The spatial transformation of color in the primary visual cortex of the macaque monkey

An analysis of information segregation in parallel streams of a multi-stream convolutional neural network

Visual information is processed in hierarchically organized parallel streams in the primate brain. In the present study, information segregation in parallel streams was examined by constructing a convolutional neural network with parallel architecture in all of the convolutional layers. Although filter weights for convolution were initially set to random values, color information was segregated from shape information in most model instances after training. Deletion of the color-related stream decreased recognition accuracy of animate images, whereas deletion of the shape-related stream decreased recognition accuracy of both animate and inanimate images. The results suggest that properties of filters and functions of a stream are spontaneously segregated in parallel streams of neural networks.

Binocular luster elicited by isoluminant chromatic stimuli relies on mechanisms similar to those in the achromatic case

The phenomenon of binocular luster can be evoked by simple dichoptic center-surround stimuli showing a luminance contrast difference between the eyes. Previous findings support the idea that this phenomenon is mediated by a low-level conflict mechanism that integrates the monocular signals from different types of contrast detector cells. Also, isoluminant stimuli with different chromatic contrasts between eyes can trigger sensations of luster. Here, we investigate whether the lustrous impression in such purely chromatic stimuli depends on interocular contrast differences and in particular on interocular contrast polarity pairings in a similar way as in the achromatic case. In our experiments, we measured the magnitude of the lustrous response using a series of isoluminant dichoptic center-ring-surround stimuli with varying ring width whose chromatic properties were varied along the red-green and blue-yellow cardinal directions. The trends in the data were very similar to those of our former study with achromatic stimuli, indicating similar mechanisms in both cases. The empirical luster data could also be predicted fairly well by a chromatic version of our interocular conflict model (with overall R2 values between 0.577 and 0.639), for which two different receptive field models were used, simulating the behavior of color-sensitive double-opponent cells in V1.

Color constancy in real-world settings

Color constancy denotes the ability to assign a particular and stable color percept to an object, irrespective of its surroundings and illumination. The light reaching the eye confounds illumination and spectral reflectance of the object, making the recovery of constant object color an ill-posed problem. How good the visual system is at accomplishing this task is still a matter of heated debate, despite more than a 100 years of research. Depending on the laboratory task and the specific cues available to observers, color constancy was found to be at levels ranging between 15% and 80%, which seems incompatible with the relatively stable color appearance of objects around us and the consistent usage of color names in real life. Here, we show close-to-perfect color constancy using real objects in a natural task and natural environmental conditions, chosen to mimic the role of color constancy in everyday life. Participants had to identify the color of a (non-present) item familiar to them in an office room under five different experimental illuminations. They mostly selected the same colored Munsell chip as their match to the absent object, even though the light reaching the eye in each case differed substantially. Our results demonstrate that color constancy under ideal conditions in the real world can indeed be exceptionally good. We found it to be as good as visual memory permits and not generally compromised by sensory uncertainty.

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

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

Differential encoding of temporally evolving color patterns across nearby V1 neurons

Whereas studies of the V1 cortex have focused mainly on neural line orientation preference, color inputs are also known to have a strong presence among these neurons. Individual neurons typically respond to multiple colors and nearby neurons have different combinations of preferred color inputs. However, the computations performed by V1 neurons on such color inputs have not been extensively studied. Here we aimed to address this issue by studying how different V1 neurons encode different combinations of inputs composed of four basic colors. We quantified the decoding accuracy of individual neurons from multi-electrode array recordings, comparing multiple individual neurons located within 2 mm along the vertical axis of the V1 cortex of the anesthetized rat. We found essentially all V1 neurons to be good at decoding spatiotemporal patterns of color inputs and they did so by encoding them in different ways. Quantitative analysis showed that even adjacent neurons encoded the specific input patterns differently, suggesting a local cortical circuitry organization which tends to diversify rather than unify the neuronal responses to each given input. Using different pairs of monocolor inputs, we also found that V1 neocortical neurons had a diversified and rich color opponency across the four colors, which was somewhat surprising given the fact that rodent retina express only two different types of opsins. We propose that the processing of color inputs in V1 cortex is extensively composed of multiple independent circuitry components that reflect abstract functionalities resident in the internal cortical processing rather than the raw sensory information per se.

Comparing the Dominance of Color and Form Information across the Human Ventral Visual Pathway and Convolutional Neural Networks

Color and form information can be decoded in every region of the human ventral visual hierarchy, and at every layer of many convolutional neural networks (CNNs) trained to recognize objects, but how does the coding strength of these features vary over processing? Here, we characterize for these features both their absolute coding strength-how strongly each feature is represented independent of the other feature-and their relative coding strength-how strongly each feature is encoded relative to the other, which could constrain how well a feature can be read out by downstream regions across variation in the other feature. To quantify relative coding strength, we define a measure called the form dominance index that compares the relative influence of color and form on the representational geometry at each processing stage. We analyze brain and CNN responses to stimuli varying based on color and either a simple form feature, orientation, or a more complex form feature, curvature. We find that while the brain and CNNs largely differ in how the absolute coding strength of color and form vary over processing, comparing them in terms of their relative emphasis of these features reveals a striking similarity: For both the brain and for CNNs trained for object recognition (but not for untrained CNNs), orientation information is increasingly de-emphasized, and curvature information is increasingly emphasized, relative to color information over processing, with corresponding processing stages showing largely similar values of the form dominance index.

Color appearance of spatial patterns compared by direct estimation and conjoint measurement

Perceptual scales of color saturation obtained by direct estimation (DE) and maximum likelihood conjoint measurement (MLCM) were compared for red checkerboard patterns and uniform red squares. For the DE task, observers were asked to rate the saturation level as a percentage, indicating the chromatic sensation for each pattern and contrast. For the MLCM procedure, observers judged on each trial which of two stimuli that varied in chromatic contrast and/or spatial pattern evoked the most salient color. In separate experiments, patterns varying only in luminance contrast were also tested. The MLCM data confirmed previous results reported with DE indicating that the slope of the checkerboard scale with cone contrast levels is steeper than that for the uniform square. Similar results were obtained with patterns modulated only in luminance. DE methods were relatively more variable within an observer, reflecting observer uncertainty, while MLCM scales showed greater relative variability across observers, perhaps reflecting individual differences in the appearance of the stimuli. MLCM provides a reliable scaling method, based only on ordinal judgments between pairs of stimuli and that provides less opportunity for subject-specific biases and strategies to intervene in perceptual judgements.

