Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N Michigan Avenue, Suite 1100, Chicago, IL 60611, USA.
J Neurosci Methods. 2010 Jan 30;186(1):107-15. doi: 10.1016/j.jneumeth.2009.10.022. Epub 2009 Nov 10.
During dynamic voluntary movements, power in the alpha- and beta-bands resulting from synchronized neuronal activity is modulated in a manner that is time-locked to movement onset. These signals can be readily recorded from the scalp surface using electroencephalography. Abnormalities in the magnitude and timing of these oscillations are present in a wide variety of movement disorders including Parkinson's disease and dystonia. Most studies have examined movement-related oscillations in the context of single discrete movements, yet marked impairments are often seen during the performance of repetitive movements. For this reason, there is considerable need for analysis methods that can resolve the modulation of these oscillations in both the frequency and time domains. Presently, there is little consensus on which is the most appropriate method for this purpose. In this paper, a comparison of commonly used time-frequency methods is presented for the analysis of movement-related power in the alpha- and beta-bands during repetitive movements. The same principles hold, however, for any form of repetitive or rhythmic input-output processes in the brain. In particular, methods based on band-pass filtering, the short-time Fourier transform (STFT), continuous wavelet transform and reduced interference distributions are discussed. The relative merits and limitations in terms of spectral or temporal resolution of each method are shown with the use of simulated and experimental data. It is shown that the STFT provides the best compromise between spectral and temporal resolution and thus is the most appropriate approach for the analysis and interpretation of repetitive movement-related oscillations in health and disease.
在动态自愿运动中，源自神经元活动同步的 alpha 和 beta 频带中的功率以与运动起始时间锁定的方式进行调制。这些信号可以使用脑电图从头皮表面上轻松记录。在包括帕金森病和肌张力障碍在内的各种运动障碍中，这些振荡的幅度和定时异常都存在。大多数研究都在单个离散运动的背景下检查了与运动相关的振荡，但在重复运动的过程中通常会出现明显的障碍。因此，非常需要能够在频率和时域中解析这些振荡调制的分析方法。目前，对于此目的，哪种方法最合适尚无共识。本文比较了常用于分析重复运动中 alpha 和 beta 频带中与运动相关的功率的时频方法。但是，相同的原理也适用于大脑中任何形式的重复或节律性输入输出过程。特别讨论了基于带通滤波，短时傅里叶变换（STFT），连续小波变换和减少干扰分布的方法。使用模拟和实验数据显示了每种方法在光谱或时间分辨率方面的相对优点和局限性。结果表明，STFT 在光谱和时间分辨率之间提供了最佳的折衷，因此是分析和解释健康和疾病中与重复运动相关的振荡的最合适方法。
