Humans do not integrate new information objectively: outcomes carrying a positive affective
value and evidence confirming one's own prior belief are overweighed. Until recently …

Rewards are crucial objects that induce learning, approach behavior, choices, and
emotions. Whereas emotions are difficult to investigate in animals, the learning function is …

In recent years deep reinforcement learning (RL) systems have attained superhuman
performance in a number of challenging task domains. However, a major limitation of such …

Midbrain dopamine neurons are well known for their role in reward-based reinforcement
learning. We found that the activity of dopamine axons in the posterior tail of the striatum …

Reinforcement learning is an adaptive process in which an animal utilizes its previous
experience to improve the outcomes of future choices. Computational theories of …

Decision making has recently emerged as a central theme in neurophysiological studies of
cognition, and experimental and computational work has led to the proposal of a cortical …

Trust is a critical social process that helps us to cooperate with others and is present to some
degree in all human interaction. However, the underlying brain mechanisms of conditional …

According to reinforcement learning theory of decision making, reward expectation is
computed by integrating past rewards with a fixed timescale. In contrast, we found that a …

Trained neural network models, which exhibit features of neural activity recorded from
behaving animals, may provide insights into the circuit mechanisms of cognitive functions …

Most utility theories of choice assume that the introduction of an irrelevant option (called the
decoy) to a choice set does not change the preference between existing options. On the …