1. Perception and Reality: Why a Wholly Empirical Paradigm is Needed to Understand Vision
- Author
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Dale ePurves, Yaniv eMorgenstern, and William Taylor Wojtach
- Subjects
Feature detection (web development) ,vision ,Visual perception ,efficient coding ,Cognitive Neuroscience ,media_common.quotation_subject ,Neuroscience (miscellaneous) ,feature detection ,visual perception ,Bayesian probability ,Data science ,lcsh:RC321-571 ,Odds ,Cellular and Molecular Neuroscience ,Vision science ,empirical ranking ,Developmental Neuroscience ,Perception ,Hypothesis & Theory ,Psychology ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Neuroscience ,Cognitive psychology ,media_common - 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.
- Published
- 2015
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