Decoding of EEG signals reveals non-uniformities in the neural geometry of colour

The idea of colour opponency maintains that colour vision arises through the comparison of two chromatic mechanisms, red versus green and yellow versus blue. The four unique hues, red, green, blue, and yellow, are assumed to appear at the null points of these the two chromatic systems. Here we hypothesise that, if unique hues represent a tractable cortical state, they should elicit more robust activity compared to other, non-unique hues. We use a spatiotemporal decoding approach to report that electroencephalographic (EEG) responses carry robust information about the tested isoluminant unique hues within a 100-350 ms window from stimulus onset. Decoding is possible in both passive and active viewing tasks, but is compromised when concurrent high luminance contrast is added to the colour signals. For large hue-differences, the efficiency of hue decoding can be predicted by mutual distance in a nominally uniform perceptual colour space. However, for small perceptual neighbourhoods around unique hues, the encoding space shows pivotal non-uniformities which suggest that anisotropies in neurometric hue-spaces may reflect perceptual unique hues.

Perception of color in primates: A conceptual color neurons hypothesis

Perception of color by humans and other primates is a complex problem, studied by neurophysiology, psychophysiology, psycholinguistics, and even philosophy. Being mostly trichromats, simian primates have three types of opsin proteins, expressed in cone neurons in the eye, which allow for the sensing of color as the physical wavelength of light. Further, in neural networks of the retina, the coding principle changes from three types of sensor proteins to two opponent channels: activity of one type of neuron encode the evolutionarily ancient blue-yellow axis of color stimuli, and another more recent evolutionary channel, encoding the axis of red-green color stimuli. Both color channels are distinctive in neural organization at all levels from the eye to the neocortex, where it is thought that the perception of color (as philosophical qualia) emerges from the activity of some neuron ensembles. Here, using data from neurophysiology as a starting point, we propose a hypothesis on how the perception of color can be encoded in the activity of certain neurons in the neocortex. These conceptual neurons, herein referred to as 'color neurons', code only the hue of the color of visual stimulus, similar to place cells and number neurons, already described in primate brains. A case study with preliminary, but direct, evidence for existing conceptual color neurons in the human brain was published in 2008. We predict that the upcoming studies in non-human primates will be more extensive and provide a more detailed description of conceptual color neurons.

Joint representations of color and form in mouse visual cortex described by random pooling from rods and cones

Spatial transitions in color can aid any visual perception task, and its neural representation, the "integration of color and form," is thought to begin at primary visual cortex (V1). Integration of color and form is untested in mouse V1, yet studies show that the ventral retina provides the necessary substrate from green-sensitive rods and ultraviolet-sensitive cones. Here, we used two-photon imaging in V1 to measure spatial frequency (SF) tuning along four axes of rod and cone contrast space, including luminance and color. We first reveal that V1's sensitivity to color is similar to luminance, yet average SF tuning is significantly shifted lowpass for color. Next, guided by linear models, we used SF tuning along all four color axes to estimate the proportion of neurons that fall into classic models of color opponency, i.e., "single-," "double-," and "non-opponent." Few neurons (∼6%) fit the criteria for double opponency, which are uniquely tuned for chromatic borders. Most of the population can be described as a unimodal distribution ranging from strongly single-opponent to non-opponent. Consistent with recent studies of the rodent and primate retina, our V1 data are well-described by a simple model in which ON and OFF channels to V1 sample the photoreceptor mosaic randomly. Finally, an analysis comparing color opponency to preferred orientation and retinotopy further validates rods, and not cone M-opsin, as opponent with cone S-opsin in the upper visual field.NEW & NOTEWORTHY This study is the first to show that mouse V1 is highly sensitive to UV-green color contrast. Furthermore, it provides a detailed characterization of "color opponency," which is the putative neural basis for color perception. Finally, using an extremely simple yet novel random wiring model, we account for our observations.

Understanding insect colour constancy

Colour constancy is the ability to recognize the colour of objects despite spectral changes in the natural illumination. As such, this phenomenon is important for most organisms with good colour vision, and it has been intensively studied in humans and primates. Colour constancy is also documented for several species of insects, which is not surprising given the ecological importance of colour vision. But how do insects, with their small brains, solve the complex problem of colour vision and colour constancy? In an interspecies approach, this review reports on behavioural studies on colour constancy in bees, butterflies, moths and humans, corresponding computational models and possible neurophysiological correlates. This article is part of the theme issue 'Understanding colour vision: molecular, physiological, neuronal and behavioural studies in arthropods'.

Action-based predictions affect visual perception, neural processing, and pupil size, regardless of temporal predictability

Sensory consequences of one's own action are often perceived as less intense, and lead to reduced neural responses, compared to externally generated stimuli. Presumably, such sensory attenuation is due to predictive mechanisms based on the motor command (efference copy). However, sensory attenuation has also been observed outside the context of voluntary action, namely when stimuli are temporally predictable. Here, we aimed at disentangling the effects of motor and temporal predictability-based mechanisms on the attenuation of sensory action consequences. During fMRI data acquisition, participants (N = 25) judged which of two visual stimuli was brighter. In predictable blocks, the stimuli appeared temporally aligned with their button press (active) or aligned with an automatically generated cue (passive). In unpredictable blocks, stimuli were presented with a variable delay after button press/cue, respectively. Eye tracking was performed to investigate pupil-size changes and to ensure proper fixation. Self-generated stimuli were perceived as darker and led to less neural activation in visual areas than their passive counterparts, indicating sensory attenuation for self-generated stimuli independent of temporal predictability. Pupil size was larger during self-generated stimuli, which correlated negatively with the blood oxygenation level dependent (BOLD) response: the larger the pupil, the smaller the BOLD amplitude in visual areas. Our results suggest that sensory attenuation in visual cortex is driven by action-based predictive mechanisms rather than by temporal predictability. This effect may be related to changes in pupil diameter. Altogether, these results emphasize the role of the efference copy in the processing of sensory action consequences.

