we investigated the activities of presumed projection neurons in the putamen of macaque monkeys performing a visually instructed GO-NOGO button-press task for large and small rewards. Regression analyses of neuronal discharge rates, actions, and reward values revealed three major categories of neurons. First, neurons activated during the preinstruction delay period were selective to either the GO(large reward)-NOGO(small reward) or NOGO(large reward)-GO(small reward) combinations, although the actions to be instructed were not predictable. Second, during the postinstruction epoch, GO and NOGO action-related activities were highly selective to reward size. The pre- and postinstruction activities of a large subset of neurons were also selective to cue position or GO-response direction. Third, neurons activated during both the pre- and postinstruction epochs were selective to both action and reward size. The results support the view that putamen neurons encode reward value and direction of actions, which may be a basis for mediating the processes leading from reward-value mapping to guiding ongoing actions toward their expected outcomes and directions.},
 pages = {3530--3543},
 title = {Neuronal Encoding of Reward Value and Direction of Actions in the Primate Putamen},
 volume = {102},
 year = {2009}
}