Dynamic Electrode-to-Image (DETI) mapping reveals the human brain's spatiotemporal code of visual information.

A number of neuroimaging techniques have been employed to understand how visual information is transformed along the visual pathway. Although each technique has spatial and temporal limitations, they can each provide important insights into the visual code. While the BOLD signal of fMRI can be quite informative, the visual code is not static and this can be obscured by fMRI's poor temporal resolution. In this study, we leveraged the high temporal resolution of EEG to develop an encoding technique based on the distribution of responses generated by a population of real-world scenes. This approach maps neural signals to each pixel within a given image and reveals location-specific transformations of the visual code, providing a spatiotemporal signature for the image at each electrode. Our analyses of the mapping results revealed that scenes undergo a series of nonuniform transformations that prioritize different spatial frequencies at different regions of scenes over time. This mapping technique offers a potential avenue for future studies to explore how dynamic feedforward and recurrent processes inform and refine high-level representations of our visual world.

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization.

Human scene categorization is characterized by its remarkable speed. While many visual and conceptual features have been linked to this ability, significant correlations exist between feature spaces, impeding our ability to determine their relative contributions to scene categorization. Here, we used a whitening transformation to decorrelate a variety of visual and conceptual features and assess the time course of their unique contributions to scene categorization. Participants (both sexes) viewed 2250 full-color scene images drawn from 30 different scene categories while having their brain activity measured through 256-channel EEG. We examined the variance explained at each electrode and time point of visual event-related potential (vERP) data from nine different whitened encoding models. These ranged from low-level features obtained from filter outputs to high-level conceptual features requiring human annotation. The amount of category information in the vERPs was assessed through multivariate decoding methods. Behavioral similarity measures were obtained in separate crowdsourced experiments. We found that all nine models together contributed 78% of the variance of human scene similarity assessments and were within the noise ceiling of the vERP data. Low-level models explained earlier vERP variability (88 ms after image onset), whereas high-level models explained later variance (169 ms). Critically, only high-level models shared vERP variability with behavior. Together, these results suggest that scene categorization is primarily a high-level process, but reliant on previously extracted low-level features.SIGNIFICANCE STATEMENT In a single fixation, we glean enough information to describe a general scene category. Many types of features are associated with scene categories, ranging from low-level properties, such as colors and contours, to high-level properties, such as objects and attributes. Because these properties are correlated, it is difficult to understand each property's unique contributions to scene categorization. This work uses a whitening transformation to remove the correlations between features and examines the extent to which each feature contributes to visual event-related potentials over time. We found that low-level visual features contributed first but were not correlated with categorization behavior. High-level features followed 80 ms later, providing key insights into how the brain makes sense of a complex visual world.

Towards a state-space geometry of neural responses to natural scenes: A steady-state approach.

Our understanding of information processing by the mammalian visual system has come through a variety of techniques ranging from psychophysics and fMRI to single unit recording and EEG. Each technique provides unique insights into the processing framework of the early visual system. Here, we focus on the nature of the information that is carried by steady state visual evoked potentials (SSVEPs). To study the information provided by SSVEPs, we presented human participants with a population of natural scenes and measured the relative SSVEP response. Rather than focus on particular features of this signal, we focused on the full state-space of possible responses and investigated how the evoked responses are mapped onto this space. Our results show that it is possible to map the relatively high-dimensional signal carried by SSVEPs onto a 2-dimensional space with little loss. We also show that a simple biologically plausible model can account for a high proportion of the explainable variance (~73%) in that space. Finally, we describe a technique for measuring the mutual information that is available about images from SSVEPs. The techniques introduced here represent a new approach to understanding the nature of the information carried by SSVEPs. Crucially, this approach is general and can provide a means of comparing results across different neural recording methods. Altogether, our study sheds light on the encoding principles of early vision and provides a much needed reference point for understanding subsequent transformations of the early visual response space to deeper knowledge structures that link different visual environments.

Spatial summation of broadband contrast.

