Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China.
Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
J Neurosci Methods. 2022 Jun 1;375:109577. doi: 10.1016/j.jneumeth.2022.109577. Epub 2022 Mar 25.
Detecting dynamic targets from complex visual scenes is an important problem in real world. However, the cognitive mechanism accounting for dynamic visual target detection remains unclear.
Herein, we aim to explore the cognitive process of dynamic visual target detection from searching to spotting and provide more concrete evidence for cognitive studies related to target detection. Cortical source responses with high spatiotemporal resolution were reconstructed from scalp EEG signals. Then, time-varying cortical networks were built using adaptive directed transfer function to explore the cognitive processes while detecting the dynamic visual target.
The experimental results demonstrated that the dynamic visual target detection enhanced the activation in both the visual and attention networks. Specially, the information flow from the middle occipital gyrus (MOG) mainly contributed to the position function, whereas the activation of the prefrontal cortex (PFC) reflected spatial attention maintenance.
The left "frontal-central-parietal" network played as a leading information source in dynamic target detection tasks. These findings provide new insights into cognitive processes of dynamic visual target detection.
从复杂的视觉场景中检测动态目标是现实世界中的一个重要问题。然而，用于解释动态视觉目标检测的认知机制仍不清楚。
本文旨在从搜索到发现的角度探索动态视觉目标检测的认知过程，并为与目标检测相关的认知研究提供更具体的证据。从头皮 EEG 信号中重建具有高时空分辨率的皮质源响应。然后，使用自适应有向传递函数构建时变皮质网络，以探索检测动态视觉目标时的认知过程。
实验结果表明，动态视觉目标检测增强了视觉和注意力网络的激活。特别是，从中脑枕叶（MOG）的信息流主要有助于位置功能，而前额叶皮层（PFC）的激活反映了空间注意力的维持。
左“额-中央-顶”网络在动态目标检测任务中充当主要信息源。这些发现为动态视觉目标检测的认知过程提供了新的见解。
