本文選題：精神分裂癥 + 腦網(wǎng)絡(luò)��； 參考：《天津醫(yī)科大學(xué)》2017年碩士論文

【摘要】：研究目的:精神分裂是一種嚴(yán)重的精神障礙類疾病,相關(guān)研究表明,腦區(qū)之間的不正常連接、紊亂的振蕩活動和同步性的改變是精神分裂癥的顯著特征。為了研究精神分裂患者在聽覺門控過程中的腦網(wǎng)絡(luò)連接狀態(tài),本文利用基于頻域的格蘭杰因果方法分析了聽覺條件-測試范式下門控過程中腦電信號因果連接特性,并利用圖論參數(shù)分頻段量化分析了精神分裂患者門控過程中的全局和局部網(wǎng)絡(luò)連接特征,探索是否存在腦網(wǎng)絡(luò)的特異性標(biāo)志對精神分裂癥患者在臨床上的診斷和治療進(jìn)行評估,為定量分析精神分裂的腦網(wǎng)絡(luò)和腦功能狀態(tài)提供理論基礎(chǔ)和技術(shù)支持。研究方法:本論文基于聽覺條件-測試范式下32通道EEGs,應(yīng)用基于Granger因果分析的DTF方法計算兩組受試者的因果連接矩陣,并根據(jù)矩陣構(gòu)建腦功能連接網(wǎng)絡(luò)并定量分析了兩組受試者的連接特性差異。研究方法包括:(1)實驗數(shù)據(jù):利用聽覺條件-測試聽覺刺激范式,分別采集20名精神分裂患者和20名正常受試者32通道的腦電;(2)對32通道的EEGs數(shù)據(jù)進(jìn)行預(yù)處理,去除工頻干擾、基線漂移等噪聲和偽跡;(3)對預(yù)處理后的數(shù)據(jù)利用基于頻域的格蘭杰因果的直接傳遞函數(shù)方法計算從通道j到通道i的因果連接矩陣,構(gòu)建出了因果連接網(wǎng)絡(luò);(4)計算全腦的平均因果連接強度,并計算額區(qū)、中央?yún)^(qū)及頂區(qū)的腦區(qū)內(nèi)部和腦區(qū)之間的因果連接強度;(5)計算兩組受試者的集群系數(shù)和全局效率等因果網(wǎng)絡(luò)評價參數(shù);(6)計算整個腦區(qū)的信息流增益情況,畫出信息流增益的空間分布;(7)計算兩組受試者的rich-club系數(shù),判斷是否存在rich-club特性。研究結(jié)果:1.各頻段的平均因果連接強度在High-beta和Gamma頻段,SZ組(精神分裂受試組)的DTF_(mean)顯著高于HC組(健康對照組),并且存在顯著性差異。2.各腦區(qū)平均因果連接強度在中央?yún)^(qū)內(nèi)部及中央?yún)^(qū)到頂區(qū)的連接中,在High-beta和Gamma頻段SZ組的DTF連接值顯著大于HC組;在中央?yún)^(qū)到額區(qū)的連接中,在各頻段SZ組的DTF連接值均顯著大于HC組;在頂區(qū)內(nèi)部的連接中,在Theta和Alpha頻段SZ組的DTF連接值均顯著大于HC組。3.因果網(wǎng)絡(luò)的定量描述在High-beta和Gamma頻段,SZ組的集群系數(shù)值顯著高于HC組,且SZ組的全局效率值顯著高于HC組。4.各頻段信息流增益兩組受試者的主要信息活躍區(qū)均在中央-頂葉區(qū)域,SZ組的PO_3通道附近的信息流增益低于HC組,而SZ組Cz通道的增益值高于HC組,并且隨著頻段的增加,SZ組Fz通道的信息流增益變大。5.Rich-club系數(shù)SZ組和HC組均存在rich-club特性,且除High-beta頻段外,SZ組的rich-club系數(shù)均顯著低于HC組。研究結(jié)論:在聽覺門控抑制過程中,High-beta和Gamma頻段下大腦因果網(wǎng)絡(luò)存在著過連接現(xiàn)象,這可能是精神分裂患者無法有效的進(jìn)行聽覺門控抑制的潛在原因。精神分裂患者的腦區(qū)內(nèi)部與腦區(qū)之間的連接存在異常,提示精神分裂受試者的因果網(wǎng)絡(luò)連接的異常主要在中央?yún)^(qū)內(nèi)部及中央?yún)^(qū)到額區(qū)和頂區(qū)的連接。精神分裂受試者的聚集系數(shù)和全局效率在High-beta和Gamma頻段均顯著高于正常受試者,表明在高頻段,精神分裂患者腦網(wǎng)絡(luò)的局部連接特性和全局連接特性參數(shù)提高,提示精神分裂患者在聽覺門控抑制過程中,無法有效的區(qū)分外界的有效信息和干擾信息,部分腦區(qū)被干擾信息激活,復(fù)雜網(wǎng)絡(luò)特性出現(xiàn)異常。信息流增益研究進(jìn)一步發(fā)現(xiàn),精神分裂受試者的Cz通道和高頻段額區(qū)的信息流活動增加,頂枕區(qū)的信息流活動減少。計算網(wǎng)絡(luò)的rich-club系數(shù)發(fā)現(xiàn),精神分裂患者和正常受試者都具有rich-club特性,說明在網(wǎng)絡(luò)中存在節(jié)點度大的節(jié)點且相互之間更趨向于緊密連接。
[Abstract]:Research objectives: schizophrenia is a serious mental disorder. Related studies have shown that abnormal connections between the brain regions, chaotic oscillations and synchrony changes are significant characteristics of schizophrenia. In order to study the brain network connection status of schizophrenic patients in the auditory gating process, this paper uses the frequency domain. The Grainger causality method analyses the causality connection characteristics of the EEG in the threshold control process under the auditory condition test paradigm, and quantifies the global and local network connection characteristics in the gated process of schizophrenic patients by using the graph parameter frequency division to explore whether there is a specific sign of the brain network for the schizophrenic patients in clinical practice. The diagnosis and treatment are evaluated to provide theoretical basis and technical support for quantitative analysis of schizophrenia brain networks and brain functions. Research methods: Based on the 32 channel EEGs under the auditory conditioned test paradigm, this paper uses the DTF method based on Granger causality analysis to calculate the causal connection matrix of the two groups of subjects, and according to the matrix structure. The brain functional connection network and quantitative analysis of the differences in connection characteristics between the two groups were made. The research methods included: (1) experimental data: using auditory condition - Testing auditory stimulus paradigm, 20 schizophrenic patients and 20 normal subjects were collected separately in 32 channels of brain electricity; (2) the EEGs data of the 32 channels were preprocessed to remove the frequency interference, base Line drift and other noise and artifacts; (3) the preprocessed data is calculated using the direct transfer function method of Grainger causality based on the frequency domain to calculate the causal connection matrix