Correction to: A Limiting Channel Capacity of Visual Perception: Spreading Attention Divides the Rates of Perceptual Processes.

An error occurred in labeling the data in Fig. 5a-b, p. 2661. The figure caption is correct as printed. A corrected Fig. 5 is below.

A Limiting Channel Capacity of Visual Perception: Spreading Attention Divides the Rates of Perceptual Processes.

This study investigated effects of divided attention on the temporal processes of perception. During continuous watch periods, observers responded to sudden changes in the color or direction of any one of a set of moving objects. The set size of moving objects was a primary variable. A simple detection task required responses to any display change, and a selective task required responses to a subset of the changes. Detection rates at successive points in time were measured by response time (RT) hazard functions.The principal finding was that increasing the set size divided the detection rates-and these divisive effects were essentially constant over time and over the time-varying influence of the target signals and response tasks. The set size, visual target signal, and response task exerted mutually invariant influence on detection rates at given times, indicating independent joint contributions of parallel component processes. The lawful structure of these effects was measured by RT hazard functions but not by RTs as such. The results generalized the time-invariant divisive effects of set size on visual process rates found by Lappin, Morse, & Seiffert (Attention, Perception, & Psychophysics, 78, 2469-2493, 2016). These findings suggest that the rate of visual perception has a limiting channel capacity.

Optimistic metacognitive judgments predict poor performance in relatively complex visual tasks.

In some cases, people overestimate how much they can see. This can produce a metacognitive blind spot that may lead participants to devote fewer cognitive resources than a visual task demands. However, little research has tested whether individuals who are particularly optimistic about their visual capabilities are susceptible to poor visual performance. We tested whether optimistic metacognitive judgments would predict poor performance in a visual task, especially when it placed a large attentional load on the participant, and when it required balancing between multiple sources of information. We tested participants in a simplified battle command simulation in which they were asked to detect visual changes. Participants who predicted spatially expansive visual attention performance performed more poorly in the change detection task when the task required tracking larger numbers of aircraft, and when it included a secondary change-list display.

Are failures to look, to represent, or to learn associated with change blindness during screen-capture video learning?

Although phenomena such as change blindness and inattentional blindness are robust, it is not entirely clear how these failures of visual awareness are related to failures to attend to visual information, to represent it, and to ultimately learn in visual environments. On some views, failures of visual awareness such as change blindness underestimate the true extent of otherwise rich visual representations. This might occur if people did represent the changing features but failed to compare them across views. In contrast, other approaches emphasize visual representations that are created only when they are functional. On this view, change blindness may be associated with poor representations of the changing properties. It is possible to compromise and propose that representational richness varies across contexts, but then it becomes important to detail relationships among attention, awareness, and learning in specific, but applicable, settings. We therefore assessed these relationships in an important visual setting: screen-captured instructional videos. In two experiments, we tested the degree to which attention (as measured by gaze) predicts change detection, and whether change detection is associated with visual representations and content learning. We observed that attention sometimes predicted change detection, and that change detection was associated with representations of attended objects. However, there was no relationship between change detection and learning.

The channel capacity of visual awareness divided among multiple moving objects.

If attention is distributed among multiple moving objects, how does this divided attention affect the temporal process for detecting a specific target motion? Well-trained observers in three experiments monitored ongoing random motions of multiple objects, trying to rapidly detect non-random target motions. Response time hazard rates revealed a simple lawful structure of the detection processes. Target detection rates (hazard rates, in bits /s) were inversely proportional to the number of observed objects. Detection rates at any response time and in any condition equaled a product of two parallel (functionally independent and concurrent) visual processes: visual awareness and motion integration. The rate of visual awareness was inversely proportional to Set Size (n = 1-12), constant over time, and invariant with integrated motion information. Thus, a single rate parameter, indicating a constant channel capacity of visual awareness, described detection rates over a wide range of conditions and response times. During an initial interval of roughly 0.5 s, detection rates increased proportionally with the duration and length of motion; but after this initial integration, detection rates were constant, independent of the time the target remained undetected. The relationship between the quantity of visual information and detection rates was simpler than anticipated by contemporary theories of attention, perception, and performance.

Looking ahead: attending to anticipatory locations increases perception of control.

