Individual differences within and across attentional blink tasks revisited

When the second of two targets (T2) is presented in close temporal proximity (within 200–500 ms) to the first (T1), the accuracy for reporting T2 is reduced relative to when the targets are separated by longer durations; this effect is known as the attentional blink (AB). Two recent studies have shown that individual differences in the magnitudes of the AB are stable both within a single testing session and over time. While one study found a large positive correlation between AB magnitudes when there was an attentional-set/task switch between T1 and T2 and when there was not, the other study found no relationship between the switch and no-switch paradigms. The present study was conducted to clarify this discrepancy by examining the reliability of, and relationships among, individual differences in AB performance on five different versions of the standard dual-target RSVP paradigm, three of which involved an attentional-set/task switch between T1 and T2, and two of which did not. Participants completed all five paradigms, and then returned 7–10 days later to again complete the same paradigms. The performance on all five versions was reliable both within and across testing sessions, demonstrating again that individual differences in AB performance are stable over time. In addition, all five AB versions were significantly intercorrelated, although the strengths of the relationships differed depending on the extent to which the T1 and T2 attentional sets/tasks overlapped. These findings provide evidence that multiple distinct dual-target RSVP tasks do share underlying variability, providing support for the use of different versions of the paradigm in the literature.     

Object file continuity predicts attentional blink magnitude

When asked to identify targets embedded within a rapid consecutive stream of visual stimuli, observers are less able to identify the second target (T2) when it is presented within half a second of the first (T1); this deficit has been termed the attentional blink (AB). Rapid serial visual presentation methodology was used to investigate the relationship between the AB and object files (episodic representations implicated in object identification and perceptual constancy). An inverse linear relationship was found between the degree of object file continuity and AB magnitude. An important locus of object file continuity was the intervening stream items between T1 and T2. The results are discussed in terms of the heuristic of the object file to preserve limited attentional capacity.     

Resting EEG in alpha and beta bands predicts individual differences in attentional blink magnitude

Accuracy for a second target (T2) is reduced when it is presented within 500 ms of a first target (T1) in a rapid serial visual presentation (RSVP) - an attentional blink (AB). There are reliable individual differences in the magnitude of the AB. Recent evidence has shown that the attentional approach that an individual typically adopts during a task or in anticipation of a task, as indicated by various measures, predicts individual differences in the AB deficit. It has yet to be observed whether indices of attentional approach when not engaged in a goal-directed task are also relevant to individual differences in the AB. The current studies investigated individual differences in the AB by examining their relationship with attention at rest using quantitative measures of EEG. Greater levels of alpha at rest were associated with larger AB magnitudes, where greater levels of beta at rest were associated with smaller AB magnitudes. Furthermore, individuals with more beta than alpha demonstrated a smaller AB effect than individuals with more alpha than beta. Our results suggest that greater attentional engagement at rest, when not engaged in a goal-directed task, is associated with smaller AB magnitudes.     

Executive control processes of working memory predict attentional blink magnitude over and above storage capacity

When two masked, to-be-attended targets are presented within approximately half a second of each other, performance on the second target (T2) suffers, relative to when the targets are presented further apart in time or when the first target (T1) can be ignored. This phenomenon is known as the attentional blink (AB). Colzato et al. (Psychon Bull Rev 14:1051–1057, 2007) used an individual differences approach to examine whether individual AB magnitude was predicted by individual differences in working memory (WM), using the operation span paradigm (OSPAN). They found that OSPAN score was inversely related to AB magnitude even when a fluid intelligence measure (Raven’s SPM) was partialled out. However, it is not clear from this study whether it was the executive control aspect of working memory, the capacity aspect of short-term memory, (or both), that related to AB magnitude. In the present study we used a variety of WM measures that required varying degrees of executive control. OSPAN was negatively related to AB magnitude with Raven’s SPM, reading comprehension, reading rate, and digit forward and backward partialled out. Backward and forward digit span did not predict AB magnitude. These results support the conclusion that a “working” executive component of WM predicts temporal limitations of selective attention beyond static STM capacity and general cognitive ability.     

The attention cascade model and attentional blink

An attention cascade model is proposed to account for attentional blinks in rapid serial visual presentation (RSVP) of stimuli. Data were collected using single characters in a single RSVP stream at 10Hz [Shih, S., & Reeves, A. (2007). Attentional capture in rapid serial visual presentation. Spatial Vision, 20(4), 301-315], and single words, in both single and dual RSVP streams at 19Hz [Potter, M. C., Staub, A., & O'Connor, D. H. (2002). The time course of competition for attention: Attention is initially labile. Journal of Experimental Psychology: Human Perception and Performance, 28(5), 1149-1162]. The model adopts similar architecture of the cognitive accounts of attentional blinks and employs computational details from theories of attention gating. The model has elaborated working memory and attention control mechanism. Both bottom-up and top-down salience are explicit in the model. Quantitative fits are good and the model parameters have plausible values. The model handles stimulus competition, lag 1 sparing, intrusion errors, and magnitude of the dip; it also accounts for commonly observed effects such as stimulus similarities (local and global), target+1 blank, and stimulus salience.     

