How Does Information Processing Speed Relate to the Attentional Blink?

Background When observers are asked to identify two targets in rapid sequence, they often suffer profound performance deficits for the second target, even when the spatial location of the targets is known. This attentional blink (AB) is usually attributed to the time required to process a previous target, implying that a link should exist between individual differences in information processing speed and the AB. Methodology/Principal Findings The present work investigated this question by examining the relationship between a rapid automatized naming task typically used to assess information-processing speed and the magnitude of the AB. The results indicated that faster processing actually resulted in a greater AB, but only when targets were presented amongst high similarity distractors. When target-distractor similarity was minimal, processing speed was unrelated to the AB. Conclusions/Significance Our findings indicate that information-processing speed is unrelated to target processing efficiency per se, but rather to individual differences in observers' ability to suppress distractors. This is consistent with evidence that individuals who are able to avoid distraction are more efficient at deploying temporal attention, but argues against a direct link between general processing speed and efficient information selection.

Effects of addiction-associated and affective stimuli on the attentional blink in a sample of abstinent opiate dependent patients

The attentional blink reveals the limits of the brain's ability in information processing. It has been extensively studied in people with neurological and psychiatric disturbances to explore the temporal characteristics of information processing and exami

A dose-response investigation of the attentional blink during sleep restriction /

Recent dose-response sleep restriction studies, in which nightly sleep is curtailed to varying degrees (e.g., 3-, 5-, 7-hours), have found cumulative, dose-dependent changes in sleepiness, mood, and reaction time. However, brain activity has typically not been measured, and attentionbased tests employed tend to be simple (e.g., reaction time). One task addressing the behavioural and electrophysiological aspects of a specific attention mechanism is the Attentional Blink (AB), which shows that the report accuracy of a second target (T2) is impaired when it is presented soon after a first target (Tl). The aim of the present study was to examine behavioural and electrophysioiogical responses to the AB task to elucidate how sleep restriction impacts attentional capacity. Thirty-six young-adults spent four consecutive days and nights in a sleep laboratory where sleep, food, and activity were controlled. Nightly sleep began with a baseline sleep (8 hours), followed by two nights of sleep restriction (3,5 or 8 hours of sleep), and a recovery sleep (8 hours). An AB task was administered each day at 11 am. Results from a basic battery oftests (e.g., sleepiness, mood, reaction time) confirmed the effectiveness of the sleep restriction manipulation. In terms of the AB, baseline performance was typical (Le., T2 accuracy impaired when presented soon after Tl); however, no changes in any AB behavioural measures were observed following sleep restriction for the 3- or 5-hour groups. The only statistically significant electrophysiological result was a decrease in P300 amplitude (for Tl) from baseline to the second sleep restriction night for the 3-hour group. Therefore, following a brief, two night sleep restriction paradigm, brain functioning was impaired for the TI of the AB in the absence of behavioural deficit. Study limitations and future directions are discussed.

An electrophysiological investigation into the influence of affect on the attentional blink

Accuracy at identifying or detecting a second-target (T2) is reduced if presented within approximately 500 ms of the first target (TI) - an attentional blink (AB). Affect has previously been shown to influence the magnitude of the AB such that positive affect (PA) is associated with smaller ABs. To account for these findings, Olivers and Nieuwenhuis (2005) proposed an overinvestment hypothesis where P A was said to reduce overinvestment of attentional resources in TI and distractors, leaving more resources for T2. In the present study, P3, CNV, and average activation on distracter-only trials were used to measure attentional investment. The goal was to investigate whether these electrophysiological measures mediated the relationship between self-reported affect and the AB. Results demonstrated that investment of attentional resources was not associated with self-reported affect, or AB magnitude. However, self-report measures of affect, personality and electrophysiological measures of investment did follow some predictions derived from the overinvestment hypothesis.