When people manipulate a moving object, such as writing with a pen or driving a car, they experience their actions as intimately related to the object's motion, that is they perceive control. Here, we tested the hypothesis that observers would feel more control over a moving object if an unrelated task drew attention to a location to which the object subsequently moved. Participants steered an object within a narrow path and discriminated the color of a flash that appeared briefly close to the object. Across two experiments, participants provided higher ratings of perceived control when an object moved over a flash's location than when an object moved away from a flash's location. This result suggests that we use the location of spatial attention to determine the perception of control. If an object goes where we are attending, we feel like we made it go there.

Direction-selective patterns of activity in human visual cortex suggest common neural substrates for different types of motion.

A sense of motion can be elicited by the movement of both luminance- and texture-defined patterns, what is commonly referred to as first- and second-order, respectively. Although there are differences in the perception of these two classes of motion stimuli, including differences in temporal and spatial sensitivity, it is debated whether common or separate direction-selective mechanisms are responsible for processing these two types of motion. Here, we measured direction-selective responses to luminance- and texture-defined motion in the human visual cortex by using functional MRI (fMRI) in conjunction with multivariate pattern analysis (MVPA). We found evidence of direction selectivity for both types of motion in all early visual areas (V1, V2, V3, V3A, V4, and MT+), implying that none of these early visual areas is specialized for processing a specific type of motion. More importantly, linear classifiers trained with cortical activity patterns to one type of motion (e.g., first-order motion) could reliably classify the direction of motion defined by the other type (e.g., second-order motion). Our results suggest that the direction-selective mechanisms that respond to these two types of motion share similar spatial distributions in the early visual cortex, consistent with the possibility that common mechanisms are responsible for processing both types of motion.

How Many Objects are You Worth? Quantification of the Self-Motion Load on Multiple Object Tracking.

Perhaps walking and chewing gum is effortless, but walking and tracking moving objects is not. Multiple object tracking is impaired by walking from one location to another, suggesting that updating location of the self puts demands on object tracking processes. Here, we quantified the cost of self-motion in terms of the tracking load. Participants in a virtual environment tracked a variable number of targets (1-5) among distractors while either staying in one place or moving along a path that was similar to the objects' motion. At the end of each trial, participants decided whether a probed dot was a target or distractor. As in our previous work, self-motion significantly impaired performance in tracking multiple targets. Quantifying tracking capacity for each individual under move versus stay conditions further revealed that self-motion during tracking produced a cost to capacity of about 0.8 (±0.2) objects. Tracking your own motion is worth about one object, suggesting that updating the location of the self is similar, but perhaps slightly easier, than updating locations of objects.

Tracking objects that move where they are headed.

Previous work has demonstrated that the ability to keep track of moving objects is improved when the objects have unique visual features, such as color or shape. In the present study, we investigated how orientation information is used during the tracking of objects. Orientation is an interesting feature to explore in moving objects because it is directional and is often informative of the direction of motion. Most objects move forward, in the direction they are oriented. In the present experiments, participants tracked a subset of moving isosceles triangles whose orientations were constant, related, or unrelated to the direction of motion. In the standard multiple object tracking (MOT) task, tracking performance improved when orientations were unique and remained constant, but not when orientation and direction of motion were aligned. In the target recovery task, in which MOT was interrupted by a brief blanking of the display, performance did improve when orientation and direction were aligned. In the final experiment, results showed that orientation was not used before the blank to predict future target locations, but was instead used after the blank. We concluded that people use orientation to compare a stored representation to target position for recovery of lost targets.

Tracking planets and moons: mechanisms of object tracking revealed with a new paradigm.

People can attend to and track multiple moving objects over time. Cognitive theories of this ability emphasize location information and differ on the importance of motion information. Results from several experiments have shown that increasing object speed impairs performance, although speed was confounded with other properties such as proximity of objects to one another. Here, we introduce a new paradigm to study multiple object tracking in which object speed and object proximity were manipulated independently. Like the motion of a planet and moon, each target-distractor pair rotated about both a common local point as well as the center of the screen. Tracking performance was strongly affected by object speed even when proximity was controlled. Additional results suggest that two different mechanisms are used in object tracking--one sensitive to speed and proximity and the other sensitive to the number of distractors. These observations support models of object tracking that include information about object motion and reject models that use location alone.

