History constrains the evolution of efficient color naming, enabling historical inference.

Color naming in natural languages is not arbitrary: It reflects efficient partitions of perceptual color space [T. Regier, P. Kay, N. Khetarpal, Proc. Natl. Acad. Sci. U.S.A. 104, 1436-1441 (2007)] modulated by the relative needs to communicate about different colors [C. Twomey, G. Roberts, D. Brainard, J. Plotkin, Proc. Natl. Acad. Sci. U.S.A. 118, e2109237118 (2021)]. These psychophysical and communicative constraints help explain why languages around the world have remarkably similar, but not identical, mappings of colors to color terms. Languages converge on a small set of efficient representations.But languages also evolve, and the number of terms in a color vocabulary may change over time. Here we show that history, i.e. the existence of an antecedent color vocabulary, acts as a nonadaptive constraint that biases the choice of efficient solution as a language transitions from a vocabulary of size [Formula: see text] to [Formula: see text] terms. Moreover, as efficient vocabularies evolve to include more terms they explore a smaller fraction of all possible efficient vocabularies compared to equally sized vocabularies constructed de novo. This path dependence of the cultural evolution of color naming presents an opportunity. Historical constraints can be used to reconstruct ancestral color vocabularies, allowing us to answer long-standing questions about the evolutionary sequences of color words, and enabling us to draw inferences from phylogenetic patterns of language change.

What we talk about when we talk about colors.

Names for colors vary widely across languages, but color categories are remarkably consistent. Shared mechanisms of color perception help explain consistent partitions of visible light into discrete color vocabularies. But the mappings from colors to words are not identical across languages, which may reflect communicative needs-how often speakers must refer to objects of different color. Here we quantify the communicative needs of colors in 130 different languages by developing an inference algorithm for this problem. We find that communicative needs are not uniform: Some regions of color space exhibit 30-fold greater demand for communication than other regions. The regions of greatest demand correlate with the colors of salient objects, including ripe fruits in primate diets. Our analysis also reveals a hidden diversity in the communicative needs of colors across different languages, which is partly explained by differences in geographic location and the local biogeography of linguistic communities. Accounting for language-specific, nonuniform communicative needs improves predictions for how a language maps colors to words, and how these mappings vary across languages. Our account closes an important gap in the compression theory of color naming, while opening directions to study cross-cultural variation in the need to communicate different colors and its impact on the cultural evolution of color categories.

Evaluating recall error in preschoolers: Category expectations influence episodic memory for color.

Despite limited memory capacity, children are exceptional learners. How might children engage in meaningful learning despite limited memory systems? Past research suggests that adults integrate category knowledge and noisy episodic traces to aid recall when episodic memory is noisy or incomplete (e.g. Hemmer & Steyvers, 2009a,b). We suspect children utilize a similar process but integrate category and episodic traces in recall to a different degree. Here we conduct two experiments to empirically assess children's color category knowledge (Study 1) and recall of target hue values (Study 2). In Study 1, although children's generated hue values appear to be noisier than adults, we found no significant difference between children and adult's generated color category means (prototypes), suggesting that preschool-aged children's color categories are well established. In Study 2, we found that children's (like adult's) free recall of target hue values regressed towards color category means. We implemented three probabilistic memory models: one that combines category knowledge and specific target information (Integrative), a category only (Noisy Prototype) model, and a target only (Noisy Target) model to computationally evaluate recall performance. Consistent with previous studies with older children (Duffy, Huttenlocher, & Crawford, 2006), quantitative fits of the models to aggregate group-level data provided strong support for the Integrative process. However, at the individual subject level, a greater proportion of preschoolers' recall was better fit by a Prototype only model. Our results provide evidence that the integration of category knowledge in episodic memory comes online early and strongly. Implications for how the greater reliance on category knowledge by preschoolers relative to adults might track with developmental shifts in relational episodic memory are discussed.

Focal colors across languages are representative members of color categories.

Focal colors, or best examples of color terms, have traditionally been viewed as either the underlying source of cross-language color-naming universals or derived from category boundaries that vary widely across languages. Existing data partially support and partially challenge each of these views. Here, we advance a position that synthesizes aspects of these two traditionally opposed positions and accounts for existing data. We do so by linking this debate to more general principles. We show that best examples of named color categories across 112 languages are well-predicted from category extensions by a statistical model of how representative a sample is of a distribution, independently shown to account for patterns of human inference. This model accounts for both universal tendencies and variation in focal colors across languages. We conclude that categorization in the contested semantic domain of color may be governed by principles that apply more broadly in cognition and that these principles clarify the interplay of universal and language-specific forces in color naming.

The color lexicon of American English.

