title: Adaptive neural coding: from biological to behavioral decision-making.
abstract: Empirical decision-making in diverse species deviates from the predictions of normative choice theory, but why such suboptimal behavior occurs is unknown. Here, we propose that deviations from optimality arise from biological decision mechanisms that have evolved to maximize choice performance within intrinsic biophysical constraints. Sensory processing utilizes specific computations such as divisive normalization to maximize information coding in constrained neural circuits, and recent evidence suggests that analogous computations operate in decision-related brain areas. These adaptive computations implement a relative value code that may explain the characteristic context-dependent nature of behavioral violations of classical normative theory. Examining decision-making at the computational level thus provides a crucial link between the architecture of biological decision circuits and the form of empirical choice behavior.
authors.affiliation: Center for Neural Science, New York University, New York, NY 10003 ; Institute for the Interdisciplinary Study of Decision Making, New York University, New York, NY 10003.
authors.forename: Kenway
authors.initials: K
authors.lastname: Louie
authors.affiliation: Center for Neural Science, New York University, New York, NY 10003 ; Institute for the Interdisciplinary Study of Decision Making, New York University, New York, NY 10003.
authors.forename: Paul W
authors.initials: PW
authors.lastname: Glimcher
authors.affiliation: Rotman School of Management, University of Toronto, Toronto, Ontario, Canada M5S 3E6.
authors.forename: Ryan
authors.initials: R
authors.lastname: Webb