Spatial summation of luminance contrast signals has historically been psychophysically measured with stimuli isolated in spatial frequency (i.e., narrowband). Here, we revisit the study of spatial summation with noise patterns that contain the naturalistic 1/fα distribution of contrast across spatial frequency. We measured amplitude spectrum slope (α) discrimination thresholds and verified if sensitivity to α improved according to stimulus size. Discrimination thresholds did decrease with an increase in stimulus size. These data were modeled with a summation model originally designed for narrowband stimuli (i.e., single detecting channel; Baker & Meese, 2011; Meese & Baker, 2011) that we modified to include summation across multiple-differently tuned-spatial frequency channels. To fit our data, contrast gain control weights had to be inversely related to spatial frequency (1/f); thus low spatial frequencies received significantly more divisive inhibition than higher spatial frequencies, which is a similar finding to previous models of broadband contrast perception (Haun & Essock, 2010; Haun & Peli, 2013). We found summation across spatial frequency channels to occur prior to summation across space, channel summation was near linear and summation across space was nonlinear. Our analysis demonstrates that classical psychophysical models can be adapted to computationally define visual mechanisms under broadband visual input, with the adapted models offering novel insight on the integration of signals across channels and space.

Shared spatiotemporal category representations in biological and artificial deep neural networks.

Visual scene category representations emerge very rapidly, yet the computational transformations that enable such invariant categorizations remain elusive. Deep convolutional neural networks (CNNs) perform visual categorization at near human-level accuracy using a feedforward architecture, providing neuroscientists with the opportunity to assess one successful series of representational transformations that enable categorization in silico. The goal of the current study is to assess the extent to which sequential scene category representations built by a CNN map onto those built in the human brain as assessed by high-density, time-resolved event-related potentials (ERPs). We found correspondence both over time and across the scalp: earlier (0-200 ms) ERP activity was best explained by early CNN layers at all electrodes. Although later activity at most electrode sites corresponded to earlier CNN layers, activity in right occipito-temporal electrodes was best explained by the later, fully-connected layers of the CNN around 225 ms post-stimulus, along with similar patterns in frontal electrodes. Taken together, these results suggest that the emergence of scene category representations develop through a dynamic interplay between early activity over occipital electrodes as well as later activity over temporal and frontal electrodes.

Non-uniform phase sensitivity in spatial frequency maps of the human visual cortex.

KEY POINTS: Just as a portrait painting can come from a collection of coarse and fine details, natural vision can be decomposed into coarse and fine components. Previous studies have shown that the early visual areas in the brain represent these components in a map-like fashion. Other studies have shown that these same visual areas can be sensitive to how coarse and fine features line up in space. We found that the brain actually jointly represents both the scale of the feature (fine, medium, or coarse) and the alignment of these features in space. The results suggest that the visual cortex has an optimized representation particularly for the alignment of fine details, which are crucial in understanding the visual scene. ABSTRACT: Complex natural scenes can be decomposed into their oriented spatial frequency (SF) and phase relationships, both of which are represented locally at the earliest stages of cortical visual processing. The SF preference map in the human cortex, obtained using synthetic stimuli, is orderly and correlates strongly with eccentricity. In addition, early visual areas show sensitivity to the phase information that describes the relationship between SFs and thereby dictates the structure of the image. Taken together, two possibilities arise for the joint representation of SF and phase: either the entirety of the cortical SF map is uniformly sensitive to phase, or a particular set of SFs is selectively phase sensitive - for example, greater phase sensitivity for higher SFs that define fine-scale edges in a complex scene. To test between these two possibilities, we constructed a novel continuous natural scene video whereby phase information was maintained in one SF band but scrambled elsewhere. By shifting the central frequency of the phase-aligned band in time, we mapped the phase-sensitive SF preference of the visual cortex. Using functional magnetic resonance imaging, we found that phase sensitivity in early visual areas is biased toward higher SFs. Compared to a SF map of the same scene obtained using linear-filtered stimuli, a much larger patch of areas V1 and V2 is sensitive to the phase alignment of higher SFs. The results of early areas cannot be explained by attention. Our results suggest non-uniform sensitivity to phase alignment in population-level SF representations, with phase alignment being particularly important for fine-scale edge representations of natural scenes.

Visual information representation and rapid-scene categorization are simultaneous across cortex: An MEG study.