Signals from Single-Opponent Cortical Cells in the Human cVEP

We used the chromatic visual evoked potential (cVEP) to study responses in human visual cortex evoked by equiluminant color stimuli for 6 male and 11 female observers. Large-area, colored squares were used to stimulate Single-Opponent cells preferentially, and fine color-checkerboard stimuli were used to activate Double-Opponent responses preferentially. Stimuli were modulated along the following two directions in color space: (1) the cardinal direction, L-M or M-L of DKL (Derrington, Krauskopf, and Lennie) space; and (2) the line from the white point to the color of the Red LED in the display screen, which was approximately intermediate between the L-M and -S directions in DKL space in cone-contrast coordinates. The amplitudes of cVEPs to large squares were smaller than those to checkerboards, and the latency of the cVEP response to squares was significantly less than the checkerboard latency. The latency of cVEP responses to the squares varied little with cone-contrast unlike the steep reduction of latency with cone-contrast observed in responses to color checkerboard patterns. The dynamic differences between cVEPs to squares and checkerboards support the hypothesis that a distinct neuronal mechanism responded to squares: Single-Opponent cells. Response amplitude, latency, and transientness-and their dependence on cone-contrast-were similar in the responses in the L-M and Red color directions. The similarity supports the hypothesis that the Single-Opponent signals in the cVEP come from a distinct population of cells that receives subtractive inputs from L and M cones, either L-M or M-L.SIGNIFICANCE STATEMENT This article is about characterizing the visual behavior of a distinct population of neurons in the human visual cortex, the Single-Opponent color cells. Based on single-cell results in the visual cortex of macaque monkeys, we used large uniformly colored stimuli to isolate the responses of Single-Opponent cells in the chromatic visual evoked potential (cVEP) recorded on the scalp of human observers. VEP signals recorded under conditions believed to reveal Single-Opponent responses are small and transient. Their time course is relatively unaffected by cone-contrast, and they are relatively insensitive to stimulus modulation of short wavelength-sensitive S cones. Because Single-Opponent cells convey signals that can be used to judge the color of scene illumination, knowing their visual properties is important for understanding color vision.

The contribution of luminance and chromatic channels to color assimilation

Color induction is the phenomenon where the physical and the perceived colors of an object differ owing to the color distribution and the spatial configuration of the surrounding objects. Previous works studying this phenomenon on the lsY MacLeod-Boynton color space, show that color assimilation is present only when the magnocellular pathway (i.e., the Y axis) is activated (i.e., when there are luminance differences). Concretely, the authors showed that the effect is mainly induced by the koniocellular pathway (s axis), but not by the parvocellular pathway (l axis), suggesting that when magnocellular pathway is activated it inhibits the koniocellular pathway. In the present work, we study whether parvo-, konio-, and magnocellular pathways may influence on each other through the color induction effect. Our results show that color assimilation does not depend on a chromatic-chromatic interaction, and that chromatic assimilation is driven by the interaction between luminance and chromatic channels (mainly the magno- and the koniocellular pathways). Our results also show that chromatic induction is greatly decreased when all three visual pathways are simultaneously activated, and that chromatic pathways could influence each other through the magnocellular (luminance) pathway. In addition, we observe that chromatic channels can influence the luminance channel, hence inducing a small brightness induction. All these results show that color induction is a highly complex process where interactions between the several visual pathways are yet unknown and should be studied in greater detail.

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.

Coding of chromatic spatial contrast by macaque V1 neurons

Color perception relies on comparisons between adjacent lights, but how the brain performs these comparisons is poorly understood. To elucidate the underlying neural mechanisms, we recorded spiking responses of individual V1 neurons in macaque monkeys to pairs of stimuli within the classical receptive field (RF). We estimated the spatial-chromatic RF of each neuron and then presented customized colored edges using a novel closed-loop technique. We found that many double-opponent (DO) cells, which have spatially and chromatically opponent RFs, responded to chromatic contrast as a weighted sum, akin to how other V1 cells responded to luminance contrast. Yet other neurons integrated chromatic signals non-linearly, confirming that linear signal integration is not an obligate property of V1 neurons. The functional similarity of cone-opponent DO cells and cone non-opponent simple cells suggests that these two groups may share a common underlying neural circuitry, promotes the construction of image-computable models for full-color image representation, and sheds new light on V1 complex cells.

Representation of Color, Form, and their Conjunction across the Human Ventral Visual Pathway

Despite decades of research, our understanding of the relationship between color and form processing in the primate ventral visual pathway remains incomplete. Using fMRI multivoxel pattern analysis, we examined coding of color and form, using a simple form feature (orientation) and a mid-level form feature (curvature), in human ventral visual processing regions. We found that both color and form could be decoded from activity in early visual areas V1 to V4, as well as in the posterior color-selective region and shape-selective regions in ventral and lateral occipitotemporal cortex defined based on their univariate selectivity to color or shape, respectively (the central color region only showed color but not form decoding). Meanwhile, decoding biases towards one feature or the other existed in the color- and shape-selective regions, consistent with their univariate feature selectivity reported in past studies. Additional extensive analyses show that while all these regions contain independent (linearly additive) coding for both features, several early visual regions also encode the conjunction of color and the simple, but not the complex, form feature in a nonlinear, interactive manner. Taken together, the results show that color and form are encoded in a biased distributed and largely independent manner across ventral visual regions in the human brain.

Influence of Stimulus Size on Simultaneous Chromatic Induction

Chromatic induction is a major contextual effect of color appearance. Patterned backgrounds are known to induce strong chromatic induction effects. However, it has not been clarified whether the spatial extent of the chromatic surrounding induces a chromatic contrast or assimilation effects. In this study, we examined the influence of the width of a center line and its flanking white contour on the color appearance when the line was surrounded by chromatic backgrounds. A strong color shift was observed when the center line was flanked by white contours with the L/M- and S-cone chromatic backgrounds. There was a difference between the optimal widths of the center line and the contour for the shift in color appearance for the L/M-cone chromaticity (0.9 and 1.1–1.7 min, respectively) and the S-cone chromaticity (8.2–17.5 and 0.9–2.5 min, respectively). The optimal width of the center line for the L/M-cone was finer than the resolution-limit width of the chromatic contrast sensitivity and coarser than that of the luminance contrast sensitivity. Thus, the color appearance of the center line could be obtained by integrating broad chromatic information and fine luminance details. Due to blurring and chromatic aberrations, the simulated artifact was large for the darker center line and S-cone background, thus suggesting that the artifact could explain the luminance dependency of the induction along the S-cone chromaticity. Moreover, the findings of this study reveal that the dominant factor of the color shift is neural instead of optical.

