Department of Neurology and Neurological Sciences, Stanford University, Stanford, California 94304,
Department of Neurology and Neurological Sciences, Stanford University, Stanford, California 94304.
J Neurosci. 2018 Apr 25;38(17):4230-4242. doi: 10.1523/JNEUROSCI.0217-18.2018. Epub 2018 Apr 6.
Evidence for intrinsic functional connectivity (FC) within the human brain is largely from neuroimaging studies of hemodynamic activity. Data are lacking from anatomically precise electrophysiological recordings in the most widely studied nodes of human brain networks. Here we used a combination of fMRI and electrocorticography (ECoG) in five human neurosurgical patients with electrodes in the canonical "default" (medial prefrontal and posteromedial cortex), "dorsal attention" (frontal eye fields and superior parietal lobule), and "frontoparietal control" (inferior parietal lobule and dorsolateral prefrontal cortex) networks. In this unique cohort, simultaneous intracranial recordings within these networks were anatomically matched across different individuals. Within each network and for each individual, we found a positive, and reproducible, spatial correlation for FC measures obtained from resting-state fMRI and separately recorded ECoG in the same brains. This relationship was reliably identified for electrophysiological FC based on slow (<1 Hz) fluctuations of high-frequency broadband (70-170 Hz) power, both during wakeful rest and sleep. A similar FC organization was often recovered when using lower-frequency (1-70 Hz) power, but anatomical specificity and consistency were greatest for the high-frequency broadband range. An interfrequency comparison of fluctuations in FC revealed that high and low-frequency ranges often temporally diverged from one another, suggesting that multiple neurophysiological sources may underlie variations in FC. Together, our work offers a generalizable electrophysiological basis for intrinsic FC and its dynamics across individuals, brain networks, and behavioral states. The study of human brain networks during wakeful "rest", largely with fMRI, is now a major focus in both cognitive and clinical neuroscience. However, little is known about the neurophysiology of these networks and their dynamics. We studied neural activity during wakeful rest and sleep within neurosurgical patients with directly implanted electrodes. We found that network activity patterns showed striking similarities between fMRI and direct recordings in the same brains. With improved resolution of direct recordings, we also found that networks were best characterized with specific activity frequencies and that different frequencies show different profiles of within-network activity over time. Our work clarifies how networks spontaneously organize themselves across individuals, brain networks, and behavioral states.
人类大脑内固有功能连接（FC）的证据主要来自于对血液动力学活动的神经影像学研究。在最广泛研究的人类大脑网络节点中，缺乏精确的解剖电生理记录数据。在这里，我们使用了 fMRI 和皮质电图（ECoG）在 5 名接受电极的神经外科患者中的组合，这些电极位于规范的“默认”（内侧前额叶和后内侧皮质）、“背侧注意”（额眼区和上顶叶）和“额顶控制”（下顶叶和背外侧前额叶皮质）网络中。在这个独特的队列中，不同个体之间这些网络内的颅内同步记录在解剖上是匹配的。在每个网络和每个个体中，我们发现来自静息状态 fMRI 的 FC 测量值与在同一大脑中单独记录的 ECoG 之间存在正的、可重复的空间相关性。这种关系可以可靠地基于慢（<1 Hz）的高频宽带（70-170 Hz）功率的电生理 FC 来识别，无论是在清醒休息还是睡眠期间。当使用较低的频率（1-70 Hz）功率时，通常可以恢复类似的 FC 组织，但高频宽带范围的解剖特异性和一致性最大。对 FC 波动的频域比较表明，高频和低频范围通常彼此暂时分开，这表明多个神经生理源可能是 FC 变化的基础。总之，我们的工作为个体、大脑网络和行为状态之间的固有 FC 及其动力学提供了一种可推广的电生理基础。在清醒的“休息”期间研究人类大脑网络，主要使用 fMRI，现在是认知和临床神经科学的一个主要焦点。然而，对于这些网络的神经生理学及其动力学知之甚少。我们在直接植入电极的神经外科患者中研究了清醒休息和睡眠期间的神经活动。我们发现，在相同的大脑中，功能磁共振成像和直接记录之间的网络活动模式显示出惊人的相似性。随着直接记录分辨率的提高，我们还发现，网络最好用特定的活动频率来描述，并且不同的频率随着时间的推移显示出不同的网络内活动特征。我们的工作阐明了网络如何在个体、大脑网络和行为状态之间自发组织。
