title: The Neuroscience of Human Decision-Making Through the Lens of Learning and Memory.
abstract: We are called upon to make decisions, large and small, many times a day. Whether in the voting booth, the stock exchange, or the cafeteria line, we identify potential options, estimate and compare their subjective values, and make a choice. Decision-making has only recently become a focus for cognitive neuroscience. The last two decades have seen rapid progress in our understanding of the brain basis of at least some aspects of this rather complex aspect of cognition. This work has provided fresh perspectives on poorly understood brain regions, such as orbitofrontal cortex and ventral striatum. It has led to interesting interdisciplinary exchanges with diverse fields, notably economics, but also ecology and political science, among others. The novel perspectives arising from these exchanges have begun to be related to better understood aspects of cognition. In particular, it is increasingly clear that decision-making is tightly interlinked with learning and memory. Key early insights in decision neuroscience came from what were essentially reinforcement learning tasks. Recent work has made similar links to aspects of declarative memory. Indeed, decision-making can be seen as the link between memory of the past and future actions. This chapter reviews selected topics in decision neuroscience, with a particular focus on the links to learning and memory, and a particular emphasis on regions within prefrontal cortex.
authors.affiliation: Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada. lesley.fellows@mcgill.ca.
authors.forename: Lesley K
authors.initials: LK
authors.lastname: Fellows
mesh_terms: D001921:Brain / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D007858:Learning / Q000502:physiology*; D008568:Memory / Q000502:physiology*
keywords: Choice; Frontal lobes; Heuristics; Orbitofrontal cortex; Reinforcement learning; Reward