The acute effects of cocoa flavanols on temporal and spatial attention

In this study, we investigated how the acute physiological effects of cocoa flavanols might result in specific cognitive changes, in particular in temporal and spatial attention. To this end, we pre-registered and implemented a randomized, double-blind, placebo- and baseline-controlled crossover design. A sample of 48 university students participated in the study and each of them completed the experimental tasks in four conditions (baseline, placebo, low dose, and high-dose flavanol), administered in separate sessions with a 1-week washout interval. A rapid serial visual presentation task was used to test flavanol effects on temporal attention and integration, and a visual search task was similarly employed to investigate spatial attention. Results indicated that cocoa flavanols improved visual search efficiency, reflected by reduced reaction time. However, cocoa flavanols did not facilitate temporal attention nor integration, suggesting Potential underlying mechanisms are discussed

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

Temporal perception deficits in schizophrenia: integration is the problem, not deployment of attentions

Patients with schizophrenia are known to have impairments in sensory processing. In order to understand the specific temporal perception deficits of schizophrenia, we investigated and determined to what extent impairments in temporal integration can be dissociated from attention deployment using Attentional Blink (AB). Our findings showed that there was no evident deficit in the deployment of attention in patients with schizophrenia. However, patients showed an increased temporal integration deficit within a hundred-millisecond timescale. The degree of such integration dysfunction was correlated with the clinical manifestations of schizophrenia. There was no difference between individuals with/without schizotypal personality disorder in temporal integration. Differently from previous studies using the AB, we did not find a significant impairment in deployment of attention in schizophrenia. Instead, we used both theoretical and empirical approaches to show that previous findings (using the suppression ratio to correct for the baseline difference) produced a systematic exaggeration of the attention deficits. Instead, we modulated the perceptual difficulty of the task to bring the baseline levels of target detection between the groups into closer alignment. We found that the integration dysfunction rather than deployment of attention is clinically relevant, and thus should be an additional focus of research in schizophrenia

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

Dynamic hidden states underlying working-memory-guided behavior

Recent theoretical models propose that working memory is mediated by rapid transitions in 'activity-silent' neural states (for example, short-term synaptic plasticity). According to the dynamic coding framework, such hidden state transitions flexibly configure memory networks for memory-guided behavior and dissolve them equally fast to allow forgetting. We developed a perturbation approach to measure mnemonic hidden states in an electroencephalogram. By 'pinging' the brain during maintenance, we show that memory-item-specific information is decodable from the impulse response, even in the absence of attention and lingering delay activity. Moreover, hidden memories are remarkably flexible: an instruction cue that directs people to forget one item is sufficient to wipe the corresponding trace from the hidden state. In contrast, temporarily unattended items remain robustly coded in the hidden state, decoupling attentional focus from cue-directed forgetting. Finally, the strength of hidden-state coding predicts the accuracy of working-memory-guided behavior, including memory precision