Neuroeconomic studies of decision making have emphasized reward learning as critical in
the representation of value-driven choice behaviour. However, it is readily apparent that …

Learning to make choices that yield rewarding outcomes requires the computation of three
distinct signals: stimulus values that are used to guide choices at the time of decision …

Money is a secondary reinforcer commonly used across a range of disciplines in
experimental paradigms investigating reward learning and decision-making. The …

Studies on human monetary prediction and decision making emphasize the role of the
striatum in encoding prediction errors for financial reward. However, less is known about …

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

While the concept of “expected utility” informs many theories of decision making, little is
known about whether and how the human brain might compute this quantity. This article …

Recent research in neuroeconomics has demonstrated that the reinforcement learning
model of reward learning captures the patterns of both behavioral performance and neural …

Prediction error, defined by the discrepancy between real and expected outcomes, lies at
the core of associative learning. Behavioural investigations have provided evidence that …

Favors from a sender to a receiver are known to bias decisions made by the recipient,
especially when the decision relates to the sender, a feature of social exchange known as …

Deciding between stimuli requires combining their learned value with one's sensory
confidence. We trained mice in a visual task that probes this combination. Mouse choices …