Representation of color stimuli in awake macaque primary visual cortex

A Bayesian observer model reveals a prior for natural daylights in hue perception

Incorporating statistical characteristics of stimuli in perceptual processing can be highly beneficial for reliable estimation from noisy sensory measurements but may generate perceptual bias. According to Bayesian inference, perceptual biases arise from the integration of internal priors with noisy sensory inputs. In this study, we used a Bayesian observer model to derive biases and priors in hue perception based on discrimination data for hue ensembles with varying levels of chromatic noise. Our results showed that discrimination thresholds for isoluminant stimuli with hue defined by azimuth angle in cone-opponent color space exhibited a bimodal pattern, with lowest thresholds near a non-cardinal blue-yellow axis that aligns closely with the variation of natural daylights. Perceptual biases showed zero crossings around this axis, indicating repulsion away from yellow and attraction towards blue. These biases could be explained by the Bayesian observer model through a non-uniform prior with a preference for blue. Our findings suggest that visual processing takes advantage of knowledge of the distribution of colors in natural environments for hue perception.

Color appearance and the end of Hering's Opponent-Colors Theory

Hering's Opponent-Colors Theory has been central to understanding color appearance for 150 years. It aims to explain the phenomenology of colors with two linked propositions. First, a psychological hypothesis stipulates that any color is described necessarily and sufficiently by the extent to which it appears reddish-versus-greenish, bluish-versus-yellowish, and blackish-versus-whitish. Second, a physiological hypothesis stipulates that these perceptual mechanisms are encoded by three innate brain mechanisms. We review the evidence and conclude that neither side of the linking proposition is accurate: the theory is wrong. We sketch out an alternative, Utility-Based Coding, by which the known retinal cone-opponent mechanisms represent optimal encoding of spectral information given competing selective pressure to extract high-acuity spatial information; and phenomenological color categories represent an adaptive, efficient, output of the brain governed by behavioral demands.

Cone opponent functional domains in primary visual cortex combine signals for color appearance mechanisms

Studies of color perception have led to mechanistic models of how cone-opponent signals from retinal ganglion cells are integrated to generate color appearance. But it is unknown how this hypothesized integration occurs in the brain. Here we show that cone-opponent signals transmitted from retina to primary visual cortex (V1) are integrated through highly organized circuits within V1 to implement the color opponent interactions required for color appearance. Combining intrinsic signal optical imaging (ISI) and 2-photon calcium imaging (2PCI) at single cell resolution, we demonstrate cone-opponent functional domains (COFDs) that combine L/M cone-opponent and S/L + M cone-opponent signals following the rules predicted from psychophysical studies of color perception. These give rise to an orderly organization of hue preferences of the neurons within the COFDs and the generation of hue "pinwheels". Thus, spatially organized neural circuits mediate an orderly transition from cone-opponency to color appearance that begins in V1.

Representation of Cone-Opponent Color Space in Macaque Early Visual Cortices

In primate vision, the encoding of color perception arises from three types of retinal cone cells (L, M, and S cones). The inputs from these cones are linearly integrated into two cone-opponent channels (cardinal axes) before the lateral geniculate nucleus. In subsequent visual cortical stages, color-preferring neurons cluster into functional domains within "blobs" in V1, "thin/color stripes" in V2, and "color bands" in V4. Here, we hypothesize that, with increasing cortical hierarchy, the functional organization of hue representation becomes more balanced and less dependent on cone opponency. To address this question, we used intrinsic signal optical imaging in macaque V1, V2, and V4 cortices to examine the domain-based representation of specific hues (here referred to as "hue domains") in cone-opponent color space (4 cardinal and 4 intermediate hues). Interestingly, we found that in V1, the relative size of S-cone hue preference domain was significantly smaller than that for other hues. This notable difference was less prominent in V2, and, in V4 was virtually absent, resulting in a more balanced representation of hues. In V2, hue clusters contained sequences of shifting preference, while in V4 the organization of hue clusters was more complex. Pattern classification analysis of these hue maps showed that accuracy of hue classification improved from V1 to V2 to V4. These results suggest that hue representation by domains in the early cortical hierarchy reflects a transformation away from cone-opponency and toward a full-coverage representation of hue.

Luminance dependency of perceived color shift after color contrast adaptation caused by higher-order color channels

Color adaptation is a phenomenon in which, after prolonged exposure to a specific color (i.e. adaptation color), the perceived color shifts to approximately the opposite color direction of the adaptation color. Color adaptation is strongly related to sensitivity changes in photoreceptors, such as von Kries adaptation and cone-opponent mechanisms. On the other hand, the perceptual contrast of colors (e.g. perceptual saturation of the red-green direction) decreases after adaptation to a stimulus with spatial and/or temporal color modulation along the color direction. This phenomenon is referred to as color contrast adaptation. Color contrast adaptation has been used to investigate the representation of colors in the visual system. In the present study, we measured color perception after color contrast adaptation to stimuli with temporal color modulations along complicated color loci in a luminance-chromaticity plane. We found that, after the observers adapted to color modulations with different chromaticities at higher, medium, and lower luminance (e.g. temporal alternations among red, green, and red, each at a different luminance level), the chromaticity corresponding to perceptual achromaticity (the achromatic point) shifted to the same color direction as the adaptation chromaticity in each test stimulus luminance. In contrast, this luminance dependence of the achromatic point shift was not observed after adaptation to color modulations with more complex luminance-chromaticity correspondences (e.g. alternating red, green, red, green, and red, at five luminance levels, respectively). In addition, the occurrence or nonoccurrence of the luminance-dependent achromatic point shift was qualitatively predicted using a noncardinal model composed of channels preferring intermediate color directions between the cardinal chromaticity and luminance axes. These results suggest that the noncardinal channels are involved in the luminance-dependent perceived color shift after adaptation.

Color Sensitivity of the Duration Aftereffect Depends on Sub- and Supra-second Durations

The perception of duration becomes biased after repetitive duration adaptation; this is known as the duration aftereffect. The duration aftereffect exists in both the sub-second and supra-second ranges. However, it is unknown whether the properties and mechanisms of the adaptation aftereffect differ between sub-second and supra-second durations. In the present study, we addressed this question by investigating the color sensitivity of the duration aftereffect in the sub-second (Experiment 1) and supra-second (Experiment 2) ranges separately. We found that the duration aftereffect in the sub-second range could only partly transfer across different visual colors, whereas the duration aftereffect in the supra-second range could completely transfer across different visual colors. That is, the color-sensitivity of the duration aftereffect in the sub-second duration was stronger than that in the supra-second duration. These results imply that the mechanisms underlying the adaptation aftereffects of the sub-second and supra-second ranges are distinct.

