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脑电描记术测量的人类静息大脑活动的优势频率。

Dominant frequencies of resting human brain activity as measured by the electrocorticogram.

机构信息

Department of Neurosurgery, Hofstra North Shore LIJ School of Medicine and Feinstein Institute for Medical Research, 300 Community Dr., Manhasset, NY 11030, USA.

出版信息

Neuroimage. 2013 Oct 1;79:223-33. doi: 10.1016/j.neuroimage.2013.04.044. Epub 2013 Apr 30.

Abstract

The brain's spontaneous, intrinsic activity is increasingly being shown to reveal brain function, delineate large scale brain networks, and diagnose brain disorders. One of the most studied and clinically utilized types of intrinsic brain activity are oscillations in the electrocorticogram (ECoG), a relatively localized measure of cortical synaptic activity. Here we objectively characterize the types of ECoG oscillations commonly observed over particular cortical areas when an individual is awake and immobile with eyes closed, using a surface-based cortical atlas and cluster analysis. Both methods show that [1] there is generally substantial variability in the dominant frequencies of cortical regions and substantial overlap in dominant frequencies across the areas sampled (primarily lateral central, temporal, and frontal areas), [2] theta (4-8 Hz) is the most dominant type of oscillation in the areas sampled with a mode around 7 Hz, [3] alpha (8-13 Hz) is largely limited to parietal and occipital regions, and [4] beta (13-30 Hz) is prominent peri-Rolandically, over the middle frontal gyrus, and the pars opercularis. In addition, the cluster analysis revealed seven types of ECoG spectral power densities (SPDs). Six of these have peaks at 3, 5, 7 (narrow), 7 (broad), 10, and 17 Hz, while the remaining cluster is broadly distributed with less pronounced peaks at 8, 19, and 42 Hz. These categories largely corroborate conventional sub-gamma frequency band distinctions (delta, theta, alpha, and beta) and suggest multiple sub-types of theta. Finally, we note that gamma/high gamma activity (30+ Hz) was at times prominently observed, but was too infrequent and variable across individuals to be reliably characterized. These results should help identify abnormal patterns of ECoG oscillations, inform the interpretation of EEG/MEG intrinsic activity, and provide insight into the functions of these different oscillations and the networks that produce them. Specifically, our results support theories of the importance of theta oscillations in general cortical function, suggest that alpha activity is primarily related to sensory processing/attention, and demonstrate that beta networks extend far beyond primary sensorimotor regions.

摘要

大脑的自发性内在活动越来越多地被证明可以揭示大脑功能、描绘大规模的大脑网络,并诊断大脑疾病。内在脑活动中最受研究和临床应用的一种类型是脑电描记图(ECoG)中的振荡,这是皮质突触活动的一种相对局部的测量。在这里,我们使用基于表面的皮质图谱和聚类分析客观地描述个体在清醒、闭眼、不动时特定皮质区域常见的 ECoG 振荡类型。这两种方法都表明:

  1. 皮质区域的主导频率存在很大的可变性,采样区域的主导频率有很大的重叠(主要是侧中央、颞部和额部);

  2. theta(4-8 Hz)是采样区域中最主要的振荡类型,模式约为 7 Hz;

  3. alpha(8-13 Hz)主要局限于顶叶和枕叶区域;

  4. beta(13-30 Hz)在 Roland 周围、额中回和脑岛盖部较为突出。

此外,聚类分析揭示了七种 ECoG 光谱功率密度(SPD)类型。其中六种类型的峰值分别在 3、5、7(窄)、7(宽)、10 和 17 Hz,而剩余的聚类则分布广泛,8、19 和 42 Hz 的峰值不明显。这些类别在很大程度上证实了传统的亚伽马频带区分(德尔塔、theta、阿尔法和贝塔),并表明 theta 有多种亚型。最后,我们注意到,伽马/高伽马活动(30+ Hz)有时也会明显观察到,但在个体之间过于频繁且变化,无法可靠地描述。这些结果应该有助于识别 ECoG 振荡的异常模式,为 EEG/MEG 内在活动的解释提供信息,并深入了解这些不同振荡及其产生的网络的功能。具体来说,我们的结果支持 theta 振荡在一般皮质功能中的重要性理论,表明 alpha 活动主要与感觉处理/注意力有关,并证明 beta 网络远远超出了主要感觉运动区域。

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