Brightening prospects for early cortical coding of perceived luminance: a high-density electrical mapping study

Behavioural and electrophysiological correlates of lightness contrast and assimilation

Lightness contrast and assimilation are opposite phenomena: in contrast grey targets appear darker when bordering bright rather than dark surfaces; in assimilation grey targets appear lighter when bordering bright rather than dark surfaces. The underlying neurophysiological mechanisms of these phenomena are not known. The aim of this study was to investigate the relationship between contrast and assimilation, and the timing and levels of perceptual and cognitive processing using combined behavioural and electrophysiological methods. Thirty undergraduate students (23 female, age range 18–48 years) participated in a forced-choice (grey target is lighter/darker than a comparison square) task, using stimuli designed such that the inducers were in two configurations (small and large) and two shades (white and black). The behavioural data (more consistent and faster responses) corroborated previous findings of stronger contrast effects with white inducers and stronger assimilation effects with black inducers. According to the Event-Related Potentials (ERP) results the mean amplitude was larger in conditions with less consistent and slower behavioural responses. Thus, with contrast responses P1 amplitude was larger with black than white inducers, and N1 amplitude was larger to assimilation than contrast when the configuration of the stimulus was held constant. These results suggest contrast may occur as early as P1 (~ 110 ms) and assimilation may occur later in N2 (~ 220 ms), whereas in some conditions, differences in ERPs associated with contrast vs assimilation may happen as early as in N1 (~ 170 m), in occipital and parietal cortical sites.

Cortical configuration by stimulus onset visual evoked potentials (SO-VEPs) predicts performance on a motion direction discrimination task

The slowing of information processing, a hallmark of cognitive aging, has several origins. Previously we reported that in a motion direction discrimination task, older as compared to younger participants showed prolonged non-decision time, an index of an early perceptual stage, while in motion onset visual evoked potentials (MO-VEPs) the P1 component was enhanced and N2 was diminished. We did not find any significant correlations between behavioral and MO-VEP measures. Here, we investigated the role of age in encoding and perceptual processing of stimulus onset visually evoked potentials (SO-VEPs). Twelve healthy adults (age<55years) and 19 elderly (age>55years) performed a motion direction discrimination task during EEG recording. Prior to motion, the stimulus consisted of a static cloud of white dots on a black background. As expected, SO-VEPs evoked well defined P1, N1, and P2 components. Elderly participants as compared to young participants showed increased P1 amplitude while their P2 amplitude was reduced. In addition elderly participants showed increased latencies for P1 and N1 components. Contrary to the findings with MO-VEPs, SO-VEP parameters were significant predictors of average response times and diffusion model parameters. Our electrophysiological results support the notion that slowing of information processing in older adults starts at the very beginning of encoding in visual cortical processing, most likely in striate and extrastriate visual cortices. More importantly, the earliest SO-VEP components, possibly reflecting configuration of visual cortices and encoding processes, predict subsequent prolonging and tardiness of perceptual and higher-level cognitive processes.

Orientation enhancement in early visual processing can explain time course of brightness contrast and White's illusion

Dynamics of orientation tuning in V1 indicates that computational model of V1 should not only comprise of bank of static spatially oriented filters but also include the contribution for dynamical response facilitation or suppression along orientation. Time evolution of orientation response in V1 can emerge due to time- dependent excitation and lateral inhibition in the orientation domain. Lateral inhibition in the orientation domain suggests that Ernst Mach's proposition can be applied for the enhancement of initial orientation distribution that is generated due to interaction of visual stimulus with spatially oriented filters and subcortical temporal filter. Oriented spatial filtering that appears much early (<70 ms) in the sequence of visual information processing can account for many of the brightness illusions observed at steady state. It is therefore expected that time evolution of orientation response might be reflecting in the brightness percept over time. Our numerical study suggests that only spatio-temporal filtering at early phase can explain experimentally observed temporal dynamics of brightness contrast illusion. But, enhancement of orientation response at early phase of visual processing is the key mechanism that can guide visual system to predict the brightness by "Max-rule" or "Winner Takes All" (WTA) estimation and thus producing White's illusions at any exposure.

