Perception of brightness and brightness illusions in the macaque monkey

How to reward animals based on their subjective percepts: A Bayesian approach to online estimation of perceptual biases

Elucidating the neural basis of perceptual biases, such as those produced by visual illusions, can provide powerful insights into the neural mechanisms of perceptual inference. However, studying the subjective percepts of animals poses a fundamental challenge: unlike human participants, animals cannot be verbally instructed to report what they see, hear, or feel. Instead, they must be trained to perform a task for reward, and researchers must infer from their responses what the animal perceived. However, animals' responses are shaped by reward feedback, thus raising the major concern that the reward regimen may alter the animal's decision strategy or even intrinsic perceptual biases. We developed a method that estimates perceptual bias during task performance and then computes the reward for each trial based on the evolving estimate of the animal's perceptual bias. Our approach makes use of multiple stimulus contexts to dissociate perceptual biases from decision-related biases. Starting with an informative prior, our Bayesian method updates a posterior over the perceptual bias after each trial. The prior can be specified based on data from past sessions, thus reducing the variability of the online estimates and allowing it to converge to a stable estimate over a small number of trials. After validating our method on synthetic data, we apply it to estimate perceptual biases of monkeys in a motion direction discrimination task in which varying background optic flow induces robust perceptual biases. This method overcomes an important challenge to understanding the neural basis of subjective percepts.

Illusory light drives pupil responses in primates

In humans, the eye pupils respond to both physical light sensed by the retina and mental representations of light produced by the brain. Notably, our pupils constrict when a visual stimulus is illusorily perceived brighter, even if retinal illumination is constant. However, it remains unclear whether such perceptual penetrability of pupil responses is an epiphenomenon unique to humans or whether it represents an adaptive mechanism shared with other animals to anticipate variations in retinal illumination between successive eye fixations. To address this issue, we measured the pupil responses of both humans and macaque monkeys exposed to three chromatic versions (cyan, magenta, and yellow) of the Asahi brightness illusion. We found that the stimuli illusorily perceived brighter or darker trigger differential pupil responses that are very similar in macaques and human participants. Additionally, we show that this phenomenon exhibits an analogous cyan bias in both primate species. Beyond evincing the macaque monkey as a relevant model to study the perceptual penetrability of pupil responses, our results suggest that this phenomenon is tuned to ecological conditions because the exposure to a "bright cyan-bluish sky" may be associated with increased risks of dazzle and retinal damages.

Neural encoding of multiple motion speeds in visual cortical area MT

Segmenting objects from each other and their background is critical for vision. The speed at which objects move provides a salient cue for segmentation. However, how the visual system represents and differentiates multiple speeds is largely unknown. Here we investigated the neural encoding of multiple speeds of overlapping stimuli in the primate visual cortex. We first characterized the perceptual capacity of human and monkey subjects to segment spatially overlapping stimuli moving at different speeds. We then determined how neurons in the motion-sensitive, middle-temporal (MT) cortex of macaque monkeys encode multiple speeds. We made a novel finding that the responses of MT neurons to two speeds of overlapping stimuli showed a robust bias toward the faster speed component when both speeds were slow (≤ 20°/s). The faster-speed bias occurred even when a neuron had a slow preferred speed and responded more strongly to the slower component than the faster component when presented alone. The faster-speed bias emerged very early in neuronal response and was robust over time and to manipulations of motion direction and attention. As the stimulus speed increased, the faster-speed bias changed to response averaging. Our finding can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons elicited by the individual speeds. Our results suggest that the neuron population, referred to as the weighting pool, includes neurons that have a broad range of speed preferences. As a result, the response weights for the speed components are determined by the stimulus speeds and invariant to the speed preferences of individual neurons. Our findings help to define the neural encoding rule of multiple stimuli and provide new insight into the underlying neural mechanisms. The faster-speed bias would benefit behavioral tasks such as figure-ground segregation if figural objects tend to move faster than the background in the natural environment.

Gamma oscillations in primate primary visual cortex are severely attenuated by small stimulus discontinuities

Gamma oscillations (30 to 80 Hz) have been hypothesized to play an important role in feature binding, based on the observation that continuous long bars induce stronger gamma in the visual cortex than bars with a small gap. Recently, many studies have shown that natural images, which have discontinuities in several low-level features, do not induce strong gamma oscillations, questioning their role in feature binding. However, the effect of different discontinuities on gamma has not been well studied. To address this, we recorded spikes and local field potential from 2 monkeys while they were shown gratings with discontinuities in 4 attributes: space, orientation, phase, or contrast. We found that while these discontinuities only had a modest effect on spiking activity, gamma power drastically reduced in all cases, suggesting that gamma could be a resonant phenomenon. An excitatory–inhibitory population model with stimulus-tuned recurrent inputs showed such resonant properties. Therefore, gamma could be a signature of excitation–inhibition balance, which gets disrupted due to discontinuities.

