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Optimality is critical when it comes to testing computation-level hypotheses
Published online by Cambridge University Press: 10 January 2019
Abstract
We disagree with Rahnev & Denison (R&D) that optimality should be abandoned altogether. Rather, we argue that adopting a normative approach enables researchers to test hypotheses about the brain's computational goals, avoids just-so explanations, and offers insights into function that are simply inaccessible to the alternatives proposed by R&D.
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- Open Peer Commentary
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- Copyright © Cambridge University Press 2018
Footnotes
†
Authors Chetverikov and van Bergen contributed equally to this work.
References
Girshick, A. R., Landy, M. S. & Simoncelli, E. P. (2011) Cardinal rules: Visual orientation perception reflects knowledge of environmental statistics. Nature Neuroscience 14(7):926–32. Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3125404&tool=pmcentrez&rendertype=abstract.Google Scholar
Marr, D. (1982) Vision: A computational investigation into the human representation and processing of visual information. W. H. Freeman.Google Scholar
Tomassini, A., Morgan, M. J. & Solomon, J. A. (2010) Orientation uncertainty reduces perceived obliquity. Vision Research 50:541–47.Google Scholar
Target article
Suboptimality in perceptual decision making
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