Emotion and executive control are often conceptualized as two distinct modes of human brain functioning. Little, however, is known about how the dynamic organization of large-scale functional brain networks that support flexible emotion processing and executive control, especially their interactions. The amygdala and prefrontal systems have long been thought to play crucial roles in these processes. Recent advances in human neuroimaging studies have begun to delineate functional organization principles among the large-scale brain networks underlying emotion, executive control, and their interactions. Here, we propose a dynamic brain network model to account for interactive competition between emotion and executive control by reviewing recent resting-state and task-related neuroimaging studies using network-based approaches. In this model, dynamic interactions among the executive control network, the salience network, the default mode network, and sensorimotor networks enable dynamic processes of emotion and support flexible executive control of multiple processes; neural oscillations across multiple frequency bands and the locus coeruleus−norepinephrine pathway serve as communicational mechanisms underlying dynamic synergy among large-scale functional brain networks. This model has important implications for understanding how the dynamic organization of complex brain systems and networks empowers flexible cognitive and affective functions.

情绪和执行控制通常被概念化为人类大脑功能的两种不同模式。然而，人们对大规模功能性大脑网络的动态组织如何支持灵活的情绪处理和执行控制，尤其是它们的相互作用知之甚少。长期以来，杏仁核和前额叶系统一直被认为在这些过程中发挥着至关重要的作用。人类神经影像学研究的最新进展已经开始描绘情绪、执行控制及其相互作用的大规模大脑网络中的功能组织原则。在这里，我们通过回顾最近使用基于网络的方法的静息状态和任务相关的神经影像学研究，提出了一个动态大脑网络模型来解释情绪和执行控制之间的交互竞争。在该模型中，执行控制网络、显着网络、默认模式网络和感觉运动网络之间的动态交互实现了情感的动态过程，并支持多个过程的灵活执行控制；跨多个频段的神经振荡和蓝斑-去甲肾上腺素通路是大规模功能性大脑网络之间动态协同作用的通信机制。该模型对于理解复杂大脑系统和网络的动态组织如何赋予灵活的认知和情感功能具有重要意义。