Flower Color as Predictor for Nectar Reward Quantity in an Alpine Flower Community

Entomophilous plants have evolved colorful floral displays to attract flower visitors to achieve pollination. Although many insects possess innate preferences for certain colors, the underlying proximate and ultimate causes for this behavior are still not well understood. It has been hypothesized that the floral rewards, e.g., sugar content, of plants belonging to a particular color category correlate with the preference of the flower visitors. However, this hypothesis has been tested only for a subset of plant communities worldwide. Bumble bees are the most important pollinators in alpine environments and show a strong innate preference for (bee) “UV-blue” and “blue” colors. We surveyed plants visited by bumble bees in the subalpine and alpine zones (>1,400 m a.s.l.) of the Austrian Alps and measured nectar reward and spectral reflectance of the flowers. We found that the majority of the 105 plant samples visited by bumble bees fall into the color categories “blue” and “blue-green” of a bee-specific color space. Our study shows that color category is only a weak indicator for nectar reward quantity; and due to the high reward variance within and between categories, we do not consider floral color as a reliable signal for bumble bees in the surveyed habitat. Nevertheless, since mean floral reward quantity differs between categories, naïve bumble bees may benefit from visiting flowers that fall into the innately preferred color category during their first foraging flights.

The evolution of color naming reflects pressure for efficiency: Evidence from the recent past

It has been proposed that semantic systems evolve under pressure for efficiency. This hypothesis has so far been supported largely indirectly, by synchronic cross-language comparison, rather than directly by diachronic data. Here, we directly test this hypothesis in the domain of color naming, by analyzing recent diachronic data from Nafaanra, a language of Ghana and Côte d'Ivoire, and comparing it with quantitative predictions derived from the mathematical theory of efficient data compression. We show that color naming in Nafaanra has changed over the past four decades while remaining near-optimally efficient, and that this outcome would be unlikely under a random drift process that maintains structured color categories without pressure for efficiency. To our knowledge, this finding provides the first direct evidence that color naming evolves under pressure for efficiency, supporting the hypothesis that efficiency shapes the evolution of the lexicon.

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.

Lexical Color Categories

Color is a continuous variable, and humans can distinguish more than a million colors, yet world color lexicons contain no more than a dozen basic color terms. It has been understood for 160 years that the number of color terms in a lexicon varies greatly across languages, yet the lexical color categories defined by these terms are similar worldwide. Starting with the seminal study by Berlin and Kay, this review considers how and why this is so. Evidence from psychological, linguistic, and computational studies has advanced our understanding of how color categories came into being, how they contribute to our shared understanding of color, and how the resultant categories influence color perception and cognition. A key insight from the last 50 years of research is how human perception and the need for communication within a society worked together to create color lexicons that are somewhat diverse, yet show striking regularities worldwide.

Interactions Between Visual Working Memory, Attention, and Color Categories: a Pupillometry Study

Recent studies have found that visual working memory (VWM) for color shows a categorical bias: observers typically remember colors as more prototypical to the category they belong to than they actually are. Here, we further examine color-category effects on VWM using pupillometry. Participants remembered a color for later reproduction on a color wheel. During the retention interval, a colored probe was presented, and we measured the pupil constriction in response to this probe, assuming that the strength of constriction reflects the visual saliency of the probe. We found that the pupil initially constricted most strongly for non-matching colors that were maximally different from the memorized color; this likely reflects a lack of visual adaptation for these colors, which renders them more salient than memory-matching colors (shown before). Strikingly, this effect reversed later in time, such that pupil constriction was more prolonged for memory-matching colors as compared to non-matching colors; this likely reflects that memory-matching colors capture attention more strongly, and perhaps for a longer time, than non-matching colors do. We found no effects of color categories on pupil constriction: after controlling for color distance, (non-matching) colors from the same category as the memory color did not result in a different pupil response as compared to colors from a different category; however, we did find that behavioral responses were biased by color categories. In summary, we found that pupil constriction to colored probes reflects both visual adaptation and VWM content, but, unlike behavioral measures, is not notably affected by color categories.

