Is there opponent-orientation coding in the second-order channels of pattern vision?

Pre-frontal cortex guides dimension-reducing transformations in the occipito-ventral pathway for categorization behaviors

To interpret our surroundings, the brain uses a visual categorization process. Current theories and models suggest that this process comprises a hierarchy of different computations that transforms complex, high-dimensional inputs into lower-dimensional representations (i.e., manifolds) in support of multiple categorization behaviors. Here, we tested this hypothesis by analyzing these transformations reflected in dynamic MEG source activity while individual participants actively categorized the same stimuli according to different tasks: face expression, face gender, pedestrian gender, and vehicle type. Results reveal three transformation stages guided by the pre-frontal cortex. At stage 1 (high-dimensional, 50-120 ms), occipital sources represent both task-relevant and task-irrelevant stimulus features; task-relevant features advance into higher ventral/dorsal regions, whereas task-irrelevant features halt at the occipital-temporal junction. At stage 2 (121-150 ms), stimulus feature representations reduce to lower-dimensional manifolds, which then transform into the task-relevant features underlying categorization behavior over stage 3 (161-350 ms). Our findings shed light on how the brain's network mechanisms transform high-dimensional inputs into specific feature manifolds that support multiple categorization behaviors.

Nonlocal contrast calculated by the second order visual mechanisms and its significance in identifying facial emotions

Background: Previously obtained results indicate that faces are / preattentively/ detected in the visual scene very fast, and information on facial expression is rapidly extracted at the lower levels of the visual system. At the same time different facial attributes make different contributions in facial expression recognition. However, it is known, among the preattentive mechanisms there are none that would be selective for certain facial features, such as eyes or mouth. The aim of our study was to identify a candidate for the role of such a mechanism. Our assumption was that the most informative areas of the image are those characterized by spatial heterogeneity, particularly with nonlocal contrast changes. These areas may be identified / in the human visual system/ by the second-order visual / mechanisms/ filters selective to contrast modulations of brightness gradients. Methods: We developed a software program imitating the operation of these / mechanisms/ filters and finding areas of contrast heterogeneity in the image. Using this program, we extracted areas with maximum, minimum and medium contrast modulation amplitudes from the initial face images, then we used these to make three variants of one and the same face. The faces were demonstrated to the observers along with other objects synthesized the same way. The participants had to identify faces and define facial emotional expressions. Results: It was found that the greater is the contrast modulation amplitude of the areas shaping the face, the more precisely the emotion is identified. Conclusions: The results suggest that areas with a greater increase in nonlocal contrast are more informative in facial images, and the second-order visual / mechanisms/ filters can claim the role of /filters/ elements that detect areas of interest, attract visual attention and are windows through which subsequent levels of visual processing receive valuable information.

Surround suppression supports second-order feature encoding by macaque V1 and V2 neurons

Single neurons in areas V1 and V2 of macaque visual cortex respond selectively to luminance-modulated stimuli. These responses are often influenced by context, for example when stimuli extend outside the classical receptive field (CRF). These contextual phenomena, observed in many sensory areas, reflect a fundamental cortical computation and may inform perception by signaling second-order visual features which are defined by spatial relationships of contrast, orientation and spatial frequency. In the anesthetized, paralyzed macaque, we measured single-unit responses to a drifting preferred sinusoidal grating; low spatial frequency sinusoidal contrast modulations were applied to the grating, creating contrast-modulated, second-order forms. Most neurons responded selectively to the orientation of the contrast modulation of the preferred grating and were therefore second-order orientation-selective. Second-order selectivity was created by the asymmetric spatial organization of the excitatory CRF and suppressive extraclassical surround. We modeled these receptive field subregions using spatial Gaussians, sensitive to the modulation of contrast (not luminance) of the preferred carrier grating, that summed linearly and were capable of recovering asymmetrical receptive field organizations. Our modeling suggests that second-order selectivity arises both from elongated excitatory CRFs, asymmetrically organized extraclassical surround suppression, or both. We validated the model by successfully testing its predictions against conventional surround suppression measurements and spike-triggered analysis of second-order form responses. Psychophysical adaptation measurements on human observers revealed a pattern of second-order form selectivity consistent with neural response patterns. We therefore propose that cortical cells in primates do double duty, providing signals about both first- and second-order forms.

