Neuronal nonlinearity explains greater visual spatial resolution for darks than lights

Visual Field Asymmetries in Responses to ON and OFF Pathway Biasing Stimuli

Recent reports suggest the ON and OFF pathways are differentially susceptible to selective vision loss in glaucoma. Thus, perimetric assessment of ON- and OFF-pathway function may serve as a useful diagnostic. However, this necessitates a developed understanding of normal ON/OFF pathway function around the visual field and as a function of input intensity. Here, using electroencephalography, we measured ON- and OFF-pathway biased contrast response functions in the upper and lower visual fields. Using the steady-state visually evoked potential paradigm, we flickered achromatic luminance probes according to a saw-tooth waveform, the fast phase of which biased responses towards the ON or OFF pathways. Neural responses from the upper and lower visual fields were simultaneously measured using frequency tagging - probes in the upper visual field modulated at 3.75 Hz, while those in the lower visual field modulated at 3 Hz. We find that responses to OFF/decrements are larger than ON/increments, especially in the lower visual field. In the lower visual field, both ON and OFF responses were well described by a sigmoidal non-linearity. In the upper visual field, the ON pathway function was very similar to that of the lower, but the OFF pathway function showed reduced saturation and more cross-subject variability. Overall, this demonstrates that the relationship between the ON and OFF pathways depends on the visual field location and contrast level, potentially reflective of natural scene statistics.

Plaid masking explained with input-dependent dendritic nonlinearities

A serious obstacle for understanding early spatial vision comes from the failure of the so-called standard model (SM) to predict the perception of plaid masking. But the SM originated from a major oversimplification of single neuron computations, ignoring fundamental properties of dendrites. Here we show that a spatial vision model including computations mimicking the input-dependent nature of dendritic nonlinearities, i.e. including nonlinear neural summation, has the potential to explain plaid masking data.

OPTICAL BLUR AFFECTS DIFFERENTLY ON AND OFF VISUAL PATHWAYS

The human eye has a crystalline lens that focuses retinal images at the point of fixation. Outside this fixation region, images are distorted by optical blur, which increases light scatter and reduces the spatial resolution and contrast processed by neuronal pathways. The spectacle lenses that humans use for optical correction also minify or magnify the images, affecting neuronal surround suppression in visual processing. Because light and dark stimuli are processed with ON and OFF pathways that have different spatial resolution, contrast sensitivity and surround suppression, optical blur and image magnification should affect differently the two pathways and the perception of lights and darks. Our results provide support for this prediction in cats and humans. We demonstrate that optical blur expands ON receptive fields while shrinking OFF receptive fields, as expected from the expansion of light stimuli and shrinkage of dark stimuli with light scatter. Spectacle-induced image magnification also shrinks OFF more than ON receptive fields, as expected from the stronger surround suppression in OFF than ON pathways. Optical blur also decreases the population response of OFF more than ON pathways, consistent with the different effects of light scatter on dark and light stimuli and the ON-OFF pathway differences in contrast sensitivity. Based on these results, we conclude that optical blur and image magnification reduce the receptive field sizes and cortical responses of OFF more than ON pathways, making the ON-OFF response balance a reliable signal to optimize the size and quality of the retinal image.

Understanding contrast perception in amblyopia: a psychophysical analysis of the ON and OFF visual pathways

Purpose

The study aimed to explore potential discrepancies in contrast sensitivity in the ON and OFF visual pathways among individuals with amblyopia compared to controls.

Methods

Eleven adult amblyopes (26.2 ± 4.4 [SD] years old) and 10 controls (24.6 ± 0.8 years old) with normal or corrected to normal visual acuity (logMAR VA ≤ 0) participated in this study. Using the quick contrast sensitivity function (qCSF) algorithm, we measured balanced CSF which would stimulate the ON and OFF pathways unselectively, and CSFs for increments and decrements that would selectively stimulate the ON and OFF visual pathways. Contrast sensitivity and area under log contrast sensitivity function were extracted for statistical analysis.

Results

For the balanced CSF, we found significant interocular differences in sensitivity and area under log contrast sensitivity function in both amblyopes [F(1,10) = 74.992, p < 0.001] and controls [F(1,9) = 35.6, p < 0.001], while such differences were more pronounced in amblyopes than in controls. For increment and decrement CSFs, we found that the increment sensitivity (p = 0.038) and area under log contrast sensitivity function (p = 0.001) were significantly lower than the decrement in the amblyopic eye. Such differences between increment and decrement CSFs were not observed in the fellow eye of the amblyopes or in the controls.

Conclusion

There is a subtle difference in the contrast sensitivity of the amblyopic eye when exposed to stimulation in the ON and OFF pathways.

Regional tuning of photoreceptor adaptation in the primate retina

Adaptation in cone photoreceptors allows our visual system to effectively operate over an enormous range of light intensities. However, little is known about the properties of cone adaptation in the specialized region of the primate central retina called the fovea, which is densely packed with cones and mediates high-acuity central vision. Here we show that macaque foveal cones exhibit weaker and slower luminance adaptation compared to cones in the peripheral retina. We find that this difference in adaptive properties between foveal and peripheral cones is due to differences in the magnitude of a hyperpolarization-activated current, Ih. This Ih current regulates the strength and time course of luminance adaptation in peripheral cones where it is more prominent than in foveal cones. A weaker and slower adaptation in foveal cones helps maintain a higher sensitivity for a longer duration which may be well-suited for maximizing the collection of high-acuity information at the fovea during gaze fixation between rapid eye movements.

Combined manifestation of two geometric visual illusions

The present study continued to investigate whether the effects of length misperception caused by cross-shaped (formed by two pairs of the oppositely oriented Müller-Lyer wings) contextual distractors can be explained by the combined manifestation of two different (i.e., the Müller-Lyer and filled-space) geometric illusions of extent. In psychophysical experiments, the luminance of one pair of wings was randomly changed, while the luminance of the other pair remained constant. Two different distractor orientations were used-when the wings with constant luminance formed the right side of the cross or the left side, otherwise. To separately evaluate the manifestation of the Müller-Lyer illusion under different luminance conditions, two distracting crosses of the same orientation were attached to the lateral stimulus terminators in the first series of experiments. In the following four series, a single distracting cross (with different orientation) was attached to one of the lateral stimulus terminators and various combinations of the constant and background luminance were used. To interpret the experimental data, we used the basic computational principles of previously developed quantitative models of hypothetical visual mechanisms underlying the emergence of the Müller-Lyer illusion and the filled-space illusion. It was shown that the results of theoretical calculations adequately approximate the experimental curves obtained for all modifications of stimuli, which strongly supports the suggestion that the joint manifestations of these two illusions can be considered among the main factors determining the features of the illusion investigated.

Lower indoor spatial frequency increases the risk of myopia in children

BACKGROUND/AIMS

Animal models have shown that the absence of high-frequency visual information can precipitate the onset of myopia, but this relationship remains unclear in humans. This study aims to explore the association between the spatial frequency content of the visual environment and myopia in children.

METHODS

Images from the rooms of children and their frequently visited outdoor areas were taken by their parents and collected by the researcher through questionnaires. The spatial frequency was quantified using Matlab. Cycloplegic refraction was used to measure the spherical equivalent (SE), and IOL Master was used to measure axial length (AL) and corneal radius (CR). AL/CR ratio was calculated.

