Time-of-day perception in paintings.

The spectral shape, irradiance, direction, and diffuseness of daylight vary regularly throughout the day. The variations in illumination and their effect on the light reflected from objects may in turn provide visual information as to the time of day. We suggest that artists' color choices for paintings of outdoor scenes might convey this information and that therefore the time of day might be decoded from the colors of paintings. Here we investigate whether human viewers' estimates of the depicted time of day in paintings correlate with their image statistics, specifically chromaticity and luminance variations. We tested time-of-day perception in 17th- to 20th-century Western European paintings via two online rating experiments. In Experiment 1, viewers' ratings from seven time choices varied significantly and largely consistently across paintings but with some ambiguity between morning and evening depictions. Analysis of the relationship between image statistics and ratings revealed correlations with the perceived time of day: higher "morningness" ratings associated with higher brightness, contrast, and saturation and darker yellow/brighter blue hues; "eveningness" with lower brightness, contrast, and saturation and darker blue/brighter yellow hues. Multiple linear regressions of extracted principal components yielded a predictive model that explained 76% of the variance in time-of-day perception. In Experiment 2, viewers rated paintings as morning or evening only; rating distributions differed significantly across paintings, and image statistics predicted people's perceptions. These results suggest that artists used different color palettes and patterns to depict different times of day, and the human visual system holds consistent assumptions about the variation of natural light depicted in paintings.

Color constancy for daylight illumination changes in anomalous trichromats and dichromats.

Color constancy is the perceptual stability of surface colors under temporal changes in the illumination spectrum. The illumination discrimination task (IDT) reveals worse discrimination for "bluer" illumination changes in normal-trichromatic observers (changes towards cooler color temperatures on the daylight chromaticity locus), indicating greater stability of scene colors or better color constancy, compared with illumination changes in other chromatic directions. Here, we compare the performance of individuals with X-linked color-vision deficiencies (CVDs) to normal trichromats on the IDT performed in an immersive setting with a real scene illuminated by spectrally tunable LED lamps. We determine discrimination thresholds for illumination changes relative to a reference illumination (D65) in four chromatic directions, roughly parallel and orthogonal to the daylight locus. We find, using both a standard CIELUV metric and a cone-contrast metric tailored to distinct CVD types, that discrimination thresholds for daylight changes do not differ between normal trichromats and CVD types, including dichromats and anomalous trichromats, but thresholds for atypical illuminations do differ. This result extends a previous report of illumination discrimination ability in dichromats for simulated daylight changes in images. In addition, using the cone-contrast metric to compare thresholds for bluer and yellower daylight changes with those for unnatural redder and greener changes, we suggest that reduced sensitivity to daylight changes is weakly preserved in X-linked CVDs.

CNV-Net: Segmentation, Classification and Activity Score Measurement of Choroidal Neovascularization (CNV) Using Optical Coherence Tomography Angiography (OCTA).

This paper aims to present an artificial intelligence-based algorithm for the automated segmentation of Choroidal Neovascularization (CNV) areas and to identify the presence or absence of CNV activity criteria (branching, peripheral arcade, dark halo, shape, loop and anastomoses) in OCTA images. Methods: This retrospective and cross-sectional study includes 130 OCTA images from 101 patients with treatment-naïve CNV. At baseline, OCTA volumes of 6 × 6 mm2 were obtained to develop an AI-based algorithm to evaluate the CNV activity based on five activity criteria, including tiny branching vessels, anastomoses and loops, peripheral arcades, and perilesional hypointense halos. The proposed algorithm comprises two steps. The first block includes the pre-processing and segmentation of CNVs in OCTA images using a modified U-Net network. The second block consists of five binary classification networks, each implemented with various models from scratch, and using transfer learning from pre-trained networks. Results: The proposed segmentation network yielded an averaged Dice coefficient of 0.86. The individual classifiers corresponding to the five activity criteria (branch, peripheral arcade, dark halo, shape, loop, and anastomoses) showed accuracies of 0.84, 0.81, 0.86, 0.85, and 0.82, respectively. The AI-based algorithm potentially allows the reliable detection and segmentation of CNV from OCTA alone, without the need for imaging with contrast agents. The evaluation of the activity criteria in CNV lesions obtains acceptable results, and this algorithm could enable the objective, repeatable assessment of CNV features.

Developmental changes in colour constancy in a naturalistic object selection task.

