Florin Esther, Watanabe Masataka, Logothetis Nikos K
Max Planck Institute for Biological Cybernetics, Spemannstraße 38, 72076 Tübingen, Germany; Department of Neurology, University Hospital Cologne, Kerpener Str. 62, 50937 Köln, Germany.
Max Planck Institute for Biological Cybernetics, Spemannstraße 38, 72076 Tübingen, Germany.
Curr Opin Neurobiol. 2015 Jun;32:24-30. doi: 10.1016/j.conb.2014.10.006. Epub 2014 Oct 30.
Human fMRI studies have identified well-reproducible resting-state networks (RSN) from spontaneous recordings. These networks are extracted from correlation metrics across the brain using several minutes of data. However, a majority of electrophysiological events occur at a sub-second time scale and their contribution to RSN generation is likely. According to recent fMRI studies RSNs separate into smaller networks when studied with higher temporal resolution. Moreover, using simultaneous electrophysiology and fMRI recordings it was shown that transient functional networks form around neural events. Therefore, considering neural events as sources of functional networks might improve the understanding of spontaneous brain activity. This endeavor will benefit from technical advances in simultaneous BOLD and electrophysiology recordings, as well as a more principled modeling of neurovascular coupling.
人类功能磁共振成像（fMRI）研究已从自发记录中识别出可良好重现的静息态网络（RSN）。这些网络是通过使用几分钟的数据，从全脑的相关性指标中提取出来的。然而，大多数电生理事件发生在亚秒级时间尺度，它们对RSN生成的贡献很可能存在。根据最近的fMRI研究，当以更高的时间分辨率进行研究时，RSN会分离成更小的网络。此外，通过同时进行电生理和fMRI记录表明，在神经事件周围会形成瞬态功能网络。因此，将神经事件视为功能网络的来源可能会增进对自发脑活动的理解。这一努力将受益于同时进行血氧水平依赖（BOLD）和电生理记录的技术进步，以及对神经血管耦合更有原则性的建模。