RESULTS

The study included 566 children with an average age of (8.04±1.47) years, of which 270 were girls (47.7%), and the average SE was (0.70±1.21) D. Image analysis revealed that indoor spatial frequency slope was lower than that of the outdoor environment (-1.43±0.18 vs -1.11±0.23, p<0.001). There were 79 myopic individuals (14.0%). Images from indoor content of myopic children had a lower spatial frequency slope than non-myopic children (-1.47±0.16 vs 1.43±0.18, p=0.03) while there was no significant difference in outdoor spatial frequency slope. Regression analysis indicated that the indoor spatial frequency slope was positively associated with SE value (β=0.60, p=0.02) and inversely related to myopia (OR=0.24, p<0.05).

CONCLUSION

The spatial frequency of the outdoor environment is significantly higher than that of the indoor environment. Indoor spatial frequency is related to children's refractive status, with lower indoor spatial frequency being associated with a higher degree of myopia.

A comprehensive data-driven model of cat primary visual cortex

Knowledge integration based on the relationship between structure and function of the neural substrate is one of the main targets of neuroinformatics and data-driven computational modeling. However, the multiplicity of data sources, the diversity of benchmarks, the mixing of observables of different natures, and the necessity of a long-term, systematic approach make such a task challenging. Here we present a first snapshot of a long-term integrative modeling program designed to address this issue in the domain of the visual system: a comprehensive spiking model of cat primary visual cortex. The presented model satisfies an extensive range of anatomical, statistical and functional constraints under a wide range of visual input statistics. In the presence of physiological levels of tonic stochastic bombardment by spontaneous thalamic activity, the modeled cortical reverberations self-generate a sparse asynchronous ongoing activity that quantitatively matches a range of experimentally measured statistics. When integrating feed-forward drive elicited by a high diversity of visual contexts, the simulated network produces a realistic, quantitatively accurate interplay between visually evoked excitatory and inhibitory conductances; contrast-invariant orientation-tuning width; center surround interactions; and stimulus-dependent changes in the precision of the neural code. This integrative model offers insights into how the studied properties interact, contributing to a better understanding of visual cortical dynamics. It provides a basis for future development towards a comprehensive model of low-level perception.

A virtual patient simulation modeling the neural and perceptual effects of human visual cortical stimulation, from pulse trains to percepts

The field of cortical sight restoration prostheses is making rapid progress with three clinical trials of visual cortical prostheses underway. However, as yet, we have only limited insight into the perceptual experiences produced by these implants. Here we describe a computational model or 'virtual patient', based on the neurophysiological architecture of V1, which successfully predicts the perceptual experience of participants across a wide range of previously published human cortical stimulation studies describing the location, size, brightness and spatiotemporal shape of electrically induced percepts in humans. Our simulations suggest that, in the foreseeable future the perceptual quality of cortical prosthetic devices is likely to be limited by the neurophysiological organization of visual cortex, rather than engineering constraints.

Primate retina trades single-photon detection for high-fidelity contrast encoding

How the spike output of the retina enables human visual perception is not fully understood. Here, we address this at the sensitivity limit of vision by correlating human visual perception with the spike outputs of primate ON and OFF parasol (magnocellular) retinal ganglion cells in tightly matching stimulus conditions. We show that human vision at its ultimate sensitivity limit depends on the spike output of the ON but not the OFF retinal pathway. Consequently, nonlinear signal processing in the retinal ON pathway precludes perceptual detection of single photons in darkness but enables quantal-resolution discrimination of differences in light intensity.

Asymmetries between achromatic increments and decrements: Perceptual scales and discrimination thresholds

The perceptual response to achromatic incremental (A+) and decremental (A-) visual stimuli is known to be asymmetrical, due most likely to differences between ON and OFF channels. In the current study, we further investigated this asymmetry psychophysically. In Experiment 1, maximum likelihood difference scaling (MLDS) was used to estimate separately observers' perceptual scales for A+ and A-. In Experiment 2, observers performed two spatial alternative forced choice (2SAFC) pedestal discrimination on multiple pedestal contrast levels, using all combinations of A+ and A- pedestals and tests. Both experiments showed the well-known asymmetry. The perceptual scale curves of A+ follow a modified Naka-Rushton equation, whereas those of A- follow a cubic function. Correspondingly, the discrimination thresholds for the A+ pedestal increased monotonically with pedestal contrast, whereas the thresholds of the A- pedestal first increased as the pedestal contrast increased, then decreased as the contrast became higher. We propose a model that links the results of the two experiments, in which the pedestal discrimination threshold is inversely related to the derivative of the perceptual scale curve. Our findings generally agree with Whittle's previous findings (Whittle, 1986, 1992), which also included strong asymmetry between A+ and A-. We suggest that the perception of achromatic balanced incremental and decremental (bipolar) stimuli, such as gratings or flicker, might be dominated by one polarity due to this asymmetry under some conditions.

Encoding luminance surfaces in the visual cortex of mice and monkeys: difference in responses to edge and center

Luminance and spatial contrast provide information on the surfaces and edges of objects. We investigated neural responses to black and white surfaces in the primary visual cortex (V1) of mice and monkeys. Unlike primates that use their fovea to inspect objects with high acuity, mice lack a fovea and have low visual acuity. It thus remains unclear whether monkeys and mice share similar neural mechanisms to process surfaces. The animals were presented with white or black surfaces and the population responses were measured at high spatial and temporal resolution using voltage-sensitive dye imaging. In mice, the population response to the surface was not edge-dominated with a tendency to center-dominance, whereas in monkeys the response was edge-dominated with a "hole" in the center of the surface. The population response to the surfaces in both species exhibited suppression relative to a grating stimulus. These results reveal the differences in spatial patterns to luminance surfaces in the V1 of mice and monkeys and provide evidence for a shared suppression process relative to grating.

Predicting Single Neuron Responses of the Primary Visual Cortex with Deep Learning Model

Modeling neuron responses to stimuli can shed light on next-generation technologies such as brain-chip interfaces. Furthermore, high-performing models can serve to help formulate hypotheses and reveal the mechanisms underlying neural responses. Here the state-of-the-art computational model is presented for predicting single neuron responses to natural stimuli in the primary visual cortex (V1) of mice. The algorithm incorporates object positions and assembles multiple models with different train-validation data, resulting in a 15%-30% improvement over the existing models in cross-subject predictions and ranking first in the SENSORIUM 2022 Challenge, which benchmarks methods for neuron-specific prediction based on thousands of images. Importantly, The model reveals evidence that the spatial organizations of V1 are conserved across mice. This model will serve as an important noninvasive tool for understanding and utilizing the response patterns of primary visual cortex neurons.

