A model of the ventral visual system based on temporal stability and local memory
Open accessAbstract
The cerebral cortex is a remarkably homogeneous structure suggesting a rather generic computational machinery. Indeed, under a variety of conditions, functions attributed to specialized areas can be supported by other regions. However, a host of studies have laid out an ever more detailed map of functional cortical areas. This leaves us with the puzzle of whether different cortical areas are intrinsically specialized, or whether they differ mostly by their position in the processing hierarchy and their inputs but apply the same computational principles. Here we show that the computational principle of optimal stability of sensory representations combined with local memory gives rise to a hierarchy of processing stages resembling the ventral visual pathway when it is exposed to continuous natural stimuli. Early processing stages show receptive fields similar to those observed in the primary visual cortex. Subsequent stages are selective for increasingly complex configurations of local features, as observed in higher visual areas. The last stage of the model displays place fields as observed in entorhinal cortex and hippocampus. The results suggest that functionally heterogeneous cortical areas can be generated by only a few computational principles and highlight the importance of the variability of the input signals in forming functional specialization.
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Imposing continuity within certain models gives rise to aspects of the visual system including complex cells, specific properties of visual invariance, and even other representational properties such as the existence of place cells.
“Imposing continuity within certain models gives rise to aspects of the visual system including complex cells (Körding et al., 2004), specific properties of visual invariance (Isik et al., 2012), and even other representational properties such as the existence of place cells (Wyss et al., 2006; Franzius et al., 2007).”
From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Wyss et al., 2006
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- Authors
- Wyss, R., König, P., & Verschure, P. F. M. J.
- Affiliations
- California Institute of Technology (US)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Venue
- PLoS Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2006-04-18
- Volume
- 4
- Issue
- 5
- Pages
- e120
- ISSN
- 1544-9173 (ISSN-L)
- 1545-7885
- PMC
- PMC1436026
- OpenAlex
- W2040572703
- Cited by
- 145
- References
- 37
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 1 · 2023: 4 · 2022: 7 · 2021: 5 · 2020: 5 · 2019: 7 · 2018: 6 · 2017: 7 · 2016: 5 · 2015: 5 · 2014: 11 · 2013: 6 · 2012: 13
- FWCI
- 4.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- ETH Zürich Research Collection (cc-by)
- Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (28127)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- ventral stream, temporal stability, local memory, computational model of visual cortex, receptive fields, place fields, entorhinal cortex, hippocampus, natural stimuli
- MeSH terms
- Cerebral Cortex, Computer Simulation, Memory, Models, Neurological, Robotics, Visual Perception
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