Deep neural models for color classification and color constancy

Color constancy is our ability to perceive constant colors across varying illuminations. Here, we trained deep neural networks to be color constant and evaluated their performance with varying cues. Inputs to the networks consisted of two-dimensional images of simulated cone excitations derived from three-dimensional (3D) rendered scenes of 2,115 different 3D shapes, with spectral reflectances of 1,600 different Munsell chips, illuminated under 278 different natural illuminations. The models were trained to classify the reflectance of the objects. Testing was done with four new illuminations with equally spaced CIEL*a*b* chromaticities, two along the daylight locus and two orthogonal to it. High levels of color constancy were achieved with different deep neural networks, and constancy was higher along the daylight locus. When gradually removing cues from the scene, constancy decreased. Both ResNets and classical ConvNets of varying degrees of complexity performed well. However, DeepCC, our simplest sequential convolutional network, represented colors along the three color dimensions of human color vision, while ResNets showed a more complex representation.

Perceptual hue, lightness, and chroma are represented in a multidimensional functional anatomical map in macaque V1

Humans perceive millions of colors along three dimensions of color space: hue, lightness, and chroma. A major gap in knowledge is where the brain represents these specific dimensions in cortex, and how they relate to each other. Previous studies have shown that brain areas V4 and the posterior inferotemporal cortex (PIT) are central to computing color dimensions. To determine the contribution of V1 to setting up these downstream processing mechanisms, we studied cortical color responses in macaques-who share color vision mechanisms with humans. We used two-photon calcium imaging at both meso- and micro-scales and found that hue and lightness are laid out in orthogonal directions on the cortical map, with chroma represented by the strength of neuronal responses, as previously shown in PIT. These findings suggest that the earliest cortical stages of vision determine the three primary dimensions of human color perception.

Predictive coding of natural images by V1 firing rates and rhythmic synchronization

Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that sensory responses result from comparisons between bottom-up inputs and contextual predictions, a process in which rates and synchronization may play distinct roles. We recorded from awake macaque V1 and developed a technique to quantify stimulus predictability for natural images based on self-supervised, generative neural networks. We find that neuronal firing rates were mainly modulated by the contextual predictability of higher-order image features, which correlated strongly with human perceptual similarity judgments. By contrast, V1 gamma (γ)-synchronization increased monotonically with the contextual predictability of low-level image features and emerged exclusively for larger stimuli. Consequently, γ-synchronization was induced by natural images that are highly compressible and low-dimensional. Natural stimuli with low predictability induced prominent, late-onset beta (β)-synchronization, likely reflecting cortical feedback. Our findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.

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Predictability in natural images quantified with self-supervised neural networks

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V1 firing rates decrease with predictability of high- not low-level image features

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γ-synchronization increases with predictability of low-level image features

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Late-onset β-synchronization for natural scenes with low predictability

Extreme neural machines

Recurrent neural networks can solve a variety of computational tasks and produce patterns of activity that capture key properties of brain circuits. However, learning rules designed to train these models are time-consuming and prone to inaccuracies when tuning connection weights located deep within the network. Here, we describe a rapid one-shot learning rule to train recurrent networks composed of biologically-grounded neurons. First, inputs to the model are compressed onto a smaller number of recurrent neurons. Then, a non-iterative rule adjusts the output weights of these neurons based on a target signal. The model learned to reproduce natural images, sequential patterns, as well as a high-resolution movie scene. Together, results provide a novel avenue for one-shot learning in biologically realistic recurrent networks and open a path to solving complex tasks by merging brain-inspired models with rapid optimization rules.

Electrophysiological evidence for higher-level chromatic mechanisms in humans

Color vision in humans starts with three types of cones (short [S], medium [M], and long [L] wavelengths) in the retina and three retinal and subcortical cardinal mechanisms, which linearly combine cone signals into the luminance channel (L + M), the red-green channel (L - M), and the yellow-blue channel (S-(L + M)). Chromatic mechanisms at the cortical level, however, are less well characterized. The present study investigated such higher-order chromatic mechanisms by recording electroencephalograms (EEGs) on human observers in a noise masking paradigm. Observers viewed colored stimuli that consisted of a target embedded in noise. Color directions of the target and noise varied independently and systematically in an isoluminant plane of color space. The target was flickering on-off at 3 Hz, eliciting steady-state visual evoked potential (SSVEP) responses. As a result, the masking strength could be estimated from the SSVEP amplitude in the presence of 6 Hz noise. Masking was strongest (i.e. target eliciting smallest SSVEPs) when the target and noise were along the same color direction, and was weakest (i.e. target eliciting highest SSVEPs) when the target and noise were along orthogonal directions. This pattern of results was observed both when the target color varied along the cardinal and intermediate directions, which is evidence for higher-order chromatic mechanisms tuned to intermediate axes. The SSVEP result can be well predicted by a model with multiple broadly tuned chromatic mechanisms. In contrast, a model with only cardinal mechanisms failed to account for the data. These results provide strong electrophysiological evidence for multiple chromatic mechanisms in the early visual cortex of humans.

Abrupt darkening under high dynamic range (HDR) luminance invokes facilitation for high-contrast targets and grouping by luminance similarity

When scanning across a scene, luminance can vary by up to 100,000-to-1 (high dynamic range, HDR), requiring multiple normalizing mechanisms spanning from the retina to the cortex to support visual acuity and recognition. Vision models based on standard dynamic range (SDR) luminance contrast ratios below 100-to-1 have limited ability to generalize to real-world scenes with HDR luminance. To characterize how orientation and luminance are linked in brain mechanisms for luminance normalization, we measured orientation discrimination of Gabor targets under HDR luminance dynamics. We report a novel phenomenon, that abrupt 10- to 100-fold darkening engages contextual facilitation, distorting the apparent orientation of a high-contrast central target. Surprisingly, facilitation was influenced by grouping by luminance similarity, as well as by the degree of luminance variability in the surround. These results challenge vision models based solely on activity normalization and raise new questions that will lead to models that perform better in real-world scenes.