Contrast Sensitivity of ON and OFF Human Retinal Pathways in Myopia

The human visual cortex processes light and dark stimuli with ON and OFF pathways that are differently modulated by luminance contrast. We have previously demonstrated that ON cortical pathways have higher contrast sensitivity than OFF cortical pathways and the difference increases with luminance range (defined as the maximum minus minimum luminance in the scene). Here, we demonstrate that these ON-OFF cortical differences are already present in the human retina and that retinal responses measured with electroretinography are more affected by reductions in luminance range than cortical responses measured with electroencephalography. Moreover, we show that ON-OFF pathway differences measured with electroretinography become more pronounced in myopia, a visual disorder that elongates the eye and blurs vision at far distance. We find that, as the eye axial length increases across subjects, ON retinal pathways become less responsive, slower in response latency, less sensitive, and less effective and slower at driving pupil constriction. Based on these results, we conclude that myopia is associated with a deficit in ON pathway function that decreases the ability of the retina to process low contrast and regulate retinal illuminance in bright environments.

The neural origin for asymmetric coding of surface color in the primate visual cortex

The coding privilege of end-spectral hues (red and blue) in the early visual cortex has been reported in primates. However, the origin of such bias remains unclear. Here, we provide a complete picture of the end-spectral bias in visual system by measuring fMRI signals and spiking activities in macaques. The correlated end-spectral biases between the LGN and V1 suggest a subcortical source for asymmetric coding. Along the ventral pathway from V1 to V4, red bias against green peaked in V1 and then declined, whereas blue bias against yellow showed an increasing trend. The feedforward and recurrent modifications of end-spectral bias were further revealed by dynamic causal modeling analysis. Moreover, we found that the strongest end-spectral bias in V1 was in layer 4C[Formula: see text]. Our results suggest that end-spectral bias already exists in the LGN and is transmitted to V1 mainly through the parvocellular pathway, then embellished by cortical processing.

Dynamic Recruitment of the Feedforward and Recurrent Mechanism for Black-White Asymmetry in the Primary Visual Cortex

Black and white information is asymmetrically distributed in natural scenes, evokes asymmetric neuronal responses, and causes asymmetric perceptions. Recognizing the universality and essentiality of black-white asymmetry in visual information processing, the neural substrates for black-white asymmetry remain unclear. To disentangle the role of the feedforward and recurrent mechanisms in the generation of cortical black-white asymmetry, we recorded the V1 laminar responses and LGN responses of anesthetized cats of both sexes. In a cortical column, we found that black-white asymmetry starts at the input layer and becomes more pronounced in the output layer. We also found distinct dynamics of black-white asymmetry between the output layer and the input layer. Specifically, black responses dominate in all layers after stimulus onset. After stimulus offset, black and white responses are balanced in the input layer, but black responses still dominate in the output layer. Compared with that in the input layer, the rebound response in the output layer is significantly suppressed. The relative suppression strength evoked by white stimuli is notably stronger and depends on the location within the ON-OFF cortical map. A model with delayed and polarity-selective cortical suppression explains black-white asymmetry in the output layer, within which prominent recurrent connections are identified by Granger causality analysis. In addition to black-white asymmetry in response strength, the interlaminar differences in spatial receptive field varied dynamically. Our findings suggest that the feedforward and recurrent mechanisms are dynamically recruited for the generation of black-white asymmetry in V1.SIGNIFICANCE STATEMENT Black-white asymmetry is universal and essential in visual information processing, yet the neural substrates for cortical black-white asymmetry remain unknown. Leveraging V1 laminar recordings, we provided the first laminar pattern of black-white asymmetry in cat V1 and found distinct dynamics of black-white asymmetry between the output layer and the input layer. Comparing black-white asymmetry across three visual hierarchies, the LGN, V1 input layer, and V1 output layer, we demonstrated that the feedforward and recurrent mechanisms are dynamically recruited for the generation of cortical black-white asymmetry. Our findings not only enhance our understanding of laminar processing within a cortical column but also elucidate how feedforward connections and recurrent connections interact to shape neuronal response properties.

Spatiotemporal visual statistics of aquatic environments in the natural habitats of zebrafish

Animal sensory systems are tightly adapted to the demands of their environment. In the visual domain, research has shown that many species have circuits and systems that exploit statistical regularities in natural visual signals. The zebrafish is a popular model animal in visual neuroscience, but relatively little quantitative data is available about the visual properties of the aquatic habitats where zebrafish reside, as compared to terrestrial environments. Improving our understanding of the visual demands of the aquatic habitats of zebrafish can enhance the insights about sensory neuroscience yielded by this model system. We analyzed a video dataset of zebrafish habitats captured by a stationary camera and compared this dataset to videos of terrestrial scenes in the same geographic area. Our analysis of the spatiotemporal structure in these videos suggests that zebrafish habitats are characterized by low visual contrast and strong motion when compared to terrestrial environments. Similar to terrestrial environments, zebrafish habitats tended to be dominated by dark contrasts, particularly in the lower visual field. We discuss how these properties of the visual environment can inform the study of zebrafish visual behavior and neural processing and, by extension, can inform our understanding of the vertebrate brain.

State-of-the-art image and video quality assessment with a metric based on an intrinsically non-linear neural summation model

The development of automatic methods for image and video quality assessment that correlate well with the perception of human observers is a very challenging open problem in vision science, with numerous practical applications in disciplines such as image processing and computer vision, as well as in the media industry. In the past two decades, the goal of image quality research has been to improve upon classical metrics by developing models that emulate some aspects of the visual system, and while the progress has been considerable, state-of-the-art quality assessment methods still share a number of shortcomings, like their performance dropping considerably when they are tested on a database that is quite different from the one used to train them, or their significant limitations in predicting observer scores for high framerate videos. In this work we propose a novel objective method for image and video quality assessment that is based on the recently introduced Intrinsically Non-linear Receptive Field (INRF) formulation, a neural summation model that has been shown to be better at predicting neural activity and visual perception phenomena than the classical linear receptive field. Here we start by optimizing, on a classic image quality database, the four parameters of a very simple INRF-based metric, and proceed to test this metric on three other databases, showing that its performance equals or surpasses that of the state-of-the-art methods, some of them having millions of parameters. Next, we extend to the temporal domain this INRF image quality metric, and test it on several popular video quality datasets; again, the results of our proposed INRF-based video quality metric are shown to be very competitive.

A model of colour appearance based on efficient coding of natural images

An object's colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and "illusions" have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for in quantitative models of colour appearance. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial band's lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next, we systematically test the model's ability to qualitatively predict over 50 brightness and colour phenomena, with almost complete success. This implies that much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a well-founded basis for modelling the vision of humans and other animals.

Differences in visual stimulation between reading and walking and implications for myopia development

Visual input plays an important role in the development of myopia (nearsightedness), a visual disorder that blurs vision at far distances. The risk of myopia progression increases with the time spent reading and decreases with outdoor activity for reasons that remain poorly understood. To investigate the stimulus parameters driving this disorder, we compared the visual input to the retina of humans performing two tasks associated with different risks of myopia progression, reading and walking. Human subjects performed the two tasks while wearing glasses with cameras and sensors that recorded visual scenes and visuomotor activity. When compared with walking, reading black text in white background reduced spatiotemporal contrast in central vision and increased it in peripheral vision, leading to a pronounced reduction in the ratio of central/peripheral strength of visual stimulation. It also made the luminance distribution heavily skewed toward negative dark contrast in central vision and positive light contrast in peripheral vision, decreasing the central/peripheral stimulation ratio of ON visual pathways. It also decreased fixation distance, blink rate, pupil size, and head-eye coordination reflexes dominated by ON pathways. Taken together with previous work, these results support the hypothesis that reading drives myopia progression by understimulating ON visual pathways.