An Electrophysiological Investigation into the Role of Cognitive Control in the Attentional Blink

Accuracy at reporting a second-target (T2) is reduced if it is presented within approximately 500 ms of the first target (T1) – an attentional blink (AB). Early models explained the AB in terms of attentional limitations creating a processing bottleneck such that T2 processing would be impaired while T1 processing was ongoing. Theoretical models of the AB have more recently been expanded to include the role of cognitive control. In this dissertation I propose that cognitive control, defined as the optimization of information processing in order to achieve goals, is maladapted to the dual-task conditions of the AB task in that cognitive control optimizes the T1 goal, due to its temporal proximity, at the cost of T2. I start with the concept that the role of cognitive control is to serve goals, and that how goals are conceived of and the degree of motivation associated with those goals will determine whether cognitive control will create the condition that cause the AB. This leads to the hypothesis that electrophysiological measures of cognitive control and the degree of attentional investment resulting from cognitive control modulate the AB and explain individual differences in the AB. In a series of four studies feedback-related N2 amplitude, (reflecting individual differences in the strength of cognitive control), and event-related and resting alpha frequency oscillatory activity (reflecting degree of attentional investment), are used to explain both intra- and inter-individual variability in performance on the AB task. Results supported the hypothesis that stronger cognitive control and greater attentional investment are associated with larger AB magnitudes. Attentional investment, as measured by alpha frequency oscillations, and cognitive control, as measured by the feedback-related N2, did not relate to each other as hypothesized. It is proposed that instead of a measure of attentional investment alone, alpha frequency oscillatory activity actually reflects control over information processing over time, in other words the timing of attention. With this conceptualization, various aspects of cognitive control, either related to the management of goals (feedback-related N2) or the management of attention over time to meet goals, explain variability in the AB.

Individual Differences in Global/Local Processing Bias and the Attentional Blink

When the second of two targets (T2) is presented temporally close to the first target (T1) in rapid serial visual presentation, accuracy to detect/identify T2 is markedly reduced as compared to longer target separations. This is known as the attentional blink (AB), and is thought to reflect a limitation of selective attention. While most individuals show an AB, research has demonstrated that individuals are variously susceptible to this effect. To explain these differences, Dale and Arnell (2010) examined whether dispositional differences in attentional breadth, as measured by the Navon letter task, could predict individual AB magnitude. They found that individuals who showed a natural bias toward the broad, global level of Navon letter stimuli were less susceptible to the AB as compared to individuals who showed a natural bias toward the detailed, local aspects of Navon letter stimuli. This suggests that individuals who naturally broaden their attention can overcome the AB. However, it was unclear how stable these individual differences were over time, and whether a variety of global/local tasks could predict AB performance. As such, the purpose of this dissertation was to investigate, through four empirical studies, the nature of individual differences in both global/local bias and the AB, and how these differences in attentional breadth can modulate AB performance. Study 1 was designed to examine the stability of dispositional global/local biases over time, as well as the relationships among three different global/local processing measures. Study 2 examined the stability of individual differences in the AB, as well as the relationship among two distinct AB tasks. Study 3 examined whether the three distinct global/local tasks used in Study 1 could predict performance on the two AB tasks from Study 2. Finally, Study 4 explored whether individual differences in global/local bias could be manipulated by exposing participants to high/low spatial frequencies and Navon stimuli. In Study 1, I showed that dispositional differences in global/local bias were reliable over a period of at least a week, demonstrating that these individual biases may be trait-like. However, the three tasks that purportedly measure global/local bias were unrelated to each other, suggesting that they measure unique aspects of global/local processing. In Study 2, I found that individual variation in AB performance was also reliable over a period of at least a week, and that the two AB task versions were correlated. Study 3 showed that dispositional global/local biases, as measured by the three tasks from Study 1, predicted AB magnitude, such that individuals who were naturally globally biased had smaller ABs. Finally, in Study 4 I demonstrated that these dispositional global/local biases are resistant to both spatial frequency and Navon letter manipulations, indicating that these differences are robust and intractable. Overall, the results of the four studies in this dissertation help clarify the role of individual differences in attentional breadth in selective attention.

