The challenges natural images pose for visual adaptation

Adaptation with Naturalistic Textures in Macaque V1 and V2

Adaptation affects neuronal responsivity and selectivity throughout the visual hierarchy. However, because most prior studies have tailored stimuli to a single brain area of interest, we have a poor understanding of how exposure to a particular image alters responsivity and tuning at different stages of visual processing. Here we assess how adaptation with naturalistic textures alters neuronal responsivity and selectivity in primary visual cortex (V1) and area V2 of macaque monkeys. Neurons in both areas respond to textures, but V2 neurons are sensitive to higher-order image statistics which do not strongly modulate V1 responsivity. We tested the specificity of adaptation in each area with textures and spectrally matched "noise" stimuli. Adaptation reduced responsivity in both V1 and V2, but only in V2 was the reduction dependent on the presence of higher-order texture statistics. Despite this specificity, the texture information provided by single neurons and populations was reduced after adaptation, in both V1 and V2. Our results suggest that adaptation effects for a given feature are induced at the stage of processing that tuning for that feature first arises and that stimulus-specific adaptation effects need not result in improved sensory encoding.

Enhanced restoration of visual code after targeting ON bipolar cells compared with retinal ganglion cells with optogenetic therapy

Optogenetic therapy is a promising vision restoration method where light-sensitive opsins are introduced to the surviving inner retina following photoreceptor degeneration. The cell type targeted for opsin expression will likely influence the quality of restored vision. However, a like-for-like preclinical comparison of visual responses evoked following equivalent opsin expression in the two major targets, ON bipolar (ON BCs) or retinal ganglion cells (RGCs), is absent. We address this deficit by comparing stimulus-response characteristics at single-unit resolution in the retina and dorsal lateral geniculate nucleus of retinally degenerate mice genetically engineered to express the opsin ReaChR in Grm6- or Brn3c-expressing cells (ON BC vs. RGCs, respectively). For both targeting strategies, we find ReaChR-evoked responses have equivalent sensitivity and can encode contrast across different background irradiances. Compared with ON BCs, targeting RGCs decreased response reproducibility and resulted in more stereotyped responses with reduced diversity in response polarity, contrast sensitivity, and temporal frequency tuning. Recording ReaChR-driven responses in visually intact retinas confirmed that RGC-targeted ReaChR expression disrupts visual feature selectivity of individual RGCs. Our data show that, while both approaches restore visual responses with impressive fidelity, ON BC targeting produces a richer visual code closer to that of wild-type mice.

Fixational eye movements and edge integration in lightness perception

A neural theory of human lightness computation is described and computer-simulated. The theory proposes that lightness is derived from transient ON and OFF cell responses in the early visual pathways that have different characteristic neural gains and that are generated by fixational eye movements (FEMs) as the eyes transit luminance edges in the image. The ON and OFF responses are combined with corollary discharge signals that encode the eye movement direction to create directionally selective ON and OFF responses. Cortical neurons with large-scale receptive fields independently integrate the outputs of all of the directional ON or OFF responses whose associated eye movement directions point towards their receptive field centers, with a spatial weighting determined by the receptive field profile. Lightness is computed by subtracting the spatially integrated OFF activity from spatially integrated ON activity and normalizing the difference signal so that the maximum response in the spatial lightness map at any given time equals a fixed activation level corresponding to the percept of white. Two different mechanisms for ON and OFF cells responses are considered and simulated, and both are shown to produce an overall lightness model that explains a host of quantitative and qualitative lightness phenomena, including the Staircase Gelb and related illusions, failures of lightness constancy in the simultaneous contrast illusion, Chevreul's illusion, lightness filling-in, and perceptual fading of stabilized images. The neural plausibility of the two variants of the theory, as well as its implication for lightness constancy and failures of lightness constancy are discussed.

Asymmetric Activation of Retinal ON and OFF Pathways by AOSLO Raster-Scanned Visual Stimuli

Adaptive optics scanning light ophthalmoscopy (AOSLO) enables high-resolution retinal imaging, eye tracking, and stimulus delivery in the living eye. AOSLO-mediated visual stimuli are created by temporally modulating the excitation light as it scans across the retina. As a result, each location within the field of view receives a brief flash of light during each scanner cycle (every 33-40 ms). Here we used in vivo calcium imaging with AOSLO to investigate the impact of this intermittent stimulation on the retinal ON and OFF pathways. Raster-scanned backgrounds exaggerated existing ON-OFF pathway asymmetries leading to high baseline activity in ON cells and increased response rectification in OFF cells.

Neuronal heterogeneity of normalization strength in a circuit model

The size of a neuron's receptive field increases along the visual hierarchy. Neurons in higher-order visual areas integrate information through a canonical computation called normalization, where neurons respond sublinearly to multiple stimuli in the receptive field. Neurons in the visual cortex exhibit highly heterogeneous degrees of normalization. Recent population recordings from visual cortex find that the interactions between neurons, measured by spike count correlations, depend on their normalization strengths. However, the circuit mechanism underlying the heterogeneity of normalization is unclear. In this work, we study normalization in a spiking neuron network model of visual cortex. The model produces a range of neuronal heterogeneity of normalization strength and the heterogeneity is highly correlated with the inhibitory current each neuron receives. Our model reproduces the dependence of spike count correlations on normalization as observed in experimental data, which is explained by the covariance with the inhibitory current. We find that neurons with stronger normalization are more sensitive to contrast differences in images and encode information more efficiently. In addition, networks with more heterogeneity in normalization encode more information about visual stimuli. Together, our model provides a mechanistic explanation of heterogeneous normalization strengths in the visual cortex, and sheds new light on the computational benefits of neuronal heterogeneity.