Contrast Increment and Decrement Processing in Individuals With and Without Diabetes

Purpose

Animal models suggest that ON retinal ganglion cells (RGCs) may be more vulnerable to diabetic insult than OFF cells. Using three psychophysical tasks to infer the function of ON and OFF RGCs, we hypothesized that functional responses to contrast increments will be preferentially affected in early diabetes mellitus (DM) compared to contrast decrement responses.

Methods

Fifty-two people with DM (type 1 or type 2) (mean age = 34.8 years, range = 18-60 years) and 48 age-matched controls (mean age = 35.4 years, range = 18-60 years) participated. Experiment 1 measured contrast sensitivity to increments and decrements at four visual field locations. Experiments 2 and 3 measured visual temporal processing using (i) a response time (RT) task, and (ii) a temporal order judgment task. Mean RT and accuracy were collected for experiment 2, whereas experiment 3 measured temporal thresholds.

Results

For experiment 1, the DM group showed reduced increment and decrement contrast sensitivity (F (1, 97) = 4.04, P = 0.047) especially for the central location. For experiment 2, those with DM demonstrated slower RT and lower response accuracies to increments and decrements (increments: U = 780, P = 0.01, decrements: U = 749, P = 0.005). For experiment 3, performance was similar between groups (F (1, 91) = 2.52, P = 0.137).

Conclusions

When assessed cross-sectionally, nonselective functional consequences of retinal neuron damage are present in early DM, particularly for foveal testing. Whether increment-decrement functional indices relate to diabetic retinopathy (DR) progression or poorer visual prognosis in DM requires further study.

Pulse trains to percepts: A virtual patient describing the perceptual effects of human visual cortical stimulation

The field of cortical sight restoration prostheses is making rapid progress with three clinical trials of visual cortical prostheses underway. However, as yet, we have only limited insight into the perceptual experiences produced by these implants. Here we describe a computational model or 'virtual patient', based on the neurophysiological architecture of V1, which successfully predicts the perceptual experience of participants across a wide range of previously published cortical stimulation studies describing the location, size, brightness and spatiotemporal shape of electrically induced percepts in humans. Our simulations suggest that, in the foreseeable future the perceptual quality of cortical prosthetic devices is likely to be limited by the neurophysiological organization of visual cortex, rather than engineering constraints.

Model-Based Approach Shows ON Pathway Afferents Elicit a Transient Decrease of V1 Responses

Neurons in the primary visual cortex (V1) receive excitation and inhibition from distinct parallel pathways processing lightness (ON) and darkness (OFF). V1 neurons overall respond more strongly to dark than light stimuli, consistent with a preponderance of darker regions in natural images, as well as human psychophysics. However, it has been unclear whether this "dark-dominance" is because of more excitation from the OFF pathway or more inhibition from the ON pathway. To understand the mechanisms behind dark-dominance, we record electrophysiological responses of individual simple-type V1 neurons to natural image stimuli and then train biologically inspired convolutional neural networks to predict the neurons' responses. Analyzing a sample of 71 neurons (in anesthetized, paralyzed cats of either sex) has revealed their responses to be more driven by dark than light stimuli, consistent with previous investigations. We show that this asymmetry is predominantly because of slower inhibition to dark stimuli rather than to stronger excitation from the thalamocortical OFF pathway. Consistent with dark-dominant neurons having faster responses than light-dominant neurons, we find dark-dominance to solely occur in the early latencies of neurons' responses. Neurons that are strongly dark-dominated also tend to be less orientation-selective. This novel approach gives us new insight into the dark-dominance phenomenon and provides an avenue to address new questions about excitatory and inhibitory integration in cortical neurons.SIGNIFICANCE STATEMENT Neurons in the early visual cortex respond on average more strongly to dark than to light stimuli, but the mechanisms behind this bias have been unclear. Here we address this issue by combining single-unit electrophysiology with a novel machine learning model to analyze neurons' responses to natural image stimuli in primary visual cortex. Using these techniques, we find slower inhibition to light than to dark stimuli to be the leading mechanism behind stronger dark responses. This slower inhibition to light might help explain other empirical findings, such as why orientation selectivity is weaker at earlier response latencies. These results demonstrate how imbalances in excitation versus inhibition can give rise to response asymmetries in cortical neuron responses.

Contrast and Luminance Gain Control in the Macaque's Lateral Geniculate Nucleus

There is substantial variation in the mean and variance of light levels (luminance and contrast) in natural visual scenes. Retinal ganglion cells maintain their sensitivity despite this variation using two adaptive mechanisms, which control how responses depend on luminance and on contrast. However, the nature of each mechanism and their interactions downstream of the retina are unknown. We recorded neurons in the magnocellular and parvocellular layers of the lateral geniculate nucleus (LGN) in anesthetized adult male macaques and characterized how their responses adapt to changes in contrast and luminance. As contrast increases, neurons in the magnocellular layers maintain sensitivity to high temporal frequency stimuli but attenuate sensitivity to low-temporal frequency stimuli. Neurons in the parvocellular layers do not adapt to changes in contrast. As luminance increases, both magnocellular and parvocellular cells increase their sensitivity to high-temporal frequency stimuli. Adaptation to luminance is independent of adaptation to contrast, as previously reported for LGN neurons in the cat. Our results are similar to those previously reported for macaque retinal ganglion cells, suggesting that adaptation to luminance and contrast result from two independent mechanisms that are retinal in origin.

Tablet-based 'ON/OFF' pathway test can distinguish between rod- and cone-dominated diseases

INTRODUCTION

The photopic ON pathway defect is associated with nocturnal vision loss. However, the measurement of ON function to detect a rod-dominated disease (rods affected more than cones) has not been explored. We evaluated whether the psychophysical evaluation of ON/OFF pathways can be used to distinguish cone-dominated from rod-dominated diseases.

METHODS

Thirty-seven patients with inherited retinal diseases were tested using the 'EyeSpeed' [iOS application] on an iPad. The test displayed a random number (1-3) of light or dark targets on a black-and-white noise background. Participants responded on a touch screen indicating the correct number of targets displayed. The outcome variables-reaction time, accuracy and performance index (speed [1/reaction time] * accuracy) to both light and dark targets were assessed for diagnostic ability using standard receiver-operating characteristic (ROC) analysis.

RESULTS

Mean ± standard deviation age and visual acuity for the cone- and rod-dominated groups were 25.15 ± 11.74 years, 0.80 ± 0.25 logMAR and 28.3 ± 14.29 years, 0.48 ± 0.26 logMAR, respectively. The median reaction time to light targets in rod-dominated disease [interquartile range] was 5.28 s [3.17], significantly greater than for patients with cone-dominated disease (2.07 s [0.93]; Mann-Whitney U test, p < 0.001). Amongst all of the outcome variables evaluated, the reaction time to light targets (criterion of ≥2.98 s) exhibited the highest area under the ROC curve (area = 0.89 ± 0.11; p < 0.001), with a sensitivity and specificity of 82.4% and 85% respectively.

