Laboratory of Brain Atlas and Brain-Inspired Intelligence, State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Science, Beijing 100190, China.
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
Cereb Cortex. 2023 Jun 20;33(13):8594-8604. doi: 10.1093/cercor/bhad143.
Brain dynamics can be modeled by a sequence of transient, nonoverlapping patterns of quasi-stable electrical potentials named "microstates." While electroencephalographic (EEG) microstates among patients with chronic pain remained inconsistent in the literature, this study characterizes the temporal dynamics of EEG microstates among healthy individuals during experimental sustained pain. We applied capsaicin (pain condition) or control (no-pain condition) cream to 58 healthy participants in different sessions and recorded resting-state EEG 15 min after application. We identified 4 canonical microstates (A-D) that are related to auditory, visual, salience, and attentional networks. Microstate C had less occurrence, as were bidirectional transitions between microstate C and microstates A and B during sustained pain. In contrast, sustained pain was associated with more frequent and longer duration of microsite D, as well as more bidirectional transitions between microstate D and microstates A and B. Microstate D duration positively correlated with intensity of ongoing pain. Sustained pain improved global integration within microstate C functional network, but weakened global integration and efficiency within microstate D functional network. These results suggest that sustained pain leads to an imbalance between processes that load on saliency (microstate C) and processes related to switching and reorientation of attention (microstate D).
大脑活动可以通过一系列短暂、非重叠的准稳定电势能模式来模拟,这些模式被称为“微状态”。虽然慢性疼痛患者的脑电图(EEG)微状态在文献中仍不一致,但本研究描述了健康个体在实验性持续性疼痛期间 EEG 微状态的时间动态。我们在不同的疗程中向 58 名健康参与者应用辣椒素(疼痛条件)或对照(无疼痛条件)乳膏,并在应用后 15 分钟记录静息状态 EEG。我们确定了 4 个典型的微状态(A-D),它们与听觉、视觉、突显和注意力网络有关。微状态 C 的出现频率较低,在持续性疼痛期间,微状态 C 与微状态 A 和 B 之间的双向转换也较少。相比之下,持续性疼痛与微状态 D 的出现频率更高、持续时间更长,以及微状态 D 与微状态 A 和 B 之间的双向转换更多有关。微状态 D 的持续时间与持续疼痛的强度呈正相关。持续性疼痛改善了微状态 C 功能网络中的全局整合,但削弱了微状态 D 功能网络中的全局整合和效率。这些结果表明,持续性疼痛导致突显(微状态 C)相关过程与注意力切换和重定向(微状态 D)相关过程之间的不平衡。