基于独立成分分析和时间相关分析的脑功能连通研究方法

目的：利用静息状态功能磁共振成像（functional magnetic resonance imaging，fMRI）技术，提出联合独立成分分析（independent component analysis，ICA）和时间相关分析的人脑功能连通性研究方法。方法：首先采用空间ICA定位任务激活的脑区；然后选择一个激活区作为感兴趣区域（region of interest，ROI），采用时间相关分析方法检测静息状态大脑特定皮层的功能连通性，并通过检测人脑运动皮层的功能连通性验证方法的有效性。结果：大脑运动皮层功能连通网络包括初级运动区、辅助运动区、初级感觉皮层、背侧前运动区和后顶骨体觉区。实验结果表明，静息状态下。时间相关分析检测到的运动皮层的功能连通网络与已知的解剖连通相一致。结论：利用静息fMRI。结合空间ICA和时间相关分析方法。检测了静息时人脑运动皮层的功能连通网络。为脑区间功能连通的研究提供了一种简便的、无损的、有效的研究方法。     

基于功能磁共振的人脑视觉皮层V5区功能连通网络变化的研究

利用功能磁共振成像(functional magnetic resonance imaging,f MRI)技术,将空间独立成分分析(spatial independent component analysis,sICA)和时间相关方法相结合研究不同活动状态下人脑视觉运动功能连通网络的变化特性。首先利用sICA处理组块视觉运动刺激的数据,定位V5区;然后分别计算静息和连续视觉运动刺激两种稳态下V5区与其它脑区低频振荡的时间相关,检测出该区的功能连通网络。实验结果表明,静息时V5区的功能连通网络更广泛,且与已知的解剖连通一致;当被试接受连续视觉运动刺激时,与V5区连通的脑区网络局限在视觉皮层,此时的网络特定于处理视觉运动这一任务。     

基于fMRI数据的静息脑功能连接

目的:应用功能磁共振成像数据,对静息状态下大脑视觉系统功能连接模式[1]进行考证,并对不同状态下人脑视觉功能连接网络的变化[2,3]情况进行了研究。方法:基于脑区局部同一性[4],测量出一给定体素的时间序列与全脑其他体素时间序列的相似性。我们分别采集了视觉任务和静止两种状态下的功能磁共振成像数据,先是用K-均值的聚类方法[5,6]对视觉任务状态下的功能磁共振成像数据进行分析,做出分类图。然后通过分类图找到感兴趣种子区,平均种子区中各个体素的时间响应曲线,利用这个时间序列曲线与全脑体素作互相关分析[7],得出视觉任务下的全脑功能连接图,再把同样的感兴趣种子区域定位到静息状态下的脑区中用种子相关分析方法,作出静息状态下全脑视觉系统功能连接的网络模式及分布规律。结果:分别得到了视觉任务状态下和静息状态下以相同种子区为中心的功能连接网络图。结论:无论是在静息状态还是在任务状态下,大脑视觉系统各脑区之间的确存在密切的功能连接,而且状态不同所得到的视觉功能连接网络也不相同。     

基于静息态fMRI和DTI的大脑性别差异性研究

本研究从功能和结构两个方面来研究大脑存在的性别差异。利用ICA方法从大脑静息态fMRI数据中分离出大脑默认网络和感觉运动网络,通过双样本t检验来分析男女两性在脑皮层功能上所表现出来的异同;通过构建大脑白质纤维束结构网络,利用网络特征参数来分析男女脑部纤维结构上所存在的差异;通过二者联合技术来探讨两性大脑功能差异和结构差异的关系。结果发现两性大脑功能差异和结构差异在某些脑区有一定的一致性。男女两性大脑生理结构和功能有一定的关联性,两性大脑在功能上的差别可认为与两性在负责相关功能的脑区所具有的差异相关。     

低频重复经颅磁刺激刺激初级运动皮层对大脑功能连接影响的研究

重复经颅磁刺激(rTMS)能对刺激脑区及与其相连接的远端脑区产生影响。本文将从大脑功能连接、脑区之间相互协调工作状态改变的角度,研究低频rTMS刺激脑初级运动皮层对大脑的影响作用。募集了10名健康受试者,采用1 Hz rTMS刺激脑初级运动皮层20 min,采集刺激前后1 min闭目静息状态下的脑电(EEG)数据。对EEG进行相位同步分析,建立脑功能网络,并计算脑功能网络特征参数。最后使用符号秩和检验进行统计学分析。结果表明,低频rTMS刺激使大脑alpha频段全局相位同步指数显著降低(P0.05)。两两脑区分析表现为刺激侧的运动皮层与额叶皮层和顶叶皮层、非刺激侧顶叶皮层与双侧额叶皮层之间alpha频段相位同步显著降低。alpha频段脑功能网络的平均度、全局效率降低(P0.05),平均最短路径长度显著增加(P0.05)。表明低频rTMS使脑功能网络的信息传输变慢,传输效率变低。本文从大脑功能连接性的角度上证明了低频rTMS对大脑活动的抑制作用,说明低频rTMS能够对刺激脑区及与刺激脑区相连接的远端脑区产生影响。本研究有望为低频rTMS应用于临床疾病的治疗提供一定的指导。     

