發(fā)布時間：2018-03-28 18:49

  本文選題：靜息態(tài)功能磁共振成像　切入點：重性抑郁癥　出處：《第四軍醫(yī)大學》2017年博士論文

【摘要】：重性抑郁障礙(major depressive disorder,MDD)是一種常見的精神疾病。隨著對于抑郁癥的認識逐漸深入,目前的觀點認為MDD是大腦中異常連接所導致的多腦區(qū)功能紊亂�；诠δ艽殴舱癯上�(functional magnetic resonance imaging,fMRI)的研究發(fā)現大腦可以被分解為不同的功能網絡,各個功能網絡覆蓋的腦區(qū)在結構上不相連,然而在功能上卻存在緊密聯系。功能網絡在大腦處于任務狀態(tài)和靜息狀態(tài)下都具有相似的分布模式。以功能網絡為基礎研究大腦功能的重組和交互,能夠從網絡連接的角度解釋多腦區(qū)功能紊亂。因此靜息態(tài)功能網絡連接分析對精神疾病研究具有重要意義。MDD患者功能網絡內的功能連接異常已經被許多研究報道過。默認網絡(default mode network,DMN)、凸顯網絡(salience network,SN)和中央執(zhí)行網絡(central executive network,CEN)在MDD患者中均存不同程度的異常。腦區(qū)的異常能夠通過神經連接傳遞到另外的腦區(qū),因此研究異常腦區(qū)之間神經活動的作用方向,對理解疾病發(fā)病機制具有重要意義。功能連接反映腦區(qū)活動的相關性,卻不能提供神經活動的方向信息。有效連接分析方法能夠估計神經活動的連接方向及強度,但是需要基于先驗知識構建模型。因此探究不同功能網絡內部節(jié)點間的有效連接是功能網絡研究的熱點問題。大腦處于不同的功能狀態(tài)時,功能網絡的活躍程度也存在差異。比較功能網絡的活躍程度在時間上的變化關系,能夠得到網絡之間的連接關系。功能網絡之間的連接關系反映不同大腦功能之間的協同性。這種大腦功能網絡的協同性在許多精神疾病中都發(fā)生了異常。功能網絡之間的協同作用也是大腦功能網絡研究的一個熱點問題。皮層下深部腦區(qū)對大腦皮層具有廣泛的神經投射。深部腦區(qū)與皮層腦區(qū)在功能上的連接模式被稱為功能投射網絡。深部腦區(qū)對功能投射網絡的活動具有調節(jié)作用。根據深部腦區(qū)與功能投射網絡的連接關系,能夠對深部腦區(qū)進行功能劃分。研究疾病相關腦區(qū)與功能投射網絡的連接關系,以此進行腦區(qū)的功能劃分,對深部腦刺激技術(deep brain stimulation,DBS)等疾病干預技術有重要的指導作用。針對上面提出的三個問題,本文的研究主要從功能網絡內、功能網絡間和深部腦區(qū)的功能投射網絡三個角度研究了MDD患者的功能網絡異常。論文的主要工作包括:第一章為靜息態(tài)功能網絡的有效連接分析。前期研究表明MDD患者在DMN、CEN和SN均出現連接異常。為了發(fā)現這些網絡異常腦區(qū)間神經活動的作用方向和因果關系。本文首次采用頻譜動態(tài)因果模型(spectral dynamic causal modeling,spDCM)分析方法對功能網絡內的有效連接進行分析,并對比了MDD患者治療前、治療后和健康對照組之間的差異。通過獨立成分分析(independent component analysis,ICA)方法分解出靜息態(tài)功能網絡,并選擇出與MDD密切相關的靜息態(tài)功能網絡。再根據靜息態(tài)功能網絡的空間分布模式,分別選擇出網絡內部的關鍵節(jié)點。最后根據網絡內部關鍵節(jié)點構建DCM模型,使用spDCM估計功能網絡內關鍵節(jié)點之間的有效連接。結果發(fā)現MDD患者SN和DMN內部均存在有效連接異常。有效連接的結果表明,MDD患者DMN左側頂葉皮層(left parietal cortex,LPC)神經活動的調控作用降低。SN腹側子網絡內的右側前腦島(right anterior insula,RAI)區(qū)域的神經活動調控能力降低。SN前部子網絡的左側額葉皮層(left frontal cortex,LFC)存在異常的調控作用。第二章引入DCM方法對SN前部子網絡、SN腹側子網絡、DMN前部子網絡、DMN后部子網絡、CEN左側子網絡和CEN右側子網絡之間的有效連接進行建模,分別使用隨機DCM(stochastic dynamic causal modeling,sDCM)和spDCM對模型參數進行估計。并與Pearson相關法和最大延遲相關在MDD患者治療前、治療后和健康對照組的結果進行了對比。DCM模型選擇的結果顯示,治療前MDD組、治療后MDD組和健康對照組的功能網絡之間均存在因果聯系。DCM的結果驗證了SN對DMN與CEN相反的調節(jié)作用在MDD患者中出現異常,發(fā)現了SN與CEN之間的調節(jié)回路,以及SN與DMN后部子網絡對DMN前部子網絡相反的調控作用。同時也發(fā)現治療前MDD患者的DMN后部子網絡對CEN左側子網絡和CEN右側子網絡的異常激勵作用,這種異常調節(jié)作用在治療后也得到改善。第三部分使用功能投射網絡分析方法研究了丘腦內體素與功能投射網絡的連接關系。首先計算丘腦內每個體素的功能連接圖。再使用ICA方法估計出丘腦的全腦功能投射模式,并從這些模式中選擇出SN前部子網絡、SN腹側子網絡、DMN前部子網絡、DMN后部子網絡、CEN左側子網絡、CEN右側子網絡和運動網絡。對原有方法進行改進,使用有約束的多變量回歸模型估計每個丘腦體素與各個功能投射網絡的連接關系。最后根據丘腦體素與各個網絡連接的分布情況,對比MDD和健康對照組的丘腦的功能分區(qū)差異。結果發(fā)現MDD組右側丘腦內側前部區(qū)域與CEN右側子網絡的連接出現異常降低。丘腦腹部后側部分區(qū)域與運動網絡之間的連接在MDD患者中也低于健康對照組,但是該結果在經過多重比較校正后并不顯著。本文針對大腦功能網絡分析問題,使用功能網絡內有效連接分析、功能網絡間的連接分析和深部腦區(qū)的功能投射網絡分析方法,研究MDD患者的大腦功能網絡異常。功能網絡內有效連接分析定位了導致網絡異常的關鍵節(jié)點。功能網絡間的連接分析研究了網絡間的異常調控作用關系。功能投射網絡分析研究了丘腦內功能投射發(fā)生異常的區(qū)域。這三個種分析方法構成了一個較為全面的功能網絡分析框架。
[Abstract]:Major depressive disorder (major depressive, disorder, MDD) is a common mental disease. As for depression gradually deepening understanding, the current view is that MDD is dysfunction in multiple brain areas caused by abnormal connections in the brain. Based on functional magnetic resonance imaging (functional magnetic resonance imaging, fMRI) the study found that the brain can be the network function is decomposed into different brain regions, each functional coverage of the network is not connected in the structure, but in function are closely linked. Functional networks have similar distribution patterns of task state and resting state in brain function. In the network as the foundation to the study of brain function reorganization and interaction, from the network the connection point of interpretation function of multiple regions of the brain disorder. Resting state functional connectivity so it