A new role for excitation in the retinal direction-selective circuit

A key feature of the receptive field of neurons in the visual system is their centre-surround antagonism, whereby the centre and the surround exhibit responses of opposite polarity. This organization is thought to enhance visual acuity, but whether and how such antagonism plays a role in more complex processing remains poorly understood. Here, we investigate the role of centre and surround receptive fields in retinal direction selectivity by exposing posterior-preferring On-Off direction-selective ganglion cells (pDSGCs) to adaptive light and recording their response to globally moving objects. We reveal that light adaptation leads to surround expansion in pDSGCs. The pDSGCs maintain their original directional tuning in the centre receptive field, but present the oppositely tuned response in their surround. Notably, although inhibition is the main substrate for retinal direction selectivity, we found that following light adaptation, both the centre- and surround-mediated responses originate from directionally tuned excitatory inputs. Multi-electrode array recordings show similar oppositely tuned responses in other DSGC subtypes. Together, these data attribute a new role for excitation in the direction-selective circuit. This excitation carries an antagonistic centre-surround property, possibly designed to sharpen the detection of motion direction in the retina. KEY POINTS: Receptive fields of direction-selective retinal ganglion cells expand asymmetrically following light adaptation. The increase in the surround receptive field generates a delayed spiking phase that is tuned to the null direction and is mediated by excitation. Following light adaptation, excitation rules the computation in the centre receptive field and is tuned to the preferred direction. GABAergic and glycinergic inputs modulate the null-tuned delayed response differentially. Null-tuned delayed spiking phases can be detected in all types of direction-selective retinal ganglion cells. Light adaptation exposes a hidden directional excitation in the circuit, which is tuned to opposite directions in the centre and surround receptive fields.

Cilia structure and intraflagellar transport differentially regulate sensory response dynamics within and between C. elegans chemosensory neurons

Sensory neurons contain morphologically diverse primary cilia that are built by intraflagellar transport (IFT) and house sensory signaling molecules. Since both ciliary structural and signaling proteins are trafficked via IFT, it has been challenging to decouple the contributions of IFT and cilia structure to neuronal responses. By acutely inhibiting IFT without altering cilia structure and vice versa, here we describe the differential roles of ciliary trafficking and sensory ending morphology in shaping chemosensory responses in Caenorhabditis elegans. We show that a minimum cilium length but not continuous IFT is necessary for a subset of responses in the ASH nociceptive neurons. In contrast, neither cilia nor continuous IFT are necessary for odorant responses in the AWA olfactory neurons. Instead, continuous IFT differentially modulates response dynamics in AWA. Upon acute inhibition of IFT, cilia-destined odorant receptors are shunted to ectopic branches emanating from the AWA cilia base. Spatial segregation of receptors in these branches from a cilia-restricted regulatory kinase results in odorant desensitization defects, highlighting the importance of precise organization of signaling molecules at sensory endings in regulating response dynamics. We also find that adaptation of AWA responses upon repeated exposure to an odorant is mediated by IFT-driven removal of its cognate receptor, whereas adaptation to a second odorant is regulated via IFT-independent mechanisms. Our results reveal unexpected complexity in the contribution of IFT and cilia organization to the regulation of responses even within a single chemosensory neuron type and establish a critical role for these processes in the precise modulation of olfactory behaviors.

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.

Neural pathways and computations that achieve stable contrast processing tuned to natural scenes

Natural scenes are highly dynamic, challenging the reliability of visual processing. Yet, humans and many animals perform accurate visual behaviors, whereas computer vision devices struggle with rapidly changing background luminance. How does animal vision achieve this? Here, we reveal the algorithms and mechanisms of rapid luminance gain control in Drosophila, resulting in stable visual processing. We identify specific transmedullary neurons as the site of luminance gain control, which pass this property to direction-selective cells. The circuitry further involves wide-field neurons, matching computational predictions that local spatial pooling drive optimal contrast processing in natural scenes when light conditions change rapidly. Experiments and theory argue that a spatially pooled luminance signal achieves luminance gain control via divisive normalization. This process relies on shunting inhibition using the glutamate-gated chloride channel GluClα. Our work describes how the fly robustly processes visual information in dynamically changing natural scenes, a common challenge of all visual systems.

Adaptation in the visual system: Networked fatigue or suppressed prediction error signalling?

Our brains are constantly adapting to changes in our visual environments. Neural adaptation exerts a persistent influence on the activity of sensory neurons and our perceptual experience, however there is a lack of consensus regarding how adaptation is implemented in the visual system. One account describes fatigue-based mechanisms embedded within local networks of stimulus-selective neurons (networked fatigue models). Another depicts adaptation as a product of stimulus expectations (predictive coding models). In this review, I evaluate neuroimaging and psychophysical evidence that poses fundamental problems for predictive coding models of neural adaptation. Specifically, I discuss observations of distinct repetition and expectation effects, as well as incorrect predictions of repulsive adaptation aftereffects made by predictive coding accounts. Based on this evidence, I argue that networked fatigue models provide a more parsimonious account of adaptation effects in the visual system. Although stimulus expectations can be formed based on recent stimulation history, any consequences of these expectations are likely to co-occur (or interact) with effects of fatigue-based adaptation. I conclude by proposing novel, testable hypotheses relating to interactions between fatigue-based adaptation and other predictive processes, focusing on stimulus feature extrapolation phenomena.

A pupillary contrast response in mice and humans: Neural mechanisms and visual functions

In the pupillary light response (PLR), increases in ambient light constrict the pupil to dampen increases in retinal illuminance. Here, we report that the pupillary reflex arc implements a second input-output transformation; it senses temporal contrast to enhance spatial contrast in the retinal image and increase visual acuity. The pupillary contrast response (PCoR) is driven by rod photoreceptors via type 6 bipolar cells and M1 ganglion cells. Temporal contrast is transformed into sustained pupil constriction by the M1's conversion of excitatory input into spike output. Computational modeling explains how the PCoR shapes retinal images. Pupil constriction improves acuity in gaze stabilization and predation in mice. Humans exhibit a PCoR with similar tuning properties to mice, which interacts with eye movements to optimize the statistics of the visual input for retinal encoding. Thus, we uncover a conserved component of active vision, its cell-type-specific pathway, computational mechanisms, and optical and behavioral significance.

