Neuronal Reward and Decision Signals: From Theories to Data
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Abstract
Rewards are crucial objects that induce learning, approach behavior, choices, and emotions. Whereas emotions are difficult to investigate in animals, the learning function is mediated by neuronal reward prediction error signals which implement basic constructs of reinforcement learning theory. These signals are found in dopamine neurons, which emit a global reward signal to striatum and frontal cortex, and in specific neurons in striatum, amygdala, and frontal cortex projecting to select neuronal populations. The approach and choice functions involve subjective value, which is objectively assessed by behavioral choices eliciting internal, subjective reward preferences. Utility is the formal mathematical…
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1,143
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Topics
Keywords
- Reinforcement learning
- Psychology
- Neuroscience
- Reinforcement
- Mean squared prediction error
- Cognitive psychology
- Value (mathematics)
- Computer science
UN Sustainable Development Goals
- Peace, Justice and strong institutions
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