Understanding vision in wholly empirical terms
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This article considers visual perception, the nature of the information on which perceptions seem to be based, and the implications of a wholly empirical concept of perception and sensory processing for vision science. Evidence from studies of lightness, brightness, color, form, and motion all indicate that, because the visual system cannot access the physical world by means of retinal light patterns as such, what we see cannot and does not represent the actual properties of objects or images. The phenomenology of visual perceptions can be explained, however, in terms of empirical associations that link images whose meanings are inherently undetermined to their behavioral significance. Vision in these terms requires fundamentally different concepts of what we see, why, and how the visual system operates.
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Non-Bayesian accounts based on ecological constraints or perceptual heuristics offer equally plausible, and often more parsimonious, explanations of visual illusions.
“In many cases, non-Bayesian accounts based on ecological constraints or perceptual heuristics offer equally plausible, and often more parsimonious, explanations (Purves et al. 2011).”
From The myth of the Bayesian brain (2025) · cites this paper as Purves et al. 2011
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The Bayesian brain: The role of uncertainty in neural coding and computation
Knill, D. C., & Pouget, A. (2004) · Trends in Neurosciences · doi:10.1016/j.tins.2004.10.007 · Cited by 2,588 · see citing works
Motion illusions as optimal percepts
Weiss, Y., Simoncelli, E. P., & Adelson, E. H. (2002) · Nature Neuroscience · doi:10.1038/nn0602-858 · Cited by 1,076 · see citing works
Illusions, perception and Bayes
Geisler, W. S., & Kersten, D. (2002) · Nature Neuroscience · doi:10.1038/nn0602-508 · Cited by 249 · see citing works
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Neural circuitry of information seeking
Bromberg-Martin, E. S., & Monosov, I. E. (2020) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2020.07.006 · Cited by 89 · see citing works
The myth of the Bayesian brain
Mangalam, M. (2025) · European Journal of Applied Physiology · doi:10.1007/s00421-025-05855-6 · Cited by 14 · see citing works
“In many cases, non-Bayesian accounts based on ecological constraints or perceptual heuristics offer equally plausible, and often more parsimonious, explanations (Purves et al. 2011).”
- Authors
- Purves, D., Wojtach, W. T., & Lotto, R. B.
- Affiliations
- National University of Singapore (SG)
- Duke University (US)
- University College London (GB)
- ORCID
- Purves, Dale
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-03-07
- Volume
- 108
- Issue
- supplement_3
- Pages
- 15588-15595
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3176612
- OpenAlex
- W2113583161
- Cited by
- 106
- References
- 3
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 6 · 2023: 4 · 2022: 4 · 2021: 5 · 2020: 7 · 2019: 5 · 2018: 7 · 2017: 8 · 2016: 9 · 2015: 8 · 2014: 13 · 2013: 10 · 2012: 5
- FWCI
- 0.95
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Philosophy and Theoretical Science
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Keywords
- visual perception, sensory processing, lightness perception, brightness perception, color perception, shape perception, motion perception, fundus images, phenomenology of perception
- MeSH terms
- Animals, Humans, Light, Models, Biological, Motion, Photic Stimulation, Vision, Ocular, Visual Perception
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