Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters.
Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters.
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DOI：
10.1371/journal.pcbi.1009298
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发表时间：
2021-08
影响因子：
4.3
通讯作者：
Voytek B
中科院分区：
文献类型：
--
作者：
Schaworonkow N;Voytek B
在侵入性电生理记录中，可以在整个皮层检测到各种神经振荡，在空间和时间上重叠。这种重叠使使用标准参考方案（如共同平均或双极参考）测量神经振荡变得复杂。在这里，我们说明了空间混合测量神经振荡在侵入性电生理记录的影响，并证明了使用数据驱动的参考方案，以提高神经振荡的测量的好处。我们讨论引用作为空间滤波器的应用。空间谱分解用于估计数据驱动的空间滤波器，这是一种计算快速的方法，特别是提高了感兴趣的频带中的振荡的信噪比。我们表明，这些数据驱动的空间滤波器的应用程序有利于数据探索，调查的时间动态和评估的神经振荡的峰值频率。我们展示了多个用例，探索参与者之间的差异，存在振荡，空间扩展和不同节奏的波形形状，以及在空间滤波器的帮助下消除窄带噪声。我们发现高参与者之间的变异性存在的神经振荡，一个大的变化，在空间传播的个人节奏和许多非正弦节律在整个皮层。改进皮质节律的测量将产生更好的条件，建立皮质活动和行为之间的联系，以及有创颅内测量和无创宏观头皮测量之间的桥梁尺度。对人脑活动的侵入性电生理记录提供了测量多个同时活跃的脑节律的独特能力。分析脑节律是复杂的，因为不同的振荡往往在空间和时间上重叠。在这里，我们探索人类静息状态侵入性电生理记录，通过使用空间滤波器，联合收割机的信息，从所有可用的记录电极，专门提取高信噪比的振荡。使用这种技术，我们探讨了振荡存在的变化，跨学科的空间传播和振荡的波形形状。我们发现，参与者不同的振荡存在很多，即使当记录电极有类似的位置。我们发现，振荡表现出的空间扩散超过电极之间的距离，在不同的大脑区域的振荡的波形形状可以高度偏离正弦波。
In invasive electrophysiological recordings, a variety of neural oscillations can be detected across the cortex, with overlap in space and time. This overlap complicates measurement of neural oscillations using standard referencing schemes, like common average or bipolar referencing. Here, we illustrate the effects of spatial mixing on measuring neural oscillations in invasive electrophysiological recordings and demonstrate the benefits of using data-driven referencing schemes in order to improve measurement of neural oscillations. We discuss referencing as the application of a spatial filter. Spatio-spectral decomposition is used to estimate data-driven spatial filters, a computationally fast method which specifically enhances signal-to-noise ratio for oscillations in a frequency band of interest. We show that application of these data-driven spatial filters has benefits for data exploration, investigation of temporal dynamics and assessment of peak frequencies of neural oscillations. We demonstrate multiple use cases, exploring between-participant variability in presence of oscillations, spatial spread and waveform shape of different rhythms as well as narrowband noise removal with the aid of spatial filters. We find high between-participant variability in the presence of neural oscillations, a large variation in spatial spread of individual rhythms and many non-sinusoidal rhythms across the cortex. Improved measurement of cortical rhythms will yield better conditions for establishing links between cortical activity and behavior, as well as bridging scales between the invasive intracranial measurements and noninvasive macroscale scalp measurements. Invasive electrophysiological recordings of human brain activity offer the unique ability to measure multiple, simultaneously active brain rhythms. Analyzing brain rhythms is complex due to the fact that different oscillations often overlap in space and time. Here we explore human resting state invasive electrophysiological recordings by using spatial filters, which combine information from all available recording electrodes to specifically extract oscillations with high signal to noise ratio. Using this technique, we explore variability in oscillation presence across subjects, the spatial spread and waveform shape of oscillations. We find that participants differ a lot in presence of oscillations, even when the recording electrodes have similar placement. We find that oscillations exhibit spatial spread exceeding the distance between electrodes and that the waveform shape of oscillations in different brain regions can be highly deviating from a sine wave.
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细胞外田地和电流的起源-EEG，ECOG，LFP和尖峰。
DOI：
10.1038/nrn3241
发表时间：
2012-05-18
期刊：
Nature reviews. Neuroscience
影响因子：
--
作者：
Buzsáki G;Anastassiou CA;Koch C
通讯作者：
Koch C
影响因子：
4.3
作者：
Gramfort A;Luessi M;Larson E;Engemann DA;Strohmeier D;Brodbeck C;Goj R;Jas M;Brooks T;Parkkonen L;Hämäläinen M
通讯作者：
Hämäläinen M
影响因子：
14.5
作者：
Frauscher, Birgit;von Ellenrieder, Nicolas;Gotman, Jean
通讯作者：
Gotman, Jean
影响因子：
3
作者：
Cohen, Michael X.
通讯作者：
Cohen, Michael X.
影响因子：
3.5
作者：
Hagen, Espen;Naess, Solveig;Einevoll, Gaute T.
通讯作者：
Einevoll, Gaute T.