Optimality and heuristics in perceptual neuroscience

Nature Neuroscience
Justin L Gardner

Abstract

The foundation for modern understanding of how we make perceptual decisions about what we see or where to look comes from considering the optimal way to perform these behaviors. While statistical computation is useful for deriving the optimal solution to a perceptual problem, optimality requires perfect knowledge of priors and often complex computation. Accumulating evidence, however, suggests that optimal perceptual goals can be achieved or approximated more simply by human observers using heuristic approaches. Perceptual neuroscientists captivated by optimal explanations of sensory behaviors will fail in their search for the neural circuits and cortical processes that implement an optimal computation whenever that behavior is actually achieved through heuristics. This article provides a cross-disciplinary review of decision-making with the aim of building perceptual theory that uses optimality to set the computational goals for perceptual behavior but, through consideration of ecological, computational, and energetic constraints, incorporates how these optimal goals can be achieved through heuristic approximation.

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Citations

Jun 25, 2020·Journal of Vision·Reneta K KiryakovaMarko Nardini
Sep 16, 2020·ELife·Joseph A HengRafael Polania
Aug 4, 2019·Nature Communications·Daniel Birman, Justin L Gardner
Mar 7, 2020·PLoS Biology·Wei-Hsiang LinShih-Wei Wu
Sep 23, 2020·Nature Human Behaviour·Matteo LisiAndrei Gorea
Mar 24, 2021·Current Biology : CB·Bharath Chandra TalluriT H Donner
Jul 25, 2021·Proceedings of the National Academy of Sciences of the United States of America·Dmitry R LyamzinAndrea Benucci
Oct 15, 2021·Neuron·Jay A HennigSteven M Chase

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