Dopamine transients are sufficient and necessary for acquisition of model-based associations

Learning to predict reward is thought to be driven by dopaminergic prediction errors, which reflect discrepancies between actual and expected value. Here the authors show that learning to predict neutral events is also driven by prediction errors and that such value-neutral associative learning is a...

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Podrobná bibliografia
Vydané v:	Nature neuroscience Ročník 20; číslo 5; s. 735 - 742
Hlavní autori:	Sharpe, Melissa J, Chang, Chun Yun, Liu, Melissa A, Batchelor, Hannah M, Mueller, Lauren E, Jones, Joshua L, Niv, Yael, Schoenbaum, Geoffrey
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Nature Publishing Group US 01.05.2017 Nature Publishing Group
Predmet:	631/378/116 631/378/1595 Animal Genetics and Genomics Animals Animals, Genetically Modified Association Learning - physiology Behavior Behavioral Sciences Biological Techniques Biomedicine Conditioning, Psychological Cues Dopamine Dopaminergic Neurons - physiology Female Health aspects Male Neurobiology Neurons Neurosciences Physiological aspects Psychological aspects Rats Reward Rewards (Psychology) Ventral Tegmental Area - physiology United States United States > US Maryland Baltimore Maryland
ISSN:	1097-6256, 1546-1726, 1546-1726
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Popis
Shrnutí:	Learning to predict reward is thought to be driven by dopaminergic prediction errors, which reflect discrepancies between actual and expected value. Here the authors show that learning to predict neutral events is also driven by prediction errors and that such value-neutral associative learning is also likely mediated by dopaminergic error signals. Associative learning is driven by prediction errors. Dopamine transients correlate with these errors, which current interpretations limit to endowing cues with a scalar quantity reflecting the value of future rewards. We tested whether dopamine might act more broadly to support learning of an associative model of the environment. Using sensory preconditioning, we show that prediction errors underlying stimulus–stimulus learning can be blocked behaviorally and reinstated by optogenetically activating dopamine neurons. We further show that suppressing the firing of these neurons across the transition prevents normal stimulus–stimulus learning. These results establish that the acquisition of model-based information about transitions between nonrewarding events is also driven by prediction errors and that, contrary to existing canon, dopamine transients are both sufficient and necessary to support this type of learning. Our findings open new possibilities for how these biological signals might support associative learning in the mammalian brain in these and other contexts.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	1097-6256 1546-1726 1546-1726
DOI:	10.1038/nn.4538