Centre for Systems Modelling & Quantitative Biomedicine (SMQB), University of Birmingham, Birmingham, UK; Cardiff University Brain Research Imaging Centre, Cardiff, UK.
Cardiff University Brain Research Imaging Centre, Cardiff, UK.
Neuroimage. 2022 May 1;251:119006. doi: 10.1016/j.neuroimage.2022.119006. Epub 2022 Feb 16.
EEG microstate analysis is an approach to study brain states and their fast transitions in healthy cognition and disease. A key limitation of conventional microstate analysis is that it must be performed at the sensor level, and therefore gives limited anatomical insight. Here, we generalise the microstate methodology to be applicable to source-reconstructed electrophysiological data. Using simulations of a neural-mass network model, we first established the validity and robustness of the proposed method. Using MEG resting-state data, we uncovered ten microstates with distinct spatial distributions of cortical activation. Multivariate pattern analysis demonstrated that source-level microstates were associated with distinct functional connectivity patterns. We further demonstrated that the occurrence probability of MEG microstates were altered by auditory stimuli, exhibiting a hyperactivity of the microstate including the auditory cortex. Our results support the use of source-level microstates as a method for investigating brain dynamic activity and connectivity at the millisecond scale.
脑电微状态分析是一种研究健康认知和疾病中脑状态及其快速转换的方法。传统微状态分析的一个关键局限性是它必须在传感器水平上进行，因此提供的解剖学见解有限。在这里，我们将微状态分析方法推广到可应用于源重建电生理数据。我们首先使用神经质量网络模型的模拟来验证所提出方法的有效性和鲁棒性。使用 MEG 静息状态数据，我们发现了十个具有不同皮质激活空间分布的微状态。多变量模式分析表明，源水平微状态与不同的功能连接模式相关。我们进一步证明了听觉刺激会改变 MEG 微状态的出现概率，表现为包括听觉皮层在内的微状态的过度活跃。我们的结果支持使用源水平微状态作为一种在毫秒尺度上研究大脑动态活动和连接的方法。