This article describes color naming by 51 American English-speaking informants. A free-naming task produced 122 monolexemic color terms, with which informants named the 330 Munsell samples from the World Color Survey. Cluster analysis consolidated those terms into a glossary of 20 named color categories: the 11 Basic Color Term (BCT) categories of Berlin and Kay (1969, p. 2) plus nine nonbasic chromatic categories. The glossed data revealed two color-naming motifs: the green-blue motif of the World Color Survey and a novel green-teal-blue motif, which featured peach, teal, lavender, and maroon as high-consensus terms. Women used more terms than men, and more women expressed the novel motif. Under a constrained-naming protocol, informants supplied BCTs for the color samples previously given nonbasic terms. Most of the glossed nonbasic terms from the free-naming task named low-consensus colors located at the BCT boundaries revealed by the constrained-naming task. This study provides evidence for continuing evolution of the color lexicon of American English, and provides insight into the processes governing this evolution.

Emergent color categorization in a neural network trained for object recognition.

Color is a prime example of categorical perception, yet it is unclear why and how color categories emerge. On the one hand, prelinguistic infants and several animals treat color categorically. On the other hand, recent modeling endeavors have successfully utilized communicative concepts as the driving force for color categories. Rather than modeling categories directly, we investigate the potential emergence of color categories as a result of acquiring visual skills. Specifically, we asked whether color is represented categorically in a convolutional neural network (CNN) trained to recognize objects in natural images. We systematically trained new output layers to the CNN for a color classification task and, probing novel colors, found borders that are largely invariant to the training colors. The border locations were confirmed using an evolutionary algorithm that relies on the principle of categorical perception. A psychophysical experiment on human observers, analogous to our primary CNN experiment, shows that the borders agree to a large degree with human category boundaries. These results provide evidence that the development of basic visual skills can contribute to the emergence of a categorical representation of color.

"Red-Green" or "Brown-Green" Dichromats? The Accuracy of Dichromat Basic Color Terms Metacognition Supports Denomination Change.

Two experiments compared "Red-Green" (R-G) dichromats' empirical and metacognized capacities to discriminate basic color categories (BCCs) and to use the corresponding basic color terms (BCTs). A first experiment used a 102-related-colors set for a pointing task to identify all the stimuli that could be named with each BCT by each R-G dichromat type (8 protanopes and 9 deuteranopes). In a second experiment, a group of R-G dichromats (15 protanopes and 16 deuteranopes) estimated their difficulty discriminating BCCs-BCTs in a verbal task. The strong coincidences between the results derived from the pointing and the verbal tasks indicated that R-G dichromats have very accurate metacognition about their capacities (they only had considerable difficulty discriminating 13 out of the total of 55 possible BCT pairs) and limitations (Brown-Green and Blue-Purple pairs were rated especially difficult to differentiate) in the use of BCTs. Multidimensional scaling (MDS) solutions derived from both tasks were very similar: BCTs in R-G dichromats were properly represented in 2D MDS solutions that clearly show one chromatic dimension and one achromatic dimension. Important concordances were found between protanopes and deuteranopes. None of these dichromats showed substantial difficulty discriminating the Red-Green pair. So, to name them "R-G" dichromats is misleading considering their empirical capacities and their metacognition. Further reasons to propose the use of the alternative denomination "Brown-Green" dichromats are also discussed. We found some relevant differences between the "Brown-Green" dichromats' empirical and self-reported difficulties using BCTs. Their metacognition can be considered a "caricature" of their practical difficulties. This caricature omits some difficulties including their problems differentiating "white" and "black" from other BCTs, while they overestimate their limitations in differentiating the most difficult pairs (Brown-Green and Blue-Purple). Individual differences scaling (INDSCAL) analyses indicated that the metacognition regarding the use of BCTs in "Brown-Green" dichromats, especially deuteranopes, is driven slightly more by the chromatic dimension and driven slightly less by the achromatic dimension, than their practical use of BCTs. We discuss the relevance of our results in the framework of the debate between the linguistic relativity hypothesis (LRH) and the universal evolution (UE) theories.

Color Space Geometry Uncovered with Magnetoencephalography.

The geometry that describes the relationship among colors, and the neural mechanisms that support color vision, are unsettled. Here, we use multivariate analyses of measurements of brain activity obtained with magnetoencephalography to reverse-engineer a geometry of the neural representation of color space. The analyses depend upon determining similarity relationships among the spatial patterns of neural responses to different colors and assessing how these relationships change in time. We evaluate the approach by relating the results to universal patterns in color naming. Two prominent patterns of color naming could be accounted for by the decoding results: the greater precision in naming warm colors compared to cool colors evident by an interaction of hue and lightness, and the preeminence among colors of reddish hues. Additional experiments showed that classifiers trained on responses to color words could decode color from data obtained using colored stimuli, but only at relatively long delays after stimulus onset. These results provide evidence that perceptual representations can give rise to semantic representations, but not the reverse. Taken together, the results uncover a dynamic geometry that provides neural correlates for color appearance and generates new hypotheses about the structure of color space.