A neurodynamical model of brightness induction in v1

Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway.

Do all threats work the same way? Divergent effects of fear and disgust on sensory perception and attention

The extant literature indicates that threat enhances cognitive processing and physiological arousal. However, being largely based on fear-relevant processes, this model overlooks other adaptive but inhibitory mechanisms in alternative threat emotions such as disgust. Combining visual event-related potential (VERP) indices (P1 and P250/s) with a simple visual search task, we contrasted behavioral and neural responses to carefully controlled images of fear, disgust, or neutral emotion (as a baseline condition). Consistent with previous findings, fear augmented VERP amplitude and electrical current density in associate visual cortices, paralleled by facilitated object search. Conversely, disgust generated an opposite pattern of effects, reflected by reduced VERP potentials and diminished visual cortical current density along with slowed search time. These results demonstrated suppressed sensory perceptual and attentional processing of disgust information, akin to the central ecological function of disgust to minimize contact with contagious objects to avoid contamination and disease. Notably, the rapid emergence of discrimination between fear and disgust as early as 96 ms after stimulus emphasizes the efficiency of emotional classification not only between threat and nonthreat, but also within the threat domain itself. Finally, a positive correlation between anxiety and behavioral and neural divergence of fear and disgust further indicates that despite their convergence on the core affect of threat, disgust and fear instigate distinct response profiles, providing novel insights into the manifold and sometimes paradoxical symptomology in anxiety disorders.

Generating controlled image sets in cognitive neuroscience research

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

Responses to lightness variations in early human visual cortex

Lightness is the apparent reflectance of a surface, and it depends not only on the actual luminance of the surface but also on the context in which the surface is viewed [1-10]. The cortical mechanisms of lightness processing are largely unknown, and the role of early cortical areas is still a matter of debate [11-17]. We studied the cortical responses to lightness variations in early stages of the human visual system with functional magnetic resonance imaging (fMRI) while observers were performing a demanding fixation task. The set of dynamically presented visual stimuli included the rectangular version of the classic Craik-O'Brien stimulus [3, 18, 19] and a variant that led to a weaker lightness effect, as well as a pattern with actual luminance variations. We found that the cortical activity in retinotopic areas, including the primary visual cortex (V1), is correlated with context-dependent lightness variations.

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.

Oriented multiscale spatial filtering and contrast normalization: a parsimonious model of brightness induction in a continuum of stimuli including White, Howe and simultaneous brightness contrast

The White effect [Perception 8 (1979) 413] cannot be simply explained as due to either brightness contrast or brightness assimilation because the direction of the induced brightness change does not correlate with the amount of black or white border in contact with the gray test patch. This has led some investigators to abandon spatial filtering explanations not only for the White effect but for brightness perception in general. Offered instead are explanations based on a variety of junction analyses and/or perceptual organization schemes which in the case of the White effect are usually based on T-junctions. Recently, Howe [Perception 30 (2001) 1023] challenged T-junction based explanations with a novel variation of White's effect in which the T-junctions were constant while the brightness effect was eliminated or reversed, and proposed an alternative explanation in terms of illusory contours. The present study argues that an analysis at the level of illusory contours is not necessary and that a much simpler spatial filtering based explanation is sufficient. Brightness induction was measured in a set of stimuli chosen to illustrate the relationship between the Howe stimulus [Perception 30 (2001) 1023], the White stimulus [Perception 8 (1979) 413] and the classical simultaneous brightness contrast (SBC) stimulus. The White stimulus and the SBC stimulus occupy opposite ends of a continuum of stimuli in which the Howe stimulus is the mid-point. The psychophysical measurements were compared with the predictions of the oriented difference-of-Gaussians (ODOG) computational model of Blakeslee and McCourt [Vision Research 39 (1999) 4361]. The ODOG model parsimoniously accounted for both the direction and relative magnitude of the brightness effects suggesting that more complex mechanisms are not required to explain them.