Unique yellow shifts for small and brief stimuli in the central retina

The spectral locus of unique yellow was determined for flashes of different sizes (<11 arcmin) and durations (<500 ms) presented in and near the fovea. An adaptive optics scanning laser ophthalmoscope was used to minimize the effects of higher-order aberrations during simultaneous stimulus delivery and retinal imaging. In certain subjects, parafoveal cones were classified as L, M, or S, which permitted the comparison of unique yellow measurements with variations in local L/M ratios within and between observers. Unique yellow shifted to longer wavelengths as stimulus size or duration was reduced. This effect is most pronounced for changes in size and more apparent in the fovea than in the parafovea. The observed variations in unique yellow are not entirely predicted from variations in L/M ratio and therefore implicate neural processes beyond photoreception.

Differential modulation of sensory response dynamics by cilia structure and intraflagellar transport within and across chemosensory neurons

Sensory neurons contain morphologically diverse primary cilia that are built by intraflagellar transport (IFT) and house sensory signaling molecules. Since both ciliary structural and signaling proteins are trafficked via IFT, it has been challenging to decouple the contributions of IFT and cilia structure to neuronal responses. By acutely inhibiting IFT without altering cilia structure and vice versa , here we describe the differential roles of ciliary trafficking and sensory ending morphology in shaping chemosensory responses in C. elegans. We show that a minimum cilium length but not continuous IFT is necessary for a subset of responses in the ASH nociceptive neurons. In contrast, neither cilia nor continuous IFT are necessary for odorant responses in the AWA olfactory neurons. Instead, continuous IFT differentially modulates response dynamics in AWA. Upon acute inhibition of IFT, cilia-destined odorant receptors are shunted to ectopic branches emanating from the cilia base. Spatial segregation of receptors in these branches from a cilia-restricted regulatory kinase results in odorant desensitization defects, highlighting the importance of precise organization of signaling molecules at sensory endings in regulating response dynamics. We also find that adaptation of AWA responses upon repeated exposure to an odorant is mediated by IFT-driven removal of its cognate receptor, whereas adaptation to a second odorant is regulated via IFT-independent mechanisms. Our results reveal unexpected complexity in the contribution of IFT and cilia organization to the regulation of responses even within a single chemosensory neuron type, and establish a critical role for these processes in the precise modulation of olfactory behaviors.

Recommendations for measuring and standardizing light for laboratory mammals to improve welfare and reproducibility in animal research

Light enables vision and exerts widespread effects on physiology and behavior, including regulating circadian rhythms, sleep, hormone synthesis, affective state, and cognitive processes. Appropriate lighting in animal facilities may support welfare and ensure that animals enter experiments in an appropriate physiological and behavioral state. Furthermore, proper consideration of light during experimentation is important both when it is explicitly employed as an independent variable and as a general feature of the environment. This Consensus View discusses metrics to use for the quantification of light appropriate for nonhuman mammals and their application to improve animal welfare and the quality of animal research. It provides methods for measuring these metrics, practical guidance for their implementation in husbandry and experimentation, and quantitative guidance on appropriate light exposure for laboratory mammals. The guidance provided has the potential to improve data quality and contribute to reduction and refinement, helping to ensure more ethical animal use.

Designing for sensory adaptation: what you see depends on what you've been looking at - Recommendations, guidelines and standards should reflect this

Sensory systems continuously recalibrate their responses according to the current stimulus environment. As a result, perception is strongly affected by the current and recent context. These adaptative changes affect both sensitivity (e.g., habituating to noise, seeing better in the dark) and appearance (e.g. how things look, what catches attention) and adjust to many perceptual properties (e.g. from light level to the characteristics of someone's face). They therefore have a profound effect on most perceptual experiences, and on how and how well the senses work in different settings. Characterizing the properties of adaptation, how it manifests, and when it influences perception in modern environments can provide insights into the diversity of human experience. Adaptation could also be leveraged both to optimize perceptual abilities (e.g. in visual inspection tasks like radiology) and to mitigate unwanted consequences (e.g. exposure to potentially unhealthy stimulus environments).

Interactions between specialized gain control mechanisms in olfactory processing

Gain control is a process that adjusts a system's sensitivity when input levels change. Neural systems contain multiple mechanisms of gain control, but we do not understand why so many mechanisms are needed or how they interact. Here, we investigate these questions in the Drosophila antennal lobe, where we identify several types of inhibitory interneurons with specialized gain control functions. We find that some interneurons are nonspiking, with compartmentalized calcium signals, and they specialize in intra-glomerular gain control. Conversely, we find that other interneurons are recruited by strong and widespread network input; they specialize in global presynaptic gain control. Using computational modeling and optogenetic perturbations, we show how these mechanisms can work together to improve stimulus discrimination while also minimizing temporal distortions in network activity. Our results demonstrate how the robustness of neural network function can be increased by interactions among diverse and specialized mechanisms of gain control.

Stimulus expectations do not modulate visual event-related potentials in probabilistic cueing designs

Humans and other animals can learn and exploit repeating patterns that occur within their environments. These learned patterns can be used to form expectations about future sensory events. Several influential predictive coding models have been proposed to explain how learned expectations influence the activity of stimulus-selective neurons in the visual system. These models specify reductions in neural response measures when expectations are fulfilled (termed expectation suppression) and increases following surprising sensory events. However, there is currently scant evidence for expectation suppression in the visual system when confounding factors are taken into account. Effects of surprise have been observed in blood oxygen level dependent (BOLD) signals, but not when using electrophysiological measures. To provide a strong test for expectation suppression and surprise effects we performed a predictive cueing experiment while recording electroencephalographic (EEG) data. Participants (n=48) learned cue-face associations during a training session and were then exposed to these cue-face pairs in a subsequent experiment. Using univariate analyses of face-evoked event-related potentials (ERPs) we did not observe any differences across expected (90% probability), neutral (50%) and surprising (10%) face conditions. Across these comparisons, Bayes factors consistently favoured the null hypothesis throughout the time-course of the stimulus-evoked response. When using multivariate pattern analysis we did not observe above-chance classification of expected and surprising face-evoked ERPs. By contrast, we found robust within- and across-trial stimulus repetition effects. Our findings do not support predictive coding-based accounts that specify reduced prediction error signalling when perceptual expectations are fulfilled. They instead highlight the utility of other types of predictive processing models that describe expectation-related phenomena in the visual system without recourse to prediction error signalling.

