A forward-inverse optics model of reciprocal connections between visual cortical areas
Open accessAbstract
We propose that the feedforward connection from the lower visual cortical area to the higher visual cortical area provides an approximated inverse model of the imaging process (optics), while the backprojection connection from the higher area to the lower area provides a forward model of the optics. By mathematical analysis and computer simulation, we show that a small number of relaxation computations circulating this forward-inverse optics hierarchy achieves fast and reliable integration of vision modules, and therefore might resolve the following problems. (i) How are parallel visual modules (multiple visual cortical areas) integrated to allow a coherent scene perception? (ii) How can ill-posed vision problems be solved by the brain within several hundreds of milliseconds?
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Each cortical area comprises distinct neuronal subpopulations encoding expected states of the world and prediction error.
“Each area comprises distinct neuronal subpopulations, encoding expected states of the world and prediction error (c.f., [72]).”
From Hierarchical Models in the Brain (2008) · cites this paper as [72]
In the model’s neural-circuit description (section headed by the dynamics equation; page unavailable), P2 neurons calculate the discrepancy between a visual representation and its reconstruction, while P3 neurons carry a higher-level representation. This supports distinct representation- and error-related populations, but the paper presents their organization as a proposed model with speculative hypotheses, not an established property of every cortical area. (LLM, conf=0.84)
Experimental — accuracy not yet measuredSome have used forward motor models to motivate generative models in perception.
“Some have even used forward motor models to motivate generative models in perception (Kawato et al. 1993).”
From Action and behavior: a free-energy formulation (2010) · cites this paper as Kawato et al. 1993
The paper’s Abstract and “Twodmensional image data” section propose a forward model of optics in visual cortical connections, supporting the perception-model part of the claim. Our copy does not say that forward motor models motivated this proposal; its model concerns optics rather than motor control. No page number is available for these passages. (LLM, conf=0.82)
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References 34 · Cited by 151
Research works printed but not linked: 5
- Hayakawa H, Nishida S and Kawato M 1992 Shape from shading using discontinuity in image ATR Technical recognition machine Camp. W a n Cmphics l m g e Pmc. 37 54-1 15 55 5-15 images IEEE Trans. Pallern Anulysis Machine fnrelligeme PAMT-6 721-41 figures. and neon color spreading Psychol. Rev. 92 173-211 A model of visual cognitive functions Science 237 184-7
- I41 Johnson R R and Burkhalter A 1991 Feedback connections in visual conex contact inhibitory neumns Soc. 1151 lulesz B 1971 Foundarions of Cyclopean Perception (Chicago: Universiry of Chicago Press)
- Koch C, Marraquin J and Yuille A 1986 Analog 'neural' networks in early vision Proc. Null Acud. Sci. USA 83 4263-7 1191 Man D 1982 Vision (San Francisco: Freeman)
- Mm D and Poggio T 1979 A compulalional theory of human stereo vision Proc. R. Soc. London B 204 301-28
- Movshon J A. Adelson E H, Giui M S and Newsome W T 1986 The analysis of moving visual pauems Puttrm Recognilion Mechanisms ed C Chagas. R Gatlass and C Gross (New York: Springer) pp 117-51
- Authors
- Kawato, M., Hayakawa, H., & Inui, T.
- Affiliations
- Hokkaido University (JP)
- Advanced Telecommunications Research Institute International (JP)
- Kyoto University (JP)
- Venue
- Network: Computation in Neural Systems
- Publisher
- Informa UK Limited
- Published
- 1993-01
- Volume
- 4
- Issue
- 4
- Pages
- 415-422
- ISSN
- 0954-898X (ISSN-L)
- 1361-6536
- OpenAlex
- W2165055912
- Cited by
- 151
- References
- 34
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 7 · 2023: 8 · 2022: 4 · 2021: 8 · 2019: 3 · 2018: 8 · 2017: 3 · 2015: 4 · 2014: 10 · 2013: 6
- FWCI
- 3.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Network Computation in Neural Systems (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- reciprocal connections, feedforward connections, back-projection, scene perception, relaxation dynamics, hierarchical visual processing
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