title: Perception and Reality: Why a Wholly Empirical Paradigm is Needed to Understand Vision.
abstract: A central puzzle in vision science is how perceptions that are routinely at odds with physical measurements of real world properties can arise from neural responses that nonetheless lead to effective behaviors. Here we argue that the solution depends on: (1) rejecting the assumption that the goal of vision is to recover, however imperfectly, properties of the world; and (2) replacing it with a paradigm in which perceptions reflect biological utility based on past experience rather than objective features of the environment. Present evidence is consistent with the conclusion that conceiving vision in wholly empirical terms provides a plausible way to understand what we see and why.
authors.affiliation: Duke Institute for Brain Sciences, Duke University Durham, NC, USA.
authors.forename: Dale
authors.initials: D
authors.lastname: Purves
authors.affiliation: Duke-NUS Graduate Medical School Singapore, Singapore.
authors.forename: Yaniv
authors.initials: Y
authors.lastname: Morgenstern
authors.affiliation: Duke Institute for Brain Sciences, Duke University Durham, NC, USA ; Duke-NUS Graduate Medical School Singapore, Singapore.
authors.forename: William T
authors.initials: WT
authors.lastname: Wojtach
keywords: Bayesian probability; efficient coding; empirical ranking; feature detection; vision; visual perception