Topic: contingent learning

Efficient contingent learning requires actions and outcomes to be closely associated in time. Extensive prior work indicates that interaction between amygdala, frontal cortex, and striatum is critical for this type of learning. Here, we conducted neurophysiology recordings and applied computational approaches to understand how activity in this circuit varies when choice and reward are separated in time, intentionally decreasing animals’ ability to associate the two together. We trained 3 rhesus macaques to perform a probabilistic reward-learning task. In each session, animals learn the probabi