Luminance-dependent hue shift in protanopes

For normal trichromats, the hue of a light can change as its luminance varies. This Bezold-Brücke (B-B) hue shift is commonly attributed to nonlinearity in the blue–yellow opponent system. In the present study, we questioned whether protanopes experience analogous changes. Two protanopes (Ps) viewed spectral lights at six luminance levels across three log steps. Two normal trichromats (NTs) were tested for comparison. A variant of the color-naming method was used, with an additional “white” term. To overcome the difficulty of Ps’ idiosyncratic color naming, we converted color-naming functions into individual color spaces, by way of interstimulus similarities and multidimensional scaling (MDS). The color spaces describe each stimulus in terms of spatial coordinates, so that hue shifts are measured geometrically, as displacements along specific dimensions. For the NTs, a B-B shift derived through MDS agreed well with values obtained directly by matching color-naming functions. A change in color appearance was also observed for the Ps, distinct from that in perceived brightness. This change was about twice as large as the B-B shift for NTs and combined what the latter would distinguish as hue and saturation shifts. The protanopic analogue of the B-B shift indicates that the blue–yellow nonlinearity persists in the absence of a red–green signal. In addition, at mesopic levels (# 38 td), the Ps’ MDS solution was two dimensional at longer wavelengths, suggesting rod input. Conversely, at higher luminance levels (76 td–760 td) the MDS solution was essentially one dimensional, placing a lower limit on S-cone input at longer wavelengths

A whiter shade of pale, a blacker shade of dark: Parameters of spatially induced blackness

The surface-mode property of “blackness” is induced by simultaneous contrast with an adjacent, more luminant surround. As numerous studies have shown, the degree of blackness induced within an achromatic test field is a function of the relative luminance of the adjacent chromatic inducing field, but not of its hue. But in the converse case of chromatic test fields, susceptibility to blackening has been reported to vary with wavelength. The present study investigates this possibility, that some wavelengths are more susceptible. We also questioned whether “white” and “black” sensory components function as opposites in blackness appearance. We recorded the appearance of a central monochromatic test field of constant luminance (10 cd/m2), with wavelength ranging across the visible spectrum, while a broadband white annulus was set to six luminance levels ranging across three log steps. Three color-normal observers followed a color-naming technique. All six opponent-hue names and their combinations were response options; blackness and whiteness in the test field could therefore be reported independently. Of primary interest were the achromatic responses. When represented within a multidimensional space, these revealed the “white-to-black” dimension but in addition a quality ~dimension! of “desaturation.” Compared against chromatic properties of the test field, the results provide evidence that blackness is a function of inducing field brightness (not luminance). This result is in accord with observations made by Shinomori et al. (1997) using a different procedure. We conclude that blackness induction occurs at a stage of visual processing subsequent to the origin of the brightness signal from a combination of opponent-process channels

Variation of chromatic discrimination across the lifespan

The present study, an extension of Paramei (J. Opt. Soc. Am. A, 29, A290, 2012), provides normative data on chromatic discrimination, using the Cambridge Colour Test, for normal trichromats aged 10–88 years. Findings are in accord with a two-phase variation across the lifespan: chromatic sensitivity improves in adolescence, reaches a maximum around 30 years, and then undergoes a gradual decrease. Indicative parameters are Protan (P), Deutan (D) and Tritan (T) vector lengths; and major axes and axis ratios of Ellipses. Trivector data are modeled as non-monotonic combinations of power functions, with goodness-of-fits R2P=0.23, R2D=0.23, R2T=0.45. For advancing age, sensitivity decline in all chromatic systems was confirmed, though with a marked acceleration after 60 years (reflected by the power function exponent > 1) and more pronounced for the Tritan system

Facial-Expression Affective Attributes and their Configural Correlates: Components and Categories

