IEEE Trans Neural Syst Rehabil Eng. 2023;31:1219-1229. doi: 10.1109/TNSRE.2023.3242771.
Visual search is ubiquitous in daily life and has attracted substantial research interest over the past decades. Although accumulating evidence has suggested complex neurocognitive processes underlying visual search, the neural communication across the brain regions remains poorly understood. The present work aimed to fill this gap by investigating functional networks of fixation-related potential (FRP) during the visual search task. Multi-frequency electroencephalogram (EEG) networks were constructed from 70 university students (male/female = 35/35) using FRPs time-locked to target and non-target fixation onsets, which were determined by concurrent eye-tracking data. Then graph theoretical analysis (GTA) and a data-driven classification framework were employed to quantitatively reveal the divergent reorganization between target and non-target FRPs. We found distinct network architectures between target and non-target mainly in the delta and theta bands. More importantly, we achieved a classification accuracy of 92.74% for target and non-target discrimination using both global and nodal network features. In line with the results of GTA, we found that the integration corresponding to target and non-target FRPs significantly differed, while the nodal features contributing most to classification performance primarily resided in the occipital and parietal-temporal areas. Interestingly, we revealed that females exhibited significantly higher local efficiency in delta band when focusing on the search task. In summary, these results provide some of the first quantitative insights into the underlying brain interaction patterns during the visual search process.
视觉搜索在日常生活中无处不在,在过去几十年中引起了大量的研究兴趣。尽管有大量证据表明视觉搜索背后存在复杂的神经认知过程,但大脑区域之间的神经通讯仍知之甚少。本研究旨在通过研究视觉搜索任务中与注视相关的潜在(FRP)的功能网络来填补这一空白。使用与目标和非目标注视起始时间锁定的 FRP 从 70 名大学生(男/女=35/35)构建多频脑电图(EEG)网络,这些数据是通过同时进行的眼动追踪数据确定的。然后,使用图论分析(GTA)和数据驱动的分类框架来定量揭示目标和非目标 FRP 之间的发散重组。我们发现目标和非目标之间的网络结构存在明显差异,主要在 delta 和 theta 频段。更重要的是,我们使用全局和节点网络特征实现了目标和非目标分类的 92.74%的准确率。与 GTA 的结果一致,我们发现目标和非目标 FRP 的整合明显不同,而对分类性能贡献最大的节点特征主要位于枕叶和颞顶叶区域。有趣的是,我们发现女性在集中搜索任务时 delta 频段的局部效率明显更高。总之,这些结果为视觉搜索过程中大脑相互作用模式提供了一些首批定量见解。