Duecker Katharina, Shapiro Kimron L, Hanslmayr Simon, Griffiths Benjamin J, Quinn Andrew J, Wolfe Jeremy, Pan Yali, Pastuszak Aleksandra, Jensen Ole
Department of Neuroscience, Brown University, RI, USA.
Centre for Human Brain Health, School of Psychology, University of Birmingham, UK (current or former).
bioRxiv. 2025 Aug 29:2025.08.29.673162. doi: 10.1101/2025.08.29.673162.
Visual search models have long emphasised that task-relevant items must be prioritized for optimal performance. While it is known that search efficiency also benefits from active distractor inhibition, the underlying neuronal mechanisms are debated. Neuronal alpha oscillations (7-14 Hz) have been associated with functional inhibition of cortical excitability, as well as distractor suppression in spatial attention and visual working memory tasks. We therefore hypothesised that alpha oscillations similarly support the deselection of distractors in visual search. Using Magnetoencephalography (MEG), we here show that high alpha power before the onset of a complex search display is associated with faster search performance. Crucially, we used a General Linear Model (GLM) approach to control for confounds between alpha power and task duration, ruling out that this result was merely driven by practice effects paired with increased fatigue over time. In addition to spontaneous oscillatory activity, we quantified the cortical excitability to colours of the search stimuli based on Rapid Invisible Frequency Tagging (RIFT) responses. In contrast to our initial hypothesis, increased pre-search alpha power did not correlate with the RIFT response, providing no direct evidence for feature-specific inhibition of distracting stimuli by alpha. Our findings challenge the traditional view of alpha oscillations reducing visual processing, showing instead that increased occipital alpha power can enhance performance in a visual task. We propose that the increase in alpha power may reflect increased top-down control supporting visual search.
视觉搜索模型长期以来一直强调，为了实现最佳性能，必须优先处理与任务相关的项目。虽然已知搜索效率也受益于主动抑制干扰项，但其潜在的神经元机制仍存在争议。神经元阿尔法振荡（7-14赫兹）与皮质兴奋性的功能抑制以及空间注意力和视觉工作记忆任务中的干扰项抑制有关。因此，我们假设阿尔法振荡同样支持在视觉搜索中排除干扰项。我们使用脑磁图（MEG）表明，在复杂搜索显示开始之前的高阿尔法功率与更快的搜索性能相关。至关重要的是，我们使用通用线性模型（GLM）方法来控制阿尔法功率和任务持续时间之间的混淆，排除了这一结果仅仅是由练习效应以及随着时间推移疲劳增加所驱动的可能性。除了自发振荡活动，我们还基于快速不可见频率标记（RIFT）反应量化了对搜索刺激颜色的皮质兴奋性。与我们最初的假设相反，搜索前阿尔法功率的增加与RIFT反应无关，没有提供阿尔法对干扰刺激进行特征特异性抑制的直接证据。我们的研究结果挑战了阿尔法振荡会减少视觉处理的传统观点，相反表明枕叶阿尔法功率的增加可以提高视觉任务的表现。我们提出，阿尔法功率的增加可能反映了支持视觉搜索的自上而下控制的增强。
