基于功能磁共振成像的针刺效应研究

发布时间：2018-02-24 00:49

本文关键词： 功能磁共振成像一般线性模型独立成分分析针刺效应组间独立成分分析　出处：《湖南大学》2013年硕士论文　论文类型：学位论文

【摘要】：针刺医学是中华民族优秀传统科学和文化的瑰宝，其应用广泛，疗效显著，为中华民族的繁荣昌盛作出了重大贡献。根据传统中医理论以及大量的临床研究，针刺效应存在持续性。针刺效应是指针刺刺激对机体生理、病理过程的影响，是通过针刺这种非特异性刺激激发或诱导体内固有的调节系统，使失调、紊乱的生理生化过程恢复正常。目前，与针刺效应相关的研究大都难以突破经验医学的界限，不能客观的阐明针刺的有效性和作用机理，因而限制了针刺疗法的进一步推广与应用。 fMRI(functional magnetic resonance imaging)由于其无创性为研究针刺效应提供了方便，也使得探寻经穴－大脑－脏腑之间的相互作用关系成为可能。该技术由于无创性、无辐射以及图像的时间和空间分辨率高等优势，，已经成为研究针刺效应以及活体研究人脑中枢神经系统的重要手段。用功能磁共振成像技术来研究针刺效应，采集的数据包含的只是脑皮层不同位置对针刺响应的活动，这些活动是不同的脑部活动所产生的各种信号的叠加，这些独立的源信号反映了脑部实际活动情况，如果把这些独立的源信号分离出来就可以获得真正意义上的生理信号，从而有助于了解大脑活动，进而达到了解针刺对人脑中枢神经系统作用机理的目的。ICA(independent component analysis)是解决以上问题的一种有效方法。ICA不需要对实验设计的时间序列有预先的了解，具有广阔的应用前景。本文利用针刺实验中的功能磁共振像数据进行了以下研究。 (1)探讨了目前国际上广泛应用的脑功能磁共振成像数据处理软件SPM(statistical parametric mapping)的基本原理和应用，给出了SPM中利用广义线性模型(GLM)构建统计参数图的方法，并针对手针和电针实验中的fMRI数据采用SPM进行了针刺效应的统计分析和比较。 (2)介绍了ICA的原理以及目前国际上比较流行的组间独立成分分析(GroupICA)来处理多个被试的fMRI数据的方法。将其应用于手针(MA)和电针(EA)实验中的fMRI数据处理，成功提取出默认网络，并对两种模态下的脑默认模式网络进行了分析比较。
[Abstract]:Acupuncture medicine is the treasure of the excellent traditional science and culture of the Chinese nation, its application is extensive, the curative effect is remarkable, has made the great contribution to the prosperity of the Chinese nation. The acupuncture effect is the effect of needle stimulation on the physiological and pathological process of the body. It is caused by acupuncture which stimulates or induces the inherent regulatory system in the body. At present, most of the researches related to acupuncture effects are difficult to break through the limits of empirical medicine, and can not objectively clarify the effectiveness and mechanism of acupuncture. Therefore, the further popularization and application of acupuncture therapy are limited. Because of its noninvasive nature, fMRI(functional magnetic resonance imagingprovides convenience for the study of acupuncture effect and makes it possible to explore the interaction between meridian, cerebral-viscera and viscera. The advantages of no radiation and high spatial and temporal resolution of images have become an important means to study acupuncture effect and in vivo study of the central nervous system of human brain. Functional Magnetic Resonance Imaging (fMRI) is used to study the acupuncture effect. The data collected contain only the actions of the different parts of the cerebral cortex in response to acupuncture, which are the superposition of various signals generated by different brain activities. These independent source signals reflect the actual activity of the brain, and if these independent source signals are separated from each other, we can get real physiological signals, which will help us to understand the brain's activities. The purpose of understanding the mechanism of acupuncture on the central nervous system of human brain. ICA independent component analysis is an effective method to solve the above problems. ICA does not need to have a prior understanding of the experimental design time series. In this paper, the functional magnetic resonance imaging data of acupuncture experiment are used to study the following. (1) the basic principle and application of SPM(statistical parametric mapping software, which is widely used in the world, are discussed. The method of constructing statistical parameter map by using generalized linear model in SPM is given. According to the fMRI data of hand acupuncture and electroacupuncture experiment, SPM was used to analyze and compare the acupuncture effect. This paper introduces the principle of ICA and the method of processing the fMRI data of multiple subjects by using ICA, which is popular in the world at present. It is applied to fMRI data processing in hand acupuncture (MAA) and electroacupuncture (EA) experiments, and the default network is extracted successfully. The brain default network in two modes is analyzed and compared.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：R445.2;R245

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