Individual differences in electrophysiological responses to performance feedback predict AB magnitude

The attentional blink (AB) is observed when report accuracy for a second target (T2) is reduced if T2 is presented within approximately 500 ms of a first target (T1), but accuracy is relatively unimpaired at longer T1–T2 separations. The AB is thought to represent a transient cost of attending to a target, and reliable individual differences have been observed in its magnitude. Some models of the AB have suggested that cognitive control contributes to production of the AB, such that greater cognitive control is associated with larger AB magnitudes. Performance-monitoring functions are thought to modulate the strength of cognitive control, and those functions are indexed by event-related potentials in response to both endogenous and exogenous performance evaluation. Here we examined whether individual differences in the amplitudes to internal and external response feedback predict individual AB magnitudes. We found that electrophysiological responses to externally provided performance feedback, measured in two different tasks, did predict individual differences in AB magnitude, such that greater feedback-related N2 amplitudes were associated with larger AB magnitudes, regardless of the valence of the feedback.     

Individual differences in the ability to focus and divide attention

This research deals with individual differences in the ability to focus and divide attention. Eighty-five subjects performed visual search and auditory detection tasks in three conditions: single channel, focused attention, and divided attention. Reaction time (RT) was fastest in the single channel condition, intermediate in the focused attention condition, and longest in the divided attention condition, and these effects were much stronger in the auditory than the visual task. Correlations among RTs in the three conditions were very high within modality (>.88), and lower between modalities (.5 to .6). The correlational data was well fit by a model that included separate factors for the visual and auditory tasks. Measures from the three attentional conditions within each modality loaded equally on these factors. The data provided no evidence for distinct abilities to divide or focus attention.     

Individual differences in working memory capacity predict visual attention allocation

To the extent that individual differences in working memory capacity (WMC) reflect differences in attention (Baddeley, 1993; Engle, Kane, & Tuholski, 1999), differences in WMC should predict performance on visual attention tasks. Individuals who scored in the upper and lower quartiles on the OSPAN working memory test performed a modification of Egly and Homa’s (1984) selective attention task. In this task, the participants identified a central letter and localized a displaced letter flashed somewhere on one of three concentric rings. When the displaced letter occurred closer to fixation than the cue implied, high-WMC, but not low-WMC, individuals showed a cost in the letter localization task. This suggests that low-WMC participants allocated attention as a spotlight, whereas those with high WMC showed flexible allocation.     

Evidence for distinct attentional bottlenecks in attention switching and attentional blink tasks

E. Weichselgartner and G. A. Sperling (1987), using rapid serial visual presentation (RSVP), estimated that attention could be moved to a new spatial location within 300-400 ms. H. J. Müller and P. M. Rabbit (1989) used a spatial cuing task and found a similar time course for voluntarily redeploying attention. A separate phenomenon known as the attentional blink (AB) also follows a similar time course, yet occurs when participants attend to a single spatial location. The present study found that attention can be shifted more quickly than previously estimated and that part of the deficit observed during searches of spatially distinct RSVP streams is due to an AB. The results support some early and late selection accounts for the temporal dynamics of visual attention and suggest different bottlenecks during visual selection. The implications for visual search and visual processing are discussed.     

Rapid allocation of temporal attention in the attentional blink paradigm

How fast can information of a first target (T1) in a rapid serial visual presentation be used for top-down allocation of attention in time? A valid cue about the temporal position of a second target (T2) was integrated into T1. The data show that 100 ms after T1 onset, T2 was identified better than without cue, raising the conditional T2 performance. T1 apparently triggers a facilitative effect of attention, known from other paradigms such as peripheral cueing.     

The emotional attentional blink is robust to divided attention

The emotional attentional blink (EAB) refers to a temporary impairment in the ability to identify a target when it is preceded by an emotional distractor. It is thought to occur because the emotional salience of the distractor exogenously captures attention for a brief duration, rendering the target unattended and preventing it from reaching awareness. Here we tested the extent to which the EAB can be attenuated by inducing a diffuse top-down attentional state, which has been shown to improve target identification in an analogous attentional phenomenon, the attentional blink. Rapid sequences of landscape images were presented centrally, and participants reported the orientation of a ± 90° rotation of a landscape target. To induce a diffuse state of attention, participants were given a secondary task of monitoring for the appearance of a colored dot in the periphery. We found that emotional distractors impaired target recognition performance to comparable extents, regardless of whether or not participants concurrently performed the peripheral-monitoring task. Moreover, we found that performance of the secondary task led to an impaired ability to ignore neutral distractors. Subjective ratings of target vividness mirrored the behavioral accuracy, with frequent reports of intermediate levels of vividness suggesting that the EAB might impair target visibility in a graded manner. Our results demonstrate that the EAB is robust to manipulations of top-down attention, suggesting that the temporary capture of attention by emotionally salient stimuli involves processes that are distinct from those that produce the attentional blink.     

