Predictive neural coding of reward preference involves dissociable responses in human ventral midbrain and ventral striatum

Food preferences are acquired through experience and can exert strong influence on choice behavior. In order to choose which food to consume, it is necessary to maintain a predictive representation of the subjective value of the associated food stimulus. Here, we explore the neural mechanisms by whi...

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Vydané v:Neuron (Cambridge, Mass.) Ročník 49; číslo 1; s. 157
Hlavní autori: O'Doherty, John P, Buchanan, Tony W, Seymour, Ben, Dolan, Raymond J
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 05.01.2006
Predmet:
Adult
Algorithms
Cerebral Cortex - physiology
Corpus Striatum - physiology
Cues
Female
Food Preferences - physiology
Humans
Linear Models
Magnetic Resonance Imaging
Male
Mesencephalon - physiology
Models, Neurological
Pupil
Reaction Time
Reward
Taste - physiology
ISSN:0896-6273
On-line prístup:Zistit podrobnosti o prístupe
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Shrnutí:Food preferences are acquired through experience and can exert strong influence on choice behavior. In order to choose which food to consume, it is necessary to maintain a predictive representation of the subjective value of the associated food stimulus. Here, we explore the neural mechanisms by which such predictive representations are learned through classical conditioning. Human subjects were scanned using fMRI while learning associations between arbitrary visual stimuli and subsequent delivery of one of five different food flavors. Using a temporal difference algorithm to model learning, we found predictive responses in the ventral midbrain and a part of ventral striatum (ventral putamen) that were related directly to subjects' actual behavioral preferences. These brain structures demonstrated divergent response profiles, with the ventral midbrain showing a linear response profile with preference, and the ventral striatum a bivalent response. These results provide insight into the neural mechanisms underlying human preference behavior.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0896-6273
DOI:10.1016/j.neuron.2005.11.014