Mortezapouraghdam Zeinab, Corona-Strauss Farah I, Takahashi Kazutaka, Strauss Daniel J
Systems Neuroscience & Neurotechnology Unit, Faculty of Medicine, Saarland University, Homburg, Germany.
School of Engineering, Saarland University of Applied Sciences, Saarbruecken, Germany.
Front Comput Neurosci. 2018 Oct 8;12:82. doi: 10.3389/fncom.2018.00082. eCollection 2018.
The phase-reset model of oscillatory EEG activity has received a lot of attention in the last decades for decoding different cognitive processes. Based on this model, the ERPs are assumed to be generated as a result of phase reorganization in ongoing EEG. Alignment of the phase of neuronal activities can be observed within or between different assemblies of neurons across the brain. Phase synchronization has been used to explore and understand perception, attentional binding and considering it in the domain of neuronal correlates of consciousness. The importance of the topic and its vast exploration in different domains of the neuroscience presses the need for appropriate tools and methods for measuring the level of phase synchronization of neuronal activities. Measuring the level of instantaneous phase (IP) synchronization has been used extensively in numerous studies of ERPs as well as oscillatory activity for a better understanding of the underlying cognitive binding with regard to different set of stimulations such as auditory and visual. However, the reliability of results can be challenged as a result of noise artifact in IP. Phase distortion due to environmental noise artifacts as well as different pre-processing steps on signals can lead to generation of artificial phase jumps. One of such effects presented recently is the effect of low envelope on the IP of signal. It has been shown that as the instantaneous envelope of the analytic signal approaches zero, the variations in the phase increase, effectively leading to abrupt transitions in the phase. These abrupt transitions can distort the phase synchronization results as they are not related to any neurophysiological effect. These transitions are called spurious phase variation. In this study, we present a model to remove generated artificial phase variations due to the effect of low envelope. The proposed method is based on a simplified form of a Kalman smoother, that is able to model the IP behavior in narrow-bandpassed oscillatory signals. In this work we first explain the details of the proposed Kalman smoother for modeling the dynamics of the phase variations in narrow-bandpassed signals and then evaluate it on a set of synthetic signals. Finally, we apply the model on ongoing-EEG signals to assess the removal of spurious phase variations.
在过去几十年中，振荡性脑电图（EEG）活动的相位重置模型因用于解码不同认知过程而备受关注。基于该模型，事件相关电位（ERP）被认为是正在进行的脑电图中相位重组的结果。在大脑中不同的神经元集合内部或之间，可以观察到神经元活动相位的对齐。相位同步已被用于探索和理解感知、注意力绑定，并在意识的神经元关联领域加以考量。该主题的重要性及其在神经科学不同领域的广泛探索，迫切需要合适的工具和方法来测量神经元活动的相位同步水平。测量瞬时相位（IP）同步水平已在众多ERP研究以及振荡活动研究中广泛应用，以便更好地理解与不同刺激集（如听觉和视觉）相关的潜在认知绑定。然而，由于IP中的噪声伪迹，结果的可靠性可能受到挑战。环境噪声伪迹以及信号上不同的预处理步骤导致的相位失真，可能会产生人为的相位跳跃。最近出现的此类效应之一是信号低包络对IP的影响。研究表明，随着解析信号的瞬时包络接近零，相位变化增加，有效地导致相位的突然转变。这些突然转变会扭曲相位同步结果，因为它们与任何神经生理效应无关。这些转变被称为虚假相位变化。在本研究中，我们提出了一个模型，以消除由于低包络效应产生的人为相位变化。所提出的方法基于卡尔曼平滑器的简化形式，它能够对窄带振荡信号中的IP行为进行建模。在这项工作中，我们首先解释所提出的卡尔曼平滑器用于对窄带信号中相位变化动态进行建模的细节，然后在一组合成信号上对其进行评估。最后，我们将该模型应用于正在进行的脑电图信号，以评估虚假相位变化的去除情况。
