本文選題：結(jié)構(gòu)網(wǎng)絡 + 功能網(wǎng)絡��； 參考：《電子科技大學》2017年碩士論文

【摘要】：近年來人們對大腦內(nèi)部組織結(jié)構(gòu)和生理機制的研究已經(jīng)越來越成為了科研上的熱點和難點,磁共振成像技術(shù)(MRI)的不斷成熟,可以更好地用于大腦內(nèi)部結(jié)構(gòu)的探測和研究。從網(wǎng)絡層面分析人腦的內(nèi)在連接關(guān)系和結(jié)構(gòu)特性可以從宏觀上更好的理解大腦的工作原理和生理機制。利于基于圖論的復雜網(wǎng)絡分析方法對疾病大腦網(wǎng)絡進行分析以此來探測疾病對大腦網(wǎng)絡狀態(tài)和組織結(jié)構(gòu)的改變可以有助于對疾病的研究。早發(fā)精神分裂癥(EOS)是一種因腦組織結(jié)構(gòu)和功能紊亂而引起的疾病,目前從網(wǎng)絡層面來研究這種疾病患者的大腦結(jié)構(gòu)特性還不是很多。本文以磁共振數(shù)據(jù)為背景,利用基于圖論的復雜網(wǎng)絡分析方法對早發(fā)精神分裂癥患者的大腦結(jié)構(gòu)與功能網(wǎng)絡進行分析研究。首先,利用EOS患者和正常對照組的彌散張量成像(DTI)數(shù)據(jù)和功能磁共振數(shù)據(jù)(fMRI)分別構(gòu)建了大腦的結(jié)構(gòu)網(wǎng)絡和功能網(wǎng)絡,在此基礎上利用小世界網(wǎng)絡模型,研究了被試的大腦結(jié)構(gòu)和功能網(wǎng)絡的連接狀態(tài),結(jié)果發(fā)現(xiàn),兩組被試的結(jié)構(gòu)網(wǎng)絡和功能網(wǎng)絡均表現(xiàn)出了小世界網(wǎng)絡的特性,不僅如此,患者組的結(jié)構(gòu)網(wǎng)絡小世界拓撲屬性指標、聚合系數(shù)指標、局部效率指標相對于正常對照組有明顯的升高,而網(wǎng)絡的全局強度有明顯的降低,這意味著早發(fā)精神分裂癥患者結(jié)構(gòu)網(wǎng)絡的穩(wěn)態(tài)性受到了破壞,內(nèi)部的結(jié)構(gòu)可能受損。其次,本文不僅計算和統(tǒng)計了網(wǎng)路的整體指標還對網(wǎng)絡的局部拓撲屬性指標進行了計算統(tǒng)計分析,結(jié)果發(fā)現(xiàn)患者結(jié)構(gòu)網(wǎng)絡在三角部額下回、枕上回、中央后回、頂上回、角回、顳橫回、顳上回區(qū)域相對于對照組有明顯升高的節(jié)點特征路徑長度;節(jié)點效率在三角部額下回、枕上回、頂上回有明顯的降低;并且中央后回、頂上回、角回的特征路徑長度與臨床PANSS量表有明顯的相關(guān)性。這些結(jié)果意味著從這些腦區(qū)出發(fā)的纖維存在損失而引發(fā)信息加工效率減弱。
[Abstract]:In recent years, the research on the internal structure and physiological mechanism of the brain has become more and more hot and difficult. Magnetic resonance imaging (MRI) technology can be used to detect and study the internal structure of the brain. Analyzing the internal connection and structural characteristics of human brain from the network level can better understand the working principle and physiological mechanism of the brain. The complex network analysis method based on graph theory can be used to analyze the brain network of disease to detect the changes in the state and structure of the brain network, which can be helpful to the study of disease. Early onset schizophrenia (EOS) is a disease caused by the disorder of brain structure and function. Based on magnetic resonance imaging (MRI) data, the brain structure and function network of patients with early onset schizophrenia were studied by using the complex network analysis method based on graph theory. Firstly, the brain structure network and functional network were constructed by using diffusion Zhang Liang imaging data and functional magnetic resonance data of EOS patients and normal controls, respectively, and the small-world network model was used. The connection status of brain structure and functional network was studied. The results showed that the structural network and functional network of the two groups showed the characteristics of small-world network, not only that, but also the topological attributes of the small-world network of patients. The index of aggregation coefficient, the index of local efficiency, and the index of local efficiency were significantly higher than those of the normal control group, but the global strength of the network was significantly decreased, which meant that the steady-state of the structural network of patients with early onset schizophrenia was destroyed. The internal structure may be damaged. Secondly, this paper not only calculates and statistics the overall index of the network, but also calculates and analyzes the local topological attribute of the network. The results show that the patient structure network is located in the trigonometric subfrontal gyrus, supraoccipital gyrus, posterior central gyrus, superior parietal gyrus, angular gyrus. Transverse temporal gyrus and superior temporal gyrus had significantly increased nodal characteristic path length compared with the control group, and the joint efficiency was significantly decreased in the inferior frontal gyrus, superior occipital gyrus and superior parietal gyrus, and the posterior central gyrus, superior parietal gyrus, and supraparietal gyrus. There was a significant correlation between the length of characteristic pathway of angular gyrus and clinical PANSS scale. These results imply a loss of fibers from these brain regions, resulting in reduced information processing efficiency.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R445.2;O157.5

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