Biology subjects

Gegenfurtner, K. R.

Publications and source records attributed to Gegenfurtner, K. R..

11 recordsLinked to original sources

bioRxiv2026

Categorical Color Structure Persists in Color Vision Deficiency

Color vision deficiencies affect color perception and discrimination, but their consequences for the structure and stability of color categories remain less clear. We examined how trichromats, anomalous trichromats, and dichromats assigned 450 physical Munsell color samples to eleven basic color categories and measured the stability of these assignments in a retest two hours later. In each session, participants sorted a randomly mixed set of chips by hand and selected one representative chip for each category. We quantified agreement within and between color-vision groups as well as test-retest reliability within participants. For the 217 chips that all trichromats assigned to the same category, anomalous trichromats used the same category label for 85% of chips, and their category assignments were less stable across sessions as those of trichromats. Within anomalous trichromats poorer red-green discrimination, indexed by higher RG-CAD scores, was associated with lower sorting consistency. Dichromats showed lower agreement with trichromats and anomalous trichromats and greater prototype instability, but their color categories remained systematically organized rather than random. Information-theoretic analyses revealed a graded increase in categorical uncertainty from trichromats through anomalous trichromats to dichromats together with increasing reliance on lightness. Thus, the principal effect of color vision deficiency was not a collapse of color categories, but a graded reduction in the precision with which different shades were assigned to otherwise recognizable categories. In a separate subset of nine anomalous trichromats, EnChroma glasses produced no measurable immediate shift toward trichromatic category structures. Overall, our findings suggest that categorical color representations in anomalous trichromats and dichromats remain remarkably robust despite substantial sensory deficits.

neuroscience↗

bioRxiv2026

Environmental color statistics shape the anisotropic geometry of human color discrimination

Hue is a powerful cue for object discrimination, but human color discrimination is anisotropic: hue thresholds are lower than chroma thresholds for orangish colors, but nearly equal for purplish colors. Here we show that this asymmetry reflects environmental color statistics rather than being a fixed consequence of cone-opponent architecture. Across fifteen image and reflectance databases, orangish hues accounted for 62.5% of chromatic samples, compared with 5.3% for purplish hues. We replicated the hue-chroma asymmetry psychophysically in 44 participants. Magnetoencephalography revealed a corresponding neural asymmetry, with superior decoding of orangish hue differences emerging around 250 ms after stimulus onset. Deep neural networks trained on naturalistic image datasets reproduced the human-like asymmetry without explicit color supervision. Critically, training on hue-inverted images reversed the asymmetry, producing greater hue sensitivity for purplish than for orangish colors. These results suggest that the geometry of color discrimination is shaped by ecological chromatic structure.

neuroscience↗

bioRxiv2026

An empirical three-dimensional metric field for color space

A complete empirical characterization of color discrimination in three dimensions has long remained out of reach. Classical studies, beginning with MacAdams ellipses, provided local measurements in restricted chromatic planes, but a spatially dense and internally consistent mapping of discrimination structure across full color space has not yet been achieved. Here we present such a systematic three-dimensional measurement of color discrimination in the standardized sRGB stimulus space. Eight observers measured discrimination regions at 35 reference colors distributed on a body-centered cubic lattice within the RGB cube. At each location, color differences were probed along seven orientations, yielding 14 directional extents. These measurements defined centrally symmetric convex regions that were fitted with minimum-volume ellipsoids, providing a compact description of local discrimination structure. Ellipsoids were represented as symmetric positive-definite matrices and analyzed using a Frobenius geometry, enabling normalization across observers and smooth interpolation to arbitrary locations. The resulting metric field is spatially smooth, highly structured, and remarkably consistent across observers up to an individual global scale factor. Grain size increases along the achromatic axis and exhibits systematic chromatic asymmetries. Comparison with CIEDE2000 reveals substantial agreement in overall scale variation but systematic differences in local anisotropy. Because the metric field is defined geometrically, it can be transformed into linear RGB or any other color representation through the corresponding coordinate transformations. Together, these data provide a coherent three-dimensional empirical mapping of color discrimination across a large ecologically relevant volume of color space and establish an empirical framework for perceptual color metrics.

