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Introduction Marr (1982) may have been one of the first vision researchers to insist that in modeling vision it is important to separate the location of visual features from their type. He argued that in early stages of visual processing there must be "place tokens" that enable subsequent stages of the visual system to treat locations independent of what specific feature type was at that location. Thus, in certain respects a collinear array of diverse features could still be perceived as a line, and under certain conditions could function as such in perceptual phenomena like the Poggendorf illusion. The idea that locations and feature-types are encoded independently is not a new one. A closely related distinction was widely acknowledged in the literature on list-learning and letterrecognition, where it has long been known that item information could be encoded or retained independent of order information (e.g., Estes, Allmeyer & Reder, 1976; Co

The hypothesis that abrupt visual onsets capture attention automatically, as suggested by Yantis and Jonides (1984) was tested in four experiments. A centrally located cue directed attention to one of several stimulus positions in preparation for the identification of a target letter embedded in an army of distractor letters. In all experiments, one stimulus (either the target or one of the distractors) had an abrupt onset; the remaining letters did not. The effectiveness of the cue was manipulated (varying either its duration or its predictive validity) to test whether abrupt onsets capture attention even when subjects are in a highly focused attentional state. Results showed that onsets do not necessarily capture attention in violation of an observer's intentions. A mechanism for partially automatic attentional capture by abrupt onset is proposed, and the diagnosticity of the intentionality criterion for automaticity is discussed. Introspective and empirical evidence both suggest that the abrupt appearance of an object in the visual field "draws attention. " A plausible account of this phenomenon is that there exists a mechanism that is tuned to abrupt onsets and that one of its functions is to direct visual attention to the

Advances in neuroscience implicate reentrant signaling as the predominant form of communication between brain areas. This principle was used in a series of masking experiments that defy explanation by feed-forward theories. The masking occurs when a brief display of target plus mask is continued with the mask alone. Two masking processes were found: an early process affected by physical factors such as adapting luminance and a later process affected by attentional factors such as set size. This later process is called masking by object substitution, because it occurs whenever there is a mismatch between the reentrant visual representation and the ongoing lower level activity. Iterative reentrant processing was formalized in a computational model that provides an excellent fit to the data. The model provides a more comprehensive account of all forms of visual masking than do the long-held feed-forward views based on inhibitory contour interactions. From the time a stimulus first enters the eye to the time a percept emerges into consciousness, the initial stimulus has been coded at several levels in the visual system. One of the main goals in studying visual information processing is to specify the representations at each level and the temporal sequence between

Spatial attention: Visual selection and deployment over space The attentional spotlight and spatial cueing Attentional shifts, splits, and resolution Object-based Selection The visual search paradigm Top-down and bottom-up control of attention Inhibitory mechanisms of attention Invalid cueing Negative priming Inhibition of return Temporal attention: Visual selection and deployment over time Single target search Attentional blink and attentional dwell time Repetition blindness NEURAL MECHANISMS OF SELECTION Single-cell physiological method Event-related potentials Functional imaging: PET and fMRI

In three experiments, subjects attempted to track multiple items as they moved independently and unpredictably about a display. Performance was not impaired when the items were briefly (but completely) occluded at various times during their motion, suggesting that occlusion is taken into account when computing enduring perceptual objecthood. Unimpaired performance required the presence of accretion and deletion cues along fixed contours at the occluding boundaries. Performance was impaired when items were present on the visual field at the same times and to the same degrees as in the occlusion conditions, but disappeared and reappeared in ways which did not implicate the presence of occluding surfaces (e.g. by imploding and exploding into and out of existence, instead of accreting and deleting along a fixed contour). Unimpaired performance did not require visible occluders (i.e. Michotte’s tunnel effect) or globally consistent occluder positions. We discuss implications of these results for theories of objecthood in visual attention. What is an object? This is a question which draws together researchers from

Efficient categorizations of complex visual stimuli require effective encodings of their distinctive properties. However, the question remains of how processes of object and scene categorization use the information associated with different perceptual spatial scales. The psychophysics of scale perception suggests that recognition uses coarse blobs before fine scale edges, because the former is perceptually available before the latter. Although possible, this perceptually determined scenario neglects the nature of the task the recognition system must solve. If different spatial scales transmit different information about the input, an identical scene might be flexibly encoded and perceived at the scale that optimizes information for the considered task—i.e., the diagnostic scale. This paper tests the hypothesis that scale diagnosticity can determine scale selection for recognition. Experiment 1 tested whether coarse and fine spatial scales were both available at the onset of scene categorization. The second experiment tested that the selection of one scale could change depending on the diagnostic information present at this scale. The third and fourth experiments investigated whether scalespecific cues were independently processed, or whether they perceptually cooperated in the recognition of the input scene. Results suggest that a mandatory low-level registration of multiple spatial scales promotes flexible scene encodings, perceptions, and categorizations.

This article presents a theory that inte~ates space-based and object-based approaches to visual attention. The theory puts together M. P. van Oeffelen and P. G. Vos's ( 1982, 1983) COntour DEtector (CODE) theory of perceptual grouping by proximity with C. Bundesen's (1990) theory of visual attention (TVA). CODE provides input to TVA, accounting for spatially based between-object selection, and TVA converts the input to output, accounting for feature- and category-based withinobject selection. CODE clusters nearby items into perceptual groups that are both perceptual objects and regions of space, thereby integrating object-based and space-based approaches to attention. The combined theory provides a quantitative account of the effects of grouping by proximity and dis~nce between items on reaction time and accuracy data in 7 empirical situations that shaped the current literature on visual spatial attention. For the last decade the attention literature has been embroiled in a debate over the nature of visual spatial attention that focuses on the "thing " that attention selects (e.g., Baylis &

This book chapter examines the role of spatial attention from a computational perspective. It is intended as an overview for cognitive scientists interested in computational modeling of attentional phenomena. Because the function of attention can be understood only in its relation to visual information processing, we model not only the attentional system itself, but also the process of object recognition. We begin by presenting a basic model of object recognition, showing that interference prevents the system from reliably processing multiple, complex stimuli, and then we show how a simple mechanism of attentional selection can reduce this interference. Our first goal is to present a model that is computationally adequate, that is, a model that has the computational power to perform the sort of visual information processing tasks that people do. We then turn to simulations showing that the model can account for diverse experimental data, including: the benefit of attentional precuing, the time course of attention shifts, the effect of spatial uncertainty, the effect of irrelevant stimuli, the relation of object-based and location-based selection, and visual search. We conclude with a discussion of basic questions about computation modeling, including: Why build computational models? What makes a model compelling? When is a model right or wrong? Should one opt for depth or breadth in model coverage?

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