Distinct neural bases of subcomponents of the attentional blink

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Abstract

The attentional blink reflects a ubiquitous bottleneck with selecting and processing the second of two targets that occur in close temporal proximity. An extensive literature has examined the attention blink as a unitary phenomenon, As a result, which specific component of attention – perceptual sensitivity or choice bias – is compromised during the attentional blink, and their respective neural bases, remains unknown. Here, we address this question with a multialternative task and novel signal detection model, which decouples sensitivity from bias effects. We find that the attentional blink impairs specifically one component of attention – sensitivity – while leaving the other component – bias – unaffected. Distinct neural markers of the attentional blink mapped on to distinct subcomponents of the sensitivity deficits. Parieto-occipital N2p and P3 potential amplitudes characterized target detection deficits whereas long-range high-beta band (20-30 Hz) coherence between frontoparietal electrodes signalled target discrimination deficits. We synthesized these results with representational geometry analysis. The analysis revealed that detection and discrimination deficits were encoded along separable neural dimensions, whose configural distances robustly correlated with the neural markers of each. Overall, these findings shed new light on subcomponents of the attentional blink, and reveal dissociable neural bases underlying its detection and discrimination bottlenecks.

Lay summary

In daily life, our attention switches rapidly between different objects. For example, when driving, we may shift focus from a billboard on the roadside to a pedestrian in front, in quick succession. Yet, our ability to process the second object is severely compromised especially when it appears soon after the first: an impairment called the “attentional blink”. In previous work, the attentional blink has been studied essentially as a “monolithic” (indivisible) phenomenon. We design a behavioral model to divide the attentional blink into sub-components and show that the blink affects only one specific component (sensitivity). We also identify key neural markers for deficits associated with this component. Our findings may aid in understanding the neural origins of attention deficit disorders.

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