CONCLUSIONS

Reaction time to light targets using the ON/OFF pathway paradigm is a valid marker to differentiate between rod- and cone-dominated retinal dystrophies. ON pathway function measured using a tablet-based test could act as a supplemental test in the diagnosis of challenging photoreceptor-specific inherited retinal diseases.

Luminance Contrast Shifts Dominance Balance between ON and OFF Pathways in Human Vision

Human vision processes light and dark stimuli in visual scenes with separate ON and OFF neuronal pathways. In nature, stimuli lighter or darker than their local surround have different spatial properties and contrast distributions (Ratliff et al., 2010; Cooper and Norcia, 2015; Rahimi-Nasrabadi et al., 2021). Similarly, in human vision, we show that luminance contrast affects the perception of lights and darks differently. At high contrast, human subjects of both sexes locate dark stimuli faster and more accurately than light stimuli, which is consistent with a visual system dominated by the OFF pathway. However, at low contrast, they locate light stimuli faster and more accurately than dark stimuli, which is consistent with a visual system dominated by the ON pathway. Luminance contrast was strongly correlated with multiple ON/OFF dominance ratios estimated from light/dark ratios of performance errors, missed targets, or reaction times (RTs). All correlations could be demonstrated at multiple eccentricities of the central visual field with an ON-OFF perimetry test implemented in a head-mounted visual display. We conclude that high-contrast stimuli are processed faster and more accurately by OFF pathways than ON pathways. However, the OFF dominance shifts toward ON dominance when stimulus contrast decreases, as expected from the higher-contrast sensitivity of ON cortical pathways (Kremkow et al., 2014; Rahimi-Nasrabadi et al., 2021). The results highlight the importance of contrast polarity in visual field measurements and predict a loss of low-contrast vision in humans with ON pathway deficits, as demonstrated in animal models (Sarnaik et al., 2014).SIGNIFICANCE STATEMENT ON and OFF retino-thalamo-cortical pathways respond differently to luminance contrast. In both animal models and humans, low contrasts drive stronger responses from ON pathways, whereas high contrasts drive stronger responses from OFF pathways. We demonstrate that these ON-OFF pathway differences have a correlate in human vision. At low contrast, humans locate light targets faster and more accurately than dark targets but, as contrast increases, dark targets become more visible than light targets. We also demonstrate that contrast is strongly correlated with multiple light/dark ratios of visual performance in central vision. These results provide a link between neuronal physiology and human vision while emphasizing the importance of stimulus polarity in measurements of visual fields and contrast sensitivity.

Faster Detection of "Darks" than "Brights" by Monkey Superior Colliculus Neurons

Visual processing is segregated into ON and OFF channels as early as in the retina, and the superficial (output) layers of the primary visual cortex (V1) are dominated by neurons preferring dark stimuli. However, it is not clear how the timing of neural processing differs between "darks" and "brights" in general, especially in light of psychophysical evidence; it is also equally not clear how subcortical visual pathways that are critical for active orienting represent stimuli of positive (luminance increments) and negative (luminance decrements) contrast polarity. Here, we recorded from all visually-responsive neuron types in the superior colliculus (SC) of two male rhesus macaque monkeys. We presented a disk (0.51° radius) within the response fields (RFs) of neurons, and we varied, across trials, stimulus Weber contrast relative to a gray background. We also varied contrast polarity. There was a large diversity of preferences for darks and brights across the population. However, regardless of individual neural sensitivity, most neurons responded significantly earlier to dark than bright stimuli. This resulted in a dissociation between neural preference and visual response onset latency: a neuron could exhibit a weaker response to a dark stimulus than to a bright stimulus of the same contrast, but it would still have an earlier response to the dark stimulus. Our results highlight an additional candidate visual neural pathway for explaining behavioral differences between the processing of darks and brights, and they demonstrate the importance of temporal aspects in the visual neural code for orienting eye movements.SIGNIFICANCE STATEMENT Objects in our environment, such as birds flying across a bright sky, often project shadows (or images darker than the surround) on our retina. We studied how primate superior colliculus (SC) neurons visually process such dark stimuli. We found that the overall population of SC neurons represented both dark and bright stimuli equally well, as evidenced by a relatively equal distribution of neurons that were either more or less sensitive to darks. However, independent of sensitivity, the great majority of neurons detected dark stimuli earlier than bright stimuli, evidenced by a smaller response latency for the dark stimuli. Thus, SC neural response latency can be dissociated from response sensitivity, and it favors the faster detection of dark image contrasts.

Efficient processing of natural scenes in visual cortex

Neural circuits in the periphery of the visual, auditory, and olfactory systems are believed to use limited resources efficiently to represent sensory information by adapting to the statistical structure of the natural environment. This "efficient coding" principle has been used to explain many aspects of early visual circuits including the distribution of photoreceptors, the mosaic geometry and center-surround structure of retinal receptive fields, the excess OFF pathways relative to ON pathways, saccade statistics, and the structure of simple cell receptive fields in V1. We know less about the extent to which such adaptations may occur in deeper areas of cortex beyond V1. We thus review recent developments showing that the perception of visual textures, which depends on processing in V2 and beyond in mammals, is adapted in rats and humans to the multi-point statistics of luminance in natural scenes. These results suggest that central circuits in the visual brain are adapted for seeing key aspects of natural scenes. We conclude by discussing how adaptation to natural temporal statistics may aid in learning and representing visual objects, and propose two challenges for the future: (1) explaining the distribution of shape sensitivity in the ventral visual stream from the statistics of object shape in natural images, and (2) explaining cell types of the vertebrate retina in terms of feature detectors that are adapted to the spatio-temporal structures of natural stimuli. We also discuss how new methods based on machine learning may complement the normative, principles-based approach to theoretical neuroscience.

Cortical mechanisms of visual brightness

The primary visual cortex signals the onset of light and dark stimuli with ON and OFF cortical pathways. Here, we demonstrate that both pathways generate similar response increments to large homogeneous surfaces and their response average increases with surface brightness. We show that, in cat visual cortex, response dominance from ON or OFF pathways is bimodally distributed when stimuli are smaller than one receptive field center but unimodally distributed when they are larger. Moreover, whereas small bright stimuli drive opposite responses from ON and OFF pathways (increased versus suppressed activity), large bright surfaces drive similar response increments. We show that this size-brightness relation emerges because strong illumination increases the size of light surfaces in nature and both ON and OFF cortical neurons receive input from ON thalamic pathways. We conclude that visual scenes are perceived as brighter when the average response increments from ON and OFF cortical pathways become stronger.

Mazade et al. find that the visual cortex encodes brightness differently for small than large stimuli. Bright small stimuli drive cortical pathways signaling lights and suppress cortical pathways signaling darks. Conversely, large surfaces drive response increments from both pathways and appear brightest when the response average is strongest.

