本文選題：阿爾茲海默癥 + 腦電信號(hào)分析��； 參考：《天津大學(xué)》2016年碩士論文

【摘要】：腦功能網(wǎng)絡(luò)研究對(duì)于了解大腦信息處理方式以及認(rèn)知表達(dá)的神經(jīng)生理機(jī)制具有重要意義,而現(xiàn)代的腦成像技術(shù)和復(fù)雜網(wǎng)絡(luò)理論為腦功能網(wǎng)絡(luò)的研究提供了必要的基礎(chǔ)。本文基于靜息態(tài)的阿爾茲海默癥(AD)腦電信號(hào)構(gòu)建異常腦功能網(wǎng)絡(luò),并分析其網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)的改變,有助于理解AD的發(fā)病機(jī)制并為診斷提供輔助。本文應(yīng)用有限穿越可視圖與相空間最近鄰點(diǎn)建網(wǎng)方法,構(gòu)建單導(dǎo)聯(lián)腦電信號(hào)的腦功能網(wǎng)絡(luò)。首先通過(guò)將腦電信號(hào)時(shí)間序列映射為復(fù)雜網(wǎng)絡(luò),對(duì)復(fù)雜網(wǎng)絡(luò)進(jìn)行網(wǎng)絡(luò)拓?fù)浞治?提取其網(wǎng)絡(luò)的特征參數(shù)并以此來(lái)表征原始時(shí)間序列的動(dòng)力學(xué)特性。研究結(jié)果顯示,與正常老年對(duì)照組相比,AD患者單導(dǎo)聯(lián)腦功能網(wǎng)絡(luò)的拓?fù)涑霈F(xiàn)異常,網(wǎng)絡(luò)平均最短路徑長(zhǎng)度與聚類系數(shù)發(fā)生改變。其中顯著性變化主要出現(xiàn)在頂部、枕部和右顳部。本文進(jìn)一步提取序列間的同步性構(gòu)建并分析多導(dǎo)聯(lián)的腦功能網(wǎng)絡(luò)。通過(guò)前面得到的單導(dǎo)聯(lián)復(fù)雜網(wǎng)絡(luò)聚類系數(shù)序列,計(jì)算兩導(dǎo)信號(hào)間的皮爾遜相關(guān)系數(shù),以及不同導(dǎo)聯(lián)間的同步似然(SL)和模糊同步似然(FSL)系數(shù),利用圖論理論提取網(wǎng)絡(luò)拓?fù)鋮?shù),分析四個(gè)頻帶下AD腦功能網(wǎng)絡(luò)的拓?fù)浣Y(jié)構(gòu),發(fā)現(xiàn)顯著性差異主要發(fā)生在alpha頻帶,AD腦功能網(wǎng)絡(luò)具有“失連接”現(xiàn)象,即腦區(qū)之間的腦功能連接減少,導(dǎo)致功能網(wǎng)絡(luò)的圖指數(shù)復(fù)雜度降低及小世界屬性削弱。此外,對(duì)于同步似然(SL)和模糊同步似然(FSL)算法,在分析真實(shí)實(shí)驗(yàn)數(shù)據(jù)之前,本文利用Henon耦合模型產(chǎn)生仿真數(shù)據(jù),驗(yàn)證了該算法的有效性并比較其優(yōu)劣。最后,經(jīng)過(guò)多種方法和不同維度的腦功能網(wǎng)絡(luò)的構(gòu)建與分析,本文得到了阿爾茲海默癥對(duì)腦功能網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)的影響,發(fā)現(xiàn)其網(wǎng)絡(luò)特征參數(shù)的異常改變,可以通過(guò)檢測(cè)網(wǎng)絡(luò)特征參數(shù)的變化對(duì)阿爾茲海默癥進(jìn)行診斷輔助與康復(fù)評(píng)估。
[Abstract]:The study of brain functional networks is of great significance in understanding the neurophysiological mechanisms of brain information processing and cognitive expression. Modern brain imaging technology and complex network theory provide a necessary basis for the study of brain functional networks. In this paper, we construct abnormal brain functional network based on resting Alzheimer's disease (AD) EEG signal, and analyze the change of its network topology, which is helpful to understand the pathogenesis of AD and provide assistance for diagnosis. In this paper, we use the method of constructing the network between the finite traversing visual map and the nearest neighbor point in phase space to construct the functional network of the single lead EEG signal. Firstly, by mapping the EEG time series into complex networks, the network topology of complex networks is analyzed, and the characteristic parameters of the network are extracted to characterize the dynamic characteristics of the original time series. The results showed that the topology of single-lead brain functional network in AD patients was abnormal, the average shortest path length and clustering coefficient of AD patients were changed. Significant changes occurred at the top, occipital and right temporal regions. In this paper, we further extract the synchronism between sequences to construct and analyze the multi-lead brain functional network. The Pearson correlation coefficient between the two conductance signals, the synchronous likelihood SLS and the fuzzy synchronous likelihood FSLs are calculated by the clustering coefficient sequence of the single lead complex network, and the topological parameters of the network are extracted by the graph theory. After analyzing the topological structure of AD brain functional network in four bands, it was found that the significant difference occurred mainly in the "disconnection" of AD brain functional network in alpha band, that is, the reduction of brain functional connection between brain regions. It leads to the reduction of graph exponential complexity and the weakening of small world properties. In addition, for the synchronous likelihood (SL) and fuzzy synchronous likelihood (FSL) algorithms, before analyzing the real experimental data, the Henon coupling model is used to generate the simulation data, which verifies the effectiveness of the algorithm and compares its merits and demerits. Finally, through the construction and analysis of various methods and different dimensions of brain functional network, the influence of Alzheimer's disease on the topological structure of brain functional network is obtained, and the abnormal changes of network characteristic parameters are found. Diagnostic aids and rehabilitation assessments can be performed for Alzheimer's disease by detecting changes in network characteristic parameters.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：R749.16;O157.5

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