Reinforcement learning allows organisms to predict future outcomes and to update their
beliefs about value in the world. The dorsal-lateral prefrontal cortex (dlPFC) integrates …

Decision making and learning in a real-world context require organisms to track not only the
choices they make and the outcomes that follow but also other untaken, or counterfactual …

In uncertain and changing environments, optimal decision-making requires integrating
reward expectations with probabilistic beliefs about reward contingencies. Little is known …

Adaptation of learning and decision-making might depend on the regulation of activity in the
prefrontal cortex. Here we examined how volatility of reward probabilities influences …

Value-based decision making often involves integration of reward outcomes over time, but
this becomes considerably more challenging if reward assignments on alternative options …

Neurons in the dorsolateral prefrontal cortex (DLPFC) encode a diverse array of sensory
and mnemonic signals, but little is known about how this information is dynamically routed …

Reinforcement learning (RL) theories posit that dopaminergic signals are integrated within
the striatum to associate choices with outcomes. Often overlooked is that the amygdala also …

In many natural environments the value of a choice gradually gets better or worse as
circumstances change. Discerning such trends makes predicting future choice values …

Decisions occur in dynamic environments. In the framework of reinforcement learning, the
probability of performing an action is influenced by decision variables. Discrepancies …

In inverse reinforcement learning an observer infers the reward distribution available for
actions in the environment solely through observing the actions implemented by another …