Complex representation of taste quality by second-order gustatory neurons in Drosophila

Sweet and bitter compounds excite different sensory cells and drive opposing behaviors. However, it remains unclear how sweet and bitter tastes are represented by the neural circuits linking sensation to behavior. To investigate this question in Drosophila, we devised trans-Tango(activity), a strategy for calcium imaging of second-order gustatory projection neurons based on trans-Tango, a genetic transsynaptic tracing technique. We found spatial overlap between the projection neuron populations activated by sweet and bitter tastants. The spatial representation of bitter tastants in the projection neurons was consistent, while that of sweet tastants was heterogeneous. Furthermore, we discovered that bitter tastants evoke responses in the gustatory receptor neurons and projection neurons upon both stimulus onset and offset and that bitter offset and sweet onset excite overlapping second-order projections. These findings demonstrate an unexpected complexity in the representation of sweet and bitter tastants by second-order neurons of the gustatory circuit.

Detection and discrimination of achromatic contrast: A ganglion cell perspective

The magnocellular (MC) pathway in the primate has much higher achromatic contrast sensitivity than the parvocellular (PC) pathway, and is implicated in luminance contrast detection. But MC pathway responses tend to saturate at lower achromatic contrast than do PC pathway responses. It has been proposed that the PC pathway plays a major role in discriminating suprathreshold achromatic contrast, because the MC pathway is in saturation. This has been termed the pulsed-pedestal protocol. To test this hypothesis, responses of MC and PC pathway ganglion cells have been examined under suprathreshold conditions with stimulus configurations similar to those in psychophysical tests. For MC cells, response saturation was much less for flashed or moving edges than for sinusoidal modulation, and MC cell thresholds predicted for these stimuli were similar to psychophysical discrimination (and detection) data. Results suggest the protocol is not effective in segregating MC and PC function.

ON than OFF pathway disruption leads to greater deficits in visual function and retinal dopamine signaling

The visual system uses ON and OFF pathways to signal luminance increments and decrements. Increasing evidence suggests that ON and OFF pathways have different signaling properties and serve specialized visual functions. However, it is still unclear the contribution of ON and OFF pathways to visual behavior. Therefore, we examined the effects on optomotor response and the retinal dopamine system in nob mice with ON pathway dysfunction and Vsx1-/- mice with partial OFF pathway dysfunction. Spatial frequency and contrast sensitivity thresholds were determined, and values were compared to age-matched wild-type controls. Retinas were collected immediately after visual testing to measure levels of dopamine and its metabolite, DOPAC. At 4 weeks of age, we found that nob mice had significantly reduced spatial frequency (19%) and contrast sensitivity (60%) thresholds compared to wild-type mice. Vsx1-/- mice also exhibited reductions in optomotor responses (3% in spatial frequency; 18% in contrast sensitivity) at 4 weeks, although these changes were significantly smaller than those found in nob mice. Furthermore, nob mice had significantly lower DOPAC levels (53%) and dopamine turnover (41%) compared to controls while Vsx1-/- mice displayed a transient increase in DOPAC levels at 4 weeks of age (55%). Our results show that dysfunction of ON pathways leads to reductions in contrast sensitivity, spatial frequency threshold, and retinal dopamine turnover whereas partial loss of the OFF pathway has minimal effect. We conclude that ON pathways play a critical role in visual reflexes and retinal dopamine signaling, highlighting a potential association for future investigations.

Age-related decline in function of ON and OFF visual pathways

Purpose

A simple psychophysical paradigm is available as a digital application in iOS devices such as iPad to measure the function of ON and OFF visual pathways. However, an age-matched normative database is not readily available. The purpose of the study is to evaluate the response of ON and OFF visual pathways as a function of age.

Methods

158 normal healthy adults (84 males and 74 females) whose age ranged 18–80 years participated in the study. None of them had any ocular disease (except cataract of grade II or less) and visual acuity of ≤ 20/25. Monocular testing (only one eye) was performed on the ‘EyeSpeed’ application on an iPad at 40cm distance. The targets ranged between 1 to 3 light or dark squares presented randomly in a noise background and participants responded by indicating the number of squares by touching the screen as fast as possible. The main outcome variables are reaction time, accuracy and performance index (1 / speed * accuracy).

Results

The median reaction time was shorter (Median (IQR): 1.53s (0.49) [dark] Vs 1.76s (0.58) [light], p < 0.001) and accuracy was higher (97.21% (3.30) [dark] Vs 95.15% (5.10) [light], p < 0.001) for dark targets than the light targets. Performance index and reaction time for both target types significantly correlated with age (ρ = -0.41 to -0.43; p < 0.001).

Conclusions

This normative database will be useful to quantify disease-specific defects. More importantly, the ON pathway function can potentially serve as a surrogate for rod photoreceptor function.

Predicting and Manipulating Cone Responses to Naturalistic Inputs

Primates explore their visual environment by making frequent saccades, discrete and ballistic eye movements that direct the fovea to specific regions of interest. Saccades produce large and rapid changes in input. The magnitude of these changes and the limited signaling range of visual neurons mean that effective encoding requires rapid adaptation. Here, we explore how macaque cone photoreceptors maintain sensitivity under these conditions. Adaptation makes cone responses to naturalistic stimuli highly nonlinear and dependent on stimulus history. Such responses cannot be explained by linear or linear-nonlinear models but are well explained by a biophysical model of phototransduction based on well-established biochemical interactions. The resulting model can predict cone responses to a broad range of stimuli and enables the design of stimuli that elicit specific (e.g., linear) cone photocurrents. These advances will provide a foundation for investigating the contributions of cone phototransduction and post-transduction processing to visual function.SIGNIFICANCE STATEMENT We know a great deal about adaptational mechanisms that adjust sensitivity to slow changes in visual inputs such as the rising or setting sun. We know much less about the rapid adaptational mechanisms that are essential for maintaining sensitivity as gaze shifts around a single visual scene. We characterize how phototransduction in cone photoreceptors adapts to rapid changes in input similar to those encountered during natural vision. We incorporate these measurements into a quantitative model that can predict cone responses across a broad range of stimuli. This model not only shows how cone phototransduction aids the encoding of natural inputs but also provides a tool to identify the role of the cone responses in shaping those of downstream visual neurons.

Coding strategy for surface luminance switches in the primary visual cortex of the awake monkey

Both surface luminance and edge contrast of an object are essential features for object identification. However, cortical processing of surface luminance remains unclear. In this study, we aim to understand how the primary visual cortex (V1) processes surface luminance information across its different layers. We report that edge-driven responses are stronger than surface-driven responses in V1 input layers, but luminance information is coded more accurately by surface responses. In V1 output layers, the advantage of edge over surface responses increased eight times and luminance information was coded more accurately at edges. Further analysis of neural dynamics shows that such substantial changes for neural responses and luminance coding are mainly due to non-local cortical inhibition in V1’s output layers. Our results suggest that non-local cortical inhibition modulates the responses elicited by the surfaces and edges of objects, and that switching the coding strategy in V1 promotes efficient coding for luminance.

How brightness is encoded in the visual cortex remains incompletely understood. By recording from macaque V1, the authors revealed a switch from surface to edge encoding that is mediated by widespread inhibition in the output layers of the cortex.

