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A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange "contextual" information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by "asking" natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The "answer" was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the "multiplicative" center-flanker interactions previously reported in V1 neurons (Kapadia et al., 1995, 2000; Polat et al., 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed by NMDAR-dependent spatial synaptic interactions within PN dendrites - the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.

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Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2 × 2 grating patch arrangements (plaids), which differed in spatial frequency composition (low, high, or mixed), number of grating patch co-alignments (0, 1, or 2), and inter-patch distances (1° and 2° of visual angle). Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS) among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained at larger inter-patch distances. However, likelihoods were almost independent of inter-patch distance, implying that natural image statistics could not explain the crowding-like results at short distances. This failure of natural image statistics to resolve the patch distance modulation of plaid visibility remains a challenge to the approach.

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As expressed in the Gestalt law of good continuation, human perception tends to associate stimuli that form smooth continuations. Contextual modulation in primary visual cortex, in the form of association fields, is believed to play an important role in this process. Yet a unified and principled account of the good continuation law on the neural level is lacking. In this study we introduce a population model of primary visual cortex. Its contextual interactions depend on the elastica curvature energy of the smoothest contour connecting oriented bars. As expected, this model leads to association fields consistent with data. However, in addition the model displays tilt-illusions for stimulus configurations with grating and single bars that closely match psychophysics. Furthermore, the model explains not only pop-out of contours amid a variety of backgrounds, but also pop-out of single targets amid a uniform background. We thus propose that elastica is a unifying principle of the visual cortical network.

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Surround suppression is a well-known example of contextual interaction in visual cortical neurophysiology, whereby the neural response to a stimulus presented within a neuron's classical receptive field is suppressed by surrounding stimuli. Human psychophysical reports present an obvious analog to the effects seen at the single-neuron level: stimuli are perceived as lower-contrast when embedded in a surround. Here we report on a visual paradigm that provides relatively direct, straightforward indices of surround suppression in human electrophysiology, enabling us to reproduce several well-known neurophysiological and psychophysical effects, and to conduct new analyses of temporal trends and retinal location effects. Steady-state visual evoked potentials (SSVEP) elicited by flickering "foreground" stimuli were measured in the context of various static surround patterns. Early visual cortex geometry and retinotopic organization were exploited to enhance SSVEP amplitude. The foreground response was strongly suppressed as a monotonic function of surround contrast. Furthermore, suppression was stronger for surrounds of matching orientation than orthogonally-oriented ones, and stronger at peripheral than foveal locations. These patterns were reproduced in psychophysical reports of perceived contrast, and peripheral electrophysiological suppression effects correlated with psychophysical effects across subjects. Temporal analysis of SSVEP amplitude revealed short-term contrast adaptation effects that caused the foreground signal to either fall or grow over time, depending on the relative contrast of the surround, consistent with stronger adaptation of the suppressive drive. This electrophysiology paradigm has clinical potential in indexing not just visual deficits but possibly gain control deficits expressed more widely in the disordered brain.

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The tilt illusion is a compelling example of contextual influence exerted by an oriented surround on a target's perceived orientation. A vertical target appears to be tilted away from a 15° oriented surround but appears to be tilted toward a 75° tilted surround. We tested the claim that these biases result from distinct sensory processes: a low-level repulsive process and a higher-level attractive process. If this claim were correct, then surround visibility would be a requirement for attraction, but it would not necessarily be a requirement for repulsion. Indeed, Motoyoshi and Hayakawa (2010) have demonstrated that repulsion can survive removal of the surround from phenomenal awareness using adaptation-induced blindness. Here we sought to test this prediction by measuring the orientation biases in a parafoveally presented Gabor patch surrounded by tilted gratings after 20-s adaptation. The adapting stimulus was an annularly windowed plaid composed of vertical and horizontal jittering gratings. Observers were instructed to maintain fixation throughout the trial and report whether the Gabor appeared to be tilted clockwise or anticlockwise of vertical. They also had to indicate whether the surround was visible after adaptation. Postadaptation biases were then compared with those obtained in a control experiment without dynamic adaptation. We found large repulsive biases induced by 15° oriented surrounds, but no attractive biases were induced by 75° tilted surrounds. This result shows that attractive effects do require visual awareness and thereby provides robust evidence for the existence of two separate mechanisms mediating the phenomenology of the tilt illusions.

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When seen in isolation, a light that varies in chromaticity over time is perceived to oscillate in color. Perception of that same time-varying light may be altered by a surrounding light that is also temporally varying in chromaticity. The neural mechanisms that mediate these contextual interactions are the focus of this article. Observers viewed a central test stimulus that varied in chromaticity over time within a larger surround that also varied in chromaticity at the same temporal frequency. Center and surround were presented either to the same eye (monocular condition) or to opposite eyes (dichoptic condition) at the same frequency (3.125, 6.25, or 9.375 Hz). Relative phase between center and surround modulation was varied. In both the monocular and dichoptic conditions, the perceived modulation depth of the central light depended on the relative phase of the surround. A simple model implementing a linear combination of center and surround modulation fit the measurements well. At the lowest temporal frequency (3.125 Hz), the surround's influence was virtually identical for monocular and dichoptic conditions, suggesting that at this frequency, the surround's influence is mediated primarily by a binocular neural mechanism. At higher frequencies, the surround's influence was greater for the monocular condition than for the dichoptic condition, and this difference increased with temporal frequency. Our findings show that two separate neural mechanisms mediate chromatic contextual interactions: one binocular and dominant at lower temporal frequencies and the other monocular and dominant at higher frequencies (6-10 Hz).

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