Differences in chromatic noise suppression of luminance contrast discrimination in young and elderly people

Aging causes impairment of contrast sensitivity and chromatic discrimination, leading to changes in the perceptual interactions between color and luminance information. We aimed to investigate the influence of chromatic noise on luminance contrast thresholds in young and older adults. Forty participants were divided equally into Young (29.6 ± 6.3-year-old) and Elderly Groups (57.8 ± 6.6-year-old). They performed a luminance contrast discrimination task in the presence of chromatic noise maskers using a mosaic stimulus in a mosaic background. Four chromatic noise masking protocols were applied (protan, deutan, tritan, and no-noise protocols). We found that luminance contrast thresholds were significantly elevated by the addition of chromatic noise in both age groups (P < 0.05). In the Elderly group, but not the younger group, thresholds obtained in the tritan protocol were lower than those obtained from protan and deutan protocols (P < 0.05). For all protocols, the luminance contrast thresholds of elderly participants were higher than in young people (P < 0.01). Tritan chromatic noise was less effective in inhibiting luminance discrimination in elderly participants.

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.

A multiplicity of color-responsive cortical mechanisms revealed by the dynamics of cVEPs

Our results connect higher-order color mechanisms deduced from psychophysics with the known diversity of populations of double-opponent, color-responsive cells in V1. We used the chromatic visual evoked potential, the cVEP, to study responses in human visual cortex to equiluminant color patterns. Stimuli were modulated along three directions in color space: the cardinal directions, L-M and S, and along the line in color space from the white point to the color of the Red LED in the display screen (the Red direction). The Red direction is roughly intermediate between L-M and S in DKL space in cone-contrast coordinates. While cVEP response amplitude, latency, and width--and their dependences on cone contrast-- were similar in the L-M and Red directions, the Transientness of the Red response was significantly greater than for responses to stimuli in the L-M direction and in the S direction. This difference in response dynamics supports the concept that there are multiple, distinct neuronal populations, so-called higher- order color mechanisms, for color perception within human V1 cortex.

A quadratic model captures the human V1 response to variations in chromatic direction and contrast

An important goal for vision science is to develop quantitative models of the representation of visual signals at post-receptoral sites. To this end, we develop the quadratic color model (QCM) and examine its ability to account for the BOLD fMRI response in human V1 to spatially-uniform, temporal chromatic modulations that systematically vary in chromatic direction and contrast. We find that the QCM explains the same, cross-validated variance as a conventional general linear model, with far fewer free parameters. The QCM generalizes to allow prediction of V1 responses to a large range of modulations. We replicate the results for each subject and find good agreement across both replications and subjects. We find that within the LM cone contrast plane, V1 is most sensitive to L-M contrast modulations and least sensitive to L+M contrast modulations. Within V1, we observe little to no change in chromatic sensitivity as a function of eccentricity.

Signals Related to Color in the Early Visual Cortex

Visual images can be described in terms of the illuminants and objects that are causal to the light reaching the eye, the retinal image, its neural representation, or how the image is perceived. Respecting the differences among these distinct levels of description can be challenging but is crucial for a clear understanding of color vision. This article approaches color by reviewing what is known about its neural representation in the early visual cortex, with a brief description of signals in the eye and the thalamus for context. The review focuses on the properties of single neurons and advances the general theme that experimental approaches based on knowledge of feedforward signals have promoted greater understanding of the neural code for color than approaches based on correlating single-unit responses with color perception. New data from area V1 illustrate the strength of the feedforward approach. Future directions for progress in color neurophysiology are discussed: techniques for improved single-neuron characterization, for investigations of neural populations and small circuits, and for the analysis of natural image statistics.

Suppression of Luminance Contrast Sensitivity by Weak Color Presentation

The results of psychophysical studies suggest that color in a visual scene affects luminance contrast perception. In our brain imaging studies we have found evidence of an effect of chromatic information on luminance information. The dependency of saturation on brain activity in the visual cortices was measured by functional magnetic resonance imaging (fMRI) while the subjects were observing visual stimuli consisting of colored patches of various hues manipulated in saturation (Chroma value in the Munsell color system) on an achromatic background. The results indicate that the patches suppressed luminance driven brain activity. Furthermore, the suppression was stronger rather than weaker for patches with lower saturation colors, although suppression was absent when gray patches were presented instead of colored patches. We also measured brain activity while the subjects observed only the patches (on a uniformly black background) and confirmed that the colored patches alone did not give rise to differences in brain activity for different Chroma values. The chromatic information affects the luminance information in V1, since the effect was observed in early visual cortices (V2 and V3) and the ventral pathway (hV4), as well as in the dorsal pathway (V3A/B). In addition, we conducted a psychophysical experiment in which the ability to discriminate luminance contrast on a grating was measured. Discrimination was worse when weak (less saturated) colored patches were attached to the grating than when strong (saturated) colored patches or achromatic patches were attached. The results of both the fMRI and psychophysical experiments were consistent in that the effects of color were greater in the conditions with low saturation colors.

Monkey V1 epidural field potentials provide detailed information about stimulus location, size, shape, and color

Brain signal recordings with epidural microarrays constitute a low-invasive approach for recording distributed neuronal signals. Epidural field potentials (EFPs) may serve as a safe and highly beneficial signal source for a variety of research questions arising from both basic and applied neuroscience. A wider use of these signals, however, is constrained by a lack of data on their specific information content. Here, we make use of the high spatial resolution and the columnar organization of macaque primary visual cortex (V1) to investigate whether and to what extent EFP signals preserve information about various visual stimulus features. Two monkeys were presented with different feature combinations of location, size, shape, and color, yielding a total of 375 stimulus conditions. Visual features were chosen to access different spatial levels of functional organization. We found that, besides being highly specific for locational information, EFPs were significantly modulated by small differences in size, shape, and color, allowing for high stimulus classification rates even at the single-trial level. The results support the notion that EFPs constitute a low-invasive, highly beneficial signal source for longer-term recordings for medical and basic research by showing that they convey detailed and reliable information about constituent features of activating stimuli.