Personality predicts temporal attention costs in the attentional blink paradigm

Accuracy for a second target is reduced when it is presented within 500 msec of a first target. This phenomenon is called the attentional blink (AB). A diffused attentional state (via positive affect or an additional task) has been shown to reduce the AB, whereas a focused attentional state (via negative affect) has been shown to increase the AB, purportedly by influencing the amount of attentional investment and flexibility. In the present study, individual differences in personality traits related to positive affect, negative affect, and cognitive flexibility were used to predict individual differences in AB magnitude. As hypothesized, greater extraversion and openness predicted smaller ABs. Greater openness also predicted higher overall target accuracy. Greater neuroticism predicted larger ABs and lower overall target accuracy. Conscientiousness, associated with less cognitive flexibility, predicted lower overall target accuracy. Personality may modulate the AB by influencing overinvestment via dispositional tendencies toward more or less stringent or capable cognitive control.     

Spatial cuing does not affect the magnitude of the attentional blink

Identification of the second of two targets is impaired when the second target is presented less than about 500 msec after the first. Nieuwenstein, Chun, van der Lubbe, and Hooge (2005, Experiment 4) reported that the magnitude of this attentional blink (AB) is reduced when the location of the second target is precued. Here we show how that finding resulted from an artifact brought about by a ceiling imposed by data limitation. Instead of using an accuracy measure, the present work used a dynamic threshold-tracking procedure that was not constrained by a performance ceiling. The results show that, when the ceiling is removed, spatial cuing does not affect and is not affected by the AB. These results are consistent with the hypothesis that cue localization and target identification may take place along separate (dorsal and ventral) visual pathways.     

Individual differences in magnitude estimation of loudness

Twenty-two male and female subjects, aged 15 to 31 years, participated in two sessions, 11 weeks apart, of magnitude estimations of loudness. Stable individual differences in the exponent of the psychophysical power law, ψ=k?ⁿ, were shown. The correlation between subjects’ exponents of the first and second sessions was +.59. The generality of these findings and the origin of the individual differences were discussed.     

Memory search for the first target modulates the magnitude of the attentional blink

The resolution of temporal attention is limited in a manner that makes it difficult to identify two targets in short succession. This limitation produces the phenomenon known as the attentional blink (AB), in which processing of a first target (T1) impairs identification of a second target (T2). In the AB literature, there is broad agreement that increasing the time it takes to process T1 leads to a larger AB. One might, therefore, predict that increasing the number of possible T1 identities, or target set, from 1 to 16 would lead to a larger AB. We were surprised to find that this manipulation of T1 difficulty had no influence on AB magnitude. In subsequent experiments, we found that AB magnitude interacts with T1 processing time only under certain circumstances. Specifically, when the T1 task was either well masked or had to be completed online, we found a reliable interaction between AB magnitude and the target set size. When neither of these conditions was fulfilled, there was no interaction between target set size and the AB. Previous research found that when the target set changes from trial to trial, trials with more possible targets elicited a larger AB. In the present study, the target set is held constant, reducing the demands on working memory. Nevertheless, AB magnitude still interacts with target set size, as long as the T1 task cannot be processed offline. Thus, the act of searching memory delays subsequent processing, even when the role of working memory has been minimized.     

Individual differences in sensation seeking and attentional ability

Evidence is provided that high scores on the Zuckerman Sensation Seeking Scale are associated in the normal population with good focused-attention performance and poor distributed-attention performance. Focused-attention performance is assessed as the ability to select relevant information while ignoring irrelevant information, and distributed-attention performance is assessed as the ability to carry out concurrently two independent complex tasks. It is hypothesized that the observed disposition of attentional performance reflects differential patterns of arousal in individuals with high and low Sensation Seeking scores.     

Individual differences in recovery time from attentional capture

Working memory capacity reflects a core ability of the individual that affects performance on many cognitive tasks. Recent work has suggested that an important covariate of memory capacity is attentional control, and specifically that low-capacity individuals are more susceptible to attentional capture by distractors than high-capacity individuals are, with the latter being able to resist capture. Here, we tested an alternative account according to which all individuals are equally susceptible to attentional capture, but high-capacity individuals recover more quickly than low-capacity individuals. Using psychophysical and electrophysiological methods, we measured recovery time from attentional capture. In two experiments, we found that high- and low-capacity individuals showed equivalent attentional capture effects in the initial moments following capture, but that low-capacity individuals took much longer to recover than high-capacity individuals did. These results suggest that the poor attentional control associated with low capacity is due to slow disengagement from distractors.     

Delayed attentional engagement in the attentional blink

Observers often miss the 2nd of 2 visual targets (first target [T1] and second target [T2]) when these targets are presented closely in time; the attentional blink (AB). The authors hypothesized that the AB occurs because the attentional response to T2 is delayed by T1 processing, causing T2 to lose a competition for attention to the item that follows it. The authors investigated this hypothesis by determining whether the AB is attenuated when T2 is precued. The results from 4 experiments showed that the duration and magnitude of the AB were substantially reduced when T2 was precued. The observed improvement in T2 report did not occur at the expense of T1 report, suggesting that processing of T1 was already completed or was at least protected when the cue was presented. The authors conclude that, during the AB, there is a delay between detection and the selection of target candidates for consolidation in short-term memory.