Steady-State Visual Evoked Potentials Elicited from Early Visual Cortex Reflect Both Perceptual Color Space and Cone-Opponent Mechanisms

Colors are represented in the cone-opponent signals, L-M versus S cones, at least up to the level of inputs to the primary visual cortex. We explored the hue selective responses in early cortical visual areas through recordings of steady-state visual evoked potentials (SSVEPs), elicited by a flickering checkerboard whose color smoothly swept around the hue circle defined in a cone-opponent color space. If cone opponency dominates hue representation in the source of SSVEP signals, SSVEP amplitudes as a function of hue should form a profile that is line-symmetric along the cardinal axes of the cone-opponent color space. Observed SSVEP responses were clearly chromatic ones with increased SSVEP amplitudes and reduced response latencies for higher contrast conditions. The overall elliptic amplitude profile was significantly tilted away from the cardinal axes to have the highest amplitudes in the "lime-magenta" direction, indicating that the hue representation in question is not dominated by cone-opponency. The observed SSVEP amplitude hue profile was better described as a summation of a perceptual response and cone-opponent responses with a larger weight to the former. These results indicate that hue representations in the early visual cortex, measured by the SSVEP technique, are possibly related to perceptual color contrast.

Visual objects interact differently during encoding and memory maintenance

The storage mechanisms of working memory are the matter of an ongoing debate. The sensory recruitment hypothesis states that memory maintenance and perceptual encoding rely on the same neural substrate. This suggests that the same cortical mechanisms that shape object perception also apply to maintained memory content. We tested this prediction using the Direction Illusion, i.e., the mutual repulsion of two concurrently visible motion directions. Participants memorized the directions of two random dot patterns for later recall. In Experiments 1 and 2, we varied the temporal separation of spatially distinct stimuli to manipulate perceptual concurrency, while keeping concurrency within working memory constant. We observed mutual motion repulsion only under simultaneous stimulus presentation, but proactive repulsion and retroactive attraction under immediate stimulus succession. At inter-stimulus intervals of 0.5 and 2 s, however, proactive repulsion vanished, while the retroactive attraction remained. In Experiment 3, we presented both stimuli at the same spatial position and observed a reappearance of the repulsion effect. Our results indicate that the repulsive mechanisms that shape object perception across space fade during the transition from a perceptual representation to a consolidated memory content. This suggests differences in the underlying structure of perceptual and mnemonic representations. The persistence of local interactions, however, indicates different mechanisms of spatially global and local feature interactions.

Neural representations of perceptual color experience in the human ventral visual pathway

Color is a perceptual construct that arises from neural processing in hierarchically organized cortical visual areas. Previous research, however, often failed to distinguish between neural responses driven by stimulus chromaticity versus perceptual color experience. An unsolved question is whether the neural responses at each stage of cortical processing represent a physical stimulus or a color we see. The present study dissociated the perceptual domain of color experience from the physical domain of chromatic stimulation at each stage of cortical processing by using a switch rivalry paradigm that caused the color percept to vary over time without changing the retinal stimulation. Using functional MRI (fMRI) and a model-based encoding approach, we found that neural representations in higher visual areas, such as V4 and VO1, corresponded to the perceived color, whereas responses in early visual areas V1 and V2 were modulated by the chromatic light stimulus rather than color perception. Our findings support a transition in the ascending human ventral visual pathway, from a representation of the chromatic stimulus at the retina in early visual areas to responses that correspond to perceptually experienced colors in higher visual areas.

Multiplicative modulations enhance diversity of hue-selective cells

There is still much to understand about the brain's colour processing mechanisms and the transformation from cone-opponent representations to perceptual hues. Moreover, it is unclear which area(s) in the brain represent unique hues. We propose a hierarchical model inspired by the neuronal mechanisms in the brain for local hue representation, which reveals the contributions of each visual cortical area in hue representation. Hue encoding is achieved through incrementally increasing processing nonlinearities beginning with cone input. Besides employing nonlinear rectifications, we propose multiplicative modulations as a form of nonlinearity. Our simulation results indicate that multiplicative modulations have significant contributions in encoding of hues along intermediate directions in the MacLeod-Boynton diagram and that our model V2 neurons have the capacity to encode unique hues. Additionally, responses of our model neurons resemble those of biological colour cells, suggesting that our model provides a novel formulation of the brain's colour processing pathway.

A delay in sampling information from temporally autocorrelated visual stimuli

Much of our world changes smoothly in time, yet the allocation of attention is typically studied with sudden changes - transients. A sizeable lag in selecting feature information is seen when stimuli change smoothly. Yet this lag is not seen with temporally uncorrelated rapid serial visual presentation (RSVP) stimuli. This suggests that temporal autocorrelation of a feature paradoxically increases the latency at which information is sampled. To test this, participants are asked to report the color of a disk when a cue was presented. There is an increase in selection latency when the disk's color changed smoothly compared to randomly. This increase is due to the smooth color change presented after the cue rather than extrapolated predictions based on the color changes presented before. These results support an attentional drag theory, whereby attentional engagement is prolonged when features change smoothly. A computational model provides insights into the potential underlying neural mechanisms.

Hue selectivity of collinear facilitation

Collinear facilitation (CF) is the improvement of the detection sensitivity of the target when two high-contrast flanking stimuli (flankers) have the same visual properties. While it is known that CF does not occur between achromatic flanking stimuli and chromatic targets, or vice versa, it remains unclear whether CF occurs when the hue of the target and flankers are different. We measured CF for Gabor stimuli defined in an isoluminant plane using stimuli defined by isoluminant colors along isolated cone-opponent axes and in two diagonal directions. The measured CF varied with the difference in hue between the target and flankers. Moreover, increased thresholds were also observed. These results suggest that CF exhibits hue selectivity and involves a suppression as well as a facilitation component. The hue selectivity profile of these factors infer that the CF cannot be simply explained by the assumption of two independent cone opponent mechanisms.

A neural field model for color perception unifying assimilation and contrast

We address the question of color-space interactions in the brain, by proposing a neural field model of color perception with spatial context for the visual area V1 of the cortex. Our framework reconciles two opposing perceptual phenomena, known as simultaneous contrast and chromatic assimilation. They have been previously shown to act synergistically, so that at some point in an image, the color seems perceptually more similar to that of adjacent neighbors, while being more dissimilar from that of remote ones. Thus, their combined effects are enhanced in the presence of a spatial pattern, and can be measured as larger shifts in color matching experiments. Our model supposes a hypercolumnar structure coding for colors in V1, and relies on the notion of color opponency introduced by Hering. The connectivity kernel of the neural field exploits the balance between attraction and repulsion in color and physical spaces, so as to reproduce the sign reversal in the influence of neighboring points. The color sensation at a point, defined from a steady state of the neural activities, is then extracted as a nonlinear percept conveyed by an assembly of neurons. It connects the cortical and perceptual levels, because we describe the search for a color match in asymmetric matching experiments as a mathematical projection on color sensations. We validate our color neural field alongside this color matching framework, by performing a multi-parameter regression to data produced by psychophysicists and ourselves. All the results show that we are able to explain the nonlinear behavior of shifts observed along one or two dimensions in color space, which cannot be done using a simple linear model.