Perceiving the visual world around us requires the brain to represent the features of stimuli and to categorize the stimulus based on these features. Incorrect categorization can result either from errors in visual representation or from errors in processes that lead to categorical choice. To understand the temporal relationship between the neural signatures of such systematic errors, we recorded whole-scalp magnetoencephalography (MEG) data from human subjects performing a rapid-scene categorization task. We built scene category decoders based on (1) spatiotemporally resolved neural activity, (2) spatial envelope (SpEn) image features, and (3) behavioral responses. Using confusion matrices, we tracked how well the pattern of errors from neural decoders could be explained by SpEn decoders and behavioral errors, over time and across cortical areas. Across the visual cortex and the medial temporal lobe, we found that both SpEn and behavioral errors explained unique variance in the errors of neural decoders. Critically, these effects were nearly simultaneous, and most prominent between 100 and 250ms after stimulus onset. Thus, during rapid-scene categorization, neural processes that ultimately result in behavioral categorization are simultaneous and co-localized with neural processes underlying visual information representation.

On the Differentiation of Foveal and Peripheral Early Visual Evoked Potentials.

The C1 is one of the earliest visual evoked potentials observed following the onset of a patterned stimulus. The polarity of its peak is dependent on whether stimuli are presented in the upper or lower regions of the peripheral visual field, but has been argued to be negative for stimuli presented to the fovea. However, there has yet to be a systematic investigation into the extent to which the peripheral C1 (pC1) and foveal C1 (fC1) can be differentiated on the basis of response characteristics to different stimuli. The current study employed checkerboard patterns (Exp 1) and sinusoidal gratings of different spatial frequency (Exp 2) presented to the fovea or within one of the four quadrants of the peripheral visual field. The checkerboard stimuli yielded a sizable difference in peak component latency, with the fC1 peaking ~32 ms after the pC1. Further, the pC1 showed a band-pass response magnitude profile that peaked at 4 cycles per degree (cpd), whereas the fC1 was high-pass for spatial frequency, with a cut-off around 4 cpd. Finally, the scalp topographies of the pC1 and fC1 in both experiments differed greatly, with the fC1 being more posterior than the pC1. The results reported here call into question recent attempts to characterize general C1 processes without regard to whether stimuli are placed in the fovea or in the periphery.

The Effects of tDCS Across the Spatial Frequencies and Orientations that Comprise the Contrast Sensitivity Function.

Transcranial Direct Current Stimulation (tDCS) has recently been employed in traditional psychophysical paradigms in an effort to measure direct manipulations on spatial frequency channel operations in the early visual system. However, the effects of tDCS on contrast sensitivity have only been measured at a single spatial frequency and orientation. Since contrast sensitivity is known to depend on spatial frequency and orientation, we ask how the effects of anodal and cathodal tDCS may vary according to these dimensions. We measured contrast sensitivity with sinusoidal gratings at four different spatial frequencies (0.5, 4, 8, and 12 cycles/°), two orientations (45° Oblique and Horizontal), and for two stimulus size conditions [fixed size (3°) and fixed period (1.5 cycles)]. Only contrast sensitivity measured with a 45° oblique grating with a spatial frequency of 8 cycles/° (period = 1.5 cycles) demonstrated clear polarity specific effects of tDCS, whereby cathodal tDCS increased and anodal tDCS decreased contrast sensitivity. Overall, effects of tDCS were largest for oblique stimuli presented at high spatial frequencies (i.e., 8 and 12 cycles/°), and were small or absent at lower spatial frequencies, other orientations and stimulus size. Thus, the impact of tDCS on contrast sensitivity, and therefore on spatial frequency channel operations, is opposite in direction to other behavioral effects of tDCS, and only measurable in stimuli that generally elicit lower contrast sensitivity (e.g., oblique gratings with period of 1.5 cycles at spatial frequencies above the peak of the contrast sensitivity function).

A cortical locus for anisotropic overlay suppression of stimuli presented at fixation.

Human contrast sensitivity for narrowband Gabor targets is suppressed when superimposed on narrowband masks of the same spatial frequency and orientation (referred to as overlay suppression), with suppression being broadly tuned to orientation and spatial frequency. Numerous behavioral and neurophysiological experiments have suggested that overlay suppression originates from the initial lateral geniculate nucleus (LGN) inputs to V1, which is consistent with the broad tuning typically reported for overlay suppression. However, recent reports have shown narrowly tuned anisotropic overlay suppression when narrowband targets are masked by broadband noise. Consequently, researchers have argued for an additional form of overlay suppression that involves cortical contrast gain control processes. The current study sought to further explore this notion behaviorally using narrowband and broadband masks, along with a computational neural simulation of the hypothesized underlying gain control processes in cortex. Additionally, we employed transcranial direct current stimulation (tDCS) in order to test whether cortical processes are involved in driving narrowly tuned anisotropic suppression. The behavioral results yielded anisotropic overlay suppression for both broadband and narrowband masks and could be replicated with our computational neural simulation of anisotropic gain control. Further, the anisotropic form of overlay suppression could be directly modulated by tDCS, which would not be expected if the suppression was primarily subcortical in origin. Altogether, the results of the current study provide further evidence in support of an additional overlay suppression process that originates in cortex and show that this form of suppression is also observable with narrowband masks.

