Statistical method for detecting phase shifts in alpha rhythm from human electroencephalogram data
Statistical method for detecting phase shifts in alpha rhythm from human electroencephalogram data
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DOI：
10.1103/physreve.87.042708
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发表时间：
2013-04-12
影响因子：
2.4
通讯作者：
Umehara, Hiroaki
中科院分区：
文献类型：
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作者：
Naruse, Yasushi;Takiyama, Ken;Umehara, Hiroaki
我们开发了一种统计方法，用于从单一试验中获得的脑电图（EEG）数据中检测人脑波动α节律中的不连续相位变化（相移）。该方法采用状态空间模型和线条处理技术，这是一种检测图像不连续的贝叶斯方法。通过将这种方法应用于模拟数据，我们能够在一次模拟试验中检测到相位和幅度的变化。此外，我们证明了该方法即使在一次实验中也可以从实验脑电图数据中检测到由视觉刺激引起的α节律相移。实验数据的结果表明，许多实验在早期潜伏期的相移时间相似，而在晚期潜伏期的相移时间不同。传统的平均方法只能检测在许多试验之间发生在相似时间点的相移，因此，使用传统方法无法检测在不同时间点发生的相移。因此，我们得到的结果表明了我们的方法的实用性。因此，我们相信我们的方法将有助于研究非线性α节律振荡器的相位动力学。DOI: 10.1103 / PhysRevE.87.042708
We developed a statistical method for detecting discontinuous phase changes (phase shifts) in fluctuating alpha rhythms in the human brain from electroencephalogram (EEG) data obtained in a single trial. This method uses the state space models and the line process technique, which is a Bayesian method for detecting discontinuity in an image. By applying this method to simulated data, we were able to detect the phase and amplitude shifts in a single simulated trial. Further, we demonstrated that this method can detect phase shifts caused by a visual stimulus in the alpha rhythm from experimental EEG data even in a single trial. The results for the experimental data showed that the timings of the phase shifts in the early latency period were similar between many of the trials, and that those in the late latency period were different between the trials. The conventional averaging method can only detect phase shifts that occur at similar timings between many of the trials, and therefore, the phase shifts that occur at differing timings cannot be detected using the conventional method. Consequently, our obtained results indicate the practicality of our method. Thus, we believe that our method will contribute to studies examining the phase dynamics of nonlinear alpha rhythm oscillators. DOI: 10.1103/PhysRevE.87.042708