The color perception produced by an image heavily depends on the spatial distribution of its colors. From this “color in context” phenomenon, extensively studied in psychophysics for decades, has arisen the question in neuroscience of how color and space interact in the brain. Visual signals are indeed processed in such a way that neighboring pixels make the perception at some point different from its real color, inducing a color shift. In this work, we propose to emulate perception in context by modeling the activity of color sensitive neurons with a neural field. Our framework unifies two antagonistic effects, assimilation and contrast, which have been suggested to occur simultaneously but at different scales. We use the notion of color opponency inspired by the work of Hering, so as to express these effects as a combination of attraction and repulsion in physical and color spaces. We introduce the concept of “color sensation”, and show how to rigorously link the neural field model to perceptual shifts, by considering color matching as a mathematical projection on color sensations. The results show that our model is able to reproduce some nontrivial behaviors of the color shifts observed in experiments.

The precision of attentional selection is far worse than the precision of the underlying memory representation

Voluntary attentional selection requires the match of sensory input to a stored representation of the target features. We compared the precision of attentional selection to the precision of the underlying memory representation of the target. To measure the precision of attentional selection, we used a cue-target paradigm where participants searched for a colored target. Typically, RTs are shorter at the cued compared to uncued locations when the cue has the same color as the target. In contrast, cueing effects are absent or even inverted when cue and target colors are dissimilar. By systematically varying the difference between cue and target color, we calculated a function relating cue color to cueing effects. The width of this function reflects the precision of attentional selection and was compared to the precision of judgments of the target color on a color wheel. The precision of the memory representation was far better than the precision of attentional selection. When the task was made more difficult by increasing the similarity between the target and the nontarget stimuli in the target display, the precision of attentional selection increased, but was still worse than the precision of memory. When the search task was made more difficult, we also observed that for dissimilar cue colors, RTs were slower at cued than at uncued locations (i.e., same location costs), suggesting that improvements in attentional selectivity were achieved by suppressing non-target colors.

Surface color and predictability determine contextual modulation of V1 firing and gamma oscillations

The integration of direct bottom-up inputs with contextual information is a core feature of neocortical circuits. In area V1, neurons may reduce their firing rates when their receptive field input can be predicted by spatial context. Gamma-synchronized (30–80 Hz) firing may provide a complementary signal to rates, reflecting stronger synchronization between neuronal populations receiving mutually predictable inputs. We show that large uniform surfaces, which have high spatial predictability, strongly suppressed firing yet induced prominent gamma synchronization in macaque V1, particularly when they were colored. Yet, chromatic mismatches between center and surround, breaking predictability, strongly reduced gamma synchronization while increasing firing rates. Differences between responses to different colors, including strong gamma-responses to red, arose from stimulus adaptation to a full-screen background, suggesting prominent differences in adaptation between M- and L-cone signaling pathways. Thus, synchrony signaled whether RF inputs were predicted from spatial context, while firing rates increased when stimuli were unpredicted from context.

Touch engages visual spatial contextual processing

The spatial context in which we view a visual stimulus strongly determines how we perceive the stimulus. In the visual tilt illusion, the perceived orientation of a visual grating is affected by the orientation signals in its surrounding context. Conceivably, the spatial context in which a visual grating is perceived can be defined by interactive multisensory information rather than visual signals alone. Here, we tested the hypothesis that tactile signals engage the neural mechanisms supporting visual contextual modulation. Because tactile signals also convey orientation information and touch can selectively interact with visual orientation perception, we predicted that tactile signals would modulate the visual tilt illusion. We applied a bias-free method to measure the tilt illusion while testing visual-only, tactile-only or visuo-tactile contextual surrounds. We found that a tactile context can influence visual tilt perception. Moreover, combining visual and tactile orientation information in the surround results in a larger tilt illusion relative to the illusion achieved with the visual-only surround. These results demonstrate that the visual tilt illusion is subject to multisensory influences and imply that non-visual signals access the neural circuits whose computations underlie the contextual modulation of vision.

Bottom-up saliency and top-down learning in the primary visual cortex of monkeys

Early sensory cortex is better known for representing sensory inputs but less for the effect of its responses on behavior. Here we explore the behavioral correlates of neuronal responses in primary visual cortex (V1) in a task to detect a uniquely oriented bar-the orientation singleton-in a background of uniformly oriented bars. This singleton is salient or inconspicuous when the orientation contrast between the singleton and background bars is sufficiently large or small, respectively. Using implanted microelectrodes, we measured V1 activities while monkeys were trained to quickly saccade to the singleton. A neuron's responses to the singleton within its receptive field had an early and a late component, both increased with the orientation contrast. The early component started from the outset of neuronal responses; it remained unchanged before and after training on the singleton detection. The late component started ∼40 ms after the early one; it emerged and evolved with practicing the detection task. Training increased the behavioral accuracy and speed of singleton detection and increased the amount of information in the late response component about a singleton's presence or absence. Furthermore, for a given singleton, faster detection performance was associated with higher V1 responses; training increased this behavioral-neural correlate in the early V1 responses but decreased it in the late V1 responses. Therefore, V1's early responses are directly linked with behavior and represent the bottom-up saliency signals. Learning strengthens this link, likely serving as the basis for making the detection task more reflexive and less top-down driven.

Entrainment to the CIECAM02 and CIELAB colour appearance models in the human cortex

In human visual processing, information from the visual field passes through numerous transformations before perceptual attributes such as colour are derived. The sequence of transforms involved in constructing perceptions of colour can be approximated by colour appearance models such as the CIE (2002) colour appearance model, abbreviated as CIECAM02. In this study, we test the plausibility of CIECAM02 as a model of colour processing by looking for evidence of its cortical entrainment. The CIECAM02 model predicts that colour is split in to two opposing chromatic components, red-green and cyan-yellow (termed CIECAM02-a and CIECAM02-b respectively), and an achromatic component (termed CIECAM02-A). Entrainment of cortical activity to the outputs of these components was estimated using measurements of electro- and magnetoencephalographic (EMEG) activity, recorded while healthy subjects watched videos of dots changing colour. We find entrainment to chromatic component CIECAM02-a at approximately 35 ms latency bilaterally in occipital lobe regions, and entrainment to achromatic component CIECAM02-A at approximately 75 ms latency, also bilaterally in occipital regions. For comparison, transforms from a less physiologically plausible model (CIELAB) were also tested, with no significant entrainment found.