The present study investigates the perception of facial expressions of emotion, and explores the relation between the configural properties of expressions and their subjective attribution. Stimuli were a male and a female series of morphed facial expressions, interpolated between prototypes of seven emotions (happiness, sadness, fear, anger, surprise and disgust, and neutral) from Ekman and Friesen (1976). Topographical properties of the stimuli were quantified using the Facial Expression Measurement (FACEM) scheme. Perceived dissimilarities between the emotional expressions were elicited using a sorting procedure and processed with multidimensional scaling. Four dimensions were retained in the reconstructed facial-expression space, with positive and negative expressions opposed along D1, while the other three dimensions were interpreted as affective attributes distinguishing clusters of expressions categorized as “Surprise-Fear,” “Anger,” and “Disgust.” Significant relationships were found between these affective attributes and objective facial measures of the stimuli. The findings support a componential explanatory scheme for expression processing, wherein each component of a facial stimulus conveys an affective value separable from its context, rather than a categorical-gestalt scheme. The findings further suggest that configural information is closely involved in the decoding of affective attributes of facial expressions. Configural measures are also suggested as a common ground for dimensional as well as categorical perception of emotional faces.Este estudio investiga la percepción de las expresiones faciales de la emoción y explora la relación entre las propiedades configurales de las expresiones y su atribución subjetiva. Los estímulos eran una serie de expresiones faciales transformadas por ordenador, interpuestas entre los prototipos de siete emociones (felicidad, tristeza, miedo, ira, sorpresa, asco y neutral) tomados de Ekman y Friesen (1976). Las propiedades topográficas de los estímulos se cuantificaron mediante el esquema Facial Expression Measurement (FACEM). Las disimilaridades percibidas entre las expresiones emocionales se elicitaron mediante un procedimiento de clasificación y se procesaron con escalonamiento multidimensional. Se retuvieron cuatro dimensiones en el espacio facial-expresión reconstruido, con expresiones positivas y negativas contrapuestas a lo largo de D1, y las restantes tres dimensiones se interpretaron como atributos afectivos, distinguiendo clusters de expresiones clasificadas como “Sorpresa/Miedo”, “Ira”, y “Asco”. Se hallaron relaciones significativas entre estos atributos afectivos y las medidas faciales objetivas de los estímulos. Los resultados apoyan un esquema explicativo componencial para el procesamiento de las expresiones, en el que cada componente de un estímulo facial conlleva un valor afectivo separable de su contexto, más que un esquema categórico de tipo Gestalt. Además sugieren que la información configural juega un papel importante en la decodificación de los atributos afectivos de las expresiones faciales Además, sugieren que las medidas configurales constituyen en terreno común de la percepción dimensional y categórica de las caras emocionales

Editorial: Color and Form Perception: Straddling the Boundary

The Editorial on the Research Topic Color and Form Perception: Straddling the Boundary For many years, the dominating stance in neuroscience was that visual information processing is characterized by feature analysis (Hubel and Wiesel, 1959), followed by convergence and synthesis in a cascade of information processing stages (Hubel and Livingstone, 1987). In this cascade, color and features, such as orientation of achromatic contour segments, are initially separate (Zeki, 1978). So the question of how color and form perception are related was simply: At what level of processing do chromatic and achromatic features come together? This question has taken a different form today. In the present volume, whereas Moutoussis presents a contemporary version of this classical view, Rentzeperis et al. argue that neuroscience has moved on to accommodate broadband selectivity and population coding of sensory information, as well as lateral and feedback connections, enabling context-selective tuning of receptive fields. This means that the neural architecture, as understood today, enables a broad variety of perceptual integration functions. Therefore, we should not be surprised that integration of color and form appear at different levels and in various domains, from integration of color and orientation, over dynamically filling in (or the watercolor effect), to higher-order processes, such as implicit associations of color and shape in aesthetic judgments and color constancy for 3D objects. These different topics are brought together in the present E-Book. We expect that the collection of articles will be attractive to the community of researchers whose work straddles the boundary between the two visual perception fields—of color and form perception, as well as to the wider community interested in integrative/systems neuroscience

Cross-linguistic similarity affects L2 cognate representation: blu vs. blue in Italian-English bilinguals

In a psycholinguistic study we explored semantic shifts of focal colours for ‘blue’ terms in Italian-English bilinguals. Italian speakers require more than one basic colour term to name blue colours: blu ‘dark blue’ and azzurro ‘light/medium blue’; celeste ‘sky/light blue’ is salient, too [1-2]. Participants were Italian-English bilinguals residing in Liverpool (N=13). Their naming data, collected in two languages (L1, L2), were compared to those of Italian (N=13) and English (N=16) monolinguals. An unconstrained colour naming method was used to name each Munsell chip (M=237) embracing the BLUE area of colour space. Participants also indicated the best example focal colour) of blu, azzurro and celeste(Italian) or blue and light blue (English). Here we report two main findings: (i) Lightness shift: for the majority of the bilinguals, their L2 blue foci are semantically down-shifted towards L1 blu ‘dark blue’ foci. The semantic shift is thought to result from cross-linguistic similarity between the homophone Italian blu and English blue, facilitating asymmetric L1–L2 mediation in favour of the dominant language representation; (ii) Hue shift: proficient bilinguals revealed a hue shift of the L1 azzurro focus from azure, characteristic of Italian monolinguals, towards that of English monolinguals’ blue, with a purplish hint. The findings indicate Whorfian effects, or modulation of semantic-lexical representations, in proficient bilinguals immersed in L2 and, in addition, point to their integrated mental lexicon

