How people work to obtain a reward depends on the context of the reward delivery, such as the presence/absence of competition and the contingency of reward delivery. Since resources are limited, winning a competition is critically important for organisms'o btaining a reward. People usually expect ordinary performance-reward contingency, with better performers obtaining better rewards. Unordinary reward contingency, such as egalitarianism (equal rewards/no-rewards to both good and poor performers), dampens people's motivation. We previously reported that monkeys were more motivated, and neurons in the lateral prefrontal cortex (LPFC) showed higher outcome-related activity in a competitive than in a noncompetitive game (Hosokawa and Watanabe, 2012). However, monkey's behavior and LPFC neuronal activity have not been examined in a competitive situation with an unordinary performance-reward contingency. Also, the fixed performance-reward contingency in the previous study did not allow us to examine effects of win/loss separately from those of reward/no-reward on prefrontal neuronal activity. Here, we employed the egalitarian competitive situation in which both the winner and loser, or neither of them, got a reward as well as the normal competitive situation in which only the winner got a reward. Monkey's behavioral performance greatly deteriorated in trials with the egalitarian outcome conditions. LPFC neurons showed activities that reflected the normal or egalitarian outcome condition while very few neurons coded win/loss independent of reward/no-reward. Importantly, we found neurons that showed reward-related activity in the normal, but not in the egalitarian outcome conditions, even though the same reward was given to the animal. These results indicate that LPFC may play an important role in monitoring the current reward contingency and integrating it with the performance outcome (win-loss) for better performing the competitive game, and thus for better survival.
- Egalitarian reward-contingency
- Prefrontal cortex
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