Children's use of generic labels, discreteness, and stability to form a novel category

Children hold rich essentialist beliefs about natural and social categories, representing them as discrete (mutually exclusive with sharp boundaries) and stable (with membership remaining constant over an individual’s lifespan). Children use essential categories to make inductive inferences about individuals. How do children determine what categories to consider essential and to use as an inductive base? Although much research has demonstrated children’s use of labels to form categories, here we explore whether children might also use the observed discreteness or stability of a trait to form categories based on that trait. In the present study, we taught children about novel creatures and provided them with a cue (discreteness, stability, labels, or no cue) to form texture categories rather than shape or color categories. Experiment 1 found that children (4–6 years, n = 140) used labels but not discreteness or stability cues to form texture categories more often than at baseline. Experiment 2 (5–6 years, n = 152) found that children who later recognized the stability and discreteness cues used them to form categories more often than those who did not later recognize the cues, but were still overall less likely to use these cues than to use labels cues. Results underscore the unique importance of labels as a cue for category formation and suggest that children do not readily rely on the stability and discreteness of a trait to form animate categories despite readily inferring that such categories are stable and discrete. Implications for natural and social category representations are discussed.

Neural Hierarchy of Color Categorization: From Prototype Encoding to Boundary Encoding

A long-standing debate exists on how our brain assigns the fine-grained perceptual representation of color into discrete color categories. Recent functional magnetic resonance imaging (fMRI) studies have identified several regions as the candidate loci of color categorization, including the visual cortex, language-related areas, and non-language-related frontal regions, but the evidence is mixed. Distinct from most studies that emphasized the representational differences between color categories, the current study focused on the variability among members within a category (e.g., category prototypes and boundaries) to reveal category encoding in the brain. We compared and modeled brain activities evoked by color stimuli with varying distances from the category boundary in an active categorization task. The frontal areas, including the inferior and middle frontal gyri, medial superior frontal cortices, and insular cortices, showed larger responses for colors near the category boundary than those far from the boundary. In addition, the visual cortex encodes both within-category variability and cross-category differences. The left V1 in the calcarine showed greater responses to colors at the category center than to those far from the boundary, and the bilateral V4 showed enhanced responses for colors at the category center as well as colors around the boundary. The additional representational similarity analyses (RSA) revealed that the bilateral insulae and V4a carried information about cross-category differences, as cross-category colors exhibited larger dissimilarities in brain patterns than within-category colors. Our study suggested a hierarchically organized network in the human brain during active color categorization, with frontal (both lateral and medial) areas supporting domain-general decisional processes and the visual cortex encoding category structure and differences, likely due to top-down modulation.

Emergent Color Categorization in a Neural Network trained for Object Recognition

Color is a prime example of categorical perception, yet it is still unclear why and how color categories emerge. The key questions revolve around to what extent perceptual and linguistic processes shape categories. While prelinguistic infants and animals appear to treat color categorically, several recent attempts to model category formation have successfully utilized communicative concepts to predict color categories. Considering this apparent discrepancy, we take a different approach. Rather than modeling categories directly, we focus on the potential emergence of color categories as the result of acquiring basic visual skills. For this, we investigated whether color is represented categorically in a convolutional neural network (CNN) trained to recognize objects in natural images. We systematically trained novel output layers to the CNN for a color classification task, and found that clear borders arise between novel (non-training) colors that are largely invariant to the training colors. We confirmed these border locations by searching for the optimal border placement using an evolutionary algorithm that relies on the principle of categorical perception. Our findings also extend to stimuli with multiple, colored, words of varying color contrast, as well as colored objects with larger colored surfaces. These results provide strong evidence that color categorization can emerge with the development of object recognition.

Slow Spread of SARS-CoV-2 in Southern Brazil Over a 6-Month Period: Report on 8 Sequential Statewide Serological Surveys Including 35611 Participants

Objectives. To evaluate the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) over 6 months in the Brazilian State of Rio Grande do Sul (population 11.3 million), based on 8 serological surveys. Methods. In each survey, 4151 participants in round 1 and 4460 participants in round 2 were randomly sampled from all state regions. We assessed presence of antibodies against SARS-CoV-2 using a validated lateral flow point-of-care test; we adjusted figures for the time-dependent decay of antibodies. Results. The SARS-CoV-2 antibody prevalence increased from 0.03% (95% confidence interval [CI] = 0.00%, 0.34%; 1 in every 3333 individuals) in mid-April to 1.89% (95% CI = 1.36%, 2.54%; 1 in every 53 individuals) in early September. Prevalence was similar across gender and skin color categories. Older adults were less likely to be infected than younger participants. The proportion of the population who reported leaving home daily increased from 21.4% (95% CI = 20.2%, 22.7%) to 33.2% (95% CI = 31.8%, 34.5%). Conclusions. SARS-CoV-2 infection increased slowly during the first 6 months in the state, differently from what was observed in other Brazilian regions. Future survey rounds will continue to document the spread of the pandemic. (Am J Public Health. Published online ahead of print June 29, 2021: e1–e9. https://doi.org/10.2105/AJPH.2021.306351 )