静息态脑功能磁共振数据分析方法及在弱视神经机制中的应用研究
发布时间：2019-05-30 03:29
【摘要】：人类大脑具有最复杂的体系框架,是一个高度复杂的网络系统,应用脑成像技术分析脑的功能与结构特性是认知科学中的重要研究内容。功能磁共振成像技术(functional magnetic resonance imaging,fMRI)基于血氧水平依赖原理(blood-oxygen level dependent,BOLD),具有无辐射性、无创性、高时空分辨率等多重优势,已成为脑科学研究的重要工具,受到临床、心理、神经和认知等领域的极大关注。静息态功能磁共振技术不需要被试做出反应,也不需要复杂精细的实验设计,容易被患者接受,非常适合临床上的应用和研究。 大量研究表明,在静息状态下人脑存在着一种低频振荡现象。尽管目前还不清楚它的具体生理意义,但是它与某些疾病的生理病理以及静息状态人脑的脑功能有着密切的关系。本文围绕fMRI在脑科学研究中的应用,以静息状态下的fMRI数据研究方法为突破口,对独立成分分析(independent component analysis,ICA)、局域一致性(regional homogeneity,ReHo)、低频振荡振幅算法(amplitude of low frequency fluctuations,ALFF)等静息状态fMRI脑图像分析方法,进行了系统性的深入研究和探讨。以此为基础,结合认知科学和临床研究中的前沿课题,开展了对弱视患者的视觉皮层功能异常研究,从而加深对弱视神经机制的理解和认识。全文的主要内容如下: 1、提出了具有三阶收敛的快速ICA算法。ICA方法可以从观测混合信号中分离出相互之间统计独立的源信号。本文引入负熵作为独立性的估计准则,给出ICA的一个优化模型。在此基础上,采用一种改进的牛顿迭代型的独立成分分析算法来提取fMRI信号中的各个独立成分;为加快收敛速度,对标准的牛顿迭代进一步修正,使算法具有三阶收敛。将该算法应用于fMRI大型数据的盲分离,并与目前广泛使用的另外两种算法比较,本文算法具有更快的收敛速度。 2、提出了基于ReHo选取种子区域并进行功能连接的新方法。传统的功能连接分析中,种子区域的选择常常是基于激活图或是基于解剖知识,而没有利用到静息状态的功能数据。本文利用局域一致性分析静息状态下的fMRI数据,将感兴趣区域中ReHo值最大的点所在的小区域作为种子进行功能连接。将脑的功能连接研究和局域一致性分析相结合,为研究人脑静息状态功能连接网络提供了新的思路。应用该方法,发现并验证了正常被试静息视觉网络的存在。 3、提出了利用静息状态fMRI数据,从功能连接的角度对屈光参差性弱视患者静息视觉网络进行研究的新思路。目前fMRI对弱视的研究多是基于有视觉刺激的情况下,本文采用ICA算法分离静息状态fMRI数据,针对ICA算法本身无法自动识别成分顺序问题,引入Goodness-of-fit方法提取静息状态下弱视患者和正常被试的静息视觉网络,将结果进行组内和组间分析。结果表明在屈光参差性弱视患者的静息视觉网络中,纹状皮层和纹外皮层均发生了明显的功能损害,其功能连接程度显著低于正常组,并且纹外皮层比纹状皮层损害更加严重,为深入研究弱视初、高级视觉皮层功能损害的神经机制提供了新的思路。 4、提出了采用ALFF方法研究弱视患者皮层功能损害的新方法。目前绝大部分静息fMRI研究关注的是不同脑区低频振荡的同步性即功能连接,功能连接的异常说明其功能整和出现变化,但是无法说明是哪一个脑区有不同的神经元活动,而低频振荡幅度方法可以提示局部神经元的自发活动,说明神经元活动的能量。本文首先采用ALFF方法检测出人脑默认模式网络,所得结果与已知研究结果具有很大的一致性,表明ALFF是一个有效的研究大脑静息状态自发性低频振荡的方法。然后使用该方法研究弱视患者闭眼、健眼刺激、患眼刺激三种静息状态下大脑的激活情况。研究结果表明在三种静息状态下,大脑出现了不同的激活情况,健眼刺激时受到的外界视觉刺激最多,因此在视觉皮层纹外区,其ALFF值最大;而在患眼刺激时,患者需要更多的选择性注意,因此在与注意有关的额上回区域,其ALFF值最大,显示该技术在大脑皮层功能定位上具有良好的应用价值,从另一个角度为研究弱视神经机制提供了新的方法。
[Abstract]:The human brain has the most complex system framework, it is a highly complex network system, and the application of brain imaging technology to analyze the function and structure characteristics of the brain is an important research content in cognitive science. Functional magnetic resonance imaging (fMRI), based on blood oxygen level dependent (BOLD), has many advantages, such as non-radiation, non-invasive, high temporal and spatial resolution, and has become an important tool in the research of brain science, and is subject to clinical and psychological. And is of great concern in the fields of nerve and cognition and the like. The resting-state magnetic resonance (MRI) technology does not need to be tested by the subjects, and the complex and fine experimental design is not required, which is easy to be accepted by the patients, and is very suitable for clinical application and research. A large number of studies have shown that there is a low frequency oscillation in the human brain at rest. Although it is not clear of its specific physiological significance, it is closely related to the pathophysiology of certain diseases and the brain function of the human brain at rest. Based on the application of fMRI in the study of brain science, the method of fMRI data in resting state is a breakthrough, and independent component analysis (ICA), local uniformity (ReHo) and low-frequency oscillation amplitude algorithm (low-frequency oscillation amplitude) are analyzed. The resting state fMRI brain image analysis method, such as ns (ALFF), has been carried out in a systematic and in-depth study. In this paper, the functional abnormality of the visual cortex of the patients with amblyopia was studied based on the leading subjects in cognitive science and clinical research, and the understanding of the weak optic nerve mechanism was enhanced. I. The main content of the full text as follows:1, a fast-order convergence is proposed ICA (ICA) method can separate from the observed mixed signals that they are independent of each other. In this paper, we introduce the negative entropy as the