Impaired flexible reward learning in ADHD patients is associated. Top Picks for Environmental Protection computational model for learning reward contingencies and related matters.. model of contingencies. “Developmental Differences in Probabilistic Reversal Learning: A Computational Modeling Approach.” Frontiers in Neuroscience 14.
Computational models of adaptive behavior and prefrontal cortex
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Computational mechanisms of human state-action-reward
*Memory precision and age differentially predict the use of *
Computational mechanisms of human state-action-reward. Computational mechanisms of human state-action-reward contingency learning under perceptual uncertainty. Dirk Ostwald1,2 (dirk.ostwald@fu-berlin.de), Rasmus , Memory precision and age differentially predict the use of , Memory precision and age differentially predict the use of. The Rise of Supply Chain Management computational model for learning reward contingencies and related matters.
Mesostriatal dopamine is sensitive to changes in specific cue
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Mesostriatal dopamine is sensitive to changes in specific cue. The Rise of Global Operations computational model for learning reward contingencies and related matters.. Managed by This profile of changes in cue- and reward-evoked responding is computational model where DA guides retrospective causal learning (17)., Wave-like dopamine dynamics as a mechanism for spatiotemporal , Wave-like dopamine dynamics as a mechanism for spatiotemporal
Sensorimotor Learning Biases Choice Behavior: A Learning Neural
*Neural Circuitry of Salience and Reward Processing in Psychosis *
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Impaired flexible reward learning in ADHD patients is associated
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Adolescents adapt more slowly than adults to varying reward
*Probabilistic reversal learning and hierarchical Gaussian filter *
Adolescents adapt more slowly than adults to varying reward. In a probabilistic reversal learning task, adolescents and adults adapted to changes in reward contingencies. The Role of Business Progress computational model for learning reward contingencies and related matters.. We used a reinforcement learning model with an , Probabilistic reversal learning and hierarchical Gaussian filter , Probabilistic reversal learning and hierarchical Gaussian filter
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Belief states and categorical-choice biases determine reward-based
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