Decisions must be implemented through actions, and actions are prone to error. As such, when an expected outcome is not obtained, an individual should be sensitive to not only whether the choice itself was suboptimal but also whether the action required to indicate that choice was executed successfully. The intelligent assignment of credit to action execution versus action selection has clear ecological utility for the learner. To explore this, we used a modified version of a classic reinforcement learning task in which feedback indicated whether negative prediction errors were, or were not, associated with execution errors. Using fMRI, we asked if prediction error computations in the human striatum, a key substrate in reinforcement learnin...
SummaryHow the brain uses success and failure to optimize future decisions is a long-standing questi...
In reinforcement learning, an agent makes sequential decisions to maximize reward. During learning, ...
Goal-directed and instrumental learning are both important controllers of human behavior. Learning a...
The computational framework of reinforcement learning has been used to forward our understanding of ...
■ Our ability to make decisions is predicated upon our knowl-edge of the outcomes of the actions ava...
Losing a point in tennis could result from poor shot selection or faulty stroke execution. To explor...
Activation likelihood estimation (ALE) meta-analyses were used to examine the neural correlates of p...
Learning occurs when an outcome deviates from expectation (prediction error). According to formal le...
Prediction-error signals consistent with formal models of “reinforcement learning” (RL) have repeate...
Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeate...
Compared to our understanding of positive prediction error signals occurring due to unexpected rewar...
Reinforcement learning describes motivated behavior in terms of two abstract signals. The representa...
Behavioral adaptation and cognitive control are crucial for goal-reaching behaviors. Every creature ...
We assessed electrophysiological activity over the medial frontal cortex (MFC) during outcome-based ...
A recent theory holds that the anterior cingulate cortex (ACC) uses reinforcement learning signals c...
SummaryHow the brain uses success and failure to optimize future decisions is a long-standing questi...
In reinforcement learning, an agent makes sequential decisions to maximize reward. During learning, ...
Goal-directed and instrumental learning are both important controllers of human behavior. Learning a...
The computational framework of reinforcement learning has been used to forward our understanding of ...
■ Our ability to make decisions is predicated upon our knowl-edge of the outcomes of the actions ava...
Losing a point in tennis could result from poor shot selection or faulty stroke execution. To explor...
Activation likelihood estimation (ALE) meta-analyses were used to examine the neural correlates of p...
Learning occurs when an outcome deviates from expectation (prediction error). According to formal le...
Prediction-error signals consistent with formal models of “reinforcement learning” (RL) have repeate...
Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeate...
Compared to our understanding of positive prediction error signals occurring due to unexpected rewar...
Reinforcement learning describes motivated behavior in terms of two abstract signals. The representa...
Behavioral adaptation and cognitive control are crucial for goal-reaching behaviors. Every creature ...
We assessed electrophysiological activity over the medial frontal cortex (MFC) during outcome-based ...
A recent theory holds that the anterior cingulate cortex (ACC) uses reinforcement learning signals c...
SummaryHow the brain uses success and failure to optimize future decisions is a long-standing questi...
In reinforcement learning, an agent makes sequential decisions to maximize reward. During learning, ...
Goal-directed and instrumental learning are both important controllers of human behavior. Learning a...