Emotional stimuli reduce the attentional blink in sub-clinical anxious subjects. 'Los est??mulos emocionales reducen el parpadeo atencional (attentional blink) en sujetos con ansiedad subcl??nica'

Resumen tomado de la publicaci??n

How the brain blinks: towards a neurocognitive model of the attentional blink

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset-the attentional blink (AB). We provide an overview of recent neuroscientific studies devoted to analyze the neural processes underlying the AB and their temporal dynamics. The available evidence points to an attentional network involving temporal, right-parietal and frontal cortex, and suggests that the components of this neural network interact by means of synchronization and stimulus-induced desynchronization in the beta frequency range. We set up a neurocognitive scenario describing how the AB might emerge and why it depends on the presence of masks and the other event(s) the targets are embedded in. The scenario supports the idea that the AB arises from "biased competition", with the top-down bias being generated by parietal-frontal interactions and the competition taking place between stimulus codes in temporal cortex.

Lag-1 sparing in the attentional blink: benefits and costs of integrating two events into a single episode

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset-the attentional blink. However, if T2 immediately follows T1, performance is often reported being as good as that at long lags-the so-called Lag-1 sparing effect. Two experiments investigated the mechanisms underlying this effect. Experiment 1 showed that, at Lag 1, requiring subjects to correctly report both identity and temporal order of targets produces relatively good performance on T2 but relatively bad performance on T1. Experiment 2 confirmed that subjects often confuse target order at short lags, especially if the two targets are equally easy to discriminate. Results suggest that, if two targets appear in close succession, they compete for attentional resources. If the two competitors are of unequal strength the stronger one is more likely to win and be reported at the expense of the other. If the two are equally strong, however, they will often be integrated into the same attentional episode and thus get both access to attentional resources. But this comes with a cost, as it eliminates information about the targets' temporal order.

Target integration and the attentional blink

If people monitor a visual stimulus stream for targets they often miss the second (T2) if it appears soon after the first (T1)-the attentional blink. There is one exception: T2 is often not missed if it appears right after T1, i.e., at lag 1. This lag-l sparing is commonly attributed to the possibility that T1 processing opens an attentional gate, which may be so sluggish that an early T2 can slip in before it closes. We investigated why the gate may close and exclude further stimuli from processing. We compared a control approach, which assumes that gate closing is exogenously triggered by the appearance of nontargets, and an integration approach, which assumes that gate closing is under endogenous control. As predicted by the latter but not the former, T2 performance and target reversals were strongly affected by the temporal distance between T1 and T2, whereas the presence or the absence of a nontarget intervening between T1 and T2 had little impact. (c) 2005 Elsevier B.V. All rights reserved.

Short-term memory and the attentional blink: capacity versus content

When people monitor the rapid serial visual presentation (RSVP) of stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset, a phenomenon known as the attentional blink (AB). We found that overall performance in an RSVP task was impaired by a concurrent short-term memory (STM) task and, furthermore, that this effect increased when STM load was higher and when its content was more task relevant. Loading visually defined stimuli and adding articulatory suppression further impaired performance on the RSVP task, but the size of the AB over time (i.e., T1-T2 lag) remained unaffected by load or content. This suggested that at least part of the performance in an RSVP task reflects interference between competing codes within STM, as interference models have held, whereas the AB proper reflects capacity limitations in the transfer to STM, as consolidation models have claimed.

The attentional blink reveals sluggish attentional shifting in adolescents with specific language impairment

Rapid processing deficits have been the subject of much debate in the literature on specific language impairment (SLI). Hari and Renvall (2001) [Hari, R. & Renvall, H. (2001). Impaired processing of rapid stimulus sequences in dyslexia. Trends in cognitive sciences, 5, 525–532.] proposed that the source of this deficit can be attributed to sluggish attentional shifting abilities. That is, more time is required to shift attention between stimuli. To test this claim, 26 adolescents with SLI (divided into two subgroups to control for differences in non-verbal intelligence) and 14 controls were presented with a rapid serial visual presentation task. In this task participants were asked to detect two visual targets presented serially with distracter items with varying inter-target intervals (i.e., time difference between targets). This task was designed to elicit an attentional blink (AB). The AB describes the phenomenon whereby non-impaired individuals are less likely to report the second of two targets presented within 200–500 ms of each other. After controlling for group differences in non-verbal intelligence, the SLI group was found to be significantly less accurate than the control group at successfully reporting the second target at inter-target intervals of 100, 200, 300, 400 and 800 ms. The results were interpreted to suggest that adolescents with language impairments have an AB which differs from non-impaired individuals in both magnitude and duration.