ON and OFF Signaling Pathways in the Retina and the Visual System

Visual processing starts at the retina of the eye, and signals are then transferred primarily to the visual cortex and the tectum. In the retina, multiple neural networks encode different aspects of visual input, such as color and motion. Subsequently, multiple neural streams in parallel convey unique aspects of visual information to cortical and subcortical regions. Bipolar cells, which are the second order neurons of the retina, separate visual signals evoked by light and dark contrasts and encode them to ON and OFF pathways, respectively. The interplay between ON and OFF neural signals is the foundation for visual processing for object contrast which underlies higher order stimulus processing. ON and OFF pathways have been classically thought to signal in a mirror-symmetric manner. However, while these two pathways contribute synergistically to visual perception in some instances, they have pronounced asymmetries suggesting independent operation in other cases. In this review, we summarize the role of the ON-OFF dichotomy in visual signaling, aiming to contribute to the understanding of visual recognition.

Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex

Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial frequency (SF) signals and had different neural origins. The low gamma (LG; 25 to 40 Hz) rhythm was generated at the V1 superficial layer and preferred a higher SF compared with spike activity, whereas both the medium gamma (MG; 40 to 65 Hz), generated at the cortical level, and the high gamma HG; (65 to 85 Hz), originated precortically, preferred lower SF information. Furthermore, compared with the rates of spike activity, the powers of the 3 gammas had better performance in discriminating the edge and surface of simple objects. These findings suggest that gamma rhythms reflect the neural dynamics of neural circuitries that process different SF information in the visual system, which may be crucial for multiplexing SF information and synchronizing different features of an object.

Enhancing the dark side: asymmetric gain of cone photoreceptors underpins their discrimination of visual scenes based on skewness

Psychophysical data indicate that humans can discriminate visual scenes based on their skewness, i.e. the ratio of dark and bright patches within a visual scene. It has also been shown that at a phenomenological level this skew discrimination is described by the so-called blackshot mechanism, which accentuates strong negative contrasts within a scene. Here, we present a set of observations suggesting that the underlying computation might start as early as the cone phototransduction cascade, whose gain is higher for strong negative contrasts than for strong positive contrasts. We recorded from goldfish cone photoreceptors and found that the asymmetry in the phototransduction gain leads to responses with larger amplitudes when using negatively rather than positively skewed light stimuli. This asymmetry in amplitude was present in the cone photocurrent, voltage response and synaptic output. Given that the properties of the phototransduction cascade are universal across vertebrates, it is possible that the mechanism shown here gives rise to a general ability to discriminate between scenes based only on their skewness, which psychophysical studies have shown humans can do. Thus, our data suggest the importance of non-linearity of the early photoreceptor for perception. Additionally, we found that stimulus skewness leads to a subtle change in photoreceptor kinetics. For negatively skewed stimuli, the impulse response functions of the cone peak later than for positively skewed stimuli. However, stimulus skewness does not affect the overall integration time of the cone. KEY POINTS: Humans can discriminate visual scenes based on skewness, i.e. the relative prevalence of bright and dark patches within a scene. Here, we show that negatively skewed time-series stimuli induce larger responses in goldfish cone photoreceptors than comparable positively skewed stimuli. This response asymmetry originates from within the phototransduction cascade, where gain is higher for strong negative contrasts (dark patches) than for strong positive contrasts (bright patches). Unlike the implicit assumption often contained within models of downstream visual neurons, our data show that cone photoreceptors do not simply relay linearly filtered versions of visual stimuli to downstream circuitry, but that they also emphasize specific stimulus features. Given that the phototransduction cascade properties among vertebrate retinas are mostly universal, our data imply that the skew discrimination by human subjects reported in psychophysical studies might stem from the asymmetric gain function of the phototransduction cascade.

Visual processing: Systematic variation in light-dark bias across visual space

Detecting changes in luminance is a fundamental property of the visual system. A new study shows that lights and darks are represented differently across visual space, with strong OFF bias in central vision and balanced ON/OFF in the periphery.

From Receptive to Perceptive Fields: Size-Dependent Asymmetries in Both Negative Afterimages and Subcortical On and Off Post-Stimulus Responses

Negative afterimages are perceptual phenomena that occur after physical stimuli disappear from sight. Their origin is linked to transient post-stimulus responses of visual neurons. The receptive fields (RFs) of these subcortical ON- and OFF-center neurons exhibit antagonistic interactions between central and surrounding visual space, resulting in selectivity for stimulus polarity and size. These two features are closely intertwined, yet their relationship to negative afterimage perception remains unknown. Here we tested whether size differentially affects the perception of bright and dark negative afterimages in humans of both sexes, and how this correlates with neural mechanisms in subcortical ON and OFF cells. Psychophysically, we found a size-dependent asymmetry whereby dark disks produce stronger and longer-lasting negative afterimages than bright disks of equal contrast at sizes >0.8°. Neurophysiological recordings from retinal and relay cells in female cat dorsal lateral geniculate nucleus showed that subcortical ON cells exhibited stronger sustained post-stimulus responses to dark disks, than OFF cells to bright disks, at sizes >1°. These sizes agree with the emergence of center-surround antagonism, revealing stronger suppression to opposite-polarity stimuli for OFF versus ON cells, particularly in dorsal lateral geniculate nucleus. Using a network-based retino-geniculate model, we confirmed stronger antagonism and temporal transience for OFF-cell post-stimulus rebound responses. A V1 population model demonstrated that both strength and duration asymmetries can be propagated to downstream cortical areas. Our results demonstrate how size-dependent antagonism impacts both the neuronal post-stimulus response and the resulting afterimage percepts, thereby supporting the idea of perceptual RFs reflecting the underlying neuronal RF organization of single cells.SIGNIFICANCE STATEMENT Visual illusions occur when sensory inputs and perceptual outcomes do not match, and provide a valuable tool to understand transformations from neural to perceptual responses. A classic example are negative afterimages that remain visible after a stimulus is removed from view. Such perceptions are linked to responses in early visual neurons, yet the details remain poorly understood. Combining human psychophysics, neurophysiological recordings in cats and retino-thalamo-cortical computational modeling, our study reveals how stimulus size and the receptive-field structure of subcortical ON and OFF cells contributes to the parallel asymmetries between neural and perceptual responses to bright versus dark afterimages. Thus, this work provides a deeper link from the underlying neural mechanisms to the resultant perceptual outcomes.

Helmholtz Versus Haute Couture: How Horizontal Stripes and Dark Clothes Make You Look Thinner

In Helmholtz’s illusion, a square with horizontal stripes appears taller than an identical square with vertical stripes. This effect has also been observed in experiments with human stimuli, where a human figure wearing a dress with horizontal stripes appears thinner than a drawing clad in vertical stripes. These findings do not agree with the common belief that clothes with horizontal stripes make someone appear wider, neither do they disentangle whether the horizontal or vertical stripes account for the thinning effect. In the present study, we focused on the effect of horizontal stripes in clothes comparing horizontal stripes against no-stripes (not against vertical; Experiments 1 and 2), using photos of a real-life female model, and controlling for the average luminance of the stripes (Experiment 2). Results showed that horizontal stripes and lower luminance have—independently—a small-to-moderate thinning effect on the perceived size of the body, and the effect is larger when the two variables are combined. In Experiment 3, we further show that the thinning effect due to the luminance of the dress is enhanced when the general background gets darker.

