心理学家Posner等人提出的注意网络理论,将注意功能解构为警觉、定向和执行控制三个子网络。大量研究表明,注意网络测验及其变式可以有效地测量这三个注意子网络的效率及其相互作用。然而,传统的注意网络评估主要使用行为学方法进行分析...心理学家Posner等人提出的注意网络理论,将注意功能解构为警觉、定向和执行控制三个子网络。大量研究表明,注意网络测验及其变式可以有效地测量这三个注意子网络的效率及其相互作用。然而,传统的注意网络评估主要使用行为学方法进行分析,反应时和正确率等指标无法深入揭示注意功能的神经机制,具有很大的局限性。本文结合认知神经科学技术方法,从行为学、脑电、磁共振、眼动以及生物化学等方面对注意网络的大脑解剖学结构、行为学特点和神经生理学机制进行综述,并基于现有研究,对未来使用多模态融合的注意网络评估进行展望,以推动对注意网络更加全面和深入的理解,为提升注意网络功能提供理论和实证依据。The attention network theory was first proposed by psychologist Posner et al., which deconstructs the attention function into three subnetworks: vigilance, orientation and executive control. A large number of studies have shown that the attention network test and its variants could effectively measure the efficiency and interaction of the three subnetworks. However, the traditional assessment of attention network mainly uses behavioral methods for analysis. Indicators such as reaction time and accuracy could not reveal the neural mechanism of attention function in depth, which has great limitations. In this manuscript, the anatomical structure, behavioral characteristics and neurophysiological mechanism of the attention network are reviewed from the aspects of behavior, EEG/ERP, MRI, eye tracking and biochemistry. Based on the existing research, the future evaluation of the attention network using multimode fusion technology is prospected. This review promotes a more comprehensive and in-depth understanding of attention networks and provides theoretical and empirical basis for enhancing attention network functions.展开更多
文摘心理学家Posner等人提出的注意网络理论,将注意功能解构为警觉、定向和执行控制三个子网络。大量研究表明,注意网络测验及其变式可以有效地测量这三个注意子网络的效率及其相互作用。然而,传统的注意网络评估主要使用行为学方法进行分析,反应时和正确率等指标无法深入揭示注意功能的神经机制,具有很大的局限性。本文结合认知神经科学技术方法,从行为学、脑电、磁共振、眼动以及生物化学等方面对注意网络的大脑解剖学结构、行为学特点和神经生理学机制进行综述,并基于现有研究,对未来使用多模态融合的注意网络评估进行展望,以推动对注意网络更加全面和深入的理解,为提升注意网络功能提供理论和实证依据。The attention network theory was first proposed by psychologist Posner et al., which deconstructs the attention function into three subnetworks: vigilance, orientation and executive control. A large number of studies have shown that the attention network test and its variants could effectively measure the efficiency and interaction of the three subnetworks. However, the traditional assessment of attention network mainly uses behavioral methods for analysis. Indicators such as reaction time and accuracy could not reveal the neural mechanism of attention function in depth, which has great limitations. In this manuscript, the anatomical structure, behavioral characteristics and neurophysiological mechanism of the attention network are reviewed from the aspects of behavior, EEG/ERP, MRI, eye tracking and biochemistry. Based on the existing research, the future evaluation of the attention network using multimode fusion technology is prospected. This review promotes a more comprehensive and in-depth understanding of attention networks and provides theoretical and empirical basis for enhancing attention network functions.
