this article. This paper has also benefited greatly from constructive feedback from Gordon Logan, Mike Stadler, and our other reviewers. We thank Joanie Sanchez for her assistance in running Experiment 1. This research was supported by a Social Science Faculty Research Award from Yale University. Portions of this research were presented at the Annual Meeting of the Association for Research in Ophthalmology and Vision, Fort Lauderdale, FL, in May, 1997, and at the Annual Meeting of the Psychonomic Society, Philadelphia, PA, in November, 1997

Search for conjunctions of highly discriminable features can be rapid or even parallel. This article explores, three possible accounts based on (a) perceptual segregation, (b) conjunction detectors, and (c) inhibition controlled separately by two or more distractor features. Search rates for conjunctions of color, size, orientation, and direction of motion correlated closely with an independent measure of perceptual segregation. However, they appeared unrelated to the physi-ology of single-unit responses. Each dimension contributed additively to conjunction search rates, suggesting that each was checked independently of the others. Unknown targets appear to be found only by serial search for each in turn. Searching through 4 sets of distractors was slower than searching through 2. The results suggest a modification of feature integration theory, in which attention is controlled not only by a unitary "window " but also by a form of feature-based inhibition. Objects in the real world vary in a large number of prop-erties, at least some of which appear to be coded by special-ized, independent channels or modules in the perceptual

blindness seems especially paradoxical: it implies that identifying "forest before trees." For later vision with processing has proceeded to the level of determining scrutiny, reverse hierarchy routines focus attention that one element is a conceptual or categorical repeti- to specific, active, low-level units, incorporating into tion of another---a repetition to which we are then blind. conscious perception detailed information available How can we know that two elements are similar if we there. Reverse Hierarchy Theory dissociates between are blind to the double occurrence? A similar paradox early explicit perception and implicit low-level vision, appears when we briefly view a scene containing many explaining a variety of phenomena. Feature search elements. We can more easily report the average value "pop-out" is attributed to high areas, where large re- of a parameter (such as the mean size or orientation of ceptive fields underlie spread attention detecting cat- elements) than ju

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

When an observer detects a target in a rapid stream of visual stimuli, there is a brief period of time during which the detection of subsequent targets is impaired. In this study, event-related potentials (ERPs) were recorded from normal adult observers to determine whether this "attentional blink " reflects a suppression of perceptual processes or an impairment in postperceptual processes. No suppression was observed during the attentional blink interval for ERP components corresponding to sensory processing (the P1 and N1 components) or semantic analysis (the N400 component). However, complete suppression was observed for an ERP component that has been hypothesized to reflect the updating of working memory (the P3 component). Results indicate that the attentional blink reflects an impairment in a postperceptual stage of processing. Over the past several decades, the vast majority of studies of visual attention have examined the operation of attention across space. In the visual search task, for example, a target item must be detected within an array of distractor items that are presented at different locations from the target. In recent

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 &

For a humanoid robot to interact easily with a person, the robot should have human-like sensory capabilities and attentional mechanisms. Particularly useful is an active vision head controlled by a visual attention system that selects viewpoints in the environment as a function of the robot's task. This paper describes a model of human visual attention called FeatureGate, which is a locally connected, pyramidal, artificial neural network that operates on 2D feature maps of the environment. Given a set of feature maps, and the description of a specific target, FeatureGate finds the location whose features most closely match those of the target. The paper describes the network, its implementation, a series of tests that characterize its performance with respect to a person's performance on a similar task, and its use in the control of an active vision system. 1 Introduction In many situations where a humanoid robot would be useful, the robot must work with aperson. This requires the r...

Four experiments investigated whether a highly salient color singleton can be ignored during serial search. Observers searched for a target letter among nontarget letters and were instructed to ignore an irrelevant, highly salient color singleton that was either compatible or incompatible with the response to the target letter. The results indicate that it was possible to prevent attentional capture by the irrelevant singleton only when both the target and the distractor color were known. When either the color of the target or the color of the to-be-ignored singleton were varied over trials, the irrelevant singleton captured attention. The ability to selectively falter singleton distractors during serial search depends on the presence of an attentional set for a specific feature value of both target and distractor. In the absence of a consistently predictable feature value of both target and distractor, top-down control is not possible. Among the most fundamental issues of visual attention research is the extent to which visual selection is controlled by the properties of the image or by the intentions, goals, and beliefs of the observer (for recent reviews, see Egeth &

A common task at almost any computer interface is that of searching for documents, which GUIs typically represent with icons. Oddly, little research has been done on the processes underlying icon search. This paper outlines the factors involved in icon search and proposes a model of the process. An experiment was conducted which suggests that the proposed model is sound, and that the most important factor in searching for files is the type of icons used. In general, simple icons (those discriminable based on a few features) seem to help users, while complex icons are no better than simple rectangles.

this article. We also thank Stephan Dekker for technical assistance