On the speed of pop-out in feature search.

When something unique is present in a scene, this element may become immediately visible and one has the impression that it pops out from the scene. This phenomenon, known as pop-out in the visual search literature, is thought to produce the fastest search possible, and response times for the detection of the pop-out target do not vary as a function of the number of nontargets. In this study, we challenge this notion and show that the detection of a given visual feature is faster for multiple targets than for a single pop-out target. However, when the task requires a detailed target analysis, the pop-out condition can be faster than the multiple-target condition. Current models of visual search are discussed in light of the findings.

Self-motion impairs multiple-object tracking.

Investigations of multiple-object tracking aim to further our understanding of how people perform common activities such as driving in traffic. However, tracking tasks in the laboratory have overlooked a crucial component of much real-world object tracking: self-motion. We investigated the hypothesis that keeping track of one's own movement impairs the ability to keep track of other moving objects. Participants attempted to track multiple targets while either moving around the tracking area or remaining in a fixed location. Participants' tracking performance was impaired when they moved to a new location during tracking, even when they were passively moved and when they did not see a shift in viewpoint. Self-motion impaired multiple-object tracking in both an immersive virtual environment and a real-world analog, but did not interfere with a difficult non-spatial tracking task. These results suggest that people use a common mechanism to track changes both to the location of moving objects around them and to keep track of their own location.

Conflicting motion information impairs multiple object tracking.

People can keep track of target objects as they move among identical distractors using only spatiotemporal information. We investigated whether or not participants use motion information during the moment-to-moment tracking of objects by adding motion to the texture of moving objects. The texture either remained static or moved relative to the object's direction of motion, either in the same direction, the opposite direction, or orthogonal to each object's trajectory. Results showed that, compared to the static texture condition, tracking performance was worse when the texture moved in the opposite direction of the object and better when the texture moved in the same direction as the object. Our results support the conclusion that motion information is used during the moment-to-moment tracking of objects. Motion information may either affect a representation of position or be used to periodically predict the future location of targets.

Looking at the center of the targets helps multiple object tracking.

The ability to move our gaze to locations of interest facilitates interactions in everyday life. Where do participants direct gaze when multiple locations are of interest simultaneously? We previously demonstrated that, when tracking several moving targets amidst distractors in a multiple object tracking (MOT) task, participants primarily looked at a central point in between the targets (H. M. Fehd & A. E. Seiffert, 2008). This strategy of center-looking is in contrast to a target-looking strategy where participants would saccade from target to target. Here we investigated what factors influence the use of center-looking as well as its effectiveness. By decreasing object speed, we determined that center-looking is not a result of avoiding costly eye movements during tracking. Decreasing object size showed that peripheral visibility is necessary for tracking, but that center-looking continues up to the limits of peripheral visibility. Further analysis revealed that participants often engaged in both target-looking and center-looking by switching gaze from the center to targets and back again. Directly comparing participants' performance when they either did or did not include center-looking along with target-looking revealed that center-looking facilitates tracking performance. These results suggest that there is value in looking at the center that relates directly to the process of tracking multiple objects.

Taking credit for success: the phenomenology of control in a goal-directed task.

We studied how people determine when they are in control of objects. In a computer task, participants moved a virtual boat towards a goal using a joystick to investigate how subjective control is shaped by (1) correspondence between motor actions and the visual consequences of those actions, and (2) attainment of higher-level goals. In Experiment 1, random discrepancies from joystick input (noise) decreased judgments of control (JoCs), but discrepancies that brought the boat closer to the goal and increased success (the autopilot) increased JoCs. In Experiment 2, participants raced to the goal against a computer-controlled rival boat while varying levels of noise interfered with each boat. Participants reached the goal more often and rated their own control higher when the computer rival had good control. Subjective control over moving objects depends partly on consistency between motor actions and their effects, but is also modulated by perceived success and competition.

Updating objects in visual short-term memory is feature selective.