Communication efficiency of color naming across languages provides a new framework for the evolution of color terms.

Languages vary in their number of color terms. A widely accepted theory proposes that languages evolve, acquiring color terms in a stereotyped sequence. This theory, by Berlin and Kay (BK), is supported by analyzing best exemplars ("focal colors") of basic color terms in the World Color Survey (WCS) of 110 languages. But the instructions of the WCS were complex and the color chips confounded hue and saturation, which likely impacted focal-color selection. In addition, it is now known that even so-called early-stage languages nonetheless have a complete representation of color distributed across the population. These facts undermine the BK theory. Here we revisit the evolution of color terms using original color-naming data obtained with simple instructions in Tsimane', an Amazonian culture that has limited contact with industrialized society. We also collected data in Bolivian-Spanish speakers and English speakers. We discovered that information theory analysis of color-naming data was not influenced by color-chip saturation, which motivated a new analysis of the WCS data. Embedded within a universal pattern in which warm colors (reds, oranges) are always communicated more efficiently than cool colors (blues, greens), as languages increase in overall communicative efficiency about color, some colors undergo greater increases in communication efficiency compared to others. Communication efficiency increases first for yellow, then brown, then purple. The present analyses and results provide a new framework for understanding the evolution of color terms: what varies among cultures is not whether colors are seen differently, but the extent to which color is useful.

Basic Color Terms (BCTs) and Categories (BCCs) in Three Dialects of the Spanish Language: Interaction Between Cultural and Universal Factors.

Two experiments were performed to identify and compare the Basic Color Terms (BCTs) and the Basic Color Categories (BCCs) included in three dialects (Castilian, Mexican, and Uruguayan) of the Spanish language. Monolexemic Elicited lists were used in the first experiment to identify the BCTs of each dialect. Eleven BCTs appeared for the Spanish and the Mexican, and twelve did so for the Uruguayan. The six primary BCTs (rojo "red," verde "green," amarillo "yellow," azul "blue," negro "black," and blanco "white") appeared in the three dialects. This occurred for only three derived BCTs (gris "gray," naranja "orange," and rosa "pink") but not for the other five derived BCTs (celeste "sky blue," marrón "brown," café "brown," morado "purple," and violeta "purple"). Color transitions were used in the second experiment for two different tasks. Extremes naming task was used to determine the relation between two different dialects' BCTs: equality, equivalence or difference. The results provided the first evidence for marrón "brown" and café "brown" being equivalent terms for the same BCC (brown in English) as is the case of morado "purple" and violeta "purple." Uruguayan celeste "sky blue" had no equivalent BCT in the other two dialects. Boundary delimitation task required the selection of the color in the boundary between two categories. The task was used to reasonably estimate the volume occupied by each BCC in the color space considering its chromatic area and lightness range. Excluding sky blue (celeste "sky blue") and blue (azul "blue"), the other BCCs color volumes were similar across the three dialects. Uruguayan sky blue and blue volumes conjointly occupied the portion of the color space corresponding to the Castilian and Mexican blue BCC. The fact that the BCT celeste "sky blue" only appeared in Uruguayan very probably derived from specific cultural factors (the use of the color in the flags and the arrival of an important number of Italian immigrants). Nevertheless, these cultural factors seem to nurture from a perceptive structuring of the color space, which nature is universal, as the boundaries of this category can be delimited from the responses of Spanish and Mexican participants.

Variations in normal color vision. VII. Relationships between color naming and hue scaling.

A longstanding and unresolved question is how observers construct a discrete set of color categories to partition and label the continuous variations in light spectra, and how these categories might reflect the neural representation of color. We explored the properties of color naming and its relationship to color appearance by analyzing individual differences in color-naming and hue-scaling patterns, using factor analysis of individual differences to identify separate and shared processes underlying hue naming (labeling) and hue scaling (color appearance). Observers labeled the hues of 36 stimuli spanning different angles in cone-opponent space, using a set of eight terms corresponding to primary (red, green, blue, yellow) or binary (orange, purple, blue-green, yellow-green) hues. The boundaries defining different terms varied mostly independently, reflecting the influence of at least seven to eight factors. This finding is inconsistent with conventional color-opponent models in which all colors derive from the relative responses of underlying red-green and blue-yellow dimensions. Instead, color categories may reflect qualitatively distinct attributes that are free to vary with the specific spectral stimuli they label. Inter-observer differences in color naming were large and systematic, and we examined whether these differences were associated with differences in color appearance by comparing the hue naming to color percepts assessed by hue scaling measured in the same observers (from Emery et al., 2017). Variability in both tasks again depended on multiple (7 or 8) factors, with some Varimax-rotated factors specific to hue naming or hue scaling, but others common to corresponding stimuli for both judgments. The latter suggests that at least some of the differences in how individuals name or categorize color are related to differences in how the stimuli are perceived.