Comparing rapid scene categorization of aerial and terrestrial views: A new perspective on scene gist.

Scene gist, a viewer's holistic representation of a scene from a single eye fixation, has been extensively studied for terrestrial views, but not for aerial views. We compared rapid scene categorization of both views in three experiments to determine the degree to which diagnostic information is view dependent versus view independent.We found large differences in observers' ability to rapidly categorize aerial and terrestrial scene views, consistent with the idea that scene gist recognition is viewpoint dependent.In addition, computational modeling showed that training models on one view (aerial or terrestrial) led to poor performance on the other view, thereby providing further evidence of viewpoint dependence as a function of available information. Importantly, we found that rapid categorization of terrestrial views (but not aerial views) was strongly interfered with by image rotation, further suggesting that terrestrial-view scene gist recognition is viewpoint dependent, with aerial-view scene recognition being viewpoint independent. Furthermore, rotation-invariant texture images synthesized from aerial views of scenes were twice as recognizable as those synthesized from terrestrial views of scenes (which were at chance), providing further evidence that diagnostic information for rapid scene categorization of aerial views is viewpoint invariant. We discuss the results within a perceptual-expertise framework that distinguishes between configural and featural processing, where terrestrial views are more effectively processed due to their predictable view-dependent configurations whereas aerial views are processed less effectively due to reliance on view-independent features.

One "shape" fits all: the orientation bandwidth of contour integration.

The ability of human participants to integrate fragmented stimulus elements into perceived coherent contours (amidst a field of distracter elements) has been intensively studied across a large number of contour element parameters, ranging from luminance contrast and chromaticity to motion and stereo. The evidence suggests that contour integration performance depends on the low-level Fourier properties of the stimuli. Thus, to understand contour integration, it would be advantageous to understand the properties of the low-level filters that the visual system uses to process contour stimuli. We addressed this issue by examining the role of stimulus element orientation bandwidth in contour integration, a previously unexplored area. We carried out three psychophysical experiments, and then simulated all of the experiments using a recently developed two-stage filter-overlap model whereby the contour grouping occurs by virtue of the overlap between the filter responses to different elements. The first stage of the model responds to the elements, while the second stage integrates the responses along the contour. We found that the first stage had to be fairly broadly tuned for orientation to account for our results. The model showed a very good fit to a large data set with relatively few free parameters, suggesting that this class of model may have an important role to play in helping us to better understand the mechanisms of contour integration.

Scene gist categorization by pigeons.

Scene gist categorization in humans is rapid, accurate, and tuned to the statistical regularities in the visual world. However, no studies have investigated whether scene gist categorization is a general process shared across species, or whether it may be influenced by species-specific adaptive specializations relying on specific low-level scene statistical regularities of the environment. Although pigeons form many types of categorical judgments, little research has examined pigeons' scene categorization, and no studies have examined pigeons' ability to do so rapidly. In Experiment 1, pigeons were trained to discriminate between either 2 basic-level categories (beach vs. mountain) or a superordinate-level natural versus a manmade scene category distinction (beach vs. street). The birds learned both tasks to a high degree of accuracy and transferred their discrimination to novel images. Furthermore, the pigeons successfully discriminated stimuli presented in the 0.2- to 0.35-s duration range. Therefore, pigeons, a highly divergent species from humans, are also capable of rapid scene categorization, but they require longer stimulus durations than humans. Experiment 2 examined whether pigeons make use of complex statistical regularities during scene gist categorization across multiple viewpoints. Pigeons were trained with the 2 natural categories from Experiment 1 (beach vs. mountain) with zenith (90°), bird's eye (45°), and terrestrial (0°) viewpoints. A sizable portion of the variability in pigeon categorization performance was explained by the systematic variation in scene category-specific statistical regularities, as with humans. Thus, rapid scene categorization is a process that is shared across pigeons and humans, but shows a degree of adaptive specialization.

