Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.
Department of Neurology & Stroke, and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
PLoS Comput Biol. 2019 May 14;15(5):e1007055. doi: 10.1371/journal.pcbi.1007055. eCollection 2019 May.
Neuronal oscillations are ubiquitous in the human brain and are implicated in virtually all brain functions. Although they can be described by a prominent peak in the power spectrum, their waveform is not necessarily sinusoidal and shows rather complex morphology. Both frequency and temporal descriptions of such non-sinusoidal neuronal oscillations can be utilized. However, in non-invasive EEG/MEG recordings the waveform of oscillations often takes a sinusoidal shape which in turn leads to a rather oversimplified view on oscillatory processes. In this study, we show in simulations how spatial synchronization can mask non-sinusoidal features of the underlying rhythmic neuronal processes. Consequently, the degree of non-sinusoidality can serve as a measure of spatial synchronization. To confirm this empirically, we show that a mixture of EEG components is indeed associated with more sinusoidal oscillations compared to the waveform of oscillations in each constituent component. Using simulations, we also show that the spatial mixing of the non-sinusoidal neuronal signals strongly affects the amplitude ratio of the spectral harmonics constituting the waveform. Finally, our simulations show how spatial mixing can affect the strength and even the direction of the amplitude coupling between constituent neuronal harmonics at different frequencies. Validating these simulations, we also demonstrate these effects in real EEG recordings. Our findings have far reaching implications for the neurophysiological interpretation of spectral profiles, cross-frequency interactions, as well as for the unequivocal determination of oscillatory phase.
神经元振荡在人类大脑中普遍存在，与几乎所有的大脑功能都有关联。尽管它们可以通过频谱中的一个显著峰值来描述，但它们的波形不一定是正弦的，而是呈现出相当复杂的形态。这种非正弦的神经元振荡的频率和时间描述都可以被利用。然而，在非侵入性的 EEG/MEG 记录中，振荡的波形往往呈现正弦形状，这反过来又导致对振荡过程的看法过于简单化。在这项研究中，我们通过模拟展示了空间同步如何掩盖潜在的节律性神经元过程的非正弦特征。因此，非正弦程度可以作为空间同步的度量。为了从经验上证实这一点，我们表明，与每个组成成分的振荡波形相比，EEG 成分的混合物确实与更正弦的振荡相关。我们还通过模拟表明，非正弦神经元信号的空间混合强烈影响构成波形的谱谐振幅比。最后，我们的模拟表明，空间混合如何影响不同频率的组成神经元谐波之间的幅度耦合的强度，甚至方向。通过验证这些模拟，我们还在真实的 EEG 记录中展示了这些效应。我们的发现对频谱谱形、交叉频率相互作用以及振荡相位的明确确定的神经生理解释具有深远的意义。
