Binocular interactions in human vision

Early visual processing is subject to binocular interactions because cells in striate cortex show binocular responses and ocular dominance (Hubel & Weisel, 1968). The work presented in this thesis suggests that these physiological interactions can be revealed in psychophysical experiments using normal human observers. In the region corresponding to the blind spot, where binocular interactions differ from areas of the visual field which are represented by two eyes, monocular contrast sensitivity is increased. This finding can be partially explained by an absence of normal binocular interactions in this location (Chapter 2). A hemianopic patient was studied in an attempt to discover whether the effect in normal observers was mediated by either a mechanism in striate cortex or via a subcortical pathway. However, the results were unable to distinguish between these two explanations (Chapter 3).In a visual search task, no difference in reaction time was observed for targets presented to the region corresponding to the blind spot compared with targets presented to adjacent binocularly represented areas of the visual field. Since performance was unaffected by the monocularity of the region corresponding to the blind, pop-out for orientation may be mediated beyond striate cortex where cells are binocularly balanced (Chapter 5). Further support for this contention was provided by studies of orientation pop-out in central vision which found that dichoptic presentation of stimuli did not affect the degree of pop-out obtained and that in general, visual search for a target based solely on eye of origin is impossible (Chapter 6). However, a task that measured orientation difference sensitivity more directly than the search experiments, found that thresholds were higher for dichoptically presented stimuli. This suggests the involvement of neurons that receive a weighted input from each eye. A model of orientation difference coding can account for the results by assuming that the range of inhibition across which orientation differences are coded is narrower for dichoptic stimuli leading to a greater resolvable orientation difference (Chapter 7)

Artificially created stimuli produced by a genetic algorithm using a saliency model as its fitness function show that Inattentional Blindness modulates performance in a pop-out visual search paradigm

Salient stimuli are more readily detected than less salient stimuli, and individual differences in such detection may be relevant to why some people fail to notice an unexpected stimulus that appears in their visual field whereas others do notice it. This failure to notice unexpected stimuli is termed 'Inattentional Blindness' and is more likely to occur when we are engaged in a resource-consuming task. A genetic algorithm is described in which artificial stimuli are created using a saliency model as its fitness function. These generated stimuli, which vary in their saliency level, are used in two studies that implement a pop-out visual search task to evaluate the power of the model to discriminate the performance of people who were and were not Inattentionally Blind (IB). In one study the number of orientational filters in the model was increased to check if discriminatory power and the saliency estimation for low-level images could be improved. Results show that the performance of the model does improve when additional filters are included, leading to the conclusion that low-level images may require a higher number of orientational filters for the model to better predict participants' performance. In both studies we found that given the same target patch image (i.e. same saliency value) IB individuals take longer to identify a target compared to non-IB individuals. This suggests that IB individuals require a higher level of saliency for low-level visual features in order to identify target patches

A theory of a saliency map in primary visual cortex (V1) tested by psychophysics of color-orientation interference in texture segmentation

It has been proposed that V1 creates a bottom-up saliency map, where saliency of any location increases with the firing rate of the most active V1 output cell responding to it, regardless the feature selectivity of the cell. Thus, a red vertical bar may have its saliency signalled by a cell tuned to red colour, or one tuned to vertical orientation, whichever cell is the most active. This theory predicts interference between colour and orientation features in texture segmentation tasks where bottom-up processes are significant. The theory not only explains existing data, but also provides a prediction. A subsequent psychophysical test confirmed the prediction by showing that segmentation of textures of oriented bars became more difficult as the colours of the bars were randomly drawn from more colour categories

Looking away from faces: influence of high-level visual processes on saccade programming

Human faces capture attention more than other visual stimuli. Here we investigated whether such face-specific biases rely on automatic (involuntary) or voluntary orienting responses. To this end, we used an anti-saccade paradigm, which requires the ability to inhibit a reflexive automatic response and to generate a voluntary saccade in the opposite direction of the stimulus. To control for potential low-level confounds in the eye-movement data, we manipulated the high-level visual properties of the stimuli while normalizing their global low-level visual properties. Eye movements were recorded in 21 participants who performed either pro- or anti-saccades to a face, car, or noise pattern, randomly presented to the left or right of a fixation point. For each trial, a symbolic cue instructed the observer to generate either a pro-saccade or an anti-saccade. We report a significant increase in anti-saccade error rates for faces compared to cars and noise patterns, as well as faster pro-saccades to faces and cars in comparison to noise patterns. These results indicate that human faces induce stronger involuntary orienting responses than other visual objects, i.e., responses that are beyond the control of the observer. Importantly, this involuntary processing cannot be accounted for by global low-level visual factors

Context-Sensitive Binding by the Laminar Circuits of V1 and V2: A Unified Model of Perceptual Grouping, Attention, and Orientation Contrast

