ArticleVision research2018
Measurements of neuronal color tuning: Procedures, pitfalls, and alternatives.
Article in Vision research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Exploiting colour space geometry for visual stimulus design across animals.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- Article
- A quadratic model captures the human V1 response to variations in chromatic direction and contrast.eLife · 2021Article
- Spatial receptive field structure of double-opponent cells in macaque V1.Journal of neurophysiology · 2021Article
- A tour of contemporary color vision research.Vision research · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Measuring the color tuning of visual neurons is important for understanding the neural basis of vision, but it is challenging because of the inherently three-dimensional nature of color. Color tuning cannot be represented by a one-dimensional curve, and measuring three-dimensional tuning curves is difficult. One approach to addressing this challenge is to analyze neuronal color tuning data through the lens of mathematical models that make assumptions about the shapes of tuning curves. In this paper, we discuss the linear-nonlinear cascade model as a platform for measuring neuronal color tuning. We compare fitting this model by three techniques: two using response-weighted averaging and one using numerical optimization of likelihood. We highlight the advantages and disadvantages of each technique and emphasize the effects of the stimulus distribution on color tuning measurements.
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Registered trials
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