Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom.
Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Neuroimage. 2018 Oct 15;180(Pt B):559-576. doi: 10.1016/j.neuroimage.2017.10.003. Epub 2017 Oct 4.
For several years it has been argued that neural synchronisation is crucial for cognition. The idea that synchronised temporal patterns between different neural groups carries information above and beyond the isolated activity of these groups has inspired a shift in focus in the field of functional neuroimaging. Specifically, investigation into the activation elicited within certain regions by some stimulus or task has, in part, given way to analysis of patterns of co-activation or functional connectivity between distal regions. Recently, the functional connectivity community has been looking beyond the assumptions of stationarity that earlier work was based on, and has introduced methods to incorporate temporal dynamics into the analysis of connectivity. In particular, non-invasive electrophysiological data (magnetoencephalography/electroencephalography (MEG/EEG)), which provides direct measurement of whole-brain activity and rich temporal information, offers an exceptional window into such (potentially fast) brain dynamics. In this review, we discuss challenges, solutions, and a collection of analysis tools that have been developed in recent years to facilitate the investigation of dynamic functional connectivity using these imaging modalities. Further, we discuss the applications of these approaches in the study of cognition and neuropsychiatric disorders. Finally, we review some existing developments that, by using realistic computational models, pursue a deeper understanding of the underlying causes of non-stationary connectivity.
多年来，人们一直认为神经同步对于认知至关重要。不同神经群之间的时间模式同步传递信息的观点超越了这些群体孤立活动的观点，这激发了功能神经影像学领域的研究重点发生转变。具体而言，对某些刺激或任务引起的特定区域的激活的研究在一定程度上已经让位于对远程区域之间的共同激活或功能连接模式的分析。最近，功能连接社区已经超越了早期工作所基于的平稳性假设，并引入了将时间动态纳入连接分析的方法。特别是，非侵入性的电生理数据（脑磁图/脑电图（MEG/EEG））提供了对全脑活动和丰富时间信息的直接测量，为研究（潜在的快速）大脑动态提供了一个极好的窗口。在这篇综述中，我们讨论了近年来为使用这些成像方式促进动态功能连接研究而开发的挑战、解决方案和一系列分析工具。此外，我们还讨论了这些方法在认知和神经精神障碍研究中的应用。最后，我们回顾了一些现有的发展，这些发展通过使用现实的计算模型，深入探讨了非平稳连接的潜在原因。