Little information loss with red-green color deficient vision in natural environments

Inherited color vision deficiency affects red-green discrimination in about one in twelve men from European populations. Its effects have been studied mainly in primitive foraging but also in detecting blushing and breaking camouflage. Yet there is no obvious relationship between these specific tasks and vision in the real world. The aim here was to quantify the impact of color vision deficiency by estimating computationally the information available to observers about colored surfaces in natural scenes. With representative independent sets of 50 and 100 hyperspectral images, estimated information was found to be only a little less in red-green color vision deficiency than in normal trichromacy. Colorimetric analyses revealed the importance of large lightness variations within scenes, small redness-greenness variations, and uneven frequencies of different colored surfaces. While red-green color vision deficiency poses challenges in some tasks, it has much less effect on gaining information from natural environments.

Insect vision: Contrast perception under fluctuating light

Natural light levels vary tremendously, both over the day and from minute to minute, creating a formidable challenge for animals that rely on vision to survive. New work in fruit flies demonstrates the neural mechanisms that produce luminance-invariant perceptions of visual contrast.

Multifaceted luminance gain control beyond photoreceptors in Drosophila

Animals navigating in natural environments must handle vast changes in their sensory input. Visual systems, for example, handle changes in luminance at many timescales, from slow changes across the day to rapid changes during active behavior. To maintain luminance-invariant perception, visual systems must adapt their sensitivity to changing luminance at different timescales. We demonstrate that luminance gain control in photoreceptors alone is insufficient to explain luminance invariance at both fast and slow timescales and reveal the algorithms that adjust gain past photoreceptors in the fly eye. We combined imaging and behavioral experiments with computational modeling to show that downstream of photoreceptors, circuitry taking input from the single luminance-sensitive neuron type L3 implements gain control at fast and slow timescales. This computation is bidirectional in that it prevents the underestimation of contrasts in low luminance and overestimation in high luminance. An algorithmic model disentangles these multifaceted contributions and shows that the bidirectional gain control occurs at both timescales. The model implements a nonlinear interaction of luminance and contrast to achieve gain correction at fast timescales and a dark-sensitive channel to improve the detection of dim stimuli at slow timescales. Together, our work demonstrates how a single neuronal channel performs diverse computations to implement gain control at multiple timescales that are together important for navigation in natural environments.

Fast visual adaptation to dim light in a cavity-nesting bird

Many birds move fast into dark nest cavities forcing the visual system to adapt to low light intensities. Their visual system takes between 15 and 60 min for complete dark adaptation, but little is known about the visual performance of birds during the first seconds in low light intensities. In a forced two-choice behavioural experiment we studied how well budgerigars can discriminate stimuli of different luminance directly after entering a darker environment. The birds made their choices within about 1 s and did not wait to adapt their visual system to the low light intensities. When moving from a bright facility into an environment with 0.5 log unit lower illuminance, the budgerigars detected targets with a luminance of 0.825 cd m^-2 on a black background. When moving into an environment with 1.7 or 3.5 log units lower illuminance, they detected targets with luminances between 0.106 and 0.136 cd m^-2. In tests with two simultaneously displayed targets, the birds discriminated similar luminance differences between the targets (Weber fraction of 0.41-0.54) in all light levels. Our results support the notion that partial adaptation of bird eyes to the lower illumination occurring within 1 s allows them to safely detect and feed their chicks.

Panoramic visual statistics shape retina-wide organization of receptive fields

Statistics of natural scenes are not uniform-their structure varies dramatically from ground to sky. It remains unknown whether these nonuniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. Using the mouse (Mus musculus) as a model species, we show that receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon, in agreement with our predictions. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell types.

Weber’s Law of perception is a consequence of resolving the intensity of natural scintillating light and sound with the least possible error

Efficient resolution of natural light and sound intensity is essential for organisms, systems and machines that rely on visual and auditory sensory perception to survive or function effectively in their environment. This resolution obeys Weber’s Law when the smallest resolvable change, a just-noticeable-difference, grows in direct proportion to the stimulus. Here, Weber’s Law is found to be a consequence of attaining the theoretical minimum mean-square error possible, the Cramer–Rao lower bound, in resolving the intensity of naturally scintillating light and sound. The finding is based on statistics from thousands of measurements of naturally scintillating environmental light and sound signals. Remarkably, just-noticeable-differences in light and sound intensity measured over decades of psychophysical experiments with artificial sources are also found to approximately attain the respective Cramer–Rao lower bounds. Human intensity resolution is in this way optimally adapted to the natural scintillation of light and sound. Pattern recognition by simple matched-filter correlation between measured and hypothetical images cancels natural scintillation. For intensity perception obeying Weber’s Law, this is found to be advantageous and statistically optimal because perceived scintillation is independent of the underlying signal pattern. A small visual patch change or acoustic signature truncation is shown to be lost in natural signal-dependent fluctuations if perception with constant intensity resolution is attempted.

Gaining the system: limits to compensating color deficiencies through post-receptoral gain changes

Color percepts of anomalous trichromats are often more similar to normal trichromats than predicted from their receptor spectral sensitivities, suggesting that post-receptoral mechanisms can compensate for chromatic losses. The basis for these adjustments and the extent to which they could discount the deficiency are poorly understood. We modeled the patterns of compensation that might result from increasing the gains in post-receptoral neurons to offset their weakened inputs. Individual neurons and the population responses jointly encode luminance and chromatic signals. As a result, they cannot independently adjust for a change in the chromatic inputs, predicting only partial recovery of the chromatic responses and increased responses to achromatic contrast. These analyses constrain the potential sites and mechanisms of compensation for a color loss and characterize the utility and limits of neural gain changes for calibrating color vision.

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.