When the illumination falling on a surface change, so does the reflected light. Despite this, adult observers are good at perceiving surfaces as relatively unchanging-an ability termed colour constancy. Very few studies have investigated colour constancy in infants, and even fewer in children. Here we asked whether there is a difference in colour constancy between children and adults; what the developmental trajectory is between six and 11 years; and whether the pattern of constancy across illuminations and reflectances differs between adults and children. To this end, we developed a novel, child-friendly computer-based object selection task. In this, observers saw a dragon's favourite sweet under a neutral illumination and picked the matching sweet from an array of eight seen under a different illumination (blue, yellow, red, or green). This set contained a reflectance match (colour constant; perfect performance) and a tristimulus match (colour inconstant). We ran two experiments, with two-dimensional scenes in one and three-dimensional renderings in the other. Twenty-six adults and 33 children took part in the first experiment; 26 adults and 40 children took part in the second. Children performed better than adults on this task, and their performance decreased with age in both experiments. We found differences across illuminations and sweets, but a similar pattern across both age groups. This unexpected finding might reflect a real decrease in colour constancy from childhood to adulthood, explained by developmental changes in the perceptual and cognitive mechanisms underpinning colour constancy, or differences in task strategies between children and adults. HIGHLIGHTS: Six- to 11-year-old children demonstrated better performance than adults on a colour constancy object selection task. Performance decreased with age over childhood. These findings may indicate development of cognitive strategies used to overcome automatic colour constancy mechanisms.

Synthetic OCT Data Generation to Enhance the Performance of Diagnostic Models for Neurodegenerative Diseases.

Purpose: Optical coherence tomography (OCT) has recently emerged as a source for powerful biomarkers in neurodegenerative diseases such as multiple sclerosis (MS) and neuromyelitis optica (NMO). The application of machine learning techniques to the analysis of OCT data has enabled automatic extraction of information with potential to aid the timely diagnosis of neurodegenerative diseases. These algorithms require large amounts of labeled data, but few such OCT data sets are available now. Methods: To address this challenge, here we propose a synthetic data generation method yielding a tailored augmentation of three-dimensional (3D) OCT data and preserving differences between control and disease data. A 3D active shape model is used to produce synthetic retinal layer boundaries, simulating data from healthy controls (HCs) as well as from patients with MS or NMO. Results: To evaluate the generated data, retinal thickness maps are extracted and evaluated under a broad range of quality metrics. The results show that the proposed model can generate realistic-appearing synthetic maps. Quantitatively, the image histograms of the synthetic thickness maps agree with the real thickness maps, and the cross-correlations between synthetic and real maps are also high. Finally, we use the generated data as an augmentation technique to train stronger diagnostic models than those using only the real data. Conclusions: This approach provides valuable data augmentation, which can help overcome key bottlenecks of limited data. Translational Relevance: By addressing the challenge posed by limited data, the proposed method helps apply machine learning methods to diagnose neurodegenerative diseases from retinal imaging.

Predicting attitudes towards screening for neurodegenerative diseases using OCT and artificial intelligence: Findings from a literature review.

Recent developments in artificial intelligence (AI) and machine learning raise the possibility of screening and early diagnosis for neurodegenerative diseases, using 3D scans of the retina. The eventual value of such screening will depend not only on scientific metrics such as specificity and sensitivity but, critically, also on public attitudes and uptake. Differential screening rates for various screening programmes in England indicate that multiple factors influence uptake. In this narrative literature review, some of these potential factors are explored in relation to predicting uptake of an early screening tool for neurodegenerative diseases using AI. These include: awareness of the disease, perceived risk, social influence, the use of AI, previous screening experience, socioeconomic status, health literacy, uncontrollable mortality risk, and demographic factors. The review finds the strongest and most consistent predictors to be ethnicity, social influence, the use of AI, and previous screening experience. Furthermore, it is likely that factors also interact to predict the uptake of such a tool. However, further experimental work is needed both to validate these predictions and explore interactions between the significant predictors.

Seeing and sensing temporal variations in natural daylight.