The purpose of this study was to examine whether the process of updating information in visual short-term memory (VSTM) is object based. We investigated whether modifying the memory of one feature of an object would automatically promote refreshing the memory of all of its other features. The results showed that the facilitative effect of updating was specific to the updated feature of an object and did not spread to its nonupdated features. This feature-selective effect suggests that updating VSTM is not object based (Experiment 1), even though storage was object based (Experiment 2). Control experiments ruled out strategy-based (Experiment 3) and stimulus-related (Experiments 4-6) accounts. Feature-selective updating may indicate that the mechanism used to modify the contents of memory may have a different basis than that used to encode or store information in memory.

Attentional costs in multiple-object tracking.

Attentional demands of multiple-object tracking were demonstrated using a dual-task paradigm. Participants were asked to make speeded responses based on the pitch of a tone, while at the same time tracking four of eight identical dots. Tracking difficulty was manipulated either concurrent with or after the tone task. If increasing tracking difficulty increases attentional demands, its effect should be larger when it occurs concurrent with the tone. In Experiment 1, tracking difficulty was manipulated by having all dots briefly attract one another on some trials, causing a transient increase in dot proximity and speed. Results showed that increasing proximity and speed had a significantly larger effect when it occurred at the same time as the tone task. Experiments 2 and 3 showed that manipulating either proximity or speed independently was sufficient to produce this pattern of results. Experiment 4 manipulated object contrast, which affected tracking performance equally whether it occurred concurrent with or after the tone task. Overall, results support the view that the moment-to-moment tracking of multiple objects demands attention. Understanding what factors increase the attentional demands of tracking may help to explain why tracking is sometimes successful and at other times fails.

Eye movements during multiple object tracking: where do participants look?

Similar to the eye movements you might make when viewing a sports game, this experiment investigated where participants tend to look while keeping track of multiple objects. While eye movements were recorded, participants tracked either 1 or 3 of 8 red dots that moved randomly within a square box on a black background. Results indicated that participants fixated closer to targets more often than to distractors. However, on 3-target trials, fixation was closer to the center of the triangle formed by the targets more often than to any individual targets. This center-looking strategy seemed to reflect that people were grouping the targets into a single object rather than simultaneously minimizing all target eccentricities. Here we find that observers deliberately focus their eyes on a location that is different from the objects they are attending, perhaps as a consequence of representing those objects as a group.

Motion aftereffects specific to surface depth order: beyond binocular disparity.

Despite evidence for concurrent processing of motion and stereopsis from psychophysics and neurophysiology, the detailed relationship between depth and motion processing is not yet clear. Using the contingent aftereffect paradigm, we investigated how the order of surfaces presented across depth influenced motion perception. After having observers adapt to two superimposed populations of dots moving in opposite directions at different binocular disparities, we assessed how much of the motion aftereffect (MAE) was specific to absolute disparity and how much was specific to the depth order of the surfaces. The test contained two planes of moving dots at several different pairs of disparities and asked observers to report the MAE direction at one of the planes (the target). In addition to the disparity-contingent MAE (Verstraten, Verlinde, Fredericksen, & van de Grind, 1994), we found MAEs dependent on surface order. When the target surface was in front of another surface, observers more often reported the MAE in the direction opposite to the front adapting surface than the back. This effect was observed despite differences in absolute and relative disparity between the adapted and test surfaces. The results suggest that some motion information is represented in terms of surface depth order.

Functional MRI studies of human visual motion perception: texture, luminance, attention and after-effects.

Motion of an object is thought to be perceived independently of the object's surface properties. However, theoretical, neuropsychological and psychophysical observations have suggested that motion of textures, called 'second-order motion', may be processed by a separate system from luminance-based, or 'first-order', motion. Functional magnetic resonance imaging (fMRI) responses during passive viewing, attentional modulation and post-adaptation motion after-effects (MAE) of these stimuli were measured in seven retinotopic visual areas (labeled V1, V2, V3, VP, V4v, V3A and LO) and the motion-sensitive area MT/MST (V5). In all visual areas, responses were strikingly similar to motion of first- and second-order stimuli. These results differ from a prior investigation, because here the motion-specific responses were isolated. Directing attention towards and away from the motion elicited equivalent response modulation for the two types. Dramatic post-adaptation (MAE) differences in perception of the two stimuli were observed and fMRI activation mimicked perceptual changes, but did not reveal the processing differences. In fact, no visual area was found to respond selectively to the motion of second-order stimuli, suggesting that motion perception arises from a unified motion detection system.