title: From biophysics to cognition: reward-dependent adaptive choice behavior.
abstract: In neurobiological studies of various cognitive abilities, neuroscientists use mathematical models to fit behavioral data from well-controlled experiments and look for neural activities that are correlated with parameters in those models. The pinpointed neural correlates are often taken as evidence that a given task is performed according to the prescription of the applied model, and the relevant brain areas encode parameters of such a model. However, to go beyond correlations toward causal understanding, it is necessary to elucidate at multiple levels the neural circuit mechanisms of cognitive processes. This review focuses on recent studies of reward-based decision-making that have begun to tackle this challenge.
authors.affiliation: Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA. soltani@caltech.edu
authors.forename: Alireza
authors.initials: A
authors.lastname: Soltani
authors.forename: Xiao-Jing
authors.initials: XJ
authors.lastname: Wang
mesh_terms: D000223:Adaptation, Psychological / Q000502:physiology*; D001703:Biophysics / Q000379:methods; D002755:Choice Behavior / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D012201:Reward; D013647:Task Performance and Analysis