Gamma oscillations (30-80 Hz) in visual cortex have been hypothesized to play an important role in feature binding, but this role has recently been questioned. This study shows that visual stimulus-induced gamma oscillations are highly attenuated with even small discontinuities in the stimulus. This "resonant" behaviour can be explained by a simple excitatory-inhibitory model in which discontinuities lead to a small reduction in lateral inputs.

Children and monkeys overestimate the size of high-contrast stimuli

The letter height superiority effect reveals that human adults judge letters to be taller than identically sized pseudoletters. This effect extends to words, such that words are estimated to be greater in size or lasting longer in duration than pseudowords of the same size or those presented for the same duration. The physical properties of letters and words also impact their perceived size, such that higher contrast between figure-ground stimuli leads to greater size estimates. Specifically, black letters on a white background (high contrast between figure and ground) are judged to be taller than gray letters and gray pseudoletters on a white background (low contrast between figure and ground) for adult humans. In the current study, we assessed whether this effect would extend to nonverbal stimuli (shapes) such that high-contrast shapes would lead to greater size estimates relative to low-contrast shapes for human children and rhesus monkeys in a two-choice discrimination task. We found that children and monkeys tended to overestimate the size of high-contrast shapes relative to low-contrast shapes consistent with results reported among human adults. Implications for perceptual fluency and its impact on subjective size estimates are discussed.

Everything is subjective under water surface, too: visual illusions in fish

The study of visual illusions has captured the attention of comparative psychologists since the last century, given the unquestionable advantage of investigating complex perceptual mechanisms with relatively simple visual patterns. To date, the observation of animal behavior in the presence of visual illusions has been largely confined to mammal and bird studies. Recently, there has been increasing interest in investigating fish, too. The attention has been particularly focused on guppies, redtail splitfin and bamboo sharks. Overall, the tested species were shown to experience a human-like perception of different illusory phenomena involving size, number, motion, brightness estimation and illusory contours. However, in some cases, no illusory effects, or evidence for a reverse illusion, were also reported. Here, we review the current state of the art in this field. We conclude that a wider investigation of visual illusions in fish is fundamental to form a broader comprehension of perceptual systems of vertebrates. Furthermore, we believe that this type of investigation could help us to address general important issues in perceptual studies, such as the role of ecology in shaping perceptual systems, the existence of interindividual variability in the visual perception of nonhuman species and the role of cortical activity in the emergence of visual illusions.

Neuronal population mechanisms of lightness perception

The way that humans and animals perceive the lightness of an object depends on its physical luminance as well as its surrounding context. While neuronal responses throughout the visual pathway are modulated by context, the relationship between neuronal responses and lightness perception is poorly understood. We searched for a neuronal mechanism of lightness by recording responses of neuronal populations in monkey primary visual cortex (V1) and area V4 to stimuli that produce a lightness illusion in humans, in which the lightness of a disk depends on the context in which it is embedded. We found that the way individual units encode the luminance (or equivalently for our stimuli, contrast) of the disk and its context is extremely heterogeneous. This motivated us to ask whether the population representation in either V1 or V4 satisfies three criteria: 1) disk luminance is represented with high fidelity, 2) the context surrounding the disk is also represented, and 3) the representations of disk luminance and context interact to create a representation of lightness that depends on these factors in a manner consistent with human psychophysical judgments of disk lightness. We found that populations of units in both V1 and V4 fulfill the first two criteria but that we cannot conclude that the two types of information in either area interact in a manner that clearly predicts human psychophysical measurements: the interpretation of our population measurements depends on how subsequent areas read out lightness from the population responses. NEW & NOTEWORTHY A core question in visual neuroscience is how the brain extracts stable representations of object properties from the retinal image. We searched for a neuronal mechanism of lightness perception by determining whether the responses of neuronal populations in primary visual cortex and area V4 could account for a lightness illusion measured using human psychophysics. Our results suggest that comparing psychophysics with population recordings will yield insight into neuronal mechanisms underlying a variety of perceptual phenomena.

Do rhesus monkeys (Macaca mulatta) perceive the Zöllner illusion?