The contribution of amplitude and phase spectra-defined scene statistics to the masking of rapid scene categorization.

Viewers can recognize the gist of a scene (i.e., its holistic semantic representation, such as its category) in less time than a single fixation, and backward masking has traditionally been employed as a means to determine that time course. The masks used in those paradigms are often characterized by either specific amplitude spectra only, or amplitude and phase spectra-defined structural properties. However, it remains unclear whether there would be a differential contribution of amplitude only or amplitude + phase defined image statistics to the effective backward masking of rapid scene categorization. The current study addresses this issue. Experiments 1-3 explored amplitude spectra defined contributions to category masking and revealed that the slope of the amplitude spectrum was more important for modulating scene category masking strength than amplitude orientation. Further, the masking effects followed an "amplitude spectrum slope similarity principle" whereby the more similar the amplitude spectrum slope of the mask was to the target's amplitude spectrum slope, the stronger the masking. Experiment 5 showed that, when holding mask amplitude spectrum slope approximately constant, both categorically specific unrecognizable amplitude only and amplitude + phase statistical regularities disrupted rapid scene categorization. Specifically, the masking effects observed in Experiment 5 followed a target-mask categorical dissimilarity principle whereby the more dissimilar the mask category is to the target image category, the stronger the masking. Overall, the results support the notion that amplitude only or amplitude + phase-defined image statistics differentially contribute to the effective backward masking of rapid scene gist recognition.

"Slight" of hand: the processing of visually degraded gestures with speech.

Co-speech hand gestures influence language comprehension. The present experiment explored what part of the visual processing system is optimized for processing these gestures. Participants viewed short video clips of speech and gestures (e.g., a person saying "chop" or "twist" while making a chopping gesture) and had to determine whether the two modalities were congruent or incongruent. Gesture videos were designed to stimulate the parvocellular or magnocellular visual pathways by filtering out low or high spatial frequencies (HSF versus LSF) at two levels of degradation severity (moderate and severe). Participants were less accurate and slower at processing gesture and speech at severe versus moderate levels of degradation. In addition, they were slower for LSF versus HSF stimuli, and this difference was most pronounced in the severely degraded condition. However, exploratory item analyses showed that the HSF advantage was modulated by the range of motion and amount of motion energy in each video. The results suggest that hand gestures exploit a wide range of spatial frequencies, and depending on what frequencies carry the most motion energy, parvocellular or magnocellular visual pathways are maximized to quickly and optimally extract meaning.

The developing visual system is not optimally sensitive to the spatial statistics of natural images.

The adult visual system is optimally tuned to process the spatial properties of natural scenes, which is demonstrated by sensitivity to changes in the 1/f(α) amplitude spectrum. It is also well documented that different aspects of spatial vision, including those likely responsible for the perception of natural scenes (e.g., spatial frequency discrimination), do not become mature until late childhood. This led us to hypothesise that the developing visual system is not optimally tuned to process the spatial properties of real-world scenes. The present study investigated how sensitivity to the statistical properties of natural images changes during development. Thresholds for discriminating a change in the slope of the amplitude spectrum of a natural scene with a reference α of 0.7, 1.0, or 1.3 where measured in children aged 6, 8, and 10 years (n=16 per age) and in adults (mean age=23). Consistent with previous studies, adults were least sensitive for the shallowest α (i.e., 0.7) and most sensitive for the steepest α (i.e., 1.3). Six- and 8-year-olds had significantly higher discrimination thresholds compared to the 10-year-olds and adults for α's of 1.0 and 1.3, and 10-year-olds did not differ significantly from adults for any of the α's tested. These data suggest that sensitivity to detecting a change in the spatial characteristics of natural scenes during childhood may not be optimally tuned to the statistics of natural images until about 10 years of age. Rather, is seems that perception of natural images could be limited by the known immaturities in spatial vision (Ellemberg, Lepore, & Turgeon, 2010). The question remains as to whether the adult's exquisite sensitivity to the spatial properties of the natural world is experience driven or whether it is part of our genetic programming that only fully expresses itself in late childhood.

