Recent studies of eye movements in reading and other information processing tasks, such as music reading, typing, visual search, and scene perception, are reviewed. The major emphasis of the review is on reading as a specific example of cognitive processing. Basic topics discussed with respect to reading are (a) the characteristics of eye movements, (b) the perceptual span, (c) integration of information across saccades, (d) eye movement control, and (e) individual differences (including dyslexia). Similar topics are discussed with respect to the other tasks examined. The basic theme of the review is that eye movement data reflect moment-to-moment cognitive processes in the various tasks examined. Theoretical and practical considerations concerning the use of eye movement data are also discussed. Many studies using eye movements to investigate cognitive processes have appeared over the past 20 years. In an earlier review, I (Rayner, 1978b) argued that since the mid-1970s we have been in a third era of eye movement research and that the success of research in the current era would depend on the ingenuity of researchers in designing interesting and informative

Recent computational models of cognition have made good progress in accounting for the visual processes needed to encode external stimuli. However, these models typically incorporate simplified models of visual processing that assume a constant encoding time for all visual objects and do not distinguish between eye movements and shifts of attention. This paper presents a domain-independent computational model, EMMA, that provides a more rigorous account of eye movements and visual encoding and their interaction with a cognitive processor. The visual-encoding component of the model describes the effects of frequency and foveal eccentricity when encoding visual objects as internal representations. The eye-movement component describes the temporal and spatial characteristics of eye movements as they arise from shifts of visual attention. When integrated with a cognitive model, EMMA generates quantitative predictions concerning when and where the eyes move, thus serving to relate higher-level cognitive processes and attention shifts with lower-level eye-movement behavior. The paper evaluates EMMA in three illustrative domains — equation solving, reading, and visual search — and demonstrates how the model accounts for aspects of behavior that simpler models of cognitive and visual processing fail to explain.

We analyzed the coordination between gaze behavior, fingertip movements, and movements of the manipulated object when subjects reached for and grasped a bar and moved it to press a target-switch. Subjects almost exclusively fixated certain landmarks critical for the control of the task. Landmarks at which contact events took place were obligatory gaze targets. These included the grasp site on the bar, the target, and the support surface where the bar was returned after target contact. Any obstacle in the direct movement path and the tip of the bar were optional landmarks. Subjects never fixated the hand or the moving bar. Gaze and hand/bar movements were linked concerning landmarks, with gaze leading. The instant that gaze exited a given landmark coincided with a kinematic event at that landmark in a manner suggesting that subjects monitored critical kinematic events for phasic verification of

While we know a great deal about the dynamics and characteristics of eye movements in relatively simple tasks performed under reduced laboratory conditions, we know less about oculomotor behavior in complex, multi-step tasks. Complex tasks are not necessarily difficult. Part of the transition from ‘hard ’ to ‘easy ’ in completing complex tasks is the gradual reduction in conscious effort required to complete the sub-tasks. We are interested in learning whether high-level perceptual strategies can aid that transition. In the past, subjects performed relatively simple tasks or the eye movements themselves were the instructed task. But outside the laboratory vision is a tool, not the task. To study the oculomotor system in its native mode, we developed a wearable eyetracker that allows natural eye, head and whole-body movements. Using the over-learned, common task of hand-washing, we measured the global characteristics of fixation duration, saccade amplitude, and the spatial distribution of fixation positions. An important observation was the emergence of higher-order perceptual strategies in the complex task: while most fixations were related to the immediate action, a small number of fixations were made to objects relevant only to future actions. Based on a control task that differed only in the high-level goal, we conclude that the look-ahead fixations represent a task-dependent strategy, not a general behavior elicited by the salience or conspicuity of objects in the environment. We propose that the strategy of looking ahead to objects of future relevance supports the conscious percept of an environment seamless in time as well as in space.

This article describes and evaluates a class of methods for performing automated analysis of eye-movement protocols. Although eye movements have become increasingly popular as a tool for investigating user behavior, they can be extremely difficult and tedious to analyze. In this article we propose an approach to automating eye-movement protocol analysis by means of tracing—relating observed eye movements to the sequential predictions of a process model. We present three tracing methods that provide fast and robust analysis and alleviate the equipment noise and individual variability prevalent in typical eye-movement protocols. We also describe three applications of the tracing methods that demonstrate how the methods facilitate the use of eye movements in the study of user behavior and the inference of user intentions. 1.

We show that spike timing adds to the information content of spike trains for transiently presented stimuli but not for comparable steady-state stimuli, even if the latter elicit transient responses. Contrast responses of 22 single neurons in macaque V1 to periodic presentation of steady-state stimuli (drifting sinusoidal gratings) and transient stimuli (drifting edges) of optimal spatiotemporal parameters were recorded extracellularly. The responses were analyzed for contrast-dependent clustering in spaces determined by metrics sensitive to the temporal structure of spike trains. Two types of metrics, costbased spike time metrics and metrics based on Fourier harmonics of the response, were used. With both families of metrics, temporal coding of contrast is lacking in responses to drifting sinusoidal gratings of most (simple and complex) V1 A prevailing view of neural coding is that the meaningful signal

We investigated how the brain selects the targets for eye movements, a process in which the outcome of visual pro-cessing is converted into guided action. Macaque monkeys were trained to make a saccade to fixate a salient target presented either alone or with multiple distracters during visual search. Neural activity was recorded in the frontal eye field, a cortical area at the interface of visual process-ing and eye movement production. Neurons discharging after stimulus presentation and before saccade initiation were analyzed. The initial visual response of frontal eye field neurons was modulated by the presence of multiple stimuli and by whether a saccade was going to be pro-duced, but the initial visual response did not discriminate the target of the search array from the distracters. In the latent period before saccade initiation, the activity of most

In the primary visual cortex (V1) the contrast response function of many neurons saturates at high contrast and adapts depending on the visual stimulus. We propose that both effects---contrast saturation and adaptation---can be explained by a fast and a slow component in the synaptic dynamics. In our model the saturation is an effect of fast synaptic depression with a recovery time constant of about 200 ms. Fast synaptic depression leads to a contrast response function with a high gain for only a limited range of contrast values. Furthermore, we propose that slow adaptation of the transmitter release probability at the geniculocortical synapses is the underlying neural mechanism that accounts for contrast adaptation on a time scale of about 7 sec. For the functional role of contrast adaptation we make the hypothesis that it serves to achieve the best visual cortical representation of the geniculate input. This representation should maximize the mutual information between the cortical a...

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In popout search, humans and monkeys are affected by trialto-trial changes in stimulus features and target location. The neuronal mechanisms underlying such sequential effects have not been examined. Single neurons were recorded in the frontal eye field (FEF) of monkeys performing a popout search during which stimulus features and target position changed unpredictably across trials. Like previous studies, repetition of stimulus features improved performance. This feature-based facilitation of return was manifested in the target discrimination process in FEF: neurons discriminated the target from distractors earlier and better with repetition of stimulus features, corresponding to improvements in saccade latency and accuracy, respectively. The selective nature of gaze behavior has been shown elegantly by Yarbus (1967), among other researchers (for review, see Viviani,