from channel J to channel I, and construct a causal connection network; (4) calculate the average causal connection intensity of the whole brain, and calculate the frontal area, the inner and brain regions of the central and top areas. The strength of causal connection between the two groups; (5) calculating the parameters of the causal network evaluation of the cluster coefficient and the global efficiency of the subjects; (6) calculating the information flow gain in the whole brain, drawing the spatial distribution of the information flow gain; (7) calculating the rich-club coefficient of the two groups of subjects and judging whether there is a rich-club characteristic. The results of the study: 1. frequency bands The average causal connection intensity was in the High-beta and Gamma bands, and the DTF_ (mean) of the SZ group (the schizophrenic group) was significantly higher than that of the HC group (the healthy control group), and there was a significant difference in the mean causal connection between the.2. regions and the central region and the central area to the top area. The DTF connection value of the SZ group in High-beta and Gamma frequency bands was significantly larger. In the HC group, in the central area to the frontal area, the DTF connection value in each band SZ group is significantly greater than that of the HC group; the DTF connection value of the SZ group in the Theta and Alpha band SZ group is significantly larger than the HC group.3. causality network in the top region. The local efficiency value is significantly higher than that of the HC group.4., the main active areas of the two groups of information flow gain are in the central parietal lobe region, the information flow gain near the PO_3 channel in the SZ group is lower than that of the HC group, while the gain value of the Cz channel in the SZ group is higher than that of the HC group, and with the increase of the frequency band, the gain of the information flow of the SZ group Fz channel becomes larger.5.Rich-club coefficient S. There are rich-club characteristics in both group Z and HC group, and the rich-club coefficient of SZ group is significantly lower than that of group HC except High-beta band. Conclusion: in the process of auditory gating suppression, there is a phenomenon of over connection in the brain causality network under High-beta and Gamma frequency bands, which may be the potential of the schizophrenic patients to be unable to effectively carry out auditory gated suppression. There is an abnormal connection between the brain area and the brain area of the schizophrenic patients, suggesting that the abnormal connections between the schizophrenic subjects are mainly in the central and central areas and the central and the top areas. The aggregation coefficient and the global efficiency of the schizophrenic subjects are significantly higher in the High-beta and Gamma frequency bands than in the normal subjects. It is shown that in the high frequency segment, the local connection characteristics and the global connection characteristic parameters of the brain network in the schizophrenic patients are improved, suggesting that the schizophrenic can not effectively distinguish the external effective information and interference information in the auditory gated control process. Some brain regions are disturbed by interference and the characteristics of the complex network are abnormal. The information flow increases. It is further found that the information flow activity in the Cz channel and the high frequency section of the schizophrenic subjects is increased and the information flow activity in the top pillow area is reduced. The rich-club coefficient of the computing network shows that both the schizophrenic and the normal subjects have the rich-club characteristics, indicating that there are nodes with large nodes in the network and tend to be closer to each other in the network. Close to close connections.
【學(xué)位授予單位】：天津醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R749.3;TN911.7

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本文編號：2022710