Research On The Acupuncture Neural Electrical Signals Conduction And Effect

The thesis is the first study of the acupuncture neural electrical signals conduction and effect. Acupuncture is an important part of Chinese medicine with unique ways of thinking and rich experiences whose efficacy has been proved by Chinese clinical research during thousands of years, but the exact mechanism of acupuncture is still unclear. The neural system is the crucial regulation system that adapts the body to a certain degree of changes of their physiological function and external environment, thus keeping the body in a balanced state. Acupuncture is equivalent to an external stimulus to the nervous system, which induces the nervous system to evoke various kinds of neural electrical signals due to both the variation of the stimulus and the highly nonlinearity of the nervous system itself. Different acupuncture manipulates lead to different kinds of neural electrical signals. In the thesis, modern signal processing techniques such as statistical methods and nonlinear time series analysis methods are applied to analyze the characteristics of neural electrical signals evoked by different manual acupuncture (MA), quantify and distinguish MA, and study the effects of acupuncture on the neural system.To explore the acupuncture neural electrical signals conduction and effect, three experiment schemes are designed that acupuncture at Zusanli acupoint with four different MA to obtain action potentials at dorsal spinal nerve root from peripheral nervous system and spinal dorsal horn from lower central nervous system in Sprague-Dawley (SD) rat. In addition body-surface electrical signals from high central neural system in human body are also obtained. The main content includes three parts as follows.Firstly, for action potential sequences at dorsal spinal nerve root and spinal dorsal horn, we introduce the concept of the point process and interspike interval (ISI). The rate coding and timing coding of neural electrical signals evoked by different MA are first studied based on firing rate and coefficient of variation. Then, power spectrum analysis and Lyapunov Exponent are used to show that the neural electrical signals evoked by acupuncture are non-random. Another two nonlinear indices, correlation dimension and Lempel-Ziv complexity, are employed to measure their complexity, which further demonstrates the typical deterministic nonlinear property of the acupuncture neural electrical signals. At last, all characteristics parameters obtained above are joined together to do the cluster analysis of acupuncture neural electrical signals, which distinguish different MA effectively.Secondly, for electroencephalographic (EEG) from human brain, we first use correlation dimension and determinism index based on recurrence plot to measure the complexity changes of different brain areas during acupuncture and find that acupuncture makes brain electrical activity more complicated. Then, the conception of phase synchronization are applied to study the effect of acupuncture on the synchronization between different brain areas. Finally, Granger causality method is applied to investigate the information communication between different brain areas during acupuncture.Last but not the least, a modified neuron model under the external electrical stimulus is built for the study of the firing pattern evoked by electrical acupuncture (EA). Via numerical simulation, it shows that various firing patterns such as period, bursting, and chaos firing pattern are evoked under the effect of external sinusoidal EA with different intensity and frequency. It is also found that there are similar firing patterns between the neural electrical signals evoked by MA and EA.The obtained results can give some theoretical supports to reveal the acupuncture action mechanism, and provide an effective way for the quantification and standardization of acupuncture diagnosis based on neural electrical information.