Functional integrity of visual coding following advanced photoreceptor degeneration

Photoreceptor degeneration sufficient to produce severe visual loss often spares the inner retina. This raises hope for vision restoration treatments using optogenetics or electrical stimulation, which generate a replacement light input signal in surviving neurons. The success of these approaches is dependent on the capacity of surviving circuits of the visual system to generate and propagate an appropriate visual code in the face of neuroanatomical remodeling. To determine whether retinally degenerate animals possess this capacity, we generated a transgenic mouse model expressing the optogenetic actuator ReaChR in ON bipolar cells (second-order neurons in the visual projection). After crossing this with the rd1 model of photoreceptor degeneration, we compared ReaChR-derived responses with photoreceptor-driven responses in wild-type (WT) mice at the level of retinal ganglion cells and the visual thalamus. The ReaChR-driven responses in rd1 animals showed low photosensitivity, but in other respects generated a visual code that was very similar to the WT. ReaChR rd1 responses had high trial-to-trial reproducibility and showed sensitivity normalization to code contrast across background intensities. At the single unit level, ReaChR-derived responses exhibited broadly similar variations in response polarity, contrast sensitivity, and temporal frequency tuning as the WT. Units from the WT and ReaChR rd1 mice clustered together when subjected to unsupervised community detection based on stimulus-response properties. Our data reveal an impressive ability for surviving circuitry to recreate a rich visual code following advanced retinal degeneration and are promising for regenerative medicine in the central nervous system.

Encoding of environmental illumination by primate melanopsin neurons

Light regulates physiology, mood, and behavior through signals sent to the brain by intrinsically photosensitive retinal ganglion cells (ipRGCs). How primate ipRGCs sense light is unclear, as they are rare and challenging to target for electrophysiological recording. We developed a method of acute identification within the live, ex vivo retina. Using it, we found that ipRGCs of the macaque monkey are highly specialized to encode irradiance (the overall intensity of illumination) by blurring spatial, temporal, and chromatic features of the visual scene. We describe mechanisms at the molecular, cellular, and population scales that support irradiance encoding across orders-of-magnitude changes in light intensity. These mechanisms are conserved quantitatively across the ~70 million years of evolution that separate macaques from mice.

After-image formation by adaptation to dynamic color gradients

The eye's retinotopic exposure to an adapter typically produces an after-image. For example, an observer who fixates a red adapter on a gray background will see an illusory cyan after-image after removing the adapter. The after-image's content, like its color or intensity, gives insight into mechanisms responsible for adaptation and processing of a specific feature. To facilitate adaptation, vision scientists traditionally present stable, unchanging adapters for prolonged durations. How adaptation affects perception when features (e.g., color) dynamically change over time is not understood. To investigate adaptation to a dynamically changing feature, participants viewed a colored patch that changed from a color to gray, following either a direct or curved path through the (roughly) equiluminant color plane of CIE LAB space. We varied the speed and curvature of color changes across trials and experiments. Results showed that dynamic adapters produce after-images, vivid enough to be reported by the majority of participants. An after-image consisted of a color complementary to the average of the adapter's colors with a small bias towards more recent rather than initial adapter colors. The modelling of the reported after-image colors further confirmed that adaptation rapidly instigates and gradually dissipates. A second experiment replicated these results and further showed that the probability of observing an after-image diminishes only slightly when the adapter displays transient (stepwise, abrupt) color transitions. We conclude from the results that the visual system can adapt to dynamic colors, to a degree that is robust to the potential interference of transient changes in adapter content.

Calibrating Vision: Concepts and Questions

The idea that visual coding and perception are shaped by experience and adjust to changes in the environment or the observer is universally recognized as a cornerstone of visual processing, yet the functions and processes mediating these calibrations remain in many ways poorly understood. In this article we review a number of facets and issues surrounding the general notion of calibration, with a focus on plasticity within the encoding and representational stages of visual processing. These include how many types of calibrations there are - and how we decide; how plasticity for encoding is intertwined with other principles of sensory coding; how it is instantiated at the level of the dynamic networks mediating vision; how it varies with development or between individuals; and the factors that may limit the form or degree of the adjustments. Our goal is to give a small glimpse of an enormous and fundamental dimension of vision, and to point to some of the unresolved questions in our understanding of how and why ongoing calibrations are a pervasive and essential element of vision.

Nonequilibrium dynamics of adaptation in sensory systems

Adaptation is used by biological sensory systems to respond to a wide range of environmental signals, by adapting their response properties to the statistics of the stimulus in order to maximize information transmission. We derive rules of optimal adaptation to changes in the mean and variance of a continuous stimulus in terms of Bayesian filters and map them onto stochastic equations that couple the state of the environment to an internal variable controlling the response function. We calculate numerical and exact results for the speed and accuracy of adaptation and its impact on information transmission. We find that, in the regime of efficient adaptation, the speed of adaptation scales sublinearly with the rate of change of the environment. Finally, we exploit the mathematical equivalence between adaptation and stochastic thermodynamics to quantitatively relate adaptation to the irreversibility of the adaptation time course, defined by the rate of entropy production. Our results suggest a means to empirically quantify adaptation in a model-free and nonparametric way.

Temporal dynamics of face adaptation

The appearance of a face can be strongly affected by adaptation to faces seen previously. A number of studies have examined the time course of these aftereffects, but the integration time over which adaptation pools signals to control the adaptation state remains uncertain. Here we examined the effects of temporal frequency on face gender aftereffects induced by a pair of faces alternating between the two genders to assess when the aftereffects were pooled over successive faces versus driven by the last face seen. In the first experiment, we found that temporal frequencies between 0.25 and 2.00 Hz all failed to produce an aftereffect, suggesting a fairly long integration time. In the second experiment, we therefore probed slower alternation rates of 0.03 to 0.25 Hz. A rate of 0.0625 Hz (i.e., 8 seconds per face) was required to generate significant aftereffects from the last presented face and was consistent with an average time constant of 15 to 20 seconds for an exponentially decaying integration window. This integration time is substantially longer than found previously for analogous effects for alternating colors, and thus points to a potentially slower mechanism of adaptation for faces compared with chromatic adaptation.

