Understanding how organisms deal with probabilistic stimulus-reward associations has been advanced by a convergence between reinforcement learning models and primate physiology, which demonstrated that the brain encodes a reward prediction error signal. However, organisms must also predict the level of risk associated with reward forecasts, monitor the errors in those risk predictions, and update these in light of new information. Risk prediction serves a dual purpose: (1) to guide choice in risk-sensitive organisms and (2) to modulate learning of uncertain rewards. To date, it is not known whether or how the brain accomplishes risk prediction. Using functional imaging during a simple gambling task in which we constantly changed risk, we sh...
When learning from direct experience, neurons in the primate brain have been shown to encode a teach...
In the past two decades, reinforcement learning (RL) has become a popular framework for understandin...
SummaryHuman subjects are proficient at tracking the mean and variance of rewards and updating these...
Understanding how organisms deal with probabilistic stimulus-reward associations has been advanced b...
Understanding how organisms deal with probabilistic stimulus-reward associations has been advanced b...
In decision-making under uncertainty, economic studies emphasize the importance of risk in addition ...
Rational, value-based decision-making mandates selecting the option with highest subjective expected...
Reward learning depends on accurate reward associations with potential choices. These associations c...
Organisms continuously monitor the stimuli they encounter and the outcome of their actions. To survi...
Behavioral studies have shown for decades that humans are sensitive to risk when making decisions. M...
This article analyzesthe simple Rescorla–Wagner learning rule from the vantage point of least square...
Anterior insula (aIns) is thought to play a crucial role in rapid adaptation in an ever-changing env...
Most accounts of the function of anterior insula in the human brain refer to concepts that are diffi...
We make decisions every waking day of our life. Facing our options, we tend to pick the most likely ...
Reinforcement learning (RL) provides a framework involving two diverse approaches to reward-based de...
When learning from direct experience, neurons in the primate brain have been shown to encode a teach...
In the past two decades, reinforcement learning (RL) has become a popular framework for understandin...
SummaryHuman subjects are proficient at tracking the mean and variance of rewards and updating these...
Understanding how organisms deal with probabilistic stimulus-reward associations has been advanced b...
Understanding how organisms deal with probabilistic stimulus-reward associations has been advanced b...
In decision-making under uncertainty, economic studies emphasize the importance of risk in addition ...
Rational, value-based decision-making mandates selecting the option with highest subjective expected...
Reward learning depends on accurate reward associations with potential choices. These associations c...
Organisms continuously monitor the stimuli they encounter and the outcome of their actions. To survi...
Behavioral studies have shown for decades that humans are sensitive to risk when making decisions. M...
This article analyzesthe simple Rescorla–Wagner learning rule from the vantage point of least square...
Anterior insula (aIns) is thought to play a crucial role in rapid adaptation in an ever-changing env...
Most accounts of the function of anterior insula in the human brain refer to concepts that are diffi...
We make decisions every waking day of our life. Facing our options, we tend to pick the most likely ...
Reinforcement learning (RL) provides a framework involving two diverse approaches to reward-based de...
When learning from direct experience, neurons in the primate brain have been shown to encode a teach...
In the past two decades, reinforcement learning (RL) has become a popular framework for understandin...
SummaryHuman subjects are proficient at tracking the mean and variance of rewards and updating these...