Averaging colors of multicolor mosaics

The present study investigated how color information was summarized in multicolor mosaics. The mosaics were composed of small elements of 17 colors that roughly belonged to a single color category. We manipulated the degree of color variation around the mean by varying the proportion of different color elements. Observers matched the mean color of the multicolor mosaic by adjusting the color of a spatially uniform matching stimulus. Results showed that when the color variation was large, the matched color deviated from the colorimetric mean toward the most-saturated color, although the hue of the matched color was almost the same as that of the colorimetric mean. These findings together suggested differential processing of hue and saturation. The deviation of the matched color decreased, but did not disappear, when the color variation was reduced. The analysis of color metric underlying color averaging revealed differential color scaling in nearly orthogonal blue-orange and green-purple directions, implying that the visual system does not solely rely on linear cone-opponent codes when summarizing color signals. The deviation itself was consistently found regardless of different color metrics tested. The robustness of the deviation indicated an inherent bias of mean color judgments favoring highly saturated colors.

Detailed spatiotemporal brain mapping of chromatic vision combining high-resolution VEP with fMRI and retinotopy

Neuroimaging studies have identified so far, several color-sensitive visual areas in the human brain, and the temporal dynamics of these activities have been separately investigated using the visual-evoked potentials (VEPs). In the present study, we combined electrophysiological and neuroimaging methods to determine a detailed spatiotemporal profile of chromatic VEP and to localize its neural generators. The accuracy of the present co-registration study was obtained by combining standard fMRI data with retinotopic and motion mapping data at the individual level. We found a sequence of occipito activities more complex than that typically reported for chromatic VEPs, including feed-forward and reentrant feedback. Results showed that chromatic human perception arises by the combined activity of at the least five parieto-occipital areas including V1, LOC, V8/VO, and the motion-sensitive dorsal region MT+. However, the contribution of V1 and V8/VO seems dominant because the re-entrant activity in these areas was present more than once (twice in V8/VO and thrice in V1). This feedforward and feedback chromatic processing appears delayed compared with the luminance processing. Associating VEPs and neuroimaging measures, we showed for the first time a complex spatiotemporal pattern of activity, confirming that chromatic stimuli produce intricate interactions of many different brain dorsal and ventral areas.

Human V4 Activity Patterns Predict Behavioral Performance in Imagery of Object Color

Color is special among basic visual features in that it can form a defining part of objects that are engrained in our memory. Whereas most neuroimaging research on human color vision has focused on responses related to external stimulation, the present study investigated how sensory-driven color vision is linked to subjective color perception induced by object imagery. We recorded fMRI activity in male and female volunteers during viewing of abstract color stimuli that were red, green, or yellow in half of the runs. In the other half we asked them to produce mental images of colored, meaningful objects (such as tomato, grapes, banana) corresponding to the same three color categories. Although physically presented color could be decoded from all retinotopically mapped visual areas, only hV4 allowed predicting colors of imagined objects when classifiers were trained on responses to physical colors. Importantly, only neural signal in hV4 was predictive of behavioral performance in the color judgment task on a trial-by-trial basis. The commonality between neural representations of sensory-driven and imagined object color and the behavioral link to neural representations in hV4 identifies area hV4 as a perceptual hub linking externally triggered color vision with color in self-generated object imagery.SIGNIFICANCE STATEMENT Humans experience color not only when visually exploring the outside world, but also in the absence of visual input, for example when remembering, dreaming, and during imagery. It is not known where neural codes for sensory-driven and internally generated hue converge. In the current study we evoked matching subjective color percepts, one driven by physically presented color stimuli, the other by internally generated color imagery. This allowed us to identify area hV4 as the only site where neural codes of corresponding subjective color perception converged regardless of its origin. Color codes in hV4 also predicted behavioral performance in an imagery task, suggesting it forms a perceptual hub for color perception.

Ocularity Feature Contrast Attracts Attention Exogenously

An eye-of-origin singleton, e.g., a bar shown to the left eye among many other bars shown to the right eye, can capture attention and gaze exogenously or reflexively, even when it appears identical to other visual input items in the scene and when the eye-of-origin feature is irrelevant to the observer’s task. Defining saliency as the strength of exogenous attraction to attention, we say that this eye-of-origin singleton, or its visual location, is salient. Defining the ocularity of a visual input item as the relative difference between its left-eye input and its right-eye input, this paper shows the general case that an ocularity singleton is also salient. For example, a binocular input item among monocular input items is salient, so is a left-eye-dominant input item (e.g., a bar with a higher input contrast to the left eye than to the right eye) among right-eye-dominant items. Saliency by unique input ocularity is analogous to saliency by unique input colour (e.g., a red item among green ones), as colour is determined by the relative difference(s) between visual inputs to different photoreceptor cones. Just as a smaller colour difference between a colour singleton and background items makes this singleton less salient, so does a smaller ocularity difference between an ocularity singleton and background items. While a salient colour difference is highly visible, a salient ocularity difference is often perceptually invisible in some cases and discouraging gaze shifts towards it in other cases, making its behavioural manifestation not as apparent. Saliency by ocularity contrast provides another support to the idea that the primary visual cortex creates a bottom-up saliency map to guide attention exogenously.

Invariance of surface color representations across illuminant changes in the human cortex

A central problem in color vision is that the light reaching the eye from a given surface can vary dramatically depending on the illumination. Despite this, our color percept, the brain's estimate of surface reflectance, remains remarkably stable. This phenomenon is called color constancy. Here we investigated which human brain regions represent surface color in a way that is invariant with respect to illuminant changes. We used physically realistic rendering methods to display natural yet abstract 3D scenes that were displayed under three distinct illuminants. The scenes embedded, in different conditions, surfaces that differed in their surface color (i.e. in their reflectance property). We used multivariate fMRI pattern analysis to probe neural coding of surface reflectance and illuminant, respectively. While all visual regions encoded surface color when viewed under the same illuminant, we found that only in V1 and V4α surface color representations were invariant to illumination changes. Along the visual hierarchy there was a gradient from V1 to V4α to increasingly encode surface color rather than illumination. Finally, effects of a stimulus manipulation on individual behavioral color constancy indices correlated with neural encoding of the illuminant in hV4. This provides neural evidence for the Equivalent Illuminant Model. Our results provide a principled characterization of color constancy mechanisms across the visual hierarchy, and demonstrate complementary contributions in early and late processing stages.