Homeostatic plasticity in the retina

Vision begins in the retina, whose intricate neural circuits extract salient features of the environment from the light entering our eyes. Neurodegenerative diseases of the retina (e.g., inherited retinal degenerations, age-related macular degeneration, and glaucoma) impair vision and cause blindness in a growing number of people worldwide. Increasing evidence indicates that homeostatic plasticity (i.e., the drive of a neural system to stabilize its function) can, in principle, preserve retinal function in the face of major perturbations, including neurodegeneration. Here, we review the circumstances and events that trigger homeostatic plasticity in the retina during development, sensory experience, and disease. We discuss the diverse mechanisms that cooperate to compensate and the set points and outcomes that homeostatic retinal plasticity stabilizes. Finally, we summarize the opportunities and challenges for unlocking the therapeutic potential of homeostatic plasticity. Homeostatic plasticity is fundamental to understanding retinal development and function and could be an important tool in the fight to preserve and restore vision.

Line element for the perceptual color space

It is generally accepted that the perceptual color space is not Euclidean. A new line element for a 3-dimensional Riemannian color space was developed. This line element is based on the Friele line elements and psychophysical color discrimination models, and comprises both the first and second stage of color vision. The line element is expressed in a contrast space based on the MacLeod-Boynton chromaticities. New equations for the contrast thresholds along the cardinal axes and new metric tensor elements were determined. Visual adaptation effects were incorporated into the model. Color discrimination threshold ellipsoids were calculated with the new line element. Adequate agreement with experimental threshold ellipsoids reported in literature was demonstrated. From a comparison with other color difference metrics a better overall predictability of threshold ellipsoids was found with the new line element.

Visual mode switching: Improved general compensation for environmental color changes requires only one exposure per day

When the visual environment changes, vision adapts in order to maintain accurate perception. For repeatedly encountered environmental changes, the visual system may learn to adjust immediately, a process called "visual mode switching." For example, following experience with red glasses, participants report that the glasses' redness fades instantly when they put the glasses on. Here we tested (1) whether once-daily experience suffices for learning to switch visual modes and (2) whether effects of mode switching apply to most stimuli affected by the environmental change. In Experiment 1, 12 participants wore bright red glasses for a single 5-hr period each day for 5 days, and we tested for changes in the perception of unique yellow, which contains neither red nor green. In Experiment 2, we tested how mode switching affects larger parts of the color space. Thirteen participants donned and removed the glasses multiple times a day for 5 days, and we used a dissimilarity rating task to measure and track perception of many different colors. Across days, immediately upon donning the glasses, the world appeared less and less reddish (Experiment 1), and colors across the whole color space appeared more and more normal (Experiment 2). These results indicate that mode switching can be acquired from a once-daily experience, and it applies to most stimuli in a given environment. These findings may help to predict when and how mode switching occurs outside the laboratory.

Retinal Encoding of Natural Scenes

An ultimate goal in retina science is to understand how the neural circuit of the retina processes natural visual scenes. Yet most studies in laboratories have long been performed with simple, artificial visual stimuli such as full-field illumination, spots of light, or gratings. The underlying assumption is that the features of the retina thus identified carry over to the more complex scenario of natural scenes. As the application of corresponding natural settings is becoming more commonplace in experimental investigations, this assumption is being put to the test and opportunities arise to discover processing features that are triggered by specific aspects of natural scenes. Here, we review how natural stimuli have been used to probe, refine, and complement knowledge accumulated under simplified stimuli, and we discuss challenges and opportunities along the way toward a comprehensive understanding of the encoding of natural scenes. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Adapting to an enhanced color gamut - implications for color vision and color deficiencies

One strategy for aiding color deficiencies is to use three narrow passbands to filter the light spectrum to increase the saturation of colors. This filtering is analogous to the narrow emission bands used in wide gamut lighting or displays. We examined how perception adapts to the greater color gamut area produced by such devices, testing color-normal observers and simulated environments. Narrowband spectra increased chromatic contrasts but also increased contrast adaptation, partially offsetting the perceived contrast enhancements. Such adaptation adjustments are important for understanding the perceptual consequences of exposure to naturally or artificially enhanced color gamut areas for both color-deficient and color-normal observers.

Visual Stimulation Induces Distinct Forms of Sensitization of On-Off Direction-Selective Ganglion Cell Responses in the Dorsal and Ventral Retina

Experience-dependent modulation of neuronal responses is a key attribute in sensory processing. In the mammalian retina, the On-Off direction-selective ganglion cell (DSGC) is well known for its robust direction selectivity. However, how the On-Off DSGC light responsiveness dynamically adjusts to the changing visual environment is underexplored. Here, we report that On-Off DSGCs tuned to posterior motion direction [i.e. posterior DSGCs (pDSGCs)] in mice of both sexes can be transiently sensitized by prior stimuli. Notably, distinct sensitization patterns are found in dorsal and ventral pDSGCs. Although responses of both dorsal and ventral pDSGCs to dark stimuli (Off responses) are sensitized, only dorsal cells show the sensitization of responses to bright stimuli (On responses). Visual stimulation to the dorsal retina potentiates a sustained excitatory input from Off bipolar cells, leading to tonic depolarization of pDSGCs. Such tonic depolarization propagates from the Off to the On dendritic arbor of the pDSGC to sensitize its On response. We also identified a previously overlooked feature of DSGC dendritic architecture that can support dendritic integration between On and Off dendritic layers bypassing the soma. By contrast, ventral pDSGCs lack a sensitized tonic depolarization and thus do not exhibit sensitization of their On responses. Our results highlight a topographic difference in Off bipolar cell inputs underlying divergent sensitization patterns of dorsal and ventral pDSGCs. Moreover, substantial crossovers between dendritic layers of On-Off DSGCs suggest an interactive dendritic algorithm for processing On and Off signals before they reach the soma.SIGNIFICANCE STATEMENT Visual neuronal responses are dynamically influenced by the prior visual experience. This form of plasticity reflects the efficient coding of the naturalistic environment by the visual system. We found that a class of retinal output neurons, On-Off direction-selective ganglion cells, transiently increase their responsiveness after visual stimulation. Cells located in dorsal and ventral retinas exhibit distinct sensitization patterns because of different adaptive properties of Off bipolar cell signaling. A previously overlooked dendritic morphologic feature of the On-Off direction-selective ganglion cell is implicated in the cross talk between On and Off pathways during sensitization. Together, these findings uncover a topographic difference in the adaptive encoding of upper and lower visual fields and the underlying neural mechanism in the dorsal and ventral retinas.

