Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-27T23:25:47.040Z Has data issue: false hasContentIssue false

Perceptual suboptimality: Bug or feature?

Published online by Cambridge University Press:  10 January 2019

Christopher Summerfield
Affiliation:
Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom. christopher.summerfield@psy.ox.ac.ukchui.li@psy.ox.ac.uk
Vickie Li
Affiliation:
Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom. christopher.summerfield@psy.ox.ac.ukchui.li@psy.ox.ac.uk

Abstract

Rahnev & Denison (R&D) argue that whether people are “optimal” or “suboptimal” is not a well-posed question. We agree. However, we argue that the critical question is why humans make suboptimal perceptual decisions in the first place. We suggest that perceptual distortions have a normative explanation – that they promote efficient coding and computation in biological information processing systems.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Appelle, S. (1972) Perception and discrimination as function of stimulus orientation. Psychological Bulletin 78:266–78.Google Scholar
de Gardelle, V. & Summerfield, C. (2011) Robust averaging during perceptual judgment. Proceedings of the National Academy of Sciences of the United States of America 108(32):13341–46. doi:10.1073/pnas.1104517108.Google Scholar
Drugowitsch, J., Wyart, V., Devauchelle, A.-D. & Koechlin, E. (2016) Computational precision of mental inference as critical source of human choice suboptimality. Neuron 92(6):1398–411. Available at: http://dx.doi.org/10.1016/j.neuron.2016.11.005.Google Scholar
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
Li, V., Herce Castanon, S., Solomon, J. A., Vandormael, H. & Summerfield, C. (2017) Robust averaging protects decisions from noise in neural computations. PLoS Computational Biology 13(8):e1005723. doi:10.1371/journal.pcbi.1005723.Google Scholar
Simoncelli, E. P. (2003) Vision and the statistics of the visual environment. Current Opinion in Neurobiology 13(2):144–49.Google Scholar
Spitzer, B., Waschke, L. & Summerfield, C. (2017) Selective overweighting of larger magnitudes during numerical comparison. Nature Human Behaviour 1:0145. doi:10.1038/s41562-017-0145.Google Scholar
Tsetsos, K., Moran, R., Moreland, J., Chater, N., Usher, M. & Summerfield, C. (2016a) Economic irrationality is optimal during noisy decision making. Proceedings of the National Academy of Sciences of the United States of America 113(11):3102–107. Available at: http://www.pnas.org/content/early/2016/02/24/1519157113.long.Google Scholar
Wei, X.-X. & Stocker, A. A. (2015) A Bayesian observer model constrained by efficient coding can explain “anti-Bayesian” percepts. Nature Neuroscience 18:1509–17. Available at: http://dx.doi.org/10.1038/nn.4105.Google Scholar
Wei, X. X. & Stocker, A. A. (2017) Lawful relation between perceptual bias and discriminability. Proceedings of the National Academy of Sciences of the United States of America 114(38):10244–49.Google Scholar