The Constancy of Colored After-Images

We undertook psychophysical experiments to determine whether the color of the after-image produced by viewing a colored patch which is part of a complex multi-colored scene depends on the wavelength-energy composition of the light reflected from that patch. Our results show that it does not. The after-image, just like the color itself, depends on the ratio of light of different wavebands reflected from it and its surrounds. Hence, traditional accounts of after-images as being the result of retinal adaptation or the perceptual result of physiological opponency, are inadequate. We propose instead that the color of after-images is generated after colors themselves are generated in the visual brain.

Source localization of S-cone and L/M-cone driven signals using silent substitution flash stimulation

This study aimed to analyze the neuronal sources of the visual evoked potentials after flash stimulation of the S- and the L/M-cone driven channels of the visual system. For 11 volunteers a 64-channel electroencephalography (EEG) was recorded during selective excitation of both color opponent channels. Individual and grand average data were analyzed topographically. Source localization was carried out using a realistically shaped three compartment boundary element model (BEM) and a mirrored moving dipole model. We found two main components (N1, P1) in all subjects, as well as a third late component in most subjects. For these components significant latency differences (N1=33 ms, P1=22 ms; p<0.05) between both color opponent channels were found. The results showed no differences in the topography and no differences in dipole localization between both color channels. Talairach coordinates of grand averages indicated activation in area 18. Comparison of results of separately stimulated eyes revealed no differences. Our findings showed that neural processing occurs in the same areas of the visual cortex for stimuli with different spectral properties. The signals of S- and L/M-cone driven channels are transmitted in distinct pathways to the cortex. Thus, the observed latency differences might be caused by different anatomical and functional properties of these pathways.

Comparison of the color selectivity of macaque V4 neurons in different color spaces

Chromatic selectivity has been studied extensively in various visual areas at different stages of visual processing in the macaque brain. In these studies, color stimuli defined in the Derrington-Krauskopf-Lennie (DKL) color space with a limited range of cone contrast were typically used in early stages, whereas those defined in the Commission Internationale de l'Eclairage (CIE) color space, based on human psychophysical measurements across the gamut of the display, were often used in higher visual areas. To understand how the color information is processed along the visual pathway, it is necessary to compare color selectivity obtained in different areas on a common color space. In the present study, we tested whether the neural color selectivity obtained in DKL space can be predicted from responses obtained in CIE space and whether stimuli with limited cone contrast are sufficient to characterize neural color selectivity. We found that for most V4 neurons, there was a strong correlation between responses measured using the two chromatic coordinate systems, and the color selectivities obtained with the two stimulus sets were comparable. However, for some neurons preferring high- or low-saturation colors, stimuli defined in DKL color space did not adequately capture the neural color selectivity. This is mainly due to the use of stimuli within a limited range of cone contrast. We conclude that regardless of the choice of color space, the sampling of colors across the entire gamut is important to characterize neural color selectivity fully or to compare color selectivities in different areas so as to understand color representation in the visual system.

Early Visual Cortex Dynamics during Top–Down Modulated Shifts of Feature-Selective Attention

Shifting attention from one color to another color or from color to another feature dimension such as shape or orientation is imperative when searching for a certain object in a cluttered scene. Most attention models that emphasize feature-based selection implicitly assume that all shifts in feature-selective attention underlie identical temporal dynamics. Here, we recorded time courses of behavioral data and steady-state visual evoked potentials (SSVEPs), an objective electrophysiological measure of neural dynamics in early visual cortex to investigate temporal dynamics when participants shifted attention from color or orientation toward color or orientation, respectively. SSVEPs were elicited by four random dot kinematograms that flickered at different frequencies. Each random dot kinematogram was composed of dashes that uniquely combined two features from the dimensions color (red or blue) and orientation (slash or backslash). Participants were cued to attend to one feature (such as color or orientation) and respond to coherent motion targets of the to-be-attended feature. We found that shifts toward color occurred earlier after the shifting cue compared with shifts toward orientation, regardless of the original feature (i.e., color or orientation). This was paralleled in SSVEP amplitude modulations as well as in the time course of behavioral data. Overall, our results suggest different neural dynamics during shifts of attention from color and orientation and the respective shifting destinations, namely, either toward color or toward orientation.

Population Code Dynamics in Categorical Perception

Categorical perception is a ubiquitous function in sensory information processing, and is reported to have important influences on the recognition of presented and/or memorized stimuli. However, such complex interactions among categorical perception and other aspects of sensory processing have not been explained well in a unified manner. Here, we propose a recurrent neural network model to process categorical information of stimuli, which approximately realizes a hierarchical Bayesian estimation on stimuli. The model accounts for a wide variety of neurophysiological and cognitive phenomena in a consistent framework. In particular, the reported complexity of categorical effects, including (i) task-dependent modulation of neural response, (ii) clustering of neural population representation, (iii) temporal evolution of perceptual color memory, and (iv) a non-uniform discrimination threshold, are explained as different aspects of a single model. Moreover, we directly examine key model behaviors in the monkey visual cortex by analyzing neural population dynamics during categorization and discrimination of color stimuli. We find that the categorical task causes temporally-evolving biases in the neuronal population representations toward the focal colors, which supports the proposed model. These results suggest that categorical perception can be achieved by recurrent neural dynamics that approximates optimal probabilistic inference in the changing environment.

Changes in unique hues induced by chromatic surrounds

A chromatic surround can have a strong influence on the perceived hue of a stimulus. We investigated whether chromatic induction has similar effects on the perception of colors that appear pure and unmixed (unique red, green, blue, and yellow) as on other colors. Subjects performed unique hue settings of stimuli in isoluminant surrounds of different chromaticities. Compared with the settings in a neutral gray surround, unique hue settings altered systematically with chromatic surrounds. The amount of induced hue shift depended on the difference between stimulus and surround hues, and was similar for unique hue settings as for settings of nonunique hues. Intraindividual variability in unique hue settings was roughly twice as high as for settings obtained in asymmetric matching experiments, which may reflect the presence of a reference stimulus in the matching task. Variabilities were also larger with chromatic surrounds than with neutral gray surrounds, for both unique hue settings and matching of nonunique hues. The results suggest that the neural representations underlying unique hue percepts are influenced by the same neural processing mechanisms as the percepts of other colors.