estimation criterion of the independence, and give the ICA's one. Based on this, an improved Newton iterative type independent component analysis algorithm is used to extract the individual components in the fMRI signal. In order to accelerate the convergence speed, the standard Newton iteration is further modified to make the algorithm There is a third-order convergence. The algorithm is applied to blind separation of large-scale fMRI data, and compared with the other two algorithms that are widely used at present, the algorithm is faster Convergence rate. A seed area based on ReHo is proposed and the seed selection is made. The new method of functional connection. In the traditional functional connection analysis, the selection of the seed region is often based on the activation map or on the basis of the anatomical knowledge, without the use of the static map. The function data of the interest status. This paper uses the local consistency to analyze the fMRI data in the resting state, and uses the small area of the point where the ReHo value in the region of interest is the largest. the functional connection of the brain is combined, the functional connection research of the brain and the local consistency analysis are combined, and the functional connection net for the rest state of the human brain is designed The network provides a new way of thinking. By applying the method, it is found and verified that the normal test is static In this paper, the resting state fMRI data and the angle of functional connection on the rest of the patients with anisometropic amblyopia were put forward. At present, the research of fMRI on the amblyopia is based on the visual stimulation. In this paper, the rest state fMRI data is separated by the ICA algorithm, the component order problem can not be automatically identified by the ICA algorithm itself, and the Goodness-of-fit method is introduced to extract the patients with amblyopia at rest. The resting visual network of the normal subjects will Results The results showed that in the resting vision network of the patients with anisometropic amblyopia, there were significant functional damage in the striated cortex and the outer cortex, and the degree of functional connection was significantly lower than that of the normal group. Severe, in order to study the functional damage of the visual cortex in the early and early stage of amblyopia The neural mechanism provides a new way of thinking.4. The method of ALFF is put forward. At present, most of the rest fMRI studies focus on the synchronization of low-frequency oscillation in different brain regions, that is, the function connection and the abnormal function of functional connection. Which brain region has different neuronal activity, and the low-frequency oscillation amplitude method can prompt the self-adaptation of local neurons. In this paper, an ALFF method is used to detect the human brain's default mode network, and the results are consistent with the results of the known research. The results show that ALFF is an effective study of the brain. A method for spontaneous low-frequency oscillation of the resting state. The method is then used to study the eye-closing of the patients with amblyopia, the stimulation of the eye and the stimulation of the affected eyes. The results of the study show that in the three rest states, the brain has different activation conditions, and the external visual stimuli at the time of eye-care stimulation are the most, so the ALFF value is the largest in the outer region of the visual cortex, and the stimulation is in the eyes of the affected eyes. As a result, the patient needs more selective attention, therefore, on the frontal area related to the attention, the value of ALFF is the largest, showing that the technique has good application value in the function positioning of the cerebral cortex, and the other angle is the research.
