The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Motion illusions as optimal percepts
Abstract
The pattern of local image velocities on the retina encodes important environmental information. Although humans are generally able to extract this information, they can easily be deceived into seeing incorrect velocities. We show that these 'illusions' arise naturally in a system that attempts to estimate local image velocity. We formulated a model of visual motion perception using standard estimation theory, under the assumptions that (i) there is noise in the initial measurements and (ii) slower motions are more likely to occur than faster ones. We found that specific instantiation of such a velocity estimator can account for a wide variety of psychophysical phenomena.
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In the citing paper
“Many motion ' illusions ' are not the result of sloppy computation by various components in the visual system, but rather a result of a coherent computational strategy that is optimal under reasonable assumptions. (Weiss et al. 2002, p. 603)”
From Whatever next? Predictive brains, situated agents, and the future of cognitive science (2013) · cites this paper as Weiss et al. 2002
In the citing paper
“Similar results have been obtained for motion perception, neatly accounting for various illusions of motion perception by invoking statistically valid priors that favor slower and smoother motions -see Weiss et al. (2002) and Ernst (2010).”
From Whatever next? Predictive brains, situated agents, and the future of cognitive science (2013) · cites this paper as Weiss et al. 2002
In the citing paper
“One success story is that of Bayesian cognitive models, which optimally combine prior knowledge about the world with sensory evidence21–23.”
From Cognitive computational neuroscience (2018) · cites this paper as [23]
In the citing paper
“which is inconsistent with the proposition that strong priors would be at the root of perceptual illusions.141,142”
From Are hallucinations due to an imbalance between excitatory and inhibitory influences on the brain? (2016) · cites this paper as [142]
In the citing paper
“Importantly, several authors (Geisler and Kersten, 2002; Weiss et al., 2002) suggested that a whole range of illusory percepts, even those that are idiosyncratic in appearance (such as motion illusions), correspond to what an optimal Bayesian observer would perceive in similar conditions.”
From What visual illusions teach us about schizophrenia (2014) · cites this paper as Weiss et al., 2002
Citations
Cites
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Self-citationComputational Models of Visual Processing
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Research works printed but not linked: 1
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Cited by
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Items 1,001–1,034 of 1,034
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Ballard, D. H. (2014) · Springer eBooks · doi:10.1007/978-0-387-31439-6_273
Purves, D. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190880163.003.0005
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Purves, D. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190880163.003.0012
Wenderoth, P. (2008) · Springer eBooks · doi:10.1007/978-3-540-29678-2_6356
Purves, D. (2021) · Springer eBooks · doi:10.1007/978-3-030-71064-4_15
(2008) · Springer eBooks · doi:10.1007/978-3-540-29678-2_22
Pinna, B. (2017) · doi:10.1093/acprof:oso/9780199794607.003.0074
Purves, D. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190880163.003.0006
(2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179675.002.0001
(2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179675.001.0001.002.003
(2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179675.001.0001.002.005
Kingdom, F. A. A. (2022) · Springer eBooks · doi:10.1007/978-1-0716-1006-0_557
Perception, Bayesian Models of
Beierholm, U. (2022) · Springer eBooks · doi:10.1007/978-1-0716-1006-0_451
Kingdom, F. A. A. (2014) · Springer eBooks · doi:10.1007/978-1-4614-7320-6_557-1
(2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199564668.002.0005
(2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199564668.002.0003
Prior Knowledge Biases the Perception of Body PosturesPreprint
Han, Q.-L., Gandolfo, M., & Peelen, M. V. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.01.518647
A dynamical model of visual motion processing for arbitrary stimuli including type II plaids
Korai, Y., & Miura, K. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.02.039
Perceiving depth and motion in depth from successive occlusion
Lee, A. R. I., Wilcox, L. M., & Allison, R. S. (2023) · Journal of Vision · doi:10.1167/jov.23.12.2
Stereoscopic slant contrast revisited
Kingdom, F. A. A., Yakobi, Y., & Wang, X. (2024) · Journal of Vision · doi:10.1167/jov.24.4.24
Purves, D. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190880163.002.0007
Purves, D. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190880163.002.0005
Purves, D. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190880163.002.0003
Perceptual axioms are irreconcilable with Euclidean geometry
Zeki, S., Hale, Z. F., Beyh, A., & Rasche, S. E. (2024) · European Journal of Neuroscience · doi:10.1111/ejn.16430
A paradigm for characterizing motion misperception in people with typical vision and low vision
Chin, B. M., Wang, M., Mikkelsen, L. T., Friedman, C. T., Ng, C., Chu, M. A., & Cooper, E. A. (2024) · Optometry and Vision Science · doi:10.1097/opx.0000000000002139
Timing-induced illusory percepts of pitch
Pazdera, J. K., Rinaldi, O. M., & Trainor, L. J. (2026) · Scientific Reports · doi:10.1038/s41598-026-53525-0 · Cited by 1
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search
Theiss, J. D., & Silver, M. A. (2024) · Neural Computation · doi:10.1162/neco_a_01700
The predictive mind in motion: exploring visuomotor expertise through interception
Harris, D., Wilson, M., Vine, S. J., & Arthur, T. (2026) · Human Movement Science · doi:10.1016/j.humov.2026.103529
Purves, D. (2025) · Springer eBooks · doi:10.1007/978-3-031-93142-0_15
Waggoner, M. (2025) · Philosophical Psychology · doi:10.1080/09515089.2025.2537896
Metadata
- Authors
- Weiss, Y., Simoncelli, E. P., & Adelson, E. H.
- Affiliations
- Hebrew University of Jerusalem (IL)
- Howard Hughes Medical Institute (US)
- Massachusetts Institute of Technology (US)
- Corresponding author
- Weiss, Yair
- ORCID
- Simoncelli, Eero P.
- Venue
- Nature Neuroscience
- Published
- 2002-05-20
- Volume
- 5
- Issue
- 6
- Pages
- 598-604
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2148596731
- Cited by
- 1,076
- References
- 49
- Citations by year
- 2026: 33 · 2025: 48 · 2024: 42 · 2023: 31 · 2022: 38 · 2021: 52 · 2020: 43 · 2019: 59 · 2018: 55 · 2017: 57 · 2016: 44 · 2015: 50 · 2014: 65 · 2013: 59 · 2012: 51
- FWCI
- 16.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01ey011005-05)
- National Eye Institute (R01 EY11005)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Keywords
- illusory motion, visual motion perception, velocity estimation, Bayesian estimation, psychophysics, measurement noise
- MeSH terms
- Humans, Models, Neurological, Motion Perception, Optical Illusions, Time Factors, Contrast Sensitivity
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