Stimulus size dependence of hue changes induced by chromatic surrounds

A chromatic surround induces a change in the perceived hue of a stimulus. This shift in hue depends on the chromatic difference between the stimulus and the surround. We investigated how chromatic induction varies with stimulus size and whether the size dependence depends on the surround hue. Subjects performed asymmetric matching of color stimuli with different sizes in surrounds of different chromaticities. Generally, induced hue shifts decreased with increasing stimulus size. This decrease was quantitatively different for different surround hues. However, when size effects were normalized to an overall induction strength, the chromatic specificity was largely reduced. The separability of inducer chromaticity and stimulus size suggests that these effects are mediated by different neural mechanisms.

Contrast adaptation to luminance and brightness modulations

Perceptual brightness and color contrast decrease after seeing a light temporally modulating along a certain direction in a color space, a phenomenon known as contrast adaptation. We investigated whether contrast adaptation along the luminance direction arises from modulation of luminance signals or apparent brightness signals. The stimulus consisted of two circles on a gray background presented on a CRT monitor. In the adaptation phase, the luminance and chromaticity of one circle were temporally modulated, while the other circle was kept at a constant luminance and color metameric with an equal-energy white. We employed two types of temporal modulations, namely, in luminance and brightness. Chromaticity was sinusoidally modulated along the L-M axis, leading to dissociation between luminance and brightness (the Helmholtz-Kohlrausch effect). In addition, luminance modulation was minimized in the brightness modulation, while brightness modulation was minimized in the luminance modulation. In the test phase, an asymmetric matching method was used to measure the magnitude of contrast adaptation for both modulations. Our results showed that, although contrast adaptation along the luminance direction occurred for both modulations, contrast adaptation for luminance modulation was significantly stronger than that for the brightness modulation regardless of the temporal frequency of the adaptation modulation. These results suggest that luminance modulation is more influential in contrast adaptation than brightness modulation.

Color-motion feature-binding errors are mediated by a higher-order chromatic representation

Peripheral and central moving objects of the same color may be perceived to move in the same direction even though peripheral objects have a different true direction of motion [Nature429, 262 (2004)10.1038/429262a]. The perceived, illusory direction of peripheral motion is a color-motion feature-binding error. Recent work shows that such binding errors occur even without an exact color match between central and peripheral objects, and, moreover, the frequency of the binding errors in the periphery declines as the chromatic difference increases between the central and peripheral objects [J. Opt. Soc. Am. A31, A60 (2014)JOAOD60740-323210.1364/JOSAA.31.000A60]. This change in the frequency of binding errors with the chromatic difference raises the general question of the chromatic representation from which the difference is determined. Here, basic properties of the chromatic representation are tested to discover whether it depends on independent chromatic differences on the l and the s cardinal axes or, alternatively, on a more specific higher-order chromatic representation. Experimental tests compared the rate of feature-binding errors when the central and peripheral colors had the identical s chromaticity (so zero difference in s) and a fixed magnitude of l difference, while varying the identical s level in center and periphery (thus always keeping the s difference at zero). A chromatic representation based on independent l and s differences would result in the same frequency of color-motion binding errors at everyslevel. The results are contrary to this prediction, thus showing that the chromatic representation at the level of color-motion feature binding depends on a higher-order chromatic mechanism.

Modeling the Effects of Perceptual Load: Saliency, Competitive Interactions, and Top-Down Biases

A computational model of visual selective attention has been implemented to account for experimental findings on the Perceptual Load Theory (PLT) of attention. The model was designed based on existing neurophysiological findings on attentional processes with the objective to offer an explicit and biologically plausible formulation of PLT. Simulation results verified that the proposed model is capable of capturing the basic pattern of results that support the PLT as well as findings that are considered contradictory to the theory. Importantly, the model is able to reproduce the behavioral results from a dilution experiment, providing thus a way to reconcile PLT with the competing Dilution account. Overall, the model presents a novel account for explaining PLT effects on the basis of the low-level competitive interactions among neurons that represent visual input and the top-down signals that modulate neural activity. The implications of the model concerning the debate on the locus of selective attention as well as the origins of distractor interference in visual displays of varying load are discussed.

Representation of Color Surfaces in V1: Edge Enhancement and Unfilled Holes

The neuronal mechanism underlying the representation of color surfaces in primary visual cortex (V1) is not well understood. We tested on color surfaces the previously proposed hypothesis that visual perception of uniform surfaces is mediated by an isomorphic, filled-in representation in V1. We used voltage-sensitive-dye imaging in fixating macaque monkeys to measure V1 population responses to spatially uniform chromatic (red, green, or blue) and achromatic (black or white) squares of different sizes (0.5°-8°) presented for 300 ms. Responses to both color and luminance squares early after stimulus onset were similarly edge-enhanced: for squares 1° and larger, regions corresponding to edges were activated much more than those corresponding to the center. At later times after stimulus onset, responses to achromatic squares' centers increased, partially "filling-in" the V1 representation of the center. The rising phase of the center response was slower for larger squares. Surprisingly, the responses to color squares behaved differently. For color squares of all sizes, responses remained edge-enhanced throughout the stimulus. There was no filling-in of the center. Our results imply that uniform filled-in representations of surfaces in V1 are not required for the perception of uniform surfaces and that chromatic and achromatic squares are represented differently in V1.

SIGNIFICANCE STATEMENT

We used voltage-sensitive dye imaging from V1 of behaving monkeys to test the hypothesis that visual perception of uniform surfaces is mediated by an isomorphic, filled-in representation. We found that the early population responses to chromatic and achromatic surfaces are edge enhanced, emphasizing the importance of edges in surface processing. Next, we show for color surfaces that responses remained edge-enhanced throughout the stimulus presentation whereas response to luminance surfaces showed a slow neuronal 'filling-in' of the center. Our results suggest that isomorphic representation is not a general code for uniform surfaces in V1.

Primary Visual Cortex as a Saliency Map: A Parameter-Free Prediction and Its Test by Behavioral Data

It has been hypothesized that neural activities in the primary visual cortex (V1) represent a saliency map of the visual field to exogenously guide attention. This hypothesis has so far provided only qualitative predictions and their confirmations. We report this hypothesis’ first quantitative prediction, derived without free parameters, and its confirmation by human behavioral data. The hypothesis provides a direct link between V1 neural responses to a visual location and the saliency of that location to guide attention exogenously. In a visual input containing many bars, one of them saliently different from all the other bars which are identical to each other, saliency at the singleton’s location can be measured by the shortness of the reaction time in a visual search for singletons. The hypothesis predicts quantitatively the whole distribution of the reaction times to find a singleton unique in color, orientation, and motion direction from the reaction times to find other types of singletons. The prediction matches human reaction time data. A requirement for this successful prediction is a data-motivated assumption that V1 lacks neurons tuned simultaneously to color, orientation, and motion direction of visual inputs. Since evidence suggests that extrastriate cortices do have such neurons, we discuss the possibility that the extrastriate cortices play no role in guiding exogenous attention so that they can be devoted to other functions like visual decoding and endogenous attention.