Chromatic micromaps in primary visual cortex

The clustering of neurons with similar response properties is a conspicuous feature of neocortex. In primary visual cortex (V1), maps of several properties like orientation preference are well described, but the functional architecture of color, central to visual perception in trichromatic primates, is not. Here we used two-photon calcium imaging in macaques to examine the fine structure of chromatic representation and found that neurons responsive to spatially uniform, chromatic stimuli form unambiguous clusters that coincide with blobs. Further, these responsive groups have marked substructure, segregating into smaller ensembles or micromaps with distinct chromatic signatures that appear columnar in upper layer 2/3. Spatially structured chromatic stimuli revealed maps built on the same micromap framework but with larger subdomains that go well beyond blobs. We conclude that V1 has an architecture for color representation that switches between blobs and a combined blob/interblob system based on the spatial content of the visual scene.

Stimulus feature maps are found in primary visual cortex of many species. Here the authors show color maps in trichromatic primates containing segregated ensembles of neurons with distinct chromatic signatures that associate with cortical modules known as blobs.

How Convolutional Neural Network Architecture Biases Learned Opponency and Color Tuning

Recent work suggests that changing convolutional neural network (CNN) architecture by introducing a bottleneck in the second layer can yield changes in learned function. To understand this relationship fully requires a way of quantitatively comparing trained networks. The fields of electrophysiology and psychophysics have developed a wealth of methods for characterizing visual systems that permit such comparisons. Inspired by these methods, we propose an approach to obtaining spatial and color tuning curves for convolutional neurons that can be used to classify cells in terms of their spatial and color opponency. We perform these classifications for a range of CNNs with different depths and bottleneck widths. Our key finding is that networks with a bottleneck show a strong functional organization: almost all cells in the bottleneck layer become both spatially and color opponent, and cells in the layer following the bottleneck become nonopponent. The color tuning data can further be used to form a rich understanding of how color a network encodes color. As a concrete demonstration, we show that shallower networks without a bottleneck learn a complex nonlinear color system, whereas deeper networks with tight bottlenecks learn a simple channel opponent code in the bottleneck layer. We develop a method of obtaining a hue sensitivity curve for a trained CNN that enables high-level insights that complement the low-level findings from the color tuning data. We go on to train a series of networks under different conditions to ascertain the robustness of the discussed results. Ultimately our methods and findings coalesce with prior art, strengthening our ability to interpret trained CNNs and furthering our understanding of the connection between architecture and learned representation. Trained models and code for all experiments are available at https://github.com/ecs-vlc/opponency.

Working Memory Alterations Plays an Essential Role in Developing Global Neuropsychological Impairment in Duchenne Muscular Dystrophy

Background

Neuropsychological profile of Indian Duchenne muscular dystrophy (DMD) subjects remains unidentified and needs to be evaluated.

Methods

A total of 69 DMD and 66 controls were subjected to detailed intelligence and neuropsychological assessment. The factor indexes were derived from various components of Malin's Intelligence Scale for Indian Children (MISIC) and Rey Auditory Verbal Learning Test (RAVLT).

Results

Poor verbal and visual memory profiles were demonstrated by DMDs, which include RAVLT-immediate recall (IR) (p = 0.042), RAVLT-delayed recall (DR) (p = 0.009), Rey-Osterrieth complex figure test (RCFT)-IR (p = 0.001), and RCFT-DR (p = 0.001). RAVLT-memory efficiency index demonstrated poor verbal memory efficiency (p = 0.008). Significant differences in the functioning of working memory axis [RAVLT T1 (p = 0.015), recency T1 (p = 0.004), Digit Span Backward (p = 0.103)] were observed along with reduced performance in visuomotor coordination, visuospatial, and visual recognition abilities. Block designing efficiency index and attention fraction showed a normal performance in DMD kids.

Conclusion

Working memory deficits were found to be the crucial element of cognitive functioning in DMD cases. Working memory interventions may be beneficial to improve the neuropsychological profile in DMD.

A distinct population of heterogeneously color-tuned neurons in macaque visual cortex

Color is a key feature of natural environments that higher mammals routinely use to detect food, avoid predators, and interpret social signals. The distribution of color signals in natural scenes is widely variable, ranging from uniform patches to highly nonuniform regions in which different colors lie in close proximity. Whether individual neurons are tuned to this high degree of variability of color signals is unknown. Here, we identified a distinct population of cells in macaque visual cortex (area V4) that have a heterogeneous receptive field (RF) structure in which individual subfields are tuned to different colors even though the full RF is only weakly tuned. This spatial heterogeneity in color tuning indicates a higher degree of complexity of color-encoding mechanisms in visual cortex than previously believed to efficiently extract chromatic information from the environment.

Spatial receptive field structure of double-opponent cells in macaque V1

The spatial processing of color is important for visual perception. Double-opponent (DO) cells likely contribute to this processing by virtue of their spatially opponent and cone-opponent receptive fields (RFs). However, the representation of visual features by DO cells in the primary visual cortex of primates is unclear because the spatial structure of their RFs has not been fully characterized. To fill this gap, we mapped the RFs of DO cells in awake macaques with colorful, dynamic white noise patterns. The spatial RF of each neuron was fitted with a Gabor function and three versions of the difference of Gaussians (DoG) function. The Gabor function provided the more accurate description for most DO cells, a result that is incompatible with a center-surround RF organization. A nonconcentric version of the DoG function, in which the RFs have a circular center and a crescent-shaped surround, performed nearly as well as the Gabor model thus reconciling results from previous reports. For comparison, we also measured the RFs of simple cells. We found that the superiority of the Gabor fits over DoG fits was slightly more decisive for simple cells than for DO cells. The implications of these results on biological image processing and visual perception are discussed.NEW & NOTEWORTHY Double-opponent cells in macaque area V1 respond to spatial chromatic contrast in visual scenes. What information they carry is debated because their receptive field organization has not been characterized thoroughly. Using white noise analysis and statistical model comparisons, De and Horwitz show that many double-opponent receptive fields can be captured by either a Gabor model or a center-with-an-asymmetric-surround model but not by a difference of Gaussians model.

