When do luminance changes capture attention?

Control of Attention in Rhesus Monkeys Measured Using a Flanker Task

At least three processes determine whether information we encounter is attended to or ignored. First, attentional capture occurs when attention is drawn automatically by "bottom up" processes, to distinctive, salient, rewarding, or unexpected stimuli when they enter our sensory field. Second, "top down" attentional control can direct cognitive processing towards goal-relevant targets. Third, selection history, operates through repeated exposure to a stimulus, particularly when associated with reward. Attentional control is measured using tasks that require subjects to selectively attend to goal-relevant stimuli in the face of distractions. In the Eriksen flanker task, human participants report which direction a centrally placed arrow is facing, while ignoring "flanking" arrows that may point in the opposite direction. Attentional control is evident to the extent that performance reflects only the direction of the central arrow. We describe four experiments in which we systematically assessed attentional control in rhesus monkeys using a flanker task. In Experiment 1, monkeys responded according to the identity of a central target, and accuracy and latency varied systematically with manipulations of flanking stimuli, validating our adaptation of the Eriksen flanker task. We then tested for converging evidence of attentional control across three experiments in which flanker performance was modulated by the distance separating targets from flankers (Experiment 2), luminance differences (Experiment 3), and differences in associative value (Experiment 4). The approach described is a new and reliable measure of attentional control in rhesus monkeys that can be applied to a wide range of situations with freely behaving animals.

How top-down and bottom-up attention modulate risky choice

We examine how bottom-up (or stimulus-driven) and top-down (or goal-driven) processes govern the distribution of attention in risky choice. In three experiments, participants chose between a certain payoff and the chance of receiving a payoff drawn randomly from an array of eight numbers. We tested the hypothesis that initial attention is driven by perceptual properties of the stimulus (e.g., font size of the numbers), but subsequent choice is goal-driven (e.g., win the best outcome). Two experiments in which task framing (goal driven) and font size (stimulus driven) were manipulated demonstrated that payoffs with the highest values and the largest font sizes had the greatest impact on choice. The third experiment added a number in large font to the array, which could not be an outcome of the gamble (i.e., a distractor). Eye movement and choice data indicated that although the distractor attracted attention, it had no influence on option selection. Together with computational modeling analyses, the results suggest that perceptual salience can induce bottom-up effects of overt selection but that the perceived value of information is the crucial arbiter of intentional control over risky choice.

RT Slowing to Valid Cues on a Reflexive Attention Task in Children and Young Adults

Peripheral cueing tasks can be used to measure reflexive (automatic) attention. In these tasks, increases in response time or RT (costs) typically follow contralateral (invalid) cues as attention must move from the location of the cue to the target. Reductions in RT (benefits) to a target typically follow ipsilateral (valid) cues because the cue draws attention to where the target will appear. Two exceptions to RT benefits are inhibition of return (IOR) and masking. IOR is the tendency to respond slower to targets that appear in locations attended within the last 200–2000 ms. Masking occurs when the visibility of a target is blocked by another stimulus (e.g., the cue). Herein, we describe two experiments, both using a modified Posner task with “earth rockets” as cues and “alien spaceships” as targets. Cues were equally likely to appear on the left or right side of a display following targets. Participants were instructed to press a left or right key corresponding to a left or right target. In Experiment 1, we obtained data from 203 children (10.58–16.55 years old). We discovered unexpected costs following cues that typically provide RT benefits. In Experiment 2, we explored IOR, masking, and age differences in the occurrence of these costs. We manipulated the cue-target temporal distance (“stimulus onset asynchrony” or SOA) to explore IOR and the cue-target spatial distance to explore masking. We also considered a wider age range. Sixty-three children and 41 young adults participated. Experiment 2 revealed a three-way interaction between SOA, spatial distance, and age. At the shorter SOA (100 ms) and moderate spatial distance, unexpected costs followed valid cues for younger children (7.07–10.15 years old). These costs also occurred in young adults (18.00–23.02 years old) following far distance cues at this SOA. At the longer SOA (200 ms), these costs followed moderate and far cues for younger children and near cues for young adults. Older children (10.31–14.92 years) did not have unexpected costs. We explain the findings in terms of masking, IOR, and possible developmental mechanisms.

