The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Intracellular Measurements of Spatial Integration and the MAX Operation in Complex Cells of the Cat Primary Visual Cortex
Abstract
We have examined the spatial integration properties of complex cells to determine whether some of their responses can be described by a maximum operation (MAX)-like computation, as suggested by Riesenhuber and Poggio's model of object recognition. Membrane potential was recorded from anesthetized cats while optimally oriented bars were presented, either alone or in pairs, in different parts of the cells' receptive field. In most cells, the membrane potential response to two bars presented simultaneously could not be predicted by the sum of the responses to individual bars. In many cells, however, the responses closely approximated a MAX-like model. That is, the response of the cell to two bars was similar to the larger of the two individual responses (“soft-MAX”). The degree of nonlinear summation varied from cell to cell and varied within single cells from one stimulus configuration to another but on average fit most closely to the MAX model. The firing response of the cells was also well predicted by the MAX-like model. The MAX-like behavior was independent of the distance between the bars (orthogonal to the preferred orientation), independent of the relative amplitude of the responses, and slightly less pronounced at low levels of contrast. This MAX-like behavior of a subset of complex cells may play an important role in invariant object recognition in clutter.
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“For instance, the model predicts (23), at the C 1 and C 2 levels, respectively, the max-like behavior of a subclass of complex cells in V1 (26) and V4 (27).”
From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [26]
Citations
Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
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Adelson, E. H., & Bergen, J. R. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.000284 · Cited by 3,442
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309
Self-citationNormalization of cell responses in cat striate cortex
Heeger, D. J. (1992) · Visual Neuroscience · doi:10.1017/s0952523800009640 · Cited by 1,835
Linearity and Normalization in Simple Cells of the Macaque Primary Visual Cortex
Carandini, M., Heeger, D. J., & Movshon, J. A. (1997) · Journal of Neuroscience · doi:10.1523/jneurosci.17-21-08621.1997 · Cited by 926
Action potential initiation and backpropagation in neurons of the mammalian CNS
Stuart, G., Spruston, N., Sakmann, B., & Häusser, M. (1997) · Trends in Neurosciences · doi:10.1016/s0166-2236(96)10075-8 · Cited by 768
Laminar differences in receptive field properties of cells in cat primary visual cortex
Gilbert, C. D. (1977) · The Journal of Physiology · doi:10.1113/jphysiol.1977.sp011863 · Cited by 670
Visual input evokes transient and strong shunting inhibition in visual cortical neurons
Graham, L. J., Monier, C., & Frégnac, Y. (1998) · Nature · doi:10.1038/30735 · Cited by 669
Summation and Division by Neurons in Primate Visual Cortex
Carandini, M., & Heeger, D. J. (1994) · Science · doi:10.1126/science.8191289 · Cited by 649 · cited 1×
“It is also possible that differences in integration properties at low compared to high contrasts are related to the well-known stimulusdependent level of saturation of V1 neurons that was suggested to arise from a contrast normalization mechanism (Carandini and Heeger 1994; Heeger 1992).”
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Representational similarity analysis-connecting the branches of systems neuroscience
Kriegeskorte, N. (2008) · Frontiers in Systems Neuroscience · doi:10.3389/neuro.06.004.2008 · Cited by 3,355
DehazeNet: An End-to-End System for Single Image Haze Removal
Cai, B., Xu, X., Jia, K., Qing, C., & Tao, D. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2598681 · Cited by 3,367
“[33] proposed that spatial integration properties of complex cells can be described by a series of pooling operations.”
BackgroundRobust Object Recognition with Cortex-Like Mechanisms
Serre, T., Wolf, L., Bileschi, S., Riesenhuber, M., & Poggio, T. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.56 · Cited by 1,667
“1), respectively, the max-like behavior of a subclass of complex cells in V1 [31] and cells in V4 [32].”
BackgroundSelf-citationA feedforward architecture accounts for rapid categorization
Serre, T., Oliva, A., & Poggio, T. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0700622104 · Cited by 918
Self-citationObject Recognition with Features Inspired by Visual Cortex
Serre, T., Wolf, L., & Poggio, T. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2005.254 · Cited by 850
“in favor of the max operation has appeared [6, 9].”
BackgroundSelf-citation
Metadata
- Authors
- Lampl, I., Ferster, D., Poggio, T., & Riesenhuber, M.
- Affiliations
- Weizmann Institute of Science (IL)
- Massachusetts Institute of Technology (US)
- Georgetown University (US)
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2004-11
- Volume
- 92
- Issue
- 5
- Pages
- 2704-2713
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- OpenAlex
- W2161126623
- Cited by
- 139
- References
- 33
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 1 · 2020: 2 · 2019: 3 · 2018: 7 · 2017: 9 · 2016: 11 · 2015: 8 · 2014: 6 · 2013: 11 · 2012: 11
- FWCI
- 3.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Neurophysiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Eye Institute (R01 EY-04726, R01EY004726)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- complex cells, primary visual cortex, spatial integration, nonlinear summation, membrane potential, receptive fields, object recognition, invariant object recognition, cat visual system
- MeSH terms
- Animals, Cats, Female, Membrane Potentials, Pattern Recognition, Visual, Space Perception, Visual Cortex
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