The gamma response to colour hue in humans: Evidence from MEG

It has recently been demonstrated through invasive electrophysiology that visual stimulation with extended patches of uniform colour generates pronounced gamma oscillations in the visual cortex of both macaques and humans. In this study we sought to discover if this oscillatory response to colour can be measured non-invasively in humans using magnetoencephalography. We were able to demonstrate increased gamma (40–70 Hz) power in response to full-screen stimulation with four different colour hues and found that the gamma response is particularly strong for long wavelength (i.e. red) stimulation, as was found in previous studies. However, we also found that gamma power in response to colour was generally weaker than the response to an identically sized luminance-defined grating. We also observed two additional responses in the gamma frequency: a lower frequency response around 25–35 Hz that showed fewer clear differences between conditions than the gamma response, and a higher frequency response around 70–100 Hz that was present for red stimulation but not for other colours. In a second experiment we sought to test whether differences in the gamma response between colour hues could be explained by their chromatic separation from the preceding display. We presented stimuli that alternated between each of the three pairings of the three primary colours (red, green, blue) at two levels of chromatic separation defined in the CIELUV colour space. We observed that the gamma response was significantly greater to high relative to low chromatic separation, but that at each level of separation the response was greater for both red-blue and red-green than for blue-green stimulation. Our findings suggest that the stronger gamma response to red stimulation cannot be wholly explained by the chromatic separation of the stimuli.

Role of Feedback Connections in Central Visual Processing

The physiological response properties of neurons in the visual system are inherited mainly from feedforward inputs. Interestingly, feedback inputs often outnumber feedforward inputs. Although they are numerous, feedback connections are weaker, slower, and considered to be modulatory, in contrast to fast, high-efficacy feedforward connections. Accordingly, the functional role of feedback in visual processing has remained a fundamental mystery in vision science. At the core of this mystery are questions about whether feedback circuits regulate spatial receptive field properties versus temporal responses among target neurons, or whether feedback serves a more global role in arousal or attention. These proposed functions are not mutually exclusive, and there is compelling evidence to support multiple functional roles for feedback. In this review, the role of feedback in vision will be explored mainly from the perspective of corticothalamic feedback. Further generalized principles of feedback applicable to corticocortical connections will also be considered.

Hierarchical Representation for Chromatic Processing across Macaque V1, V2, and V4

The perception of color is an internal label for the inferred spectral reflectance of visible surfaces. To study how spectral representation is transformed through modular subsystems of successive cortical areas, we undertook simultaneous optical imaging of intrinsic signals in macaque V1, V2, and V4, supplemented by higher-resolution electrophysiology and two-photon imaging in awake macaques. We find a progressive evolution in the scale and precision of chromotopic maps, expressed by a uniform blob-like architecture of hue responses within each area. Two-photon imaging reveals enhanced hue-specific cell clustering in V2 compared with V1. A phenomenon of endspectral (red and blue) responses that is clear in V1, recedes in V2, and is virtually absent in V4. The increase in mid- and extra-spectral hue representations through V2 and V4 reflects the nature of hierarchical processing as higher areas read out locations in chromatic space from progressive integration of signals relayed by V1.

Computational cognitive modeling and validation of Dp140 induced alteration of working memory in Duchenne Muscular Dystrophy

Duchenne Muscular Dystrophy has emerged as a model to assess cognitive domains. The DMD gene variant location and its association with variable degrees of cognitive impairment necessitate identification of a common denominator. Computer architectures provide a framework to delineate the mechanisms involved in the cognitive functioning of the human brain. Copy number variations in the 79 exons of DMD gene were screened in 84 DMD subjects by Multiplex Ligation-dependent Probe Amplification (MLPA). DMD subjects were categorized based on the presence or absence of DP140 isoform. The cognitive and neuropsychological assessments were carried out as per inclusion criteria using standard scales. Instance-based learning theory (IBLT) based on the partial matching process was developed to mimic Stroop Color and Word Task (SCWT) performance on Adaptive Control of Thought-Rational (ACT-R) cognitive architecture based on IBLT. Genotype-phenotype correlation was conducted based on the mutation location in DMD gene. Assessment of specific cognitive domains in DP140 - ve group corresponded to the involvement of multiple brain lobes including temporal (verbal and visual learning and memory), parietal (visuo-conceptual and visuo-constructive abilities) and frontal (sustained and focused attention, verbal fluency, cognitive control). Working memory axis was found to be the central domain through tasks including RAVLT trial 1, recency effect, digit span backward, working memory index, arithmetic subtests in the Dp140 - ve group. IBLT validated the non-reliance of DMD subjects on recency indicating affected working memory domain. Modeling strategy revealed altered working memory processes in DMD cases with affected Dp140 isoform. DMD brain was observed to rely on primacy than the recency suggesting alterations in working memory capacity. Modeling revealed lowered activation of DMD brain with Dp140 - ve in order to retrieve the instances.

Enhanced luminance sensitivity on color and luminance pedestals: Threshold measurements and a model of parvocellular luminance processing

Psychophysical interactions between chromatic and achromatic stimuli may inform our understanding of the cortical processing of signals of parvocellular origin, which carry both luminance and color information. We measured observers' sensitivity in discriminating the luminance of circular patch stimuli with a range of baseline ("pedestal") luminance and chromaticity. Pedestal stimuli were defined along vectors in cone-contrast space in a plane spanned by the red-green cone-opponent (L-M) and achromatic (L + M + S) axes. For a range of pedestal directions and intensities within this plane, we measured thresholds for discriminating increments from decrements along the achromatic axis. Low-contrast pedestals lowered luminance thresholds for every pedestal type. Thresholds began to increase with higher pedestal contrasts, forming a "dipper"-shaped function. Dipper functions varied systematically with pedestal chromaticity: Compared to the achromatic case, chromatic pedestals were effective at lower contrast. We suggest that the enhancement of luminance sensitivity caused by both achromatic and chromatic pedestals stems from a single mechanism, which is maximally sensitive to chromatic stimuli. We fit our data with a computational model of such a mechanism, in which luminance is computed from the rectified output of cone-opponent mechanisms similar to parvocellular neurons.

