To make decision in dynamic environment, an animal must update evaluation of candidate actions based on past experiences of actions and rewards. Reinforcement learning (RL) explains reward-based decision-making and adaptive choice of actions by the three steps: i) estimate the action value, i.e., how much reward value an action will yield; ii) compare the action values of alternatives to select an action; and iii) update the action value by the discrepancy between expected and acquired reward after the action. To test whether the striatum encodes action value, we recorded activity of striatal projection neurons of two monkeys making free choices between left- and right-turn of a handle. Reward probability of each of the two actions was fixed at either 10, 50 or 90% in a block of trials but varied between blocks. In the previous report (Samejima et al, 2003 SfN abstract), we showed that striatal activity were modulated by reward probability for a particular action in block-by-block comparisons. To study ada...