Melcón María, van Bree Sander, Sánchez-Carro Yolanda, Barreiro-Fernández Laura, Kolibius Luca D, Alzueta Elisabet, Wimber Maria, Capilla Almudena, Hanslmayr Simon
Department of Biological and Health Psychology, Universidad Autónoma de Madrid, Madrid, Spain.
Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, United Kingdom.
PLoS One. 2025 Mar 26;20(3):e0320233. doi: 10.1371/journal.pone.0320233. eCollection 2025.
While traditional behavioural and electroencephalographic studies claim that visuospatial attention stays fixed at one location at a time, recent research has rather shown that attention rhythmically fluctuates between locations at different rates. However, little is known about the temporal dynamics of this fluctuation and whether it changes over time. We addressed this question by investigating how the neural pattern of visuospatial attention behaves over space and time by employing classification and conventional analysis of occipito-parietal EEG activity. Furthermore, we simulated data with the attentional electrophysiological correlates to control for the ground truth that would give rise to certain classification patterns. We analysed two visuospatial cueing tasks, with a peripheral and a central cue to control for sensory-driven processes, where attention was covertly oriented to the left or right hemifield. First, to decode the spatial locus of attention from neural activity, we trained and tested a classifier on every timepoint from the attentional cue to the stimulus onset. This resulted in one temporal generalization matrix per participant, which was time-frequency decomposed to identify the sampling rhythm. Independently, we calculated a lateralization index based on ERPs and alpha-band power and correlated these indices with classifier performance. Eventually, we simulated two dataset, with ERPs and alpha-band attentional modulations, and employed the same decoding approach. Our results show that attention settled on the cued hemifield in a late time window, but an early and rhythmic sampling of both hemifields exclusively after the peripheral cue. Only the ERP lateralization index correlated with classifier performance in the periperhal cue dataset, suggesting that the early rhythmic state did not reflect attentional sampling but instead was driven by the cue location, idea also supported by our simulations. Together, our results characterise the occipital attentional sampling as a constant process slightly delayed after the cue.
虽然传统的行为学和脑电图研究认为视觉空间注意力一次只能固定在一个位置,但最近的研究表明,注意力会以不同的速率在不同位置之间有节奏地波动。然而,对于这种波动的时间动态以及它是否随时间变化,我们知之甚少。我们通过对枕顶叶脑电图活动进行分类和传统分析,研究视觉空间注意力的神经模式在空间和时间上的表现,从而解决了这个问题。此外,我们用注意力电生理相关数据进行模拟,以控制能产生特定分类模式的基本事实。我们分析了两个视觉空间线索任务,一个有外周线索,一个有中央线索,以控制感觉驱动过程,其中注意力被隐蔽地导向左或右半视野。首先,为了从神经活动中解码注意力的空间位置,我们在从注意力线索到刺激开始的每个时间点上训练并测试一个分类器。这为每个参与者生成了一个时间泛化矩阵,对其进行时频分解以识别采样节奏。独立地,我们基于事件相关电位(ERP)和α波段功率计算了一个偏侧化指数,并将这些指数与分类器性能相关联。最后,我们模拟了两个数据集,包含ERP和α波段注意力调制,并采用相同的解码方法。我们的结果表明,注意力在较晚的时间窗口稳定在被提示的半视野上,但在外周线索之后,两个半视野会有早期且有节奏的采样。只有ERP偏侧化指数与外周线索数据集中的分类器性能相关,这表明早期的有节奏状态并非反映注意力采样,而是由线索位置驱动,我们的模拟也支持了这一观点。总之,我们的结果将枕叶注意力采样描述为一个在线索之后稍有延迟的持续过程。