Information gains from commercial spectral filters in anomalous trichromacy

Red-green color discrimination is compromised in anomalous trichromacy, the most common inherited color vision deficiency. This computational analysis tested whether three commercial optical filters with medium-to-long-wavelength stop bands increased information about colored surfaces. The surfaces were sampled from 50 hyperspectral images of outdoor scenes. At best, potential gains in the effective number of surfaces discriminable solely by color reached 9% in protanomaly and 15% in deuteranomaly, much less than with normal trichromacy. Gains were still less with lower scene illumination and more severe color vision deficiency. Stop-band filters may offer little improvement in objective real-world color discrimination.

Feature Detection by Retinal Ganglion Cells

Retinal circuits transform the pixel representation of photoreceptors into the feature representations of ganglion cells, whose axons transmit these representations to the brain. Functional, morphological, and transcriptomic surveys have identified more than 40 retinal ganglion cell (RGC) types in mice. RGCs extract features of varying complexity; some simply signal local differences in brightness (i.e., luminance contrast), whereas others detect specific motion trajectories. To understand the retina, we need to know how retinal circuits give rise to the diverse RGC feature representations. A catalog of the RGC feature set, in turn, is fundamental to understanding visual processing in the brain. Anterograde tracing indicates that RGCs innervate more than 50 areas in the mouse brain. Current maps connecting RGC types to brain areas are rudimentary, as is our understanding of how retinal signals are transformed downstream to guide behavior. In this article, I review the feature selectivities of mouse RGCs, how they arise, and how they are utilized downstream. Not only is knowledge of the behavioral purpose of RGC signals critical for understanding the retinal contributions to vision; it can also guide us to the most relevant areas of visual feature space. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Maximal Dependence Capturing as a Principle of Sensory Processing

Sensory inputs conveying information about the environment are often noisy and incomplete, yet the brain can achieve remarkable consistency in recognizing objects. Presumably, transforming the varying input patterns into invariant object representations is pivotal for this cognitive robustness. In the classic hierarchical representation framework, early stages of sensory processing utilize independent components of environmental stimuli to ensure efficient information transmission. Representations in subsequent stages are based on increasingly complex receptive fields along a hierarchical network. This framework accurately captures the input structures; however, it is challenging to achieve invariance in representing different appearances of objects. Here we assess theoretical and experimental inconsistencies of the current framework. In its place, we propose that individual neurons encode objects by following the principle of maximal dependence capturing (MDC), which compels each neuron to capture the structural components that contain maximal information about specific objects. We implement the proposition in a computational framework incorporating dimension expansion and sparse coding, which achieves consistent representations of object identities under occlusion, corruption, or high noise conditions. The framework neither requires learning the corrupted forms nor comprises deep network layers. Moreover, it explains various receptive field properties of neurons. Thus, MDC provides a unifying principle for sensory processing.

First-order visual interneurons distribute distinct contrast and luminance information across ON and OFF pathways to achieve stable behavior

The accurate processing of contrast is the basis for all visually guided behaviors. Visual scenes with rapidly changing illumination challenge contrast computation because photoreceptor adaptation is not fast enough to compensate for such changes. Yet, human perception of contrast is stable even when the visual environment is quickly changing, suggesting rapid post receptor luminance gain control. Similarly, in the fruit fly Drosophila, such gain control leads to luminance invariant behavior for moving OFF stimuli. Here, we show that behavioral responses to moving ON stimuli also utilize a luminance gain, and that ON-motion guided behavior depends on inputs from three first-order interneurons L1, L2, and L3. Each of these neurons encodes contrast and luminance differently and distributes information asymmetrically across both ON and OFF contrast-selective pathways. Behavioral responses to both ON and OFF stimuli rely on a luminance-based correction provided by L1 and L3, wherein L1 supports contrast computation linearly, and L3 non-linearly amplifies dim stimuli. Therefore, L1, L2, and L3 are not specific inputs to ON and OFF pathways but the lamina serves as a separate processing layer that distributes distinct luminance and contrast information across ON and OFF pathways to support behavior in varying conditions.

Simple model for encoding natural images by retinal ganglion cells with nonlinear spatial integration

A central goal in sensory neuroscience is to understand the neuronal signal processing involved in the encoding of natural stimuli. A critical step towards this goal is the development of successful computational encoding models. For ganglion cells in the vertebrate retina, the development of satisfactory models for responses to natural visual scenes is an ongoing challenge. Standard models typically apply linear integration of visual stimuli over space, yet many ganglion cells are known to show nonlinear spatial integration, in particular when stimulated with contrast-reversing gratings. We here study the influence of spatial nonlinearities in the encoding of natural images by ganglion cells, using multielectrode-array recordings from isolated salamander and mouse retinas. We assess how responses to natural images depend on first- and second-order statistics of spatial patterns inside the receptive field. This leads us to a simple extension of current standard ganglion cell models. We show that taking not only the weighted average of light intensity inside the receptive field into account but also its variance over space can partly account for nonlinear integration and substantially improve response predictions of responses to novel images. For salamander ganglion cells, we find that response predictions for cell classes with large receptive fields profit most from including spatial contrast information. Finally, we demonstrate how this model framework can be used to assess the spatial scale of nonlinear integration. Our results underscore that nonlinear spatial stimulus integration translates to stimulation with natural images. Furthermore, the introduced model framework provides a simple, yet powerful extension of standard models and may serve as a benchmark for the development of more detailed models of the nonlinear structure of receptive fields.

