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Suboptimality in perceptual decision making and beyond

Published online by Cambridge University Press:  10 January 2019

Hilary C. Barth
Affiliation:
Department of Psychology, Wesleyan University, Middletown, CT 06459. hbarth@wesleyan.eduapatalano@wesleyan.eduhttp://hbarth.faculty.wesleyan.eduhttp://apatalano.faculty.wesleyan.edu
Sara Cordes
Affiliation:
Department of Psychology, Boston College, Chestnut Hill, MA 02467. cordess@bc.eduhttps://www2.bc.edu/sara-cordes/lab/
Andrea L. Patalano
Affiliation:
Department of Psychology, Wesleyan University, Middletown, CT 06459. hbarth@wesleyan.eduapatalano@wesleyan.eduhttp://hbarth.faculty.wesleyan.eduhttp://apatalano.faculty.wesleyan.edu

Abstract

We concur with the authors’ overall approach and suggest that their analysis should be taken even further. First, the same points apply to areas beyond perceptual decision making. Second, the same points apply beyond issues of optimality versus suboptimality.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2018 

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References

Anderson, B. L. (2015) Can computational goals inform theories of vision? Topics in Cognitive Science 7:274–86.Google Scholar
Anderson, B. L., O'Vari, J. & Barth, H. (2011) Non-Bayesian contour synthesis. Current Biology 21(6):492–96. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0960982211001746.Google Scholar
Barth, H., Lesser, E., Taggart, J. & Slusser, E. (2015) Spatial estimation: A non-Bayesian alternative. Developmental Science 18:853–62.Google Scholar
Bowers, J. S. & Davis, C. J. (2012a) Bayesian just-so stories in psychology and neuroscience. Psychological Bulletin 138(3):389414.Available at: http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=22545686&retmode=ref&cmd=prlinks.Google Scholar
Cicchini, G. M., Arrighi, R., Cecchetti, L., Giusti, M. & Burr, D. C. (2012) Optimal encoding of interval timing in expert percussionists. Journal of Neuroscience 32(3):1056–60. doi:10.1523/JNEUROSCI.3411-11.2012.Google Scholar
Crawford, L. E. & Duffy, S. (2010) Sequence effects in estimating spatial location. Psychonomic Bulletin & Review 17:725–30.Google Scholar
Duffy, S., Huttenlocher, J. & Crawford, L. E. (2006) Children use categories to maximize estimation. Developmental Science 9:597603.Google Scholar
Duffy, S. & Smith, J. (2017) Category effects on stimulus estimation: Shifting and skewed frequency distributions – A reexamination. Psychonomic Bulletin & Review 25(5):1740–50. Available at: https://doi.org/10.3758/s13423-017-1392-7.Google Scholar
Fleming, R. W. (2011) Visual perception: Bizarre contours go against the odds. Current Biology 21:R259–61.Google Scholar
Huttenlocher, J., Hedges, L. V. & Vevea, J. L. (2000) Why do categories affect stimulus judgment? Journal of Experimental Psychology: General 129:220–41.Google Scholar
Petzschner, F. H., Glasauer, S. & Stephan, K. E. (2015) A Bayesian perspective on magnitude estimation. Trends in Cognitive Sciences 19:285–93.Google Scholar
Sciutti, A., Burr, D., Saracco, A., Sandini, G. & Gori, M. (2015) Development of context-dependency in human space perception. Experimental Brain Research 232:3965–76.Google Scholar