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Cited by 74

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Color Contrast in Macaque V1

Conway, B. R.·2002·Cerebral Cortex

Abstract

We explored the neural basis for spatial color contrast (red looks redder surrounded by green) and temporal color contrast (red looks redder if preceded by green) in primary visual cortex (V1) of the alert macaque. Using pairs of stimuli, we found a subset of neurons that gave stronger responses to sequences of red and green spots and stronger responses to adjacent red and green spots. These cells combined their cone inputs linearly: for a red-ON-center cell, the sum of the OFF response to green and the ON response to red predicted the peak response to red preceded by green. These 'color' cells, which could underlie hue discrimination because they show cone opponency, could mediate spatial and temporal color contrast. In contrast, the majority of cortical cells, which do not show overt cone opponency but which are often orientation tuned and/or direction selective, are by themselves incapable of mediating hue discrimination. The remarkable degree of specialization shown by cells in V1, especially that of the double-opponent color cells, is discussed.

Overview

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Registry

Crossref · 10.1093/cercor/12.9.915

Cites

55 of 55 references verified0 citation errors · 0 not checkable

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Citations

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Metadata

Authors
Conway, B. R.
Venue
Cerebral Cortex
Published
2002-09-01
Volume
12
Issue
9
Pages
915-925
ISSN
1460-2199
Cited by
74
References
55

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CoChat. (2026). Citation check: Color Contrast in Macaque V1. https://app.cochat.ai/papers/10.1093/cercor/12.9.915
The paper
Conway, B. R. (2002). Color Contrast in Macaque V1. Cerebral Cortex. https://doi.org/10.1093/cercor/12.9.915

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.