A long-standing debate surrounds the issue of whether human and nonhuman animals share the same perceptual mechanisms. In humans, the Zöllner illusion occurs when two parallel lines appear to be convergent when oblique crosshatching lines are superimposed. Although one baboon study suggests that they too might perceive this illusion, the results of that study were unclear, whereas two recent studies suggest that birds see this illusion in the opposite direction from humans. It is currently unclear whether these mixed results are an artifact of the experimental design or reflect a peculiarity of birds' visual system or, instead, a wider phenomenon shared among nonhuman mammals. Here, we trained 6 monkeys to select the narrower of two gaps at the end of two convergent lines. Three different conditions were set up: control (no crosshatches), perpendicular (crosshatches not inducing the illusion), and Zöllner (crosshatches inducing the illusion in humans). During training, the degrees of convergence between the two lines ranged from 15° to 12°. Monkeys that reached the training criterion were tested with more difficult discriminations (11°-1°), including probe trials with parallel lines (0°). The results showed that monkeys perceived the Zöllner illusion in the same direction as humans. Comparison of these data with the data from bird studies points toward the existence of different orientation-tuned mechanisms between primate and nonprimate species.

Brightness discrimination in the day- and night-adapted wandering spider Cupiennius salei

Cupiennius salei is a nocturnal spider with eight eyes, which undergo a remarkable circadian cycle: the rhabdomeric membrane of the photoreceptor cells is dismantled during the day and rebuilt at the beginning of the night. Such drastic changes might influence the brightness discrimination ability. We tested this hypothesis by presenting square-shaped flickering stimuli with certain luminances on stationary backgrounds with other luminances to spiders with day- or night-adapted eyes. When the spider, through its three pairs of so-called secondary eyes, perceives a visible contrast between the stimulus and the background, its principal eye muscle activity should increase. We therefore recorded this activity in vivo to assess the brightness discrimination ability of Cupiennius salei. Our results show that this spider has good brightness discrimination ability, which is significantly better with dark-adapted eyes. A Michelson contrast of 0.1 to 0.2 at night, and of 0.2 to 0.3 for day-adapted eyes, is sufficient to elicit a significant response, except below a critical value of luminance (~16 cd m(-2)), where the minimal perceivable contrast needs to be higher. In the Discussion we compare these performances with those of other animals, in particular with jumping spiders.

Macaque monkeys perceive the flash lag illusion

Transmission of neural signals in the brain takes time due to the slow biological mechanisms that mediate it. During such delays, the position of moving objects can change substantially. The brain could use statistical regularities in the natural world to compensate neural delays and represent moving stimuli closer to real time. This possibility has been explored in the context of the flash lag illusion, where a briefly flashed stimulus in alignment with a moving one appears to lag behind the moving stimulus. Despite numerous psychophysical studies, the neural mechanisms underlying the flash lag illusion remain poorly understood, partly because it has never been studied electrophysiologically in behaving animals. Macaques are a prime model for such studies, but it is unknown if they perceive the illusion. By training monkeys to report their percepts unbiased by reward, we show that they indeed perceive the illusion qualitatively similar to humans. Importantly, the magnitude of the illusion is smaller in monkeys than in humans, but it increases linearly with the speed of the moving stimulus in both species. These results provide further evidence for the similarity of sensory information processing in macaques and humans and pave the way for detailed neurophysiological investigations of the flash lag illusion in behaving macaques.

Bright illusions reduce the eye's pupil

We recorded by use of an infrared eye-tracker the pupil diameters of participants while they observed visual illusions of lightness or brightness. Four original illusions {based on Gaetano Kanisza's [Kanizsa G (1976) Subjective contours. Sci Am 234:48-52] and Akiyoshi Kitaoka's [Kitaoka A. (2005) Trick Eyes (Barnes & Noble, New Providence, NJ).] examples} were manipulated to obtain control conditions in which the perceived illusory luminance was either eliminated or reduced. All stimuli were equiluminant so that constrictions in pupillary size could not be ascribed to changes in light energy. We found that the pupillary diameter rapidly varied according to perceived brightness and lightness strength. Differences in local contrast information could be ruled out as an explanation because, in a second experiment, the observers maintained eye fixation in the center of the display; thus, differential stimulation of the fovea by local contrast changes could not be responsible for the pupillary differences. Hence, the most parsimonious explanation for the present findings is that pupillary responses to ambient light reflect the perceived brightness or lightness of the scene and not simply the amount of physical light energy entering the eye. Thus, the pupillary physiological response reflects the subjective perception of light and supports the idea that the brain's visual circuitry is shaped by visual experience with images and their possible sources.

V1 response timing and surface filling-in

There is ample evidence from demonstrations such as color induction and stabilized images that information from surface boundaries plays a special role in determining the perception of surface interiors. Surface interiors appear to "fill-in." Psychophysical experiments also show that surface perception involves a slow scale-dependent process distinct from mechanisms involved in contour perception. The present experiments aimed to test the hypothesis that surface perception is associated with relatively slow scale-dependent neural filling-in. We found that responses in macaque primary visual cortex (V1) are slower to surface interiors than responses to optimal bar stimuli. Moreover, we found that the response to a surface interior is delayed relative to the response to the surface's border and the extent of the delay is proportional to the distance between a receptive field and the border. These findings are consistent with some forms of neural filling-in and suggest that V1 may provide the neural substrate for perceptual filling-in.