Natural illumination is a mixture of sunlight and skylight, modified by interactions with atmospheric particles and interreflections between physical surfaces. Unlike traditional artificial light sources, natural illumination is spectrally dynamic, changing over short and long timescales. Over the day, daylight's correlated color temperature typically ranges from cool (~12,000K) to warm (~2000K), following the well-defined daylight chromaticity locus. Analysis of existing spectral irradiance databases and new measurements reveal a characteristic tripartite pattern: for chromaticity, the periods of fastest change occur in early morning and late evening at the lowest irradiances, with an interim period of relative stability. Illuminance changes are governed systematically by changes in solar elevation and tend to be fastest at the day's extremities, but unsystematic largely weather-related factors perturb this smooth trajectory. The human visual and nonvisual responses to light evolved under these changes. Psychophysical studies demonstrate that the threshold visibility of temporal changes in global illumination chromaticity depends on the chromatic direction of change and adapting chromaticity, with the lowest sensitivity occurring for changes towards neutral. Comparisons with the measured systematic changes in natural illumination suggests that the latter are too slow to be directly detected. A speculation is that visual mechanisms dampen sensitivity to the largest natural changes in illumination chromaticity in order to maintain perceptual stability of object color. Nonvisual mechanisms appear tuned to chromaticity changes at dawn and dusk, and hence are critical for syncing the circadian clock with environmental conditions. The latter might also feed long-term memory of illumination conditions as well as subjective experiences of illumination atmosphere.

Temporal dynamics of daylight perception: Detection thresholds.

Temporal changes in illumination are ubiquitous; natural light, for example, varies in color temperature and irradiance throughout the day. Yet little is known about human sensitivity to temporal changes in illumination spectra. Here, we aimed to determine the minimum detectable velocity of chromaticity change of daylight metamers in an immersive environment. The main stimulus was a continuous, monotonic change in global illumination chromaticity along the daylight locus in warmer (toward lower correlated color temperatures [CCTs]) or cooler directions, away from an adapting base light (CCT: 13,000 K, 6500 K, 4160 K, or 2000 K). All lights were generated by spectrally tunable overhead lamps as smoothest-possible metamers of the desired chromaticities. Mean detection thresholds (for 22 participants) for a fixed duration of 10 seconds ranged from 15 to 2 CIELUV ΔE units, depending significantly on base light CCT and with a significant interaction between CCT and direction of change. Cool changes become less noticeable for progressively warmer base lights and vice versa. For the two extreme base lights, sensitivity to changes toward neutral is significantly lower than for the opposite direction. The results suggest a "neutral bias" in illumination change discriminability, and that typical temporal changes in daylight chromaticity are likely to be below threshold detectability, at least where there are no concomitant overall illuminance changes. These factors may contribute to perceptual stability of natural scenes and color constancy.

Exploring the Determinants of Color Perception Using #Thedress and Its Variants: The Role of Spatio-Chromatic Context, Chromatic Illumination, and Material-Light Interaction.

The colors that people see depend not only on the surface properties of objects but also on how these properties interact with light as well as on how light reflected from objects interacts with an individual's visual system. Because individual visual systems vary, the same visual stimulus may elicit different perceptions from different individuals. #thedress phenomenon drove home this point: different individuals viewed the same image and reported it to be widely different colors: blue and black versus white and gold. This phenomenon inspired a collection of demonstrations presented at the Vision Sciences Society 2015 Meeting which showed how spatial and temporal manipulations of light spectra affect people's perceptions of material colors and illustrated the variability in individual color perception. The demonstrations also explored the effects of temporal alterations in metameric lights, including Maxwell's Spot, an entoptic phenomenon. Crucially, the demonstrations established that #thedress phenomenon occurs not only for images of the dress but also for the real dress under real light sources of different spectral composition and spatial configurations.

Specular highlights improve color constancy when other cues are weakened.

Previous studies suggest that to achieve color constancy, the human visual system makes use of multiple cues, including a priori assumptions about the illumination ("daylight priors"). Specular highlights have been proposed to aid constancy, but the evidence for their usefulness is mixed. Here, we used a novel cue-combination approach to test whether the presence of specular highlights or the validity of a daylight prior improves illumination chromaticity estimates, inferred from achromatic settings, to determine whether and under which conditions either cue contributes to color constancy. Observers made achromatic settings within three-dimensional rendered scenes containing matte or glossy shapes, illuminated by either daylight or nondaylight illuminations. We assessed both the variability of these settings and their accuracy, in terms of the standard color constancy index (CCI). When a spectrally uniform background was present, neither CCIs nor variability improved with specular highlights or daylight illuminants (Experiment 1). When a Mondrian background was introduced, CCIs decreased overall but were higher for scenes containing glossy, as opposed to matte, shapes (Experiments 2 and 3). There was no overall reduction in variability of settings and no benefit for scenes illuminated by daylights. Taken together, these results suggest that the human visual system indeed uses specular highlights to improve color constancy but only when other cues, such as from the local surround, are weakened.

Illumination discrimination for chromatically biased illuminations: Implications for color constancy.