is important to analyze the function of patients with.MDD in the network research work on mental illness Can an abnormal connection has been proved by many studies reported. The default network (default mode network DMN (salience), network SN, highlighting the network) and the central executive network (central executive network, CEN) in the patients with MDD were abnormal in different degrees. The abnormal brain regions by neural connections can transfer to other brain regions therefore, the direction of neural activities between abnormal brain regions, has important significance in understanding the pathogenesis of diseases. The correlation of functional connectivity reflects brain activity, but can not provide the direction information of neural activity. Effective connectivity analysis method to estimate the connection direction and strength of neural activity, but the need to model construction based on the prior knowledge. Therefore explore the effective connection of internal nodes of different function between networks is a hot topic in the research function of the network. The brain in different functional states, active function of the network also There are differences between the degree of active function. The changes of network in time, can get the network connections between the connection between the network function. Reflect the synergy between different brain functions. The brain functional network coordination in many psychiatric disorders are abnormal. A hot issue between the function of the network the synergistic effect is the brain functional network research. Subcortical deep brain regions with extensive neural projection to the cerebral cortex. The connection mode of deep brain area and cortex function is called functional projection activities on the network. The network function mapping in deep brain regions play a role in the regulation of the network connections. According to the deep Department of brain and the function of projection, can be divided the function of deep brain regions. The connection network of brain areas related to disease and function of projection, the brain function of stroke Points of deep brain stimulation (deep brain stimulation, DBS) and other disease intervention technology has an important guiding role. Aiming at the three problems mentioned above, this paper mainly from the function of network, network function and deep brain function network projection three angles to research the function of network with MDD abnormal. The main work includes: the first chapter is the effective connectivity of resting state functional network analysis. Previous studies showed that MDD patients in DMN, CEN and SN showed abnormal connections. In order to find these network abnormal brain nerve activity interval direction and causal relationship. For the first time by the spectrum of dynamic causal model (spectral dynamic causal modeling, spDCM) were effective connection to function in the network analysis, and compares the differences between the MDD patients before treatment, after treatment and healthy control group. Through independent component analysis (in Dependent component analysis, ICA) method of decomposition of resting state functional network, and the choice of the resting state functional network closely related with MDD. According to the distribution pattern of resting state functional network space, respectively select key nodes within the network. Finally, according to the internal network of key nodes to build DCM model, using spDCM to estimate the effective connection between the key function of nodes within the network. The internal SN and DMN in