靜息態(tài)腦功能磁共振數(shù)據(jù)分析方法及在弱視神經(jīng)機(jī)制中的應(yīng)用研究
發(fā)布時(shí)間：2019-05-30 03:29
【摘要】：人類大腦具有最復(fù)雜的體系框架,是一個(gè)高度復(fù)雜的網(wǎng)絡(luò)系統(tǒng),應(yīng)用腦成像技術(shù)分析腦的功能與結(jié)構(gòu)特性是認(rèn)知科學(xué)中的重要研究內(nèi)容。功能磁共振成像技術(shù)(functional magnetic resonance imaging,fMRI)基于血氧水平依賴原理(blood-oxygen level dependent,BOLD),具有無輻射性、無創(chuàng)性、高時(shí)空分辨率等多重優(yōu)勢,已成為腦科學(xué)研究的重要工具,受到臨床、心理、神經(jīng)和認(rèn)知等領(lǐng)域的極大關(guān)注。靜息態(tài)功能磁共振技術(shù)不需要被試做出反應(yīng),也不需要復(fù)雜精細(xì)的實(shí)驗(yàn)設(shè)計(jì),容易被患者接受,非常適合臨床上的應(yīng)用和研究。 大量研究表明,在靜息狀態(tài)下人腦存在著一種低頻振蕩現(xiàn)象。盡管目前還不清楚它的具體生理意義,但是它與某些疾病的生理病理以及靜息狀態(tài)人腦的腦功能有著密切的關(guān)系。本文圍繞fMRI在腦科學(xué)研究中的應(yīng)用,以靜息狀態(tài)下的fMRI數(shù)據(jù)研究方法為突破口,對(duì)獨(dú)立成分分析(independent component analysis,ICA)、局域一致性(regional homogeneity,ReHo)、低頻振蕩振幅算法(amplitude of low frequency fluctuations,ALFF)等靜息狀態(tài)fMRI腦圖像分析方法,進(jìn)行了系統(tǒng)性的深入研究和探討。以此為基礎(chǔ),結(jié)合認(rèn)知科學(xué)和臨床研究中的前沿課題,開展了對(duì)弱視患者的視覺皮層功能異常研究,從而加深對(duì)弱視神經(jīng)機(jī)制的理解和認(rèn)識(shí)。全文的主要內(nèi)容如下: 1、提出了具有三階收斂的快速ICA算法。ICA方法可以從觀測混合信號(hào)中分離出相互之間統(tǒng)計(jì)獨(dú)立的源信號(hào)。本文引入負(fù)熵作為獨(dú)立性的估計(jì)準(zhǔn)則,給出ICA的一個(gè)優(yōu)化模型。在此基礎(chǔ)上,采用一種改進(jìn)的牛頓迭代型的獨(dú)立成分分析算法來提取fMRI信號(hào)中的各個(gè)獨(dú)立成分;為加快收斂速度,對(duì)標(biāo)準(zhǔn)的牛頓迭代進(jìn)一步修正,使算法具有三階收斂。將該算法應(yīng)用于fMRI大型數(shù)據(jù)的盲分離,并與目前廣泛使用的另外兩種算法比較,本文算法具有更快的收斂速度。 2、提出了基于ReHo選取種子區(qū)域并進(jìn)行功能連接的新方法。傳統(tǒng)的功能連接分析中,種子區(qū)域的選擇常常是基于激活圖或是基于解剖知識(shí),而沒有利用到靜息狀態(tài)的功能數(shù)據(jù)。本文利用局域一致性分析靜息狀態(tài)下的fMRI數(shù)據(jù),將感興趣區(qū)域中ReHo值最大的點(diǎn)所在的小區(qū)域作為種子進(jìn)行功能連接。將腦的功能連接研究和局域一致性分析相結(jié)合,為研究人腦靜息狀態(tài)功能連接網(wǎng)絡(luò)提供了新的思路。應(yīng)用該方法,發(fā)現(xiàn)并驗(yàn)證了正常被試靜息視覺網(wǎng)絡(luò)的存在。 3、提出了利用靜息狀態(tài)fMRI數(shù)據(jù),從功能連接的角度對(duì)屈光參差性弱視患者靜息視覺網(wǎng)絡(luò)進(jìn)行研究的新思路。目前fMRI對(duì)弱視的研究多是基于有視覺刺激的情況下,本文采用ICA算法分離靜息狀態(tài)fMRI數(shù)據(jù),針對(duì)ICA算法本身無法自動(dòng)識(shí)別成分順序問題,引入Goodness-of-fit方法提取靜息狀態(tài)下弱視患者和正常被試的靜息視覺網(wǎng)絡(luò),將結(jié)果進(jìn)行組內(nèi)和組間分析。結(jié)果表明在屈光參差性弱視患者的靜息視覺網(wǎng)絡(luò)中,紋狀皮層和紋外皮層均發(fā)生了明顯的功能損害,其功能連接程度顯著低于正常組,并且紋外皮層比紋狀皮層損害更加嚴(yán)重,為深入研究弱視初、高級(jí)視覺皮層功能損害的神經(jīng)機(jī)制提供了新的思路。 4、提出了采用ALFF方法研究弱視患者皮層功能損害的新方法。目前絕大部分靜息fMRI研究關(guān)注的是不同腦區(qū)低頻振蕩的同步性即功能連接,功能連接的異常說明其功能整和出現(xiàn)變化,但是無法說明是哪一個(gè)腦區(qū)有不同的神經(jīng)元活動(dòng),而低頻振蕩幅度方法可以提示局部神經(jīng)元的自發(fā)活動(dòng),說明神經(jīng)元活動(dòng)的能量。本文首先采用ALFF方法檢測出人腦默認(rèn)模式網(wǎng)絡(luò),所得結(jié)果與已知研究結(jié)果具有很大的一致性,表明ALFF是一個(gè)有效的研究大腦靜息狀態(tài)自發(fā)性低頻振蕩的方法。然后使用該方法研究弱視患者閉眼、健眼刺激、患眼刺激三種靜息狀態(tài)下大腦的激活情況。研究結(jié)果表明在三種靜息狀態(tài)下,大腦出現(xiàn)了不同的激活情況,健眼刺激時(shí)受到的外界視覺刺激最多,因此在視覺皮層紋外區(qū),其ALFF值最大;而在患眼刺激時(shí),患者需要更多的選擇性注意,因此在與注意有關(guān)的額上回區(qū)域,其ALFF值最大,顯示該技術(shù)在大腦皮層功能定位上具有良好的應(yīng)用價(jià)值,從另一個(gè)角度為研究弱視神經(jīng)機(jī)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.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2010
【分類號(hào)】：R777.44;O482.531
本文編號(hào)：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.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2010
【分類號(hào)】：R777.44;O482.531
【引證文獻(xiàn)】
相關(guān)期刊論文 前2條
1 郭小明;崔建明;;改進(jìn)的遺傳算法對(duì)fMRI數(shù)據(jù)分析的優(yōu)化研究[J];科技致富向?qū)?2012年09期
2 邵淑君;石妮妮;周華祥;;fMRI在弱視方面的研究進(jìn)展[J];湖南中醫(yī)雜志;2013年01期
相關(guān)博士學(xué)位論文 前1條
1 高玉杰;針刺少陽經(jīng)特定穴對(duì)偏頭痛患者腦功能動(dòng)態(tài)影響的研究[D];成都中醫(yī)藥大學(xué);2012年
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