neuroscience↗

bioRxiv2026

Color discrimination in action: High-throughput measurement in immersive VR

Precise measurement of color discrimination across color space is limited by the time and effort required to collect large psychophysical datasets. We investigated whether immersive virtual reality (VR) can support high-throughput measurement of color discrimination without compromising data quality. A standard 4-alternative forced-choice odd-one-out task was embedded in an interactive VR environment inspired by the rhythm game BeatSaber, in which participants indicated the location of a chromatic target by slicing approaching cubes. Stimuli were presented on a color-calibrated VR headset, and chromaticities were specified in DKL space. Discrimination thresholds were measured for hue and chroma shifts around two reference colors. Participants sustained response rates of approximately one trial per second while maintaining stable performance. Thresholds replicated established asymmetries in color discrimination: hue thresholds were lower than chroma thresholds, and the hue-chroma ratio differed between color quadrants. A control experiment comparing VR-based slicing responses with matched keyboard responses revealed comparable psychometric fits and threshold estimates, indicating that motor engagement did not degrade measurement precision. Questionnaire measures further showed significantly higher intrinsic motivation, enjoyment, and stimulation in the immersive condition relative to a classic static psychophysical task, without increases in reported pressure or discomfort. These results demonstrate that calibrated immersive VR can yield reliable color discrimination measurements at substantially increased throughput, providing a scalable approach for mapping the metric structure of color space.

neuroscience↗

bioRxiv2025

Human gloss perception reproduced by tiny neural networks

A key goal of visual neuroscience is to explain how our brains infer object properties like colour, curvature, or gloss. Here, we used machine learning to identify computations underlying human gloss judgments from object images--traditionally considered a challenging inference. Thousands of object images of varied shapes were rendered with a Ward reflectance model under diverse lighting and viewpoints, and we crowdsourced gloss estimates for each image. Curiously, observers judgments were highly consistent with one another, yet systematically deviated from reality. We compared these responses with neural networks trained either to estimate physical reflectance ("ground-truth networks") or to reproduce human judgments ("human-like networks"). By reducing network size, we identified the minimum computations needed for each objective. While estimating physical reflectance required deep networks, shallow networks--with as few as three layers--accurately replicated human judgments. Remarkably, even a miniscule network with just a single filter could predict human judgments better than the best ground-truth network. The human-like networks also captured known gloss illusions outside the training range. These results suggest human gloss judgments rely on simpler, more general-purpose computations than previously thought, and demonstrate the power of using tiny but interpretable neural networks to uncover functional computations in human brains.

neuroscience↗

bioRxiv2024

Keeping Your Eye, Head, and Hand on the Ball: Rapidly Orchestrated Visuomotor Behavior in a Continuous Action Task

In everyday life, we must adapt our behavior to a continuous stream of tasks and time motor responses and periods of resting accordingly. To mimic these challenges, we used a continuous interception computer game (Pong) on an iPad. This allowed us to measure the coordination of eye, hand, and head movements during natural sequential behavior while maintaining the benefits of experimental control. Participants intercepted a moving ball by sliding a paddle at the bottom of the screen so that the ball bounced back and moved toward the computerized opponent. We tested i) how participants adapted their eye, hand, and head movements to this dynamic, continuous task, ii) whether these adaptations are related to interception performance, and iii) how their behavior changed under different conditions and iv) over time. We showed that all movements are carefully adapted to the upcoming action. Pursuit eye movements provide crucial motion information and are emphasized shortly before participants must act; a strategy associated with better performance. Participants also increasingly used pursuit eye movements under more difficult conditions (fast targets and small paddles). Saccades, blinks, and head movements, which would lead to information loss, are minimized at critical times of interception. These strategic patterns are intuitively established and maintained over time and across manipulations. We conclude that humans carefully orchestrate their full repertoire of movements to aid performance and finely adjust them to the changing demands of our environment.

neuroscience↗

bioRxiv2023

Sensorimotor Confidence for Tracking Eye Movements

For successful interactions with the world, we often have to evaluate our own performance. Such metacognitive evaluations have been studied with perceptual decisions, but much less with respect to the evaluation of our own actions. While eye movements are one of the most frequent actions we perform, we are typically unaware of them. Here, we investigated if there is any evidence for metacognitive sensitivity for the accuracy of eye movements. Participants tracked a dot cloud as it followed an unpredictable sinusoidal trajectory for six seconds, and then reported if they thought their performance was better or worse than their average tracking performance. Our results show above chance identification of better tracking behavior across all trials and also for repeated attempts of the same target trajectories. While the sensitivity in discriminating performance between better and worse trials was stable across sessions, for their judgements participants relied more on performance in the final seconds of each trial. This behavior matched previous reports when judging the quality of hand movements, although overall metacognitive sensitivity for eye movements was significantly lower. Together, these results provide an additional piece of evidence for sensorimotor confidence, and open interesting questions about why it differs across actions and how it could be related to other instances of confidence. Statement of RelevanceIn everyday life, it is often critical to be able to evaluate the quality of our own cognitive decisions and actions. However, one of our most frequent actions often does not even reach our awareness: eye movements. We investigated whether observers were able to successfully judge the accuracy of their eye movements when tracking a cloud of dots that followed an unpredictable trajectory. We found that observers were able to distinguish good from bad trials, although sensitivity was lower compared to equivalent previous reports when judging the quality of hand movements. These results add an item to the growing list of our metacognitive abilities, but critically for eye movements that we are typically unaware of. They lead to important novel questions about why metacognitive abilities differ across decisions or different types of actions, and what the potential components of metacognitive abilities might be.