patients with MDD were abnormal. The effective connection of effective connection. The results showed that MDD patients with DMN left parietal cortex (left parietal cortex, LPC) Regulation of neural activity decreased.SN ventral sub network in the right anterior insula (right anterior, insula, RAI) nerve regulating the activities of regional capacity to reduce.SN sub network in front of the left frontal cortex (left frontal cortex, LFC) in regulation of anomalies. The second chapter introduces the method of DCM SN Sub network, SN ventral sub network, DMN front DMN rear sub network, sub network between CEN and CEN on the right side of the left sub network connection sub network effectively modeled respectively using stochastic DCM (stochastic dynamic causal modeling, sDCM and spDCM). The model parameters were estimated and correlated with Pearson method and the maximum delay in MDD patients before treatment, after treatment and healthy control group compared.DCM model selection showed that MDD group before treatment, there was a causal relationship between the function of.DCM network of MDD group and control group after treatment, the results show that the SN of DMN and CEN opposite role in abnormal MDD patients, were found between SN and CEN and SN and the DMN loop, the rear sub network regulation of DMN front sub network opposite. Also found before treatment in patients with MDD DMN CEN on the left rear sub network subnet The abnormal incentive effect of collaterals and the right of CEN sub network, the abnormal regulation is also improved after treatment. The third part studies the connection between the use and function of the thalamus voxel projection network analysis function mapping network. First calculate the function within the thalamus of each voxel connected graph. Then use the ICA method to estimate the total brain function projection patterns of the thalamus, and the choice of the SN front sub network from these patterns, SN ventral sub network, DMN front sub network, DMN CEN left rear sub network, sub network, CEN network and sub network. The right movement for improvement on the original method, using the constrained multivariable regression model estimation connection between each voxel and thalamus each function projection network. Finally according to the distribution of thalamic voxel connected to each network, function zoning difference comparison between MDD and thalamus in healthy control group. The results showed that MDD group On the right side of the front area of the medial thalamus and CEN right sub network is abnormal. Between the posterior portion of the thalamus decreased abdominal area and the movement of network connection in MDD patients was lower than that of the control group, but the results after correction for multiple comparisons was not significant after. According to the brain functional network analysis, network connection function analysis, link analysis and deep brain function mapping network function between the network analysis method, the brain functional network of MDD patients with abnormal function in the network. The network connection effective positioning analysis leads to different key nodes. The abnormal regulation of the relationship between the network connection between the network analysis function. The function of projection network analysis of the abnormal region of the thalamus. These three functional projection methods constitute a comprehensive analysis framework. The function of network

【學位授予單位】：第四軍醫(yī)大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：R445.2;R749.4
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本文編號：1677589