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

Abstract

A B S T R A C TLanguages 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.

Uncovering the geometry of color space with magnetoencephalography (MEG)

“…This result cannot be attributed to differences in contrast of the stimuli (the stimuli were all matched in cone contrast). The result echoes observations in monkeys showing that reddish hues produce very high gamma oscillations [31], and provides a neural correlate for the preeminence of red among all chromatic colors in color naming [23][24][25].…”

“…One asymmetry reflects an interaction of luminance contrast and hue along the warm-cool axis of color space: warm colors were better decoded when they were relatively high luminance contrast, while cool colors were better decoded when they were relatively low luminance contrast. This asymmetry reflects a universal pattern in color naming in which "light" and "dark" are associated with "warm" and "cool" [23][24][25]. A second asymmetry shows that the neural representation elicited by stimuli of the same hue across luminance levels were more dissimilar for warm colors compared to cool colors.…”

“…Warm colors are associated with "light", and cool colors (blues, greens) are associated with "dark" among all languages, even those with the most limited numbers of consensus color terms [27]. Among the 11 basic color categories (red, pink, orange, yellow, brown, green, blue, purple), the cool colors (green, blue) are not distinguished from each other by differences in lightness, whereas the warm colors are [23][24][25]28]. Consistent with this universal pattern, participants often used different terms for the light and dark versions of warm colors and the same term for light and dark versions of the cool colors (Figure 1b).…”

“…We consider three universal aspects of color naming: First, warm colors such as reds and oranges are associated with "light" and cool colors such as blues and greens are associated with "dark" [23]. Second, among all languages there is a greater precision in naming warm colors compared to cool colors [24,25]. And third, after black and white, red is the most important basic color term [26].…”

People can use the placement of objects to infer communicative goals

“…The Tsimane' live in non-industrialized communities along the Maniqui river and have little exposure to market-integrated communities. Recent research has found that the Tsimane' differ from WEIRD populations (Western, educated, and from industrialized, rich, and democratic countries; Henrich et al 2010) in several cognitive domains including numberword learning[Piantadosi et al, 2014;Jara-Ettinger et al, 2017], color-word vocabulary[Conway et al, 2020;Gibson et al, 2017], and music perception[McDermott et al, 2016].…”