It has been hypothesized that neural activities in the primary visual cortex represent a saliency map of the visual field to exogenously guide attention. This hypothesis has so far provided only qualitative predictions and their confirmations. We report this hypothesis’ first quantitative prediction, derived without free parameters, and its confirmation by human behavioral data. Using the shortness of reaction times in visual search tasks to measure saliency of the search target’s location, the hypothesis predicts the quantitative distribution of the reaction times to find a salient bar unique in color, orientation, and motion direction in a background of bars that are identical to each other. The prediction matches experimental observations in human observers. Since the prediction would be invalid without a particular neural property of the primary visual cortex, the extrastriate cortices may give little contribution to exogenous attentional guidance since they lack this neural property. Implications of this prospect on the framework of attentional network and the computational role of the higher brain areas are also discussed.

Hue Selectivity in Human Visual Cortex Revealed by Functional Magnetic Resonance Imaging

The variability of color-selective neurons in human visual cortex is considered more diverse than cone-opponent mechanisms. We addressed this issue by deriving histograms of hue-selective voxels measured using fMRI with a novel stimulation paradigm, where the stimulus hue changed continuously. Despite the large between-subject difference in hue-selective histograms, individual voxels exhibited selectivity for intermediate hues, such as purple, cyan, and orange, in addition to those along cone-opponent axes. In order to rule the possibility out that the selectivity for intermediate hues emerged through spatial summation of activities of neurons selectively responding to cone-opponent signals, we further tested hue-selective adaptations in intermediate directions of cone-opponent axes, by measuring responses to 4 diagonal hues during concurrent adaptation to 1 of the 4 hues. The selective and unidirectional reduction in response to the adapted hue lends supports to our argument that cortical neurons respond selectively to intermediate hues.

Functional magnetic resonance imaging adaptation reveals a noncategorical representation of hue in early visual cortex

Color names divide the fine-grained gamut of color percepts into discrete categories. A categorical transition must occur somewhere between the initial encoding of the continuous spectrum of light by the cones and the verbal report of the name of a color stimulus. Here, we used a functional magnetic resonance imaging (fMRI) adaptation experiment to examine the representation of hue in the early visual cortex. Our stimuli varied in hue between blue and green. We found in the early visual areas (V1, V2/3, and hV4) a smoothly increasing recovery from adaptation with increasing hue distance between adjacent stimuli during both passive viewing (Experiment 1) and active categorization (Experiment 2). We examined the form of the adaptation effect and found no evidence that a categorical representation mediates the release from adaptation for stimuli that cross the blue-green color boundary. Examination of the direct effect of stimulus hue on the fMRI response did, however, reveal an enhanced response to stimuli near the blue-green category border. This was largest in hV4 and when subjects were engaged in active categorization of the stimulus hue. In contrast with a recent report from another laboratory (Bird, Berens, Horner, & Franklin, 2014), we found no evidence for a categorical representation of color in the middle frontal gyrus. A post hoc whole-brain analysis, however, revealed several regions in the frontal cortex with a categorical effect in the adaptation response. Overall, our results support the idea that the representation of color in the early visual cortex is primarily fine grained and does not reflect color categories.

Neuronal Representation of Ultraviolet Visual Stimuli in Mouse Primary Visual Cortex

The mouse has become an important model for understanding the neural basis of visual perception. Although it has long been known that mouse lens transmits ultraviolet (UV) light and mouse opsins have absorption in the UV band, little is known about how UV visual information is processed in the mouse brain. Using a custom UV stimulation system and in vivo calcium imaging, we characterized the feature selectivity of layer 2/3 neurons in mouse primary visual cortex (V1). In adult mice, a comparable percentage of the neuronal population responds to UV and visible stimuli, with similar pattern selectivity and receptive field properties. In young mice, the orientation selectivity for UV stimuli increased steadily during development, but not direction selectivity. Our results suggest that, by expanding the spectral window through which the mouse can acquire visual information, UV sensitivity provides an important component for mouse vision.

Brightness-color interactions in human early visual cortex

The interaction between brightness and color causes there to be different color appearance when one and the same object is viewed against surroundings of different brightness. Brightness contrast causes color to be desaturated, as has been found in perceptual experiments on color induction and color-gamut expansion in human vision. However, it is not clear yet where in the cerebral cortex the brightness-color interaction that causes these major perceptual effects is located. One hypothesis is that brightness and color signals are processed separately and in parallel within the primary visual cortex V1 and only interact in extrastriate cortex. Another hypothesis is that color and brightness contrast interact strongly already within V1. We localized the brightness-color interaction in human V1 by means of recording the chromatic visual-evoked potential. The chromatic visual-evoked potential measurements decisively support the idea that brightness-color interaction arises in a recurrent inhibitory network in V1. Furthermore, our results show that the inhibitory signal for brightness-color interaction is generated by local brightness contrast at the boundary between target and surround, instead of by the luminance difference between the interior of the color target and its large background.

Effects of luminance contrast on the color selectivity of neurons in the macaque area v4 and inferior temporal cortex

Appearance of a color stimulus is significantly affected by the contrast between its luminance and the luminance of the background. In the present study, we used stimuli evenly distributed on the CIE-xy chromaticity diagram to examine how luminance contrast affects neural representation of color in V4 and the anterior inferior temporal (AITC) and posterior inferior temporal (PITC) color areas (Banno et al., 2011). The activities of single neurons were recorded from monkeys performing a visual fixation task, and the effects of luminance contrast on the color selectivity of individual neurons and their population responses were systematically examined by comparing responses to color stimuli that were brighter or darker than the background. We found that the effects of luminance contrast differed considerably across V4 and the PITC and AITC. In both V4 and the PITC, the effects of luminance contrast on the population responses of color-selective neurons depended on color. In V4, the size of the effect was largest for blue and cyan, whereas in the PITC, the effect gradually increased as the saturation of the color stimulus was reduced, and was especially large with neutral colors (white, gray, black). The pattern observed in the PITC resembles the effect of luminance contrast on color appearance, suggesting PITC neurons are closely involved in the formation of the perceived appearance of color. By contrast, the color selectivities of AITC neurons were little affected by luminance contrast, indicating that hue and saturation of color stimuli are represented independently of luminance contrast in the AITC.