The integration of straight contours (snakes and ladders): The role of spatial arrangement, spatial frequency and spatial phase

In the present study we addressed the issue of whether the Gestalt principle of grouping by similarity (iso-orientation) subtends extraction of straight contours made up of disconnected, iso-oriented Gabor elements, whether collinear (snakes) or parallel (ladders). To prevent the use of the most obvious grouping principle of good continuation, which allows us to perceive the relation between local and global orientation along the contour, we manipulated the spatial arrangement of randomly oriented Gabors in the background: they were positioned on an ordered grid, and grouped on the basis of good continuation, or randomly positioned and not grouped. Grid-positioned backgrounds exert a suppressive contextual influence on detection of good continuation along the contour path. Results obtained in a two-interval forced choice task showed that the orderly-positioned background did not completely prevent detection of snakes and ladders. Detection of snakes was hampered at low spatial frequency whereas detection of ladders was improved by the randomly-positioned background at high spatial frequency. These contextual influences support the suggestion that both iso-orientation and good continuation rules are employed by the association field underlying the binding of straight contours. In addition, they are not compatible with integration of snakes and ladders elements within a single receptive field. In support of this suggestion we found that phase constancy within contour elements (as opposed to phase randomization) improved snake detectability at low spatial frequency, and, unexpectedly, impaired ladder detectability at high spatial frequency. This suggests that a low-level mechanism based on the balance between excitatory and inhibitory lateral interactions at a first stage may account for the detection of both straight contours.

Neuronal responses to texture-defined form in macaque visual area V2

Human and macaque observers can detect and discriminate visual forms defined by differences in texture. The neurophysiological correlates of visual texture perception are not well understood and have not been studied extensively at the single-neuron level in the primate brain. We used a novel family of texture patterns to measure the selectivity of neurons in extrastriate cortical area V2 of the macaque (Macaca nemestrina, Macaca fascicularis) for the orientation of texture-defined form, and to distinguish responses to luminance- and texture-defined form. Most V2 cells were selective for the orientation of luminance-defined form; they signaled the orientation of the component gratings that made up the texture patterns but not the overall pattern orientation. In some cells, these luminance responses were modulated by the direction or orientation of the texture envelope, suggesting an interaction of luminance and texture signals. We found little evidence for a "cue-invariant" representation in monkey V2. Few cells showed selectivity for the orientation of texture-defined form; they signaled the orientation of the texture patterns and not that of the component gratings. Small datasets recorded in monkey V1 and cat area 18 showed qualitatively similar patterns of results. Consistent with human functional imaging studies, our findings suggest that signals related to texture-defined form in primate cortex are most salient in areas downstream of V2. V2 may still provide the foundation for texture perception, through the interaction of luminance- and texture-based signals.

Beyond multiple pattern analyzers modeled as linear filters (as classical V1 simple cells): useful additions of the last 25 years

This review briefly discusses processes that have been suggested in the last 25 years as important to the intermediate stages of visual processing of patterns. Five categories of processes are presented: (1) Higher-order processes including FRF structures; (2) Divisive contrast nonlinearities including contrast normalization; (3) Subtractive contrast nonlinearities including contrast comparison; (4) Non-classical receptive fields (surround suppression, cross-orientation inhibition); (5) Contour integration.

Texture modulation detection by probability summation among orientation-selective and isotropic mechanisms

Substantial evidence has accumulated for the notion that modulations of second-order properties in the visual scene are processed by mechanisms which detect contrast variations within narrow orientation/spatial frequency channels. It has also been suggested that mechanisms exist which detect contrast modulations across all orientations. Many naturally occurring texture variations (e.g., modulations in orientation and/or spatial frequency) involve simultaneous contrast modulations in multiple channels. Contrasting conclusions have been drawn regarding the manner in which the information carried in multiple channels is combined. In a series of two experiments it is shown that simultaneous contrast modulations in two narrow orientation bands are detected by three mechanisms, two of which detect contrast modulations within the modulated bands only, the third of which integrates contrast across orientations in order to detect modulations of overall contrast. The three mechanisms combine their efforts by probability summation.

Direct evidence for the existence of energy-based texture mechanisms

Two classes of models have been proposed to explain how the visual system processes texture modulations. In 'feature models', abstract representations of the featural properties of local texture regions (eg orientation, spatial frequency, contrast) are first generated, after which differences in individual feature properties across space are detected. In 'energy models', on the other hand, differences across space in the response energies of linear simple-cell-like filters are detected. This model thus processes the existing differences between texture regions directly without generating a full representation of the individual texture regions. We provide here direct evidence for the existence of the second, energy model, using an adaptation paradigm in conjunction with textures simultaneously modulated in two dimensions--orientation and spatial frequency. We found that the mechanism that processed the conjoint modulation was tuned to orientations and spatial frequencies that could not be predicted by any feature model, but which were precisely predicted by the energy model.