Different spatial frequency bands selectively signal for natural image statistics in the early visual system.

Early visual evoked potentials (VEPs) measured in humans have recently been observed to be modulated by the image statistics of natural scene imagery. Specifically, the early VEP is dominated by a strong positivity when participants view minimally complex natural scene imagery, with the magnitude of that component being modulated by luminance contrast differences across spatial frequency (i.e., the slope of the amplitude spectrum). For scenes high in structural complexity, the early VEP is dominated by a prominent negativity that exhibits little dependency on luminance contrast. However, since natural scene imagery is broad band in terms of spatial frequency, it is not known whether the above-mentioned modulation results from a complex interaction within or between the early neural processes tuned to different bands of spatial frequency. Here, we sought to address this question by measuring early VEPs (specifically, the C1, P1, and N1 components) while human participants viewed natural scene imagery that was filtered to contain specific bands of spatial frequency information. The results show that the C1 component is largely unmodulated by the luminance statistics of natural scene imagery (being only measurable when such stimuli were made to contain high spatial frequencies). The P1 and N1, on the other hand, were observed to exhibit strong spatial frequency-dependent modulation to the luminance statistics of natural scene imagery. The results therefore suggest that the dependency of early VEPs on natural image statistics results from an interaction between the early neural processes tuned to different bands of spatial frequency.

Anodal transcranial direct current stimulation reduces psychophysically measured surround suppression in the human visual cortex.

Transcranial direct current stimulation (tDCS) is a safe, non-invasive technique for transiently modulating the balance of excitation and inhibition within the human brain. It has been reported that anodal tDCS can reduce both GABA mediated inhibition and GABA concentration within the human motor cortex. As GABA mediated inhibition is thought to be a key modulator of plasticity within the adult brain, these findings have broad implications for the future use of tDCS. It is important, therefore, to establish whether tDCS can exert similar effects within non-motor brain areas. The aim of this study was to assess whether anodal tDCS could reduce inhibitory interactions within the human visual cortex. Psychophysical measures of surround suppression were used as an index of inhibition within V1. Overlay suppression, which is thought to originate within the lateral geniculate nucleus (LGN), was also measured as a control. Anodal stimulation of the occipital poles significantly reduced psychophysical surround suppression, but had no effect on overlay suppression. This effect was specific to anodal stimulation as cathodal stimulation had no effect on either measure. These psychophysical results provide the first evidence for tDCS-induced reductions of intracortical inhibition within the human visual cortex.

On the effectiveness of noise masks: naturalistic vs. un-naturalistic image statistics.

It has been argued that the human visual system is optimized for identification of broadband objects embedded in stimuli possessing orientation averaged power spectra fall-offs that obey the 1/f(ß) relationship typically observed in natural scene imagery (i.e., ß=2.0 on logarithmic axes). Here, we were interested in whether individual spatial channels leading to recognition are functionally optimized for narrowband targets when masked by noise possessing naturalistic image statistics (ß=2.0). The current study therefore explores the impact of variable ß noise masks on the identification of narrowband target stimuli ranging in spatial complexity, while simultaneously controlling for physical or perceived differences between the masks. The results show that ß=2.0 noise masks produce the largest identification thresholds regardless of target complexity, and thus do not seem to yield functionally optimized channel processing. The differential masking effects are discussed in the context of contrast gain control.

The magnitude of center-surround facilitation in the discrimination of amplitude spectrum is dependent on the amplitude of the surround.

Recent studies explored the sensitivity of human perception to natural images, in particular the sensitivity of the visual system to discriminate changes in the amplitude spectrum slope. Previous slope discrimination experiments were carried out with stimuli presented either in the fovea or the parafovea/periphery and show that both yield poor discrimination at very steep or relatively shallow slopes. We verified if the well-known center-surround spatial interactions that operate early on in the visual processing stream influence the perception of real-world images. The results show that amplitude slope discrimination is greatly reduced (i.e., flat) when the stimulus is viewed in isolation. However, when a 2° target is placed within a surround containing an amplitude spectrum slope of 1 or 1.3, we see significant facilitation in detecting variations in the slope of the amplitude spectrum, particularly when the target contains an amplitude spectrum slope of 1 and 1.3. The results suggest that our visual system is sensitive to contextual interactions for stimuli that have the characteristics of natural images.