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Our group is interested in identifying brain signals for reward and economic decisions. As information processing systems work with explicit signals, we like to identify and characterise such signals before investigating detailed neuronal mechanisms. We use concepts from animal learning theory and economic decision theory and combine behavioural, neurophysiological and neuroimaging (fMRI) methods. We search for neuronal responses that implement fundamental theoretical constructs underlying reward-seeking, learning and decision-making, such as reward prediction error, utility, probability, risk, object-action-chosen value, and revealed preference. Studied brain structures include dopamine neurons, striatum, frontal cortex and amygdala.
Research Interests
Papers共 351 篇Author StatisticsCo-AuthorSimilar Experts
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bioRxiv : the preprint server for biology (2024)
SSRN Electronic Journal (2024)
Proceedings of the National Academy of Sciences of the United States of Americano. 20 (2024): e2316658121-e2316658121
NEURONno. 22 (2023): 3683-3696.e7
Research Square (Research Square) (2023)
biorxiv(2023)
STAR Protocolsno. 2 (2023): 102296-102296
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