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

Target Cueing Provides Support for Target- and Resource-Based Models of the Attentional Blink

The attentional blink (AB) describes a time-based deficit in processing the second of two masked targets. The AB is attenuated if successive targets appear between the first and final target, or if a cueing target is positioned before the final target. Using various speeds of stimulus presentation, the current study employed successive targets and cueing targets to confirm and extend an understanding of target-target cueing in the AB. In Experiment 1, three targets were presented sequentially at rates of 30 msec/item or 90 msec/item. Successive targets presented at 90 msec improved performance compared with non-successive targets. However, accuracy was equivalently high for successive and non-successive targets presented at 30 msec/item, suggesting that–regardless of whether they occurred consecutively–those items fell within the temporally defined attentional window initiated by the first target. Using four different presentation speeds, Experiment 2 confirmed the time-based definition of the AB and the success of target-cueing at 30 msec/item. This experiment additionally revealed that cueing was most effective when resources were not devoted to the cue, thereby implicating capacity limitations in the AB. Across both experiments, a novel order-error measure suggested that errors tend to decrease with an increasing duration between the targets, but also revealed that certain stimulus conditions result in stable order accuracy. Overall, the results are best encapsulated by target-based and resource-sharing theories of the AB, which collectively value the contributions of capacity limitations and optimizing transient attention in time

The effects of Kanizsa contours on temporal integration and attention in rapid serial visual presentation

Performance in rapid serial visual presentation tasks has been shown to depend on the temporal integration of target stimuli when they are presented in direct succession. Temporal target integration produces a single, combined representation of visually compatible stimuli, which is comparatively easy to identify. It is currently unknown to what extent target compatibility affects this perceptual behavior, since it has not been studied systematically to date. In the present study the effects of compatibility on temporal integration and attention were investigated by manipulating the Gestalt properties of target features. Of particular interest were configurations in which a global illusory shape was formed when all stimulus features were present; a Kanizsa stimulus, which was expected to have a unifying effect on the perception of the successive targets. The results showed that although the presence of a Kanizsa shape can indeed enhance temporal integration, this was also observed for other good Gestalts, such as due to common fate and closure. Identification accuracy seemed to vary, possibly as a result of masking strength, but this did not seem associated with attentional processing per se. Implications for theories of Gestalt processing and temporal integration are discussed

Negative Priming Under Rapid Serial Visual Presentation

Negative priming (NP) was examined under a new paradigm wherein a target and distractors were temporally separated using rapid serial visual presentation (RSVP). The results from the two experiments revealed that (a) NP was robust under RSVP, such that the responses to a target were slower when the target served as a distractor in a previous trial than when it did not; (b) NP was found regardless of whether the distractors appeared before or after the targets; and (c) NP was stronger when the distractor was more distinctive. These findings are generally similar to those on NP in the spatial search task. The implications for the processes causing NP under RSVP are discussed in the current paper

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates

Training and the attentional blink: Raising the ceiling does not remove the limits

The attentional blink (AB) is a widely studied deficit in reporting the second of two sequentially presented targets when they occur within 500 milliseconds. The AB often is interpreted to index a structural limit in sequential visual processing. However, this interpretation is challenged by reports that the deficit can be reduced with several hundred trials of specific training (Braun in Nature, 393(6684), 424–425, 1998; Choi et al. in Proceedings of the National Academy of Sciences, 109(30), 12242–12247, 2012; Taatgen et al. in Cognitive Psychology, 59(1), 1–29, 2009) and other reports that some individuals experience very little or no deficit, even without specific training (Martens et al. in Journal of Cognitive Neuroscience, 18(9), 1423-1438, 2006). Yet neither of these claims has been studied when the artifact of ceiling effects has been removed. We sent a small number of participants (n = 5) home to practice an AB task on their mobile phones for 3,000-6,000 trials (Experiment 1) and trained a much larger number of participants (n = 48) in a similar way for 1,200-1,800 trials (Experiment 2). Both experiments used adaptive procedures to equate task difficulty throughout training to keep second-target accuracy below ceiling levels. The results showed strong training effects on the rate of processing sequential information. Despite this, there were (a) robust AB effects after training for most participants, (b) no benefit for training on difficult versus easy target tasks, and (c) substantial correlations between the magnitude of the AB before and after extensive training. These findings support the interpretation that the AB is an index of a structural limit in the ability to consciously process rapid visual sequences.No Full Tex