【学位授予单位】：南京航空航天大学
【学位级别】：博士
【学位授予年份】：2010
【分类号】：R777.44;O482.531
本文编号：2488481
[Abstract]:The human brain has the most complex system framework, it is a highly complex network system, and the application of brain imaging technology to analyze the function and structure characteristics of the brain is an important research content in cognitive science. Functional magnetic resonance imaging (fMRI), based on blood oxygen level dependent (BOLD), has many advantages, such as non-radiation, non-invasive, high temporal and spatial resolution, and has become an important tool in the research of brain science, and is subject to clinical and psychological. And is of great concern in the fields of nerve and cognition and the like. The resting-state magnetic resonance (MRI) technology does not need to be tested by the subjects, and the complex and fine experimental design is not required, which is easy to be accepted by the patients, and is very suitable for clinical application and research. A large number of studies have shown that there is a low frequency oscillation in the human brain at rest. Although it is not clear of its specific physiological significance, it is closely related to the pathophysiology of certain diseases and the brain function of the human brain at rest. Based on the application of fMRI in the study of brain science, the method of fMRI data in resting state is a breakthrough, and independent component analysis (ICA), local uniformity (ReHo) and low-frequency oscillation amplitude algorithm (low-frequency oscillation amplitude) are analyzed. The resting state fMRI brain image analysis method, such as ns (ALFF), has been carried out in a systematic and in-depth study. In this paper, the functional abnormality of the visual cortex of the patients with amblyopia was studied based on the leading subjects in cognitive science and clinical research, and the understanding of the weak optic nerve mechanism was enhanced. I. The main content of the full text as follows:1, a fast-order convergence is proposed ICA (ICA) method can separate from the observed mixed signals that they are independent of each other. In this paper, we introduce the negative entropy as the estimation criterion of the independence, and give the ICA's one. Based on this, an improved Newton iterative type independent component analysis algorithm is used to extract the individual components in the fMRI signal. In order to accelerate the convergence speed, the standard Newton iteration is further modified to make the algorithm There is a third-order convergence. The algorithm is applied to blind separation of large-scale fMRI data, and compared with the other two algorithms that are widely used at present, the algorithm is faster Convergence rate. A seed area based on ReHo is proposed and the seed selection is made. The new method of functional connection. In the traditional functional connection analysis, the selection of the seed region is often based on the activation map or on the basis of the anatomical knowledge, without the use of the static map. The function data of the interest status. This paper uses the local consistency to analyze the fMRI data in the resting state, and uses the small area of the point where the ReHo value in the region of interest is the largest. the functional connection of the brain is combined, the functional connection research of the brain and the local consistency analysis are combined, and the functional connection net for the rest state of the human brain is designed The network provides a new way of thinking. By applying the method, it is found and verified that the normal test is static In this paper, the resting state fMRI data and the angle of functional connection on the rest of the patients with anisometropic amblyopia were put forward. At present, the research of fMRI on the amblyopia is based on the visual stimulation. In this paper, the rest state fMRI data is separated by the ICA algorithm, the component order problem can not be automatically identified by the ICA algorithm itself, and the Goodness-of-fit method is introduced to extract the patients with amblyopia at rest. The resting visual network of the normal subjects will Results The results showed that in the resting vision network of the patients with anisometropic amblyopia, there were significant functional damage in the striated cortex and the outer cortex, and the degree of functional connection was significantly lower than that of the normal group. Severe, in order to study the functional damage of the visual cortex in the early and early stage of amblyopia The neural mechanism provides a new way of thinking.4. The method of ALFF is put forward. At present, most of the rest fMRI studies focus on the synchronization of low-frequency oscillation in different brain regions, that is, the function connection and the abnormal function of functional connection. Which brain region has different neuronal activity, and the low-frequency oscillation amplitude method can prompt the self-adaptation of local neurons. In this paper, an ALFF method is used to detect the human brain's default mode network, and the results are consistent with the results of the known research. The results show that ALFF is an effective study of the brain. A method for spontaneous low-frequency oscillation of the resting state. The method is then used to study the eye-closing of the patients with amblyopia, the stimulation of the eye and the stimulation of the affected eyes. The results of the study show that in the three rest states, the brain has different activation conditions, and the external visual stimuli at the time of eye-care stimulation are the most, so the ALFF value is the largest in the outer region of the visual cortex, and the stimulation is in the eyes of the affected eyes. As a result, the patient needs more selective attention, therefore, on the frontal area related to the attention, the value of ALFF is the largest, showing that the technique has good application value in the function positioning of the cerebral cortex, and the other angle is the research.
【学位授予单位】：南京航空航天大学
【学位级别】：博士
【学位授予年份】：2010
【分类号】：R777.44;O482.531
【引证文献】
相关期刊论文 前2条
1 郭小明;崔建明;;改进的遗传算法对fMRI数据分析的优化研究[J];科技致富向导;2012年09期
2 邵淑君;石妮妮;周华祥;;fMRI在弱视方面的研究进展[J];湖南中医杂志;2013年01期
相关博士学位论文 前1条
1 高玉杰;针刺少阳经特定穴对偏头痛患者脑功能动态影响的研究[D];成都中医药大学;2012年
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