We measured discrimination thresholds for illumination changes along different chromatic directions starting from chromatically biased reference illuminations. Participants viewed a Mondrian-papered scene illuminated by LED lamps. The scene was first illuminated by a reference illumination, followed by two comparisons. One comparison matched the reference (the target); the other (the test) varied from the reference, nominally either bluer, yellower, redder, or greener. The participant's task was to correctly select the target. A staircase procedure found thresholds for discrimination of an illumination change along each axis of chromatic change. Nine participants completed the task for five different reference illumination conditions (neutral, blue, yellow, red, and green). We find that relative discrimination thresholds for different chromatic directions of illumination change vary with the reference illumination. For the neutral reference, there is a trend for thresholds to be highest in the bluer illumination-change direction, replicating our previous reports of a "blue bias" for neutral reference illuminations. For the four chromatic references (blue, yellow, red, and green), the change in illumination toward the neutral reference is less well discriminated than changes in the other directions: a "neutral bias." The results have implications for color constancy: In considering the stability of surface appearance under changes in illumination, both the starting chromaticity of the illumination and direction of change must be considered, as well as the chromatic characteristics of the surface reflectance ensemble. They also suggest it will be worthwhile to explore whether and how the human visual system has internalized the statistics of natural illumination changes.

Illumination discrimination in the absence of a fixed surface-reflectance layout.

Previous studies have shown that humans can discriminate spectral changes in illumination and that this sensitivity depends both on the chromatic direction of the illumination change and on the ensemble of surfaces in the scene. These studies, however, always used stimulus scenes with a fixed surface-reflectance layout. Here we compared illumination discrimination for scenes in which the surface reflectance layout remains fixed (fixed-surfaces condition) to those in which surface reflectances were shuffled randomly across scenes, but with the mean scene reflectance held approximately constant (shuffled-surfaces condition). Illumination discrimination thresholds in the fixed-surfaces condition were commensurate with previous reports. Thresholds in the shuffled-surfaces condition, however, were considerably elevated. Nonetheless, performance in the shuffled-surfaces condition exceeded that attainable through random guessing. Analysis of eye fixations revealed that in the fixed-surfaces condition, low illumination discrimination thresholds (across observers) were predicted by low overall fixation spread and high consistency of fixation location and fixated surface reflectances across trial intervals. Performance in the shuffled-surfaces condition was not systematically related to any of the eye-fixation characteristics we examined for that condition, but was correlated with performance in the fixed-surfaces condition.

Sleep Disturbance and the Change from White to Red Lighting at Night on Old Age Psychiatry Wards: A Quality Improvement Project.

Psychiatric inpatient units often maintain a degree of lighting at night to facilitate the observation of patients, but this has the potential to disrupt sleep. Certain wavelengths of light may be less likely to disturb sleep and if such lighting permitted adequate observations, patient wellbeing may be improved. AIMS AND METHOD: This study explored the effects of changing night-lights from broad-band white to narrow-band red on the amount of sleep observed, 'as required' medication administered and number of falls, in an old age psychiatry inpatient setting. Qualitative data was also gathered with a staff questionnaire. We hypothesised that compared to the use of white lights, red lights would be associated with a greater amount of recorded sleep, lesser use of 'as required' medication and no increase in the number of falls (reflecting comparable safety). RESULTS: Whilst there were no significant differences in quantitative measures recorded, there were more observations of sleep during the red light period than the white light period (14.1 versus 13.9 times per night) (U=627.5, z=-0.69, p=0.49) and fewer 'as required' medication administrations during the red light period compared to the white light period (3.3 versus 4.8 times per night) (U=640.0, z=0.56, p=0.57). Qualitatively, the staff of the organic assessment unit reported that patients were sleeping better and less agitated at night. CLINICAL IMPLICATIONS: Larger and more in-depth studies are required to examine the full effectiveness of using safe, sleep-enhancing lighting on wards at night.

Aversive Learning in the Praying Mantis (Tenodera aridifolia), a Sit and Wait Predator.

Animals learn to associate sensory cues with the palatability of food in order to avoid bitterness in food (a common sign of toxicity). Associations are important for active foraging predators to avoid unpalatable prey and to invest energy in searching for palatable prey only. However, it has been suggested that sit-and-wait predators might rely on the opportunity that palatable prey approach them by chance: the most efficient strategy could be to catch every available prey and then decide whether to ingest them or not. In the present study, we investigated avoidance learning in a sit-and-wait predator, the praying mantis (Tenodera aridifolia). To examine the effects of conspicuousness and novelty of prey on avoidance learning, we used three different prey species: mealworms (novel prey), honeybees (novel prey with conspicuous signals) and crickets (familiar prey). We sequentially presented the prey species in pairs and made one of them artificially bitter. In the absence of bitterness, the mantises consumed bees and crickets more frequently than mealworms. When the prey were made bitter, the mantises still continued to attack bitter crickets as expected. However, they reduced their attacks on bitter mealworms more than on bitter bees. This contrasts with the fact that conspicuous signals (e.g. coloration in bees) facilitate avoidance learning in active foraging predators. Surprisingly, we found that the bitter bees were totally rejected after an attack whereas bitter mealworms were partially eaten (~35%). Our results highlight the fact that the mantises might maintain a selection pressure on bees, and perhaps on aposematic species in general.