Changes in Local Network Activity Approximated by Reverse Spike-Triggered Local Field Potentials Predict the Focus of Attention

The effects of visual spatial attention on neuronal firing rates have been well characterized for neurons throughout the visual processing hierarchy. Interestingly, the mechanisms by which attention generates more or fewer spikes in response to a visual stimulus remain unknown. One possibility is that attention boosts the likelihood that synaptic inputs to a neuron result in spikes. We performed a novel analysis to measure local field potentials (LFPs) just prior to spikes, or reverse spike-triggered LFP “wavelets,” for neurons recorded in primary visual cortex (V1) of monkeys performing a contrast change detection task requiring covert shifts in visual spatial attention. We used dimensionality reduction to define LFP wavelet shapes with single numerical values, and we found that LFP wavelet shape changes correlated with changes in neuronal firing rate. We then tested whether a simple classifier could predict monkeys’ focus of attention from LFP wavelet shape. LFP wavelet shapes sampled in discrete windows were predictive of the locus of attention for some neuronal types. These findings suggest that LFP wavelets are a useful proxy for local network activity influencing spike generation, and changes in LFP wavelet shape are predictive of the focus of attention.

Helix rotation: luminance contrast controls the shift from two-dimensional to three-dimensional perception

We present the helix rotation phenomenon, an array of moving dots that creates a conflict between two potential perceptions: a 3D Pulfrich-like horizontal rotation and a low-spatial-frequency up-down motion. We show that observers perceive up-down motion when the dots are equiluminant with the background and when the display is blurred; that the addition of sparse luminance information to equiluminant and blurred displays produces 3D perception; and that the balance between the perception of 3D rotation and up-down motion depends on the magnitude of the luminance contrast. The results are discussed in terms of the luminance capture of equiluminant information.

Color and orientation are jointly coded and spatially organized in primate primary visual cortex

Previous studies support the textbook model that shape and color are extracted by distinct neurons in primate primary visual cortex (V1). However, rigorous testing of this model requires sampling a larger stimulus space than previously possible. We used stable GCaMP6f expression and two-photon calcium imaging to probe a very large spatial and chromatic visual stimulus space and map functional microarchitecture of thousands of neurons with single-cell resolution. Notable proportions of V1 neurons strongly preferred equiluminant color over achromatic stimuli and were also orientation selective, indicating that orientation and color in V1 are mutually processed by overlapping circuits. Single neurons could precisely and unambiguously code for both color and orientation. Further analyses revealed systematic spatial relationships between color tuning, orientation selectivity, and cytochrome oxidase histology.

A Critique of Olfactory Objects

Does the sense of smell involve the perception of odor objects? General discussion of perceptual objecthood centers on three criteria: stimulus representation, perceptual constancy, and figure-ground segregation. These criteria, derived from theories of vision, have been applied to olfaction in recent philosophical debates about psychology. An inherent problem with such framing of olfactory objecthood is that philosophers explicitly ignore the constitutive factors of the sensory systems that underpin the implementation of these criteria. The biological basis of odor coding is fundamentally different from the coding principles of the visual system. This article analyzes the three measures of perceptual objecthood against the biological background of the olfactory system. It contrasts the coding principles in olfaction with the visual system to show why these criteria of objecthood fail to be instantiated in odor perception. The argument demonstrates that olfaction affords perceptual categorization without the need to form odor objects.

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.

A Compound Computational Model for Filling-In Processes Triggered by Edges: Watercolor Illusions

The goal of our research was to develop a compound computational model with the ability to predict different variations of the “watercolor effects” and additional filling-in effects that are triggered by edges. The model is based on a filling-in mechanism solved by a Poisson equation, which considers the different gradients as “heat sources” after the gradients modification. The biased (modified) contours (edges) are ranked and determined according to their dominancy across the different chromatic and achromatic channels. The color and intensity of the perceived surface are calculated through a diffusive filling-in process of color triggered by the enhanced and biased edges of stimulus formed as a result of oriented double-opponent receptive fields. The model can successfully predict both the assimilative and non-assimilative watercolor effects, as well as a number of “conflicting” visual effects. Furthermore, the model can also predict the classic Craik–O'Brien–Cornsweet (COC) effect. In summary, our proposed computational model is able to predict most of the “conflicting” filling-in effects that derive from edges that have been recently described in the literature, and thus supports the theory that a shared visual mechanism is responsible for the vast variety of the “conflicting” filling-in effects that derive from edges.

Neural Coding for Shape and Texture in Macaque Area V4

The distinct visual sensations of shape and texture have been studied separately in cortex; therefore, it remains unknown whether separate neuronal populations encode each of these properties or one population carries a joint encoding. We directly compared shape and texture selectivity of individual V4 neurons in awake macaques (1 male, 1 female) and found that V4 neurons lie along a continuum from strong tuning for boundary curvature of shapes to strong tuning for perceptual dimensions of texture. Among neurons tuned to both attributes, tuning for shape and texture were largely separable, with the latter delayed by ∼30 ms. We also found that shape stimuli typically evoked stronger, more selective responses than did texture patches, regardless of whether the latter were contained within or extended beyond the receptive field. These results suggest that there are separate specializations in mid-level cortical processing for visual attributes of shape and texture.SIGNIFICANCE STATEMENT Object recognition depends on our ability to see both the shape of the boundaries of objects and properties of their surfaces. However, neuroscientists have never before examined how shape and texture are linked together in mid-level visual cortex. In this study, we used systematically designed sets of simple shapes and texture patches to probe the responses of individual neurons in the primate visual cortex. Our results provide the first evidence that some cortical neurons specialize in processing shape whereas others specialize in processing textures. Most neurons lie between the ends of this continuum, and in these neurons we find that shape and texture encoding are largely independent.

