I describe complementary colors' physiology and functional roles in color vision, in a three-stage theory (receptor, opponent color, and complementary color stages). 40 specific roles include the complementary structuring of: S and L cones, opponent single cells, cardinal directions, hue cycle structure, hue constancy, trichromatic color mixture, additive/subtractive primaries, two unique hues, color mixture space, uniform hue difference, lightness-, saturation-, and wavelength/hue-discrimination, spectral sensitivity, chromatic adaptation, metamerism, chromatic induction, Helson-Judd effect, colored shadows, color rendering, warm-cool colors, brilliance, color harmony, Aristotle's flight of colors, white-black responsivity, Helmholtz-Kohlrausch effect, rainbows/halos/glories, dichromatism, spectral-sharpening, and trimodality of functions (RGB peaks, CMY troughs whose complementarism adapts functions to illuminant). The 40 specific roles fall into 3 general roles: color mixture, color constancy, and color perception. Complementarism evidently structures much of the visual process. Its physiology is evident in complementarism of cones, and opponent single cells in retina, LGN, and cortex. Genetics show our first cones were S and L, which are complementary in daylight D65, giving a standard white to aid chromatic adaptation. M cone later split from L to oppose the nonspectral (red and purple) hues mixed from S+L. Response curves and wavelength peaks of cones L, S, and (S+L), M, closely resemble, and lead to, those of opponent-color chromatic responses y, b, and r, g, a bimodal system whose summation gives spectral-sharpened trimodal complementarism (RGB peaks, CMY troughs). Spectral sharpening demands a post-receptoral, post-opponent-colors location, hence a third stage. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011

Complementary colors theory of color vision: physiology, color mixture, color constancy and color perception

Phosphenes, retinal discrete dark noise, negative afterimages and retinogeniculate projections: A new explanatory framework based on endogenous ocular luminescence.

Since the work of Semon was ‘rediscovered’ by Schacter in 1978, there has been a renewed interest is searching for the “engram” as the locus of memory in the brain and it has become popular to equate Hebb's cell assembly with Semon's engram. There have been many theories of memory involving some concept of synaptic change, culminating in the "Hebb Synapse" theory in 1949. However, Hebb said that the idea that any two cells or systems of cells that are repeatedly active at the same time will tend to become ‘associated’, was not his idea, but an old one. In this paper we give an overview of some of the theories of the neural basis of learning and memory before Hebb and describe the synaptic theory of William McDougall, which appears to have been an idea ahead of its time; so far ahead of its time, it was completely ignored by his contemporaries. We conclude with some comments by those who did not ignore McDougall’s theories and a short discussion on the fate of neuroscientists whose ideas were ignored when first presented, but were accepted as major insights many decades later.

/pdf/the-hebb-synapse-before-hebb-theories-of-synaptic-function-25cq0sc92o.pdf

The Hebb Synapse Before Hebb: Theories of Synaptic Function in Learning and Memory Before , With a Discussion of the Long-Lost Synaptic Theory of William McDougall.

Presently there are two dominant theories for human color vision: Young-Helmholtz-Maxwell's Trichromatic Theory
and Hering's Opponent-Color Theory. It has been widely accepted that the Trichromatic Theory holds true for retinal
color processing whereas the Opponent-Color Theory works for cortical color processing-this conception has become
the "Standard Model" for human color vision. My purposes in the present paper are threefold: First, to demonstrate that
the Opponent-Color Theory is fundamentally untenable, based on both theoretical and empirical grounds; second, to
resurrect a two-stage trichromatic model, in which both retinal and cortical color processing are trichromatic, proposed
by W. McDougall more than a century ago; and third, to map the cortical color processing stage (which directly
correlates with color consciousness) in this model to layer 4 within the primary visual cortex (V1) of the human brain.

A neurobiologically-based two-stage model for human color vision

I report a curious double helix in psychophysical data. As recently reported, color complementarism structures at least 40 functional roles in vision including all Red-, Green-, Blue-peaked functions (e.g., color matching functions, Helmholtz–Kohlrausch effect, saturation discrimination, lightness discrimination, and wavelength discrimination). These can be modeled from the relative spectral power distribution (SPD) function of complementary colors (at requisite power ratios to neutralize complements). So, the SPDs three-dimensional (3D) structure is of interest. Extended to the hue cycle, the SPD is plotted in a rectilinear graph of wavelength versus wavelength with radiance vertical to the plane. In this rectilinear color mixture space, the white locus representing the illuminant chromaticity is not a single point (representing the junction of complementary pairs of wavelengths) but a sinusoidal curve whose 3D structure is a double helix, representing an SPD and its complementary SPD. The structure's purpose is possibly to store and access global complementary colors data across illuminants. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 292–296, 2013

