Further evidence for the spread of attention during contour grouping: A reply to Crundall, Dewhurst, and Underwood (2008)

Accentuation, Boolean maps and perception of (dis)similarity in a neural model of visual segmentation

We developed an interactive cortical circuit for visual segmentation that integrates bottom-up and top-down processing to segregate or group visual elements. A bottom-up pathway incorporates stimulus-driven saliency computation, top-down feature-based weighting by relevance and winner-take-all selection. A top-down pathway encompasses multiscale feedback projections, an object-based attention network and a visual segmentation network. Computer simulations have shown that a salient element in the stimulus guides spatial attention and further influences the decomposition of the nearby object into its parts, as postulated by the principle of accentuation. By contrast, when no single salient element is present, top-down feature-based attention highlights all locations occupied by the attended feature and the model forms a Boolean map, i.e., a spatial representation that makes the feature-based grouping explicit. The same distinction between bottom-up and top-down influences in perceptual organization can also be applied to texture perception. The model suggests that the principle of accentuation and feature-based similarity grouping are two manifestations of the same cortical circuit designed to detect similarities and dissimilarities of visual elements in a stimulus.

The effect of object perception on event integration and segregation

The perceptual system must integrate information from various points in time and space to interpret continuous sensory input into meaningful units, such as visual objects or events. To explore the relationship between the perception of spatial objects and temporal events, we modified the missing element task, a typical temporal integration task, by inserting a simple spatial object. The aim was to determine whether the perceptual processing of the object would have an impact on the frequency of temporal integration and segregation. Temporal integration was most successful when the missing element was located within the object, less successful when there was no object, and least successful when the missing element appeared outside the object. The advantage of the location of the missing element within the object was observed at display durations from 30 ms to 150 ms. Interestingly, the object provided the same benefit for integration and segregation despite their opposing perceptual demands. This study demonstrates the relationship that exists between the processing of temporal events and spatial objects, and shows how such spatial information can facilitate temporal integration.

Neural dynamics of spreading attentional labels in mental contour tracing

Behavioral and neural data suggest that visual attention spreads along contour segments to bind them into a unified object representation. Such attentional labeling segregates the target contour from distractors in a process known as mental contour tracing. A recurrent competitive map is developed to simulate the dynamics of mental contour tracing. In the model, local excitation opposes global inhibition and enables enhanced activity to propagate on the path offered by the contour. The extent of local excitatory interactions is modulated by the output of the multi-scale contour detection network, which constrains the speed of activity spreading in a scale-dependent manner. Furthermore, an L-junction detection network enables tracing to switch direction at the L-junctions, but not at the X- or T-junctions, thereby preventing spillover to a distractor contour. Computer simulations reveal that the model exhibits a monotonic increase in tracing time as a function of the distance to be traced. Also, the speed of tracing increases with decreasing proximity to the distractor contour and with the reduced curvature of the contours. The proposed model demonstrated how an elaborated version of the winner-takes-all network can implement a complex cognitive operation such as contour tracing.

Testing between the gunpowder fuse and the filling-hose analogy for mental curve tracing using electroencephalography: boom!

Curve tracing occurs when a line is followed covertly to accomplish a task, for example, to determine whether two landmarks are on the same line or not (could Highway 61 take Robert Johnson from New Orleans to St Louis?). Previous work suggests that attention either moves along the curve, momentarily activating local representations of the curve during this process, leaving little or no trace of this activation once attention has passed, or attention spreads along the curve, resulting in an activated state along the entire portion of the curve that was traced. We re-examined this issue using event-related potentials. Curves to be traced were presented briefly to encourage a rapid deployment of attention. The curves started on the vertical midline and passed into the left or right visual field and terminated either on the vertical midline or at a lateral position. We measured a posterior contralateral negativity (relative to the visual field of the traced curve) that offset more rapidly when the curve was traced back to the midline than when it remained lateral. The results suggest that attention travels along the curve like fire on a fuse, with activation returning to baseline once the flame has passed.

Brain networks supporting perceptual grouping and contour selection

The human visual system groups local elements into global objects seemingly without effort. Using a contour integration task and EEG source level analyses, we tested the hypothesis that perceptual grouping requires a top-down selection, rather than a passive pooling, of neural information that codes local elements in the visual image. The participants were presented visual displays with or without a hidden contour. Two tasks were performed: a central luminance-change detection task and a peripheral contour detection task. Only in the contour-detection task could we find differential brain activity between contour and non-contour conditions, within a distributed brain network including parietal, lateral occipital and primary visual areas. Contour processing was associated with an inflow of information from lateral occipital into primary visual regions, as revealed from the slope of phase differences between source level oscillations within these areas. The findings suggest that contour integration results from a selection of neural information from lower visual areas, and that this selection is driven by the lateral occipital cortex.

Luminance contrast has little influence on the spread of object-based attention

We direct our attention to those visual stimuli that are relevant to our behavioral goals. Some of the visual stimuli that surround us are represented more strongly, because they have a higher luminance contrast. However, selective attention also boosts the representation of visual stimuli. It is not yet well understood how attention and contrast interact. Some previous theories proposed that attentional effects are strongest at low contrast, others that they are strongest at high contrast and yet others that the effects of selective attention are largely independent of contrast. In the present study, we investigated the interaction between selective attention and luminance contrast with a contour-grouping task that provides a sensitive measure of the spread of object-based attention, with delays of several hundreds of milliseconds. We find that the spread of object-based attention is largely independent of contrast, and that subjects experience little difficulty in grouping low-contrast contour elements in the presence of other contour elements with a much higher contrast. The results imply that object-based attention and contrast have largely independent effects on visual processing.

Incremental grouping of image elements in vision

One important task for the visual system is to group image elements that belong to an object and to segregate them from other objects and the background. We here present an incremental grouping theory (IGT) that addresses the role of object-based attention in perceptual grouping at a psychological level and, at the same time, outlines the mechanisms for grouping at the neurophysiological level. The IGT proposes that there are two processes for perceptual grouping. The first process is base grouping and relies on neurons that are tuned to feature conjunctions. Base grouping is fast and occurs in parallel across the visual scene, but not all possible feature conjunctions can be coded as base groupings. If there are no neurons tuned to the relevant feature conjunctions, a second process called incremental grouping comes into play. Incremental grouping is a time-consuming and capacity-limited process that requires the gradual spread of enhanced neuronal activity across the representation of an object in the visual cortex. The spread of enhanced neuronal activity corresponds to the labeling of image elements with object-based attention.

Electrophysiological evidence of enhanced cortical activity in the human brain during visual curve tracing

ERPs were recorded while participants performed a curve tracing task in which they had to identify the end point of a target curve presented among three other distractor curves. Differential activation associated with the side of the target curve was found in the form of a sustained posterior contralateral negativity (SPCN). This contralateral brain activity suggests covert attention was deployed to the target curve during performance of the tracing task. The amplitude of the SPCN varied according to the hypothesized curve-tracing process, depending on whether the start and end locations of the target curve were above to below the horizontal midline, or the opposite, and this detailed analysis of the results provided evidence supporting the spread-of-attention model of curve tracing. These results represent the first neurophysiological investigation of brain activity reflecting visual curve tracing in humans.