For understanding how sensory systems operate in the natural environment, an important goal is to develop models that capture neuronal responses to natural stimuli. For retinal ganglion cells, which connect the eye to the brain, current standard models often fail to capture responses to natural visual scenes. This shortcoming is at least partly rooted in the fact that ganglion cells may combine visual signals over space in a nonlinear fashion. We here show that a simple model, which not only considers the average light intensity inside a cell’s receptive field but also the variance of light intensity over space, can partly account for these nonlinearities and thereby improve current standard models. This provides an easy-to-obtain benchmark for modeling ganglion cell responses to natural images.

Transient and Steady-State Properties of Drosophila Sensory Neurons Coding Noxious Cold Temperature

Coding noxious cold signals, such as the magnitude and rate of temperature change, play essential roles in the survival of organisms. We combined electrophysiological and computational neuroscience methods to investigate the neural dynamics of Drosophila larva cold-sensing Class III (CIII) neurons. In response to a fast temperature change (-2 to -6°C/s) from room temperature to noxious cold, the CIII neurons exhibited a pronounced peak of a spiking rate with subsequent relaxation to a steady-state spiking. The magnitude of the peak was higher for a higher rate of temperature decrease, while slow temperature decrease (-0.1°C/s) evoked no distinct peak of the spiking rate. The rate of the steady-state spiking depended on the magnitude of the final temperature and was higher at lower temperatures. For each neuron, we characterized this dependence by estimating the temperature of the half activation of the spiking rate by curve fitting neuron's spiking rate responses to a Boltzmann function. We found that neurons had a temperature of the half activation distributed over a wide temperature range. We also found that CIII neurons responded to decrease rather than increase in temperature. There was a significant difference in spiking activity between fast and slow returns from noxious cold to room temperature: The CIII neurons usually stopped activity abruptly in the case of the fast return and continued spiking for some time in the case of the slow return. We developed a biophysical model of CIII neurons using a generalized description of transient receptor potential (TRP) current kinetics with temperature-dependent activation and Ca²⁺-dependent inactivation. This model recapitulated the key features of the spiking rate responses found in experiments and suggested mechanisms explaining the transient and steady-state activity of the CIII neurons at different cold temperatures and rates of their decrease and increase. We conclude that CIII neurons encode at least three types of cold sensory information: the rate of temperature decrease by a peak of the firing rate, the magnitude of cold temperature by the rate of steady spiking activity, and direction of temperature change by spiking activity augmentation or suppression corresponding to temperature decrease and increase, respectively.

Visuo-Acoustic Stimulation's Role in Synaptic Plasticity: A Review of the Literature

Brain plasticity is the capacity of cerebral neurons to change, structurally and functionally, in response to experiences. This is an essential property underlying the maturation of sensory functions, learning and memory processes, and brain repair in response to the occurrence of diseases and trauma. In this field, the visual system emerges as a paradigmatic research model, both for basic research studies and for translational investigations. The auditory system remains capable of reorganizing itself in response to different auditory stimulations or sensory organ modification. Acoustic biofeedback training can be an effective way to train patients with the central scotoma, who have poor fixation stability and poor visual acuity, in order to bring fixation on an eccentrical and healthy area of the retina: a pseudofovea. This review article is focused on the cellular and molecular mechanisms underlying retinal sensitivity changes and visual and auditory system plasticity.

Disentangling of Local and Wide-Field Motion Adaptation

Motion adaptation has been attributed in flying insects a pivotal functional role in spatial vision based on optic flow. Ongoing motion enhances in the visual pathway the representation of spatial discontinuities, which manifest themselves as velocity discontinuities in the retinal optic flow pattern during translational locomotion. There is evidence for different spatial scales of motion adaptation at the different visual processing stages. Motion adaptation is supposed to take place, on the one hand, on a retinotopic basis at the level of local motion detecting neurons and, on the other hand, at the level of wide-field neurons pooling the output of many of these local motion detectors. So far, local and wide-field adaptation could not be analyzed separately, since conventional motion stimuli jointly affect both adaptive processes. Therefore, we designed a novel stimulus paradigm based on two types of motion stimuli that had the same overall strength but differed in that one led to local motion adaptation while the other did not. We recorded intracellularly the activity of a particular wide-field motion-sensitive neuron, the horizontal system equatorial cell (HSE) in blowflies. The experimental data were interpreted based on a computational model of the visual motion pathway, which included the spatially pooling HSE-cell. By comparing the difference between the recorded and modeled HSE-cell responses induced by the two types of motion adaptation, the major characteristics of local and wide-field adaptation could be pinpointed. Wide-field adaptation could be shown to strongly depend on the activation level of the cell and, thus, on the direction of motion. In contrast, the response gain is reduced by local motion adaptation to a similar extent independent of the direction of motion. This direction-independent adaptation differs fundamentally from the well-known adaptive adjustment of response gain according to the prevailing overall stimulus level that is considered essential for an efficient signal representation by neurons with a limited operating range. Direction-independent adaptation is discussed to result from the joint activity of local motion-sensitive neurons of different preferred directions and to lead to a representation of the local motion direction that is independent of the overall direction of global motion.

Encoding of cutaneous stimuli by lamina I projection neurons

ABSTRACT

Lamina I of the dorsal horn, together with its main output pathway, lamina I projection neurons, has long been implicated in the processing of nociceptive stimuli, as well as the development of chronic pain conditions. However, the study of lamina I projection neurons is hampered by technical challenges, including the low throughput and selection biases of traditional electrophysiological techniques. Here we report on a technique that uses anatomical labelling strategies and in vivo imaging to simultaneously study a network of lamina I projection neurons in response to electrical and natural stimuli. Although we were able to confirm the nociceptive involvement of this group of cells, we also describe an unexpected preference for innocuous cooling stimuli. We were able to characterize the thermal responsiveness of these cells in detail and found cooling responses decline when exposed to stable cold temperatures maintained for more than a few seconds, as well as to encode the intensity of the end temperature, while heating responses showed an unexpected reliance on adaptation temperatures.

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.