Helical structure of complementary colors' relative spectral distribution function

The contemporary "Standard Model" for human color vision is a two-stage model: The first stage consists of three types of receptors at the retina of the eye, and the second stage consists of three opponent-color neural channels: Red-Green, Blue-Yellow, and Black-White. In this paper I call upon the phenomena of complementary afterimages and of the "flight of colors" to show that this model is not an adequate explanation for these color phenomena in specific and for color vision in general. To remedy the theoretical inadequacy of the "Standard Model", I propose a neural stage for color complementarity directly corresponding to our color sensation. Mapping onto the anatomical organization of human visual system, I further suggest that layer 4C in the primary visual cortex is the neural substrate directly responsible for color complementarity in particular and for color appearance (that is, color consciousness) in general.

A Multi-Stage Neural Network Model for Human Color Vision

Presently there are two dominant theories for human color vision: Young-Maxwell-Helmholtz's trichromatic theory and Hering's opponent-color theory. It is widely purported that the trichromatic theory holds true for retinal color processing whereas the opponent-color theory works for cortical color processing. My purposes in the present paper are threefold: to demonstrate, based on both empirical and logical grounds, that the opponent-color theory is fundamentally untenable; to extend the trichromatic theory from retinal color processing to the cortical level; and to present a computational model based on neuroanatomical data for human color vision.

Empirically, the opponent-color theory is false because it runs against many lines of observational and experimental data. First of all, this theory claims that it is impossible for a human being to perceive red and green colors in the same place at the same time; now there have been several demonstrations (e.g., see [1] and [2]) clearly indicating that this assumption is unwarranted. Second, colors appearing in complementary afterimages and in color contrast conditions are complementary to stimulus colors—rather than opponent colors as the opponent theory supposes. Third, in the so-called flight-of-colors phenomenon, the predominant colors are the complementary colors of three primary colors (red, green, and blue) embraced by the trichromatic theory, not the four unique hues (red, green, yellow, and blue) as assumed by the opponent-color theory. Logically, the opponent-color theory needs to postulate a neural mechanism for mixing colors between red and green colors which in turn needs to turn off neural activities along the red and the green cardinalities—it is simply impossible to realize such a mechanism in any physical system.

In contrast to the opponent-color theory, the trichromatic color theory can easily be extended to cortical color processing. In fact, such a theoretical integration had been attempted by Rollett [3] and McDougall [4] more than a century ago—It is very unfortunate that their efforts had largely been forgotten. Here I attempt to use an extended Young-Maxwell-Helmholtz trichromatic theory to explain several color perception phenomena, including co-existence of red and green colors, both positive and negative afterimages, contrast colors, and flight-of-colors.

Based on the fact that many color phenomena are monocular, I further propose that, in the primate (including the humankind) visual system, lamina 4C in the primary visual cortex (V1) is the neural substrate for cortical trichromaticity—because this is the only cortical stage where neurons are predominantly monocular. I present a three-layer computational model to simulate the first three stages of human visual processing: the retina, the LGN, and layer 4C. By incorporating anatomical data of cell distributions and a scheme of neuronal population cardinality coding, the model can account for many essential features of trichromaticity: additive and subtractive color mixing, color complementarity in afterimages and in contrast colors, and color transparency.

Conclusions
In summary, I contend that the trichromatic theory can explain both retinal and cortical color processing and that the opponent-color theory is fundamentally erroneous. Furthermore, I suggest that the neuronal trichromatic stage directly corresponding to human color sensation is layer 4C in V1.

/pdf/a-neuroanatomically-based-model-for-human-color-vision-3re7a0cot9.pdf

A neuroanatomically-based model for human color vision

I investigate the computational and the neural mechanisms for suppressing retinal vascular image (RVI) and attempt to generalize some conclusions to other visual suppression phenomena First I present a new observation demonstrating RVI in negative afterimages Then I discuss RVI suppression from a computational perspective and suggest: (1) RVI is always there in the retinal stimulation; (2) RVI must be actively suppressed on a moment-by-moment basis; and (3) in order to suppress RVI, there must exist an internal representation of RVI at a monocular stage Mapping onto the organization of the primate visual system, particularly based on Adams and Horton's neuroanatomical demonstration of a complete representation of retinal blood vessels in layer 4C of V1, I propose that layer 4C is in fact the neural site for RVI suppression Finally, I suggest that layer 4C is the neural substrate for phenomenal visual consciousness (particularly, color and brightness consciousness).

/pdf/computational-and-neural-mechanisms-for-visual-suppression-41u3c26wi3.pdf

Computational and neural mechanisms for visual suppression

Thus Spoke Laozi

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Charles Q. Wu

Author Tools

Chat about Author