neuroscience↗

bioRxiv2023

Contrast Sensitivity Function in Deep Networks

The contrast sensitivity function (CSF) is a fundamental signature of the visual system that has been measured extensively in several species. It is defined by the visibility threshold for sinusoidal gratings at all spatial fre-quencies. Here, we investigated the CSF in deep neural networks using the same 2AFC contrast detection paradigm as in human psychophysics. We examined 240 networks pretrained on several tasks. To obtain their corre-sponding CSFs, we trained a linear classifier on top of the extracted features from frozen pretrained networks. The linear classifier is exclusively trained on a contrast discrimination task with natural images. It has to find which of the two input images has higher contrast. The networks CSF is measured by detecting which one of two images contains a sinusoidal grating of varying orientation and spatial frequency. Our results demonstrate char-acteristics of the human CSF are manifested in deep networks both in the luminance channel (a band-limited inverted U-shaped function) and in the chromatic channels (two low-pass functions of similar properties). The exact shape of the networks CSF appears to be task-dependent. The human CSF is better captured by networks trained on low-level visual tasks such as image-denoising or autoencoding. However, human-like CSF also emerges in mid- and high-level tasks such as edge detection and object recognition. Our analysis shows that human-like CSF appears in all architectures but at different depths of processing, some at early layers, while others in intermediate and final layers. Overall, these results suggest that (i) deep networks model the human CSF faithfully, making them suitable candidates for applications of image quality and compression, (ii) efficient/purposeful processing of the natural world drives the CSF shape, and (iii) visual representation from all levels of visual hierarchy contribute to the tuning curve of the CSF, in turn implying a function which we intuitively think of as modulated by low-level visual features may arise as a consequence of pooling from a larger set of neurons at all levels of the visual system.

animal behavior and cognition↗

bioRxiv2022

Color and gloss constancy under diverse lighting environments

When we look at an object, we simultaneously see how glossy or matte it is, how light or dark, and what color. Yet, at each point on the objects surface, both diffuse and specular reflections are mixed in different proportions, resulting in substantial spatial chromatic and luminance variations. To further complicate matters, this pattern changes radically when the object is viewed under different lighting conditions. The purpose of this study was to simultaneously measure our ability to judge color and gloss using an image set capturing diverse object and illuminant properties. Participants adjusted the hue, lightness, chroma, and specular reflectance of a reference object so that it appeared to be made of the same material as a test object. Critically, the two objects were presented under different lighting environments. We found that hue matches were highly accurate, except for under a chromatically atypical illuminant. Chroma and lightness constancy were generally poor, but these failures correlated well with simple image statistics. Gloss constancy was particularly poor, and these failures were only partially explained by reflection contrast. Importantly, across all measures, participants were highly consistent with one another in their deviations from constancy. Although color and gloss constancy hold well in simple conditions, the variety of lighting and shape in the real world presents significant challenges to our visual systems ability to judge intrinsic material properties.

neuroscience↗

bioRxiv2021

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. While prelinguistic infants and animals treat color categorically, several recent modeling endeavors have successfully utilized communicative concepts to predict color categories. Rather than modeling categories directly, we investigate the potential emergence of color categories as a result of acquiring visual skills. Specifically, whether color is represented categorically in a convolutional neural network (CNN) trained to recognize objects in natural images. Systematically training new output layers to the CNN for a color classification task, we find clear borders between new (non-training) colors that are largely invariant to the training colors. Using an evolutionary algorithm that relies on the principle of categorical perception we verify these border locations. These results provide strong evidence that color categorization emerges as a function of basic visual skills and provide a new basis for uncovering how they emerge.

animal behavior and cognition↗

bioRxiv2018

Individual differences in visual salience vary along semantic dimensions

What determines where we look? Theories of attentional guidance hold that image features and task demands govern fixation behaviour, while differences between observers are noise. Here, we investigated the fixations of > 100 human adults freely viewing a large set of complex scenes. We found systematic individual differences in fixation frequencies along six semantic stimulus dimensions. These differences were large (> twofold) and highly stable across images and time. Surprisingly, they also held for first fixations directed towards each image, commonly interpreted as bottom-up visual salience. Their perceptual relevance was documented by a correlation between individual face salience and recognition skills. The dimensions of individual salience and their covariance pattern replicated across samples from three different countries, suggesting they reflect fundamental biological mechanisms of attention. Our findings show stable individual salience differences along semantic dimensions, with meaningful perceptual implications. Salience reflects features of the observer as well as the image.

neuroscience↗