Brightness Induction: Rate Enhancement and Neuronal Synchronization as Complementary Codes

In cat visual cortex, we investigated with parallel recordings from multiple units the neuronal correlates of perceived brightness. The perceived brightness of a center grating was changed by varying the orientation or the relative spatial phase of a surrounding grating. Brightness enhancement by orientation contrast is associated with an increase of discharge rates of responses to the center grating but not with changes in spike synchronization. In contrast, if brightness enhancement is induced by phase offset, discharge rates are unchanged but synchronization increases between neurons responding to the center grating. The changes in synchronization correlate well with changes in perceived brightness that were assessed in parallel in human subjects using the same stimuli. These results indicate that in cerebral cortex the modulation of synchronicity of responses is used as a mechanism complementary to rate changes to enhance the saliency of neuronal responses.

V2 thin stripes contain spatially organized representations of achromatic luminance change

A considerable amount of research over the last decades has focused on the apparent specialization of V2 thin stripes for the processing of color in diurnal primates. However, because V2 thin stripes are functionally heterogeneous in that they consist of largely separate color- and luminance-preferring domains and because the color-preferring domains contain a systematic representation of hue, we hypothesized that they contained functional maps that subserve luminance processing. Here we show, using optical imaging of intrinsic cortical signals and microelectrode recording, that the V2 thin stripe luminance-preferring domains contain spatially segregated modules that encode the direction of relative luminance change. Quantitative analysis of the cortical responses to luminance increments or decrements indicates that these luminance-sensitive modules also encode the magnitude of the luminance change by the magnitude of the evoked cortical response. These results demonstrate an important role of V2 thin stripes in the processing of luminance and thus suggest that thin stripes are involved in the overall processing of the surface properties of objects rather than simply the processing of color.

Do cortical neurons process luminance or contrast to encode surface properties?

On the one hand, contrast signals provide information about surface properties, such as reflectance, and patchy illumination conditions, such as shadows. On the other hand, processing of luminance signals may provide information about global light levels, such as the difference between sunny and cloudy days. We devised models of contrast and luminance processing, using principles of logarithmic signal coding and half-wave rectification. We fit each model to individual response profiles obtained from 67 surface-responsive macaque V1 neurons in a center-surround paradigm similar to those used in human psychophysical studies. The most general forms of the luminance and contrast models explained, on average, 73 and 87% of the response variance over the sample population, respectively. We used a statistical technique, known as Akaike's information criterion, to quantify goodness of fit relative to number of model parameters, giving the relative probability of each model being correct. Luminance models, having fewer parameters than contrast models, performed substantially better in the vast majority of neurons, whereas contrast models performed similarly well in only a small minority of neurons. These results suggest that the processing of local and mean scene luminance predominates over contrast integration in surface-responsive neurons of the primary visual cortex. The sluggish dynamics of luminance-related cortical activity may provide a neural basis for the recent psychophysical demonstration that luminance information dominates brightness perception at low temporal frequencies.

Functional magnetic resonance imaging of brightness induction in the human visual cortex

A grey surface on a bright background appears to be darker than the same surface on a dark background. We used functional magnetic resonance imaging to study this phenomenon called brightness induction. While being scanned, participants viewed centre-surround displays in which either centre or surround luminance was modulated in time. In both cases, participants perceive similar brightness changes in the central surface. In the region of the visual cortex encoding this central surface, both modulations evoked comparable functional magnetic resonance imaging responses. However, the surround modulation signal showed a considerable delay relative to the onset of the brightness percept. This suggests that, although correlated, the functional magnetic resonance imaging signals do not bear a direct relationship with perceived brightness. We conclude that retinotopically organized visual cortex does not represent brightness per se.

Cortical processing of a brightness illusion

Several brightness illusions indicate that borders can affect the perception of surfaces dramatically. In the Cornsweet illusion, two equiluminant surfaces appear to be different in brightness because of the contrast border between them. Here, we report the existence of cells in monkey visual cortex that respond to such an "illusory" brightness. We find that luminance responsive cells are located in color-activated regions (cytochrome oxidase blobs and bridges) of primary visual cortex (V1), whereas Cornsweet responsive cells are found preferentially in the color-activated regions (thin stripes) of second visual area (V2). This colocalization of brightness and color processing within V1 and V2 suggests a segregation of contour and surface processing in early visual pathways and a hierarchy of brightness information processing from V1 to V2 in monkeys.