A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific laminar circuits allow the responses of visual cortical neurons to be determined not only by the stimuli within their classical receptive fields, but also to be strongly influenced by stimuli in the extra-classical surround. This context-sensitive visual processing can greatly enhance the analysis of visual scenes, especially those containing targets that are low contrast, partially occluded, or crowded by distractors. We show how interactions of feedforward, feedback and horizontal circuitry can implement several types of contextual processing simultaneously, using shared laminar circuits. In particular, we present computer simulations which suggest how top-down attention and preattentive perceptual grouping, two processes that are fundamental for visual binding, can interact, with attentional enhancement selectively propagating along groupings of both real and illusory contours, thereby showing how attention can selectively enhance object representations. These simulations also illustrate how attention may have a stronger facilitatory effect on low contrast than on high contrast stimuli, and how pop-out from orientation contrast may occur. The specific functional roles which the model proposes for the cortical layers allow several testable neurophysiological predictions to be made. The results presented here simulate only the boundary grouping system of adult cortical architecture. However we also discuss how this model contributes to a larger neural theory of vision which suggests how intracortical and intercortical feedback help to stabilize development and learning within these cortical circuits. Although feedback plays a key role, fast feedforward processing is possible in response to unambiguous information. Model circuits are capable of synchronizing quickly, but context-sensitive persistence of previous events can influence how synchrony develops. Although these results focus on how the interblob cortical processing stream controls boundary grouping and attention, related modeling of the blob cortical processing stream suggests how visible surfaces are formed, and modeling of the motion stream suggests how transient responses to scenic changes can control long-range apparent motion and also attract spatial attention.Defense Advanced Research Projects agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI 94-01659, IRI 97-20333); ONR (N00014-92-J-1309, N00014-95-1-0657

Salience-based selection: attentional capture by distractors less salient than the target

Current accounts of attentional capture predict the most salient stimulus to be invariably selected first. However, existing salience and visual search models assume noise in the map computation or selection process. Consequently, they predict the first selection to be stochastically dependent on salience, implying that attention could even be captured first by the second most salient (instead of the most salient) stimulus in the field. Yet, capture by less salient distractors has not been reported and salience-based selection accounts claim that the distractor has to be more salient in order to capture attention. We tested this prediction using an empirical and modeling approach of the visual search distractor paradigm. For the empirical part, we manipulated salience of target and distractor parametrically and measured reaction time interference when a distractor was present compared to absent. Reaction time interference was strongly correlated with distractor salience relative to the target. Moreover, even distractors less salient than the target captured attention, as measured by reaction time interference and oculomotor capture. In the modeling part, we simulated first selection in the distractor paradigm using behavioral measures of salience and considering the time course of selection including noise. We were able to replicate the result pattern we obtained in the empirical part. We conclude that each salience value follows a specific selection time distribution and attentional capture occurs when the selection time distributions of target and distractor overlap. Hence, selection is stochastic in nature and attentional capture occurs with a certain probability depending on relative salience

Boundary, Brightness, and Depth Interactions During Preattentive Representation and Attentive Recognition of Figure and Ground

This article applies a recent theory of 3-D biological vision, called FACADE Theory, to explain several percepts which Kanizsa pioneered. These include 3-D pop-out of an occluding form in front of an occluded form, leading to completion and recognition of the occluded form; 3-D transparent and opaque percepts of Kanizsa squares, with and without Varin wedges; and interactions between percepts of illusory contours, brightness, and depth in response to 2-D Kanizsa images. These explanations clarify how a partially occluded object representation can be completed for purposes of object recognition, without the completed part of the representation necessarily being seen. The theory traces these percepts to neural mechanisms that compensate for measurement uncertainty and complementarity at individual cortical processing stages by using parallel and hierarchical interactions among several cortical processing stages. These interactions are modelled by a Boundary Contour System (BCS) that generates emergent boundary segmentations and a complementary Feature Contour System (FCS) that fills-in surface representations of brightness, color, and depth. The BCS and FCS interact reciprocally with an Object Recognition System (ORS) that binds BCS boundary and FCS surface representations into attentive object representations. The BCS models the parvocellular LGN→Interblob→Interstripe→V4 cortical processing stream, the FCS models the parvocellular LGN→Blob→Thin Stripe→V4 cortical processing stream, and the ORS models inferotemporal cortex.Air Force Office of Scientific Research (F49620-92-J-0499); Defense Advanced Research Projects Agency (N00014-92-J-4015); Office of Naval Research (N00014-91-J-4100

Probabilistic modeling of eye movement data during conjunction search via feature-based attention

Where the eyes fixate during search is not random; rather, gaze reflects the combination of information about the target and the visual input. It is not clear, however, what information about a target is used to bias the underlying neuronal responses. We here engage subjects in a variety of simple conjunction search tasks while tracking their eye movements. We derive a generative model that reproduces these eye movements and calculate the conditional probabilities that observers fixate, given the target, on or near an item in the display sharing a specific feature with the target. We use these probabilities to infer which features were biased by top-down attention: Color seems to be the dominant stimulus dimension for guiding search, followed by object size, and lastly orientation. We use the number of fixations it took to find the target as a measure of task difficulty. We find that only a model that biases multiple feature dimensions in a hierarchical manner can account for the data. Contrary to common assumptions, memory plays almost no role in search performance. Our model can be fit to average data of multiple subjects or to individual subjects. Small variations of a few key parameters account well for the intersubject differences. The model is compatible with neurophysiological findings of V4 and frontal eye fields (FEF) neurons and predicts the gain modulation of these cells