Temporal fractals in movies and mind

Fractal patterns are seemingly everywhere. They can be analyzed through Fourier and power analyses, and other methods. Cutting, DeLong, and Nothelfer (2010) analyzed as time-series data the fluctuations of shot durations in 150 popular movies released over 70 years. They found that these patterns had become increasingly fractal-like and concluded that they might be linked to those found in the results of psychological tasks involving attention. To explore this possibility further, we began by analyzing the shot patterns of almost twice as many movies released over a century. The increasing fractal-like nature of shot patterns is affirmed, as determined by both a slope measure and a long-range dependence measure, neither of which is sensitive to the vector lengths of their inputs within the ranges explored here. But the main reason for increased long-range dependence is related to, but not caused by, the increasing vector length of the shot-series samples. It appears that, in generating increasingly fractal-like patterns, filmmakers have systematically explored dimensions that are important for holding our attention-shot durations, scene durations, motion, and sound amplitude-and have crafted fluctuations in them like those of our endogenous attention patterns. Other dimensions-luminance, clutter, and shot scale-are important to film style but their variations seem not to be important to holding viewers' moment-to-moment attention and have not changed in their fractional dimension over time.

Do sudden onsets need to be perceived as new objects to capture attention? The interplay between sensory transients and display configuration

Yantis and Jonides (1984) and Jonides and Yantis (1988) reported robust involuntary attentional capture by sudden-onsets, the origin of which has been debated. Prominent accounts have highlighted aspects that include the "new object" status of a sudden-onset (Yantis & Hillstrom, 1994) and the substantial luminance changes accompanying their appearance (Gellatly, Cole & Blurton, 1999; Franconeri, Hollingworth & Simons, 2005), including relative differences in the amount of sensory change between target and nontarget items (Pinto, Olivers & Theeuwes, 2008). In this research we dissociate the amount of sensory change accompanying sudden onsets from the extent to which they appear as newly created objects in search displays. We attempted to determine the relative contribution of local sensory changes and display configuration to attentional capture by sudden-onsets. We showed that the display configuration of old objects modulates the impact of capture caused by sudden-onsets.

Reinstating salience effects over time: the influence of stimulus changes on visual selection behavior over a sequence of eye movements

Recently, we showed that salience affects initial saccades only in a static stimulus environment; subsequent saccades were unaffected by salience but, instead, were directed in line with task requirements (Siebold, van Zoest, & Donk, PLoS ONE 6(9): e23552, 2011). Yet multiple studies have shown that people tend to fixate salient regions more often than nonsalient ones when they are looking at images--in particular, when salience is defined by dynamic changes. The goal of the present study was to investigate how oculomotor selection beyond an initial saccade is affected by salience as derived from changing, as opposed to static, stimuli. Observers were presented with displays containing two fixation dots, one target, one distractor, and multiple background elements. They were instructed to fixate on one of the fixation dots and make a speeded eye movement to the target, either directly or preceded by an initial eye movement to the other fixation dot. In Experiment 1, target and distractor differed in orientation contrast relative to the background, such that one was more salient than the other, whereas in Experiments 2 and 3, the orientation contrast between the two elements was identical. Here, salience was implemented by a continuous luminance flicker or by a difference in luminance contrast, respectively, which was presented either simultaneously with display onset or contingent upon the first saccade. The results showed that in all experiments, initial saccades were strongly guided by salience, whereas second saccades were consistently goal directed if the salience manipulation was present from display onset. However, if the flicker or luminance contrast was presented contingent upon the initial saccade, salience effects were reinstated. We argue that salience effects are short-lived but can be reinstated if new information is presented, even when this occurs during an eye movement.