A Neuronal Network Model of the Primate Visual System: Color Mechanisms in the Retina, LGN and V1

Color plays a key role in human vision but the neural machinery that underlies the transformation from stimulus to perception is not well understood. Here, we implemented a two-dimensional network model of the first stages in the primate parvocellular pathway (retina, lateral geniculate nucleus and layer 4C[Formula: see text] in V1) consisting of conductance-based point neurons. Model parameters were tuned based on physiological and anatomical data from the primate foveal and parafoveal vision, the most relevant visual field areas for color vision. We exhaustively benchmarked the model against well-established chromatic and achromatic visual stimuli, showing spatial and temporal responses of the model to disk- and ring-shaped light flashes, spatially uniform squares and sine-wave gratings of varying spatial frequency. The spatiotemporal patterns of parvocellular cells and cortical cells are consistent with their classification into chromatically single-opponent and double-opponent groups, and nonopponent cells selective for luminance stimuli. The model was implemented in the widely used neural simulation tool NEST and released as open source software. The aim of our modeling is to provide a biologically realistic framework within which a broad range of neuronal interactions can be examined at several different levels, with a focus on understanding how color information is processed.

Visual evoked cortical potential elicited by pseudoisochromatic stimulus

PURPOSE

Visual evoked cortical potentials (VECPs) are useful for investigating the mechanisms and dysfunctions of color vision. Chromatic sinusoidal gratings are generally used to elicit VECPs, but they require long psychophysical measurements to match the perceptual luminance between their stripes. An alternative method is to use pseudoisochromatic stimuli, which makes use of luminance noise to mask luminance clues and force the target perception to be dependent on chromatic contrast. In this study, we compared VECPs generated by sinusoidal gratings and pseudoisochromatic gratings. Contrary to chromatic sinusoidal gratings, pseudoisochromatic stimuli do not require the use of previous methods to find the equiluminance of the stimulus.

METHODS

Normal trichromats were recruited to be tested with red-green chromatic sinusoidal gratings and pseudoisochromatic gratings presented by pattern onset-offset and pattern reversal modes in five spatial frequencies. In addition, we also tested four different chromatic contrast pairs in pattern onset-offset mode presentation in five trichromats and one colorblind subject (deuteranope).

RESULTS

Pattern onset-offset VECPs elicited by sinusoidal gratings had a larger amplitude than those obtained with pseudoisochromatic stimuli, whereas pattern reversal VECPs elicited by pseudoisochromatic gratings had similar amplitudes compared to those elicited by sinusoidal gratings. We found no difference between the VECP amplitudes elicited by sinusoidal and pseudoisochromatic gratings containing different chromatic contrast. Color-blind subjects displayed absent or small responses to the stimuli.

CONCLUSION

Pseudoisochromatic stimulus can be an alternative stimulus to generate VECPs dominated by the chromatic mechanism.

Color induction in equiluminant flashed stimuli

Color induction is the influence of the surrounding color (inducer) on the perceived color of a central region. There are two different types of color induction: color contrast (the color of the central region shifts away from that of the inducer) and color assimilation (the color shifts towards the color of the inducer). Several studies on these effects have used uniform and striped surrounds, reporting color contrast and color assimilation, respectively. Other authors [J. Vis.12(1), 22 (2012)1534-736210.1167/12.12.1] have studied color induction using flashed uniform surrounds, reporting that the contrast is higher for shorter flash duration. Extending their study, we present new psychophysical results using both flashed and static (i.e., non-flashed) equiluminant stimuli for both striped and uniform surrounds. Similarly to them, for uniform surround stimuli we observed color contrast, but we did not obtain the maximum contrast for the shortest (10 ms) flashed stimuli, but for 40 ms. We only observed this maximum contrast for red, green, and lime inducers, while for a purple inducer we obtained an asymptotic profile along the flash duration. For striped stimuli, we observed color assimilation only for the static (infinite flash duration) red-green surround inducers (red first inducer, green second inducer). For the other inducers' configurations, we observed color contrast or no induction. Since other studies showed that non-equiluminant striped static stimuli induce color assimilation, our results also suggest that luminance differences could be a key factor to induce it.

The Attentional Suppressive Surround: Eccentricity, Location-Based and Feature-Based Effects and Interactions

The Selective Tuning model of visual attention (Tsotsos, 1990) has proposed that the focus of attention is surrounded by an inhibitory zone, eliciting a center-surround attentional distribution. This attentional suppressive surround inhibits irrelevant information which is located close to attended information in physical space (e.g., Cutzu and Tsotsos, 2003; Hopf et al., 2010) or in feature space (e.g., Tombu and Tsotsos, 2008; Störmer and Alvarez, 2014; Bartsch et al., 2017). In Experiment 1, we investigate the interaction between location-based and feature-based surround suppression and hypothesize that the attentional surround suppression would be maximized when spatially adjacent stimuli are also represented closely within a feature map. Our results demonstrate that perceptual discrimination is worst when two similar orientations are presented in proximity to each other, suggesting the interplay of the two surround suppression mechanisms. The Selective Tuning model also predicts that the size of the attentional suppressive surround is determined by the receptive field size of the neuron which optimally processes the attended information. The receptive field size of the processing neurons is tightly associated with stimulus size and eccentricity. Therefore, Experiment 2 tested the hypothesis that the size of the attentional suppressive surround would become larger as stimulus size and eccentricity increase, corresponding to an increase in the neuron's receptive field size. We show that stimulus eccentricity but not stimulus size modulates the size of the attentional suppressive surround. These results are consistent for both low- and high-level features (e.g., orientation and human faces). Overall, the present study supports the existence of the attentional suppressive surround and reveals new properties of this selection mechanism.

The effect of luminance differences on color assimilation

The color appearance of a surface depends on the color of its surroundings (inducers). When the perceived color shifts towards that of the surroundings, the effect is called "color assimilation" and when it shifts away from the surroundings it is called "color contrast." There is also evidence that the phenomenon depends on the spatial configuration of the inducer, e.g., uniform surrounds tend to induce color contrast and striped surrounds tend to induce color assimilation. However, previous work found that striped surrounds under certain conditions do not induce color assimilation but induce color contrast (or do not induce anything at all), suggesting that luminance differences and high spatial frequencies could be key factors in color assimilation. Here we present a new psychophysical study of color assimilation where we assessed the contribution of luminance differences (between the target and its surround) present in striped stimuli. Our results show that luminance differences are key factors in color assimilation for stimuli varying along the s axis of MacLeod-Boynton color space, but not for stimuli varying along the l axis. This asymmetry suggests that koniocellular neural mechanisms responsible for color assimilation only contribute when there is a luminance difference, supporting the idea that mutual-inhibition has a major role in color induction.