Modeling color preference using color space metrics.

Studying color preferences provides a means to discover how perceptual experiences map onto cognitive and affective judgments. A challenge is finding a parsimonious way to describe and predict patterns of color preferences, which are complex with rich individual differences. One approach has been to model color preferences using factors from metric color spaces to establish direct correspondences between dimensions of color and preference. Prior work established that substantial, but not all, variance in color preferences could be captured by weights on color space dimensions using multiple linear regression. The question we address here is whether model fits may be improved by using different color metric specifications. We therefore conducted a large-scale analysis of color space models, and focused in-depth analysis on models that differed in color space (cone-contrast vs. CIELAB), coordinate system within the color space (Cartesian vs. cylindrical), and factor degrees (1st degree only, or 1st and 2nd degree). We used k-fold cross validation to avoid over-fitting the data and to ensure fair comparisons across models. The best model was the 2nd-harmonic Lch model ("LabC Cyl2"). Specified in CIELAB space, it included 1st and 2nd harmonics of hue (capturing opponency in hue preferences and simultaneous liking/disliking of both hues on an opponent axis, respectively), lightness, and chroma. These modeling approaches can be used to characterize and compare patterns for group averages and individuals in future datasets on color preference, or other measures in which correspondences between color appearance and cognitive or affective judgments may exist.

What #theDress reveals about the role of illumination priors in color perception and color constancy.

The disagreement between people who named #theDress (the Internet phenomenon of 2015) "blue and black" versus "white and gold" is thought to be caused by individual differences in color constancy. It is hypothesized that observers infer different incident illuminations, relying on illumination "priors" to overcome the ambiguity of the image. Different experiences may drive the formation of different illumination priors, and these may be indicated by differences in chronotype. We assess this hypothesis, asking whether matches to perceived illumination in the image and/or perceived dress colors relate to scores on the morningness-eveningness questionnaire (a measure of chronotype). We find moderate correlations between chronotype and illumination matches (morning types giving bluer illumination matches than evening types) and chronotype and dress body matches, but these are significant only at the 10% level. Further, although inferred illumination chromaticity in the image explains variation in the color matches to the dress (confirming the color constancy hypothesis), color constancy thresholds obtained using an established illumination discrimination task are not related to dress color perception. We also find achromatic settings depend on luminance, suggesting that subjective white point differences may explain the variation in dress color perception only if settings are made at individually tailored luminance levels. The results of such achromatic settings are inconsistent with their assumed correspondence to perceived illumination. Finally, our results suggest that perception and naming are disconnected, with observers reporting different color names for the dress photograph and their isolated color matches, the latter best capturing the variation in the matches.

Illumination discrimination in real and simulated scenes.

Characterizing humans' ability to discriminate changes in illumination provides information about the visual system's representation of the distal stimulus. We have previously shown that humans are able to discriminate illumination changes and that sensitivity to such changes depends on their chromatic direction. Probing illumination discrimination further would be facilitated by the use of computer-graphics simulations, which would, in practice, enable a wider range of stimulus manipulations. There is no a priori guarantee, however, that results obtained with simulated scenes generalize to real illuminated scenes. To investigate this question, we measured illumination discrimination in real and simulated scenes that were well-matched in mean chromaticity and scene geometry. Illumination discrimination thresholds were essentially identical for the two stimulus types. As in our previous work, these thresholds varied with illumination change direction. We exploited the flexibility offered by the use of graphics simulations to investigate whether the differences across direction are preserved when the surfaces in the scene are varied. We show that varying the scene's surface ensemble in a manner that also changes mean scene chromaticity modulates the relative sensitivity to illumination changes along different chromatic directions. Thus, any characterization of sensitivity to changes in illumination must be defined relative to the set of surfaces in the scene.

Colour Vision: Understanding #TheDress.

A widely-viewed image of a dress elicits striking individual variation in colour perception. Experiments with multiple variants of the image suggest that the individual differences may arise through the action of visual mechanisms that normally stabilise object colour.