Color appearance model incorporating contrast adaptation - implications for individual differences in color vision

Color appearance models use standard color matching functions to derive colorimetric information from spectral radiometric measurements of a visual environment, and they process that information to predict color perceptual attributes such as hue, chroma and lightness. That processing is usually done by equations with fixed numerical coefficients that were predetermined to yield optimal agreement for a given standard observer. Here we address the well-known fact that, among color-normal observers, there are significant differences of color matching functions. These cause disagreements between individuals as to whether certain colors match, an important effect that is often called observer metamerism. Yet how these individual sensitivity differences translate into differences in perceptual metrics is not fully addressed by many appearance models. It might seem that appearance could be predicted by substituting an individual's color matching functions into an otherwise-unchanged color appearance model, but this is problematic because the model's coefficients were not optimized for the new observer. Here we explore a solution guided by the idea that processes of adaptation in the visual system tend to compensate color perception for differences in cone responses and consequent color matching functions. For this purpose, we developed a simple color appearance model that uses only a few numerical coefficients, yet accurately predicts the perceptual attributes of Munsell samples under a selected standard lighting condition. We then added a feedback loop to automatically adjust the model coefficients, in response to switching between cone fundamentals simulating different observers and color matching functions. This adjustment is intended to model long term contrast adaptation in the vision system by maintaining average overall color contrast levels. Incorporating this adaptation principle into color appearance models could allow better assessments of displays and illumination systems, to help improve color appearances for most observers.

Matching visual induction effects on screens of different size

In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen-size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images.

Segmenting surface boundaries using luminance cues

Segmenting scenes into distinct surfaces is a basic visual perception task, and luminance differences between adjacent surfaces often provide an important segmentation cue. However, mean luminance differences between two surfaces may exist without any sharp change in albedo at their boundary, but rather from differences in the proportion of small light and dark areas within each surface, e.g. texture elements, which we refer to as a luminance texture boundary. Here we investigate the performance of human observers segmenting luminance texture boundaries. We demonstrate that a simple model involving a single stage of filtering cannot explain observer performance, unless it incorporates contrast normalization. Performing additional experiments in which observers segment luminance texture boundaries while ignoring super-imposed luminance step boundaries, we demonstrate that the one-stage model, even with contrast normalization, cannot explain performance. We then present a Filter–Rectify–Filter model positing two cascaded stages of filtering, which fits our data well, and explains observers' ability to segment luminance texture boundary stimuli in the presence of interfering luminance step boundaries. We propose that such computations may be useful for boundary segmentation in natural scenes, where shadows often give rise to luminance step edges which do not correspond to surface boundaries.

Different roles of subcortical inputs in V1 responses to luminance and contrast

Cells in the primary visual cortex (V1) generally respond weakly to large uniform luminance stimuli. Only a subset of V1 cells is thought to encode uniform luminance information. In natural scenes, local luminance is an important feature for defining an object that varies and coexists with local spatial contrast. However, the strategies used by V1 cells to encode local mean luminance for spatial contrast stimuli remain largely unclear. Here, using extracellular recordings in anesthetized cats, we investigated the responses of V1 cells by comparing with those of retinal ganglion (RG) cells and lateral geniculate nucleus (LGN) cells to simultaneous and rapid changes in luminance and spatial contrast. Almost all V1 cells exhibited a strong monotonic increasing luminance tuning when they were exposed to high spatial contrast. Thus, V1 cells encode the luminance carried by spatial contrast stimuli with the monotonically increasing response function. Moreover, high contrast decreased luminance tuning of OFF cells but increased that of in ON cells in RG and LGN. The luminance and contrast tunings of LGN ON cells were highly separable as V1 cells, whereas those of LGN OFF cells were lowly separable. These asymmetrical effects of spatial contrast on ON/OFF channels might underlie the robust ability of V1 cells to perform luminance tuning when exposed to spatial contrast stimuli.

Darks and Lights, the 'Yin-Yang' of Vision Depends on Luminance

We all know the disappointment when, after a wonderful snapshot, the details in the photo are at much lower contrast than seen before with our own eyes. A recent study by Rahimi-Nasrabadi et al. revealed that this is because human vision accounts for actual luminance range and for accompanied asymmetric changes in dark and light contrasts.

Image luminance changes contrast sensitivity in visual cortex

Accurate measures of contrast sensitivity are important for evaluating visual disease progression and for navigation safety. Previous measures suggested that cortical contrast sensitivity was constant across widely different luminance ranges experienced indoors and outdoors. Against this notion, here, we show that luminance range changes contrast sensitivity in both cat and human cortex, and the changes are different for dark and light stimuli. As luminance range increases, contrast sensitivity increases more within cortical pathways signaling lights than those signaling darks. Conversely, when the luminance range is constant, light-dark differences in contrast sensitivity remain relatively constant even if background luminance changes. We show that a Naka-Rushton function modified to include luminance range and light-dark polarity accurately replicates both the statistics of light-dark features in natural scenes and the cortical responses to multiple combinations of contrast and luminance. We conclude that differences in light-dark contrast increase with luminance range and are largest in bright environments.

Evidence for the intrinsically nonlinear nature of receptive fields in vision

The responses of visual neurons, as well as visual perception phenomena in general, are highly nonlinear functions of the visual input, while most vision models are grounded on the notion of a linear receptive field (RF). The linear RF has a number of inherent problems: it changes with the input, it presupposes a set of basis functions for the visual system, and it conflicts with recent studies on dendritic computations. Here we propose to model the RF in a nonlinear manner, introducing the intrinsically nonlinear receptive field (INRF). Apart from being more physiologically plausible and embodying the efficient representation principle, the INRF has a key property of wide-ranging implications: for several vision science phenomena where a linear RF must vary with the input in order to predict responses, the INRF can remain constant under different stimuli. We also prove that Artificial Neural Networks with INRF modules instead of linear filters have a remarkably improved performance and better emulate basic human perception. Our results suggest a change of paradigm for vision science as well as for artificial intelligence.

Mechanism for analogous illusory motion perception in flies and humans

Visual motion detection is one of the most important computations performed by visual circuits. Yet, we perceive vivid illusory motion in stationary, periodic luminance gradients that contain no true motion. This illusion is shared by diverse vertebrate species, but theories proposed to explain this illusion have remained difficult to test. Here, we demonstrate that in the fruit fly Drosophila, the illusory motion percept is generated by unbalanced contributions of direction-selective neurons' responses to stationary edges. First, we found that flies, like humans, perceive sustained motion in the stationary gradients. The percept was abolished when the elementary motion detector neurons T4 and T5 were silenced. In vivo calcium imaging revealed that T4 and T5 neurons encode the location and polarity of stationary edges. Furthermore, our proposed mechanistic model allowed us to predictably manipulate both the magnitude and direction of the fly's illusory percept by selectively silencing either T4 or T5 neurons. Interestingly, human brains possess the same mechanistic ingredients that drive our model in flies. When we adapted human observers to moving light edges or dark edges, we could manipulate the magnitude and direction of their percepts as well, suggesting that mechanisms similar to the fly's may also underlie this illusion in humans. By taking a comparative approach that exploits Drosophila neurogenetics, our results provide a causal, mechanistic account for a long-known visual illusion. These results argue that this illusion arises from architectures for motion detection that are shared across phyla.