‘Italian blues’: A challenge to the universal inventory of basic colour terms

‘Blue’ is one of the 11 basic colour terms (BCTs) in languages with a developed colour term inventory [1]. In a challenge to the Berlin-Kay model, Italian appears to require more than one BCT to name the blue area: blu ‘dark blue’, azzurro ‘light (-and-medium) blue’ and celeste ‘light blue’. We addressed the proposition of multiple Italian ‘blue’ BCTs in a psycholinguistic study. Eight Munsell charts embracing the BLUE area of colour space (7.5BG-5PB, Value 2-9, Chroma 2-12) were employed to explore colour name mapping in Italian speakers compared to English speakers. Participants were Italian monolinguals (N=13, Alghero; N=15, Verona) and English monolinguals (N=19; Liverpool). An unconstrained colour naming method was used; this was followed by indicating the best example (focal colour) of blu, azzurro and celeste (Italian) or blue and light blue (English). Choices of focal colours, in Munsell notation, are reported for each of the terms. In addition, distances between centroids of the focal colours, in CIELAB notation, are reported for each of the three participant groups. The dominant focal English blue and Italian blu appeared to concur in Hue (2.5PB, 5PB), but not in lightness (blue: Value 5; blu: Value 2-3). Italian speakers required, in addition, the azzurro term for naming light/medium blue colours. Notably, for the Algherese, azzurro indicates the ‘medium blue’ and is complemented by celeste for denoting light blue shades, similar to English light blue. In contrast, the Veronese use azzurro for ‘light-and-medium blue’; celeste was named conspicuously less frequently, overlapping with azzurro. The present study adds to psycholinguistic evidence that Italian possesses two BCTs, blu and azzurro, differentiating ‘blues’ along the lightness dimension. Celeste is a contender for a third BCT for the Alghero speakers. Cognitive representation (i.e. prototype) of azzurro as well as the status of celeste appear to vary markedly across Italian dialects

Gender Differences in Russian Colour Naming

In the present study we explored Russian colour naming in a web-based psycholinguistic experiment (http://www.colournaming.com). Colour singletons representing the Munsell Color Solid (N=600 in total) were presented on a computer monitor and named using an unconstrained colour-naming method. Respondents were Russian speakers (N=713). For gender-split equal-size samples (NF=333, NM=333) we estimated and compared (i) location of centroids of 12 Russian basic colour terms (BCTs); (ii) the number of words in colour descriptors; (iii) occurrences of BCTs most frequent non-BCTs. We found a close correspondence between females’ and males’ BCT centroids. Among individual BCTs, the highest inter-gender agreement was for seryj ‘grey’ and goluboj ‘light blue’, while the lowest was for sinij ‘dark blue’ and krasnyj ‘red’. Females revealed a significantly richer repertory of distinct colour descriptors, with great variety of monolexemic non-BCTs and “fancy” colour names; in comparison, males offered relatively more BCTs or their compounds. Along with these measures, we gauged denotata of most frequent CTs, reflected by linguistic segmentation of colour space, by employing a synthetic observer trained by gender-specific responses. This psycholinguistic representation revealed females’ more refined linguistic segmentation, compared to males, with higher linguistic density predominantly along the redgreen axis of colour space

Color naming in Italian language

The present study investigated Italian basic color terms (BCTs). It is an extension of our previous work that explored Italian basic color categories (BCCs) using a constrained color-naming method, with 11 Italian BCTs allowed, including blu for naming the BLUE area. Since a latter outcome indicated a categorization bias, here monolexemic color-naming method was employed, enabling also use of azzurro, deeply entrenched Italian term that designates light blue. In Experiment 1, colors (N=367), sampling the Munsell Mercator projection, were presented on a CRT; color names and reaction times of vocalization onset were recorded. Naming consistency and consensus were estimated. Consistency was obtained for 12 CTs, including the two blue terms; consensus was found for 11 CTs, excluding rosso ‘red’. For each consensus category, color with the shortest RT was considered focal. In Experiment 2, consensus stimuli (N=72) were presented; on each trial, observers indicated the focal color (“best example”) in an array of colors comprising a consensus category. For each of the 12 Italian CCs, centroid was calculated and focal color (two measures) estimated. Compared to English color terms, two outcomes are specific to Italian color naming: (i) naming of the RED-PURPLE area is highly refined, with consistent use of emergent non-BCTs; (ii) azzurro and blu both perform as BCTs dividing the BLUE area along the lightness dimension. The findings are considered in the framework of the weak relativity hypothesis. Historico-linguistic, environmental and pragmatic communication factors are discussed that conceivably have driven the extension of the BCT inventory in Italian

An online colour naming experiment in Russian using Munsell colour samples

Russian colour naming was explored in a web-based psycholinguistic experiment. The purpose was threefold: to examine (i) CIELAB coordinates of centroids for 12 Russian basic colour terms (BCTs), including two Russian terms for ‘blue’, sinij ‘dark blue’ and goluboj ‘light blue’, and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (ii) frequent non-BCTs and (iii) gender differences in colour naming. Native Russian speakers participated in the experiment using an unconstrained colour-naming method. Each participant named 20 colours, selected from 600 colours densely sampling the Munsell Color Solid. Colour names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The two Russian ‘blues’, as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of ‘brown’ and ‘red’. The Russian colour inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of non-BCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of non-BCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of colour space, employing a synthetic observer, revealed gender differences in naming colours, with more refined naming of the “warm” colours from females. We conclude that, along with universal perceptual factors, that govern categorical partition of colour space, Russian speakers’ colour naming reflects language-specific factors, supporting the weak relativity hypothesis