Halder Swagata, Raya Deepak Velgapuni, Sridharan Devarajan
Centre for Neuroscience, Indian Institute of Science, Bangalore, India.
Computer Science and Automation, Indian Institute of Science, Bangalore, India.
Elife. 2025 Jun 24;13:RP97098. doi: 10.7554/eLife.97098.
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, choice bias, or both - 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 were mapped onto 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 signaled 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 provide detailed insights into the subcomponents of the attentional blink and reveal dissociable neural bases underlying its detection and discrimination bottlenecks.
注意瞬脱反映了一种普遍存在的瓶颈，即在时间上紧密相邻出现的两个目标中选择并处理第二个目标时存在的瓶颈。大量文献将注意瞬脱作为一种单一现象进行了研究。因此，在注意瞬脱期间，注意的哪个特定成分——知觉敏感性、选择偏差或两者——受到损害，以及它们各自的神经基础，仍然未知。在这里，我们使用一项多选项任务和新颖的信号检测模型来解决这个问题，该模型将敏感性与偏差效应解耦。我们发现，注意瞬脱特别损害了注意的一个成分——敏感性——而另一个成分——偏差——则未受影响。注意瞬脱的不同神经标记被映射到敏感性缺陷的不同子成分上。顶枕区的N2p和P3电位振幅表征了目标检测缺陷，而额顶电极之间的长程高β频段（20 - 30赫兹）相干性则表明了目标辨别缺陷。我们用表征几何分析综合了这些结果。分析表明，检测和辨别缺陷是沿着可分离的神经维度进行编码的，其构型距离与每个维度的神经标记密切相关。总体而言，这些发现为注意瞬脱的子成分提供了详细的见解，并揭示了其检测和辨别瓶颈背后可分离的神经基础。
