Ordinal Pattern Based Complexity Analysis for EEG Activity Evoked by Manual Acupuncture in Healthy Subjects

Abstract

Manual acupuncture (MA) is widely used in Traditional Chinese Medicine clinic for pain treatment and controlling stress. To investigate how MA modulates brain activities, electroencephalograph (EEG) signals are recorded with 20 channels by MA at ST36 of right leg in 11 healthy subjects during rest. Two novel nonlinear measures based on ordinal patterns of EEG series, i.e. permutation entropy (PE) and order index (OI), are adopted to investigate the nonlinear complexity characteristic in EEG data at different acupuncture states. It is observed that the recorded EEG series during and after MA have higher PE values and lower OI values compared to before MA. The results show that MA at ST36 can increase EEG complexity, which is especially obvious during MA. Our findings suggest that the PE and OI measures are promising methods to reveal EEG dynamical changes associated with MA stimulus, which could provide a potential for further exploring the interactions between acupuncture and brain activity. Moreover, these preliminary conclusions highlight the beneficial modulations of brain activity by MA, which could contribute to understanding the acupuncture effects on brain, as well as the neurophysiological mechanisms underlying MA.

Complexity of resting-state EEG activity in the patients with early-stage Parkinson’s disease

“…. ; m!Þ to denote the probability distribution of permutation p j , the PE for this scalar series was defined as (Cao et al 2004;Li et al 2010;Yi et al 2014)…”

“…Based on this definition, the relevant normalized PE of the series can be written as (Cao et al 2004;Li et al 2010;Yi et al 2014) PE ¼ H p ðmÞ lnðm!Þ ð 2Þ…”

“…Like other entropies, PE was a measure of the unpredictability in the frequency distribution of a given time series Yi et al 2014). The more regular the series, the smaller the PE was.…”

“…Two common methods are permutation entropy (PE) (Bandt and Pompe 2002) and order index (OI) (Ouyang et al 2010). The former measures the unpredictability of time series Yi et al 2014), while the latter measures the predictability of the series. That is, a recorded data with high complexity corresponds to a larger PE and lower OI, whereas a low complexity leads to a lower PE and larger OI.…”

“…They have been successfully applied to analyze epileptic and anesthetic EEG data (Ouyang et al 2010;Cao et al 2004;Keller et al 2014;Li et al 2007Li et al , 2008Li et al , 2010. In our previous study (Yi et al 2014), we have also used them to detect the complexity changes of EEG activity associated with manual acupuncture at acupoint ST 36 in healthy subjects. These earlier studies demonstrate that the ordinal pattern based measures, i.e., PE or OI, offer some distinct advantages over classical complexity index.…”