The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Color in the Cortex: single- and double-opponent cells
Open accessAbstract
This is a review of the research during the past 25 years on cortical processing of color signals. At the beginning of the period the modular view of cortical processing predominated. However, at present an alternative view, that color and form are linked inextricably in visual cortical processing, is more persuasive than it seemed in 1985. Also, the role of the primary visual cortex, V1, in color processing now seems much larger than it did in 1985. The re-evaluation of the important role of V1 in color vision was caused in part by investigations of human V1 responses to color, measured with functional magnetic resonance imaging, fMRI, and in part by the results of numerous studies of single-unit neurophysiology in non-human primates. The neurophysiological results have highlighted the importance of double-opponent cells in V1. Another new concept is population coding of hue, saturation, and brightness in cortical neuronal population activity.
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Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Yarbus, A. L. (1967) · doi:10.1007/978-1-4899-5379-7 · Cited by 3,304
The contrast sensitivity of retinal ganglion cells of the cat
Enroth-Cugell, C., & Robson, J. G. (1966) · The Journal of Physiology · doi:10.1113/jphysiol.1966.sp008107 · Cited by 2,625
The functional logic of cortical connections
Zeki, S., & Shipp, S. (1988) · Nature · doi:10.1038/335311a0 · Cited by 1,067 · cited 1×
“…results on the visual cortex from the late 1980s that were interpreted in terms of the modular view (after Hubel & Livingstone, 1987; Zeki & Shipp, 1988) and then move on to reviewing more recent research on color signals in the cortex that either still reflects the modular view or…”
Population coding of shape in area V4
Pasupathy, A., & Connor, C. E. (2002) · Nature Neuroscience · doi:10.1038/972 · Cited by 552
Cited by
Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?
Kruger, N., Janssen, P., Kalkan, S., Lappe, M., Leonardis, A., Piater, J., Rodriguez-Sanchez, A. J., & Wiskott, L. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.272 · Cited by 362
Neural elements for predictive coding
Shipp, S. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.01792 · Cited by 340
Layer-specific fMRI reflects different neuronal computations at different depths in human V1
Olman, C. A., Harel, N., Feinberg, D. A., He, S., Zhang, P., Ugurbil, K., & Yacoub, E. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032536 · Cited by 194
Visual Functions Generating Conscious Seeing
Lamme, V. A. F. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00083 · Cited by 136
Running rewires the neuronal network of adult-born dentate granule cells
Vivar, C., Peterson, B. D., & van Praag, H. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.031 · Cited by 143
Metadata
- Authors
- Shapley, R., & Hawken, M. J.
- Venue
- Vision Research
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 51
- Issue
- 7
- Pages
- 701-717
- ISSN
- 0042-6989 (ISSN-L)
- OpenAlex
- W2018162634
- Cited by
- 336
- References
- 5
- FWCI
- 9.35
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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