EEG Beta Wave Trains Are Not the Second Harmonic of Mu Wave Trains in Parkinson’s Disease Patients

The goal of this study is development of a novel signal processing and analysis method for detailed investigation of the time-frequency dynamics of brain cortex electrical activity. The idea of our method of electroencephalograms (EEG) analyzing is in that we consider EEG signal as a composition of so-called wave trains. The wave train term is used to denote a signal localized in time, frequency, and space. We consider the wave train as a typical component of EEG, but not as a special kind of EEG signals. In contrast to papers devoted to detecting wave trains of one or two specific types, such as alpha spindles and sleep spindles, we analyze any kind of wave trains in a wide frequency band. Using this method, we have found three interesting frequency areas where differences were detected between a group of Parkinson’s disease (PD) patients and a control group of healthy volunteers. The goal of this work is to check whether the regularities in the mu and beta frequency bands are independent ones, that is, the beta wave trains observed in the analysis were not the second harmonics of the mu wave trains. We have developed a special algorithm that eliminates from the analysis all beta wave trains in EEG signal that were observed simultaneously with the mu wave trains. Analysis of a real experimental data set processed by this algorithm has confirmed that the beta frequency band regularity is separate from the mu frequency band regularity. Moreover, a new significant difference between the left hand tremor and right hand tremor Parkinson’s disease patients was discovered.