A computational substrate for incentive salience

Theories of dopamine function are at a crossroads. Computational models derived from single-unit recordings capture changes in dopaminergic neuron firing rate as a prediction error signal. These models employ the prediction error signal in two roles: learning to predict future rewarding events and b...

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Veröffentlicht in:	Trends in neurosciences (Regular ed.) 2003-08, Vol.26 (8), p.423-428
Hauptverfasser:	McClure, Samuel M., Daw, Nathaniel D., Read Montague, P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Animals Biological and medical sciences Brain Chemistry - physiology Central nervous system Central neurotransmission. Neuromudulation. Pathways and receptors Choice Behavior - physiology Computational Biology Dopamine - physiology Forecasting Fundamental and applied biological sciences. Psychology Learning - physiology Models, Neurological Models, Psychological Motivation Neurology Neuronal Plasticity - physiology Rats Reward Vertebrates: nervous system and sense organs
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