基于功能磁共振成像的大脑运动皮层网络连通性研究

研究的目的在于了解大脑皮层各区域间的信息传递模式,尤其是运动的时空模式。利用被试者手指运动时获得的功能磁共振图像,通过统计分析获得与运动相关的激活区域,计算各区域fMRI时间序列间的相关系数作为区域间的连接强度,建立运动皮层网络;按照距离规则建立若干个同样大小的非运动皮层网络,分别计算运动和非运动皮层网络的图测度和动力学测度。结果显示二者有显著性差异,运动皮层网络连接更加紧密,具有更高的统计独立性和整合度,可在某种程度上反映运动皮层网络的连通性。     

癫痫患者默认网络的静息态功能磁共振成像研究

目的:分析癫痫患者静息态fMRI下默认网络及其潜在结构的变化.方法:对15名临床诊断为原发全身强直痉挛癫痫患者和20名正常志愿者静息态时的fMRI数据进行独立成分分析,依据空间最佳匹配原则挑选独立成分,研究正常被试和癫痫患者的默认网络差异,并选定默认网络中11个脑区构建功能连接网络,运用图论和聚类方法探讨其潜在结构的改变.结果:与正常对照组相比,患者组默认网络的脑区激活普遍下降,功能连接网络发生明显变化,且整个网络呈现出混乱的层次化结构.结论:静息态下癫痫患者的默认网络及潜在的层次化结构发生异常.     

失眠患者大脑功能变化的磁共振影像学研究进展

失眠的脑功能改变一般先于脑实质的改变,而功能磁共振(fMRI)可以在生理状态下无创地反映不同脑区各自的功能状态。本文从失眠的静息态和任务态大脑功能变化两个方面,对失眠的fMRI研究进展进行综述。利用fMRI发现,在静息态方面,失眠患者的一些脑区的局部一致性值、低频振幅值等出现异常,功能连接出现改变;而在任务态方面,失眠患者在执行认知任务时,任务相关脑区的激活出现低水平活化。本文通过了解失眠的发病机制,以期将fMRI技术应用于失眠的临床诊断。     

基于独立成分分析的时间自相关方法在功能磁共振激活区自适应提取中的应用

传统基于ICA的激活区检测手段是将分离后的独立成分与参考信号做相关性分析。实际问题中,不同区域的脑血流动力学响应情况不同,因此往往得不到标准的参考信号。针对此类问题,提出时间自相关方法(TSC)与ICA方法结合,在不需要参考信号的情况下,通过检测体素点各周期的时间序列相关性,对fMRI数据进行激活区提取。应用5 邻域ICA方法对fMRI数据逐点处理,然后应用时间自相关算法检测各时间序列周期间的相关性,选择最大的自相关系数作为该体素点的信号值。再通过Z变换将相关系数分布转换为服从N(0,1)的Z分布,提取出具有显著性差异（a=0.05）的激活区。将自相关算法应用于仿真数据和12组双手握拳运动的真实fMRI数据的处理,结果表明该方法能够准确提取出仿真数据中的激活区。对真实数据的处理,该方法在空间准确性上与GLM方法无显著性差别(0.4653±0.1368 vs 0.4905±0.1341),在时间准确性上显著优于GLM方法 (0.6364±0.0111 vs 0.3692±0.0109),具有良好的脑功能激活区检测及空间定位能力。     

基于SPM的时间簇分析方法

目的：把时间簇分析方法和SPM这两种方法结合起来，能够提高时间簇分析方法的检测灵敏度，使得基于SPM的时间簇分析方法可以检测出大脑激活的时间曲线。方法：先用SPM得到相应的大脑激活，然后再对激活脑区进行TCA处理，就可以得到激活脑区的时间曲线。结果：用基于SPM的时间簇分析方法对一组视觉的fMRI数据进行处理，能够检测出对应于刺激的四个明显的激活峰。结论：基于SPM的时间簇分析方法的检测灵敏度比以前的时间簇分析方法的检测灵敏度有了很大提高，能够用于检测大脑激活的时间曲线。     

基于功能连接算法的斜视性弱视儿童静息态功能磁共振成像的研究

目的探索斜视性弱视儿童脑功能区及其功能连接的改变,揭示斜视性弱视的发生与脑功能改变的相关性。方法在静息态下采集22位斜视性弱视儿童和10名健康儿童脑功能磁共振图像,利用DPARSF软件计算全脑与ROI功能区的连接系数,并应用t检验对实验组和健康对照组进行组内和组间功能连接系数分析。结果发现斜视性弱视儿童部分脑功能连接低于正常对照组的相应脑区连接,这些功能区主要分布于枕叶、颞叶、小脑后叶、顶叶、额叶、扣带回等脑区。结论基于静息态的f MRI的脑功能连接算法可以反映斜视性弱视儿童视皮层的变化和多脑区神经活动的变化。     

Association Between the Basal Ganglia and Large-Scale Brain Networks in Epilepsy

Epilepsy may affect connectivity between the putamen and cortex even during the resting state. Putamen is part of the basal ganglia resting state network (BG-RSN) which is anti-correlated with the default mode network (DMN) in healthy subjects. Therefore, we aimed at studying the functional brain connectivity (FC) of the putamen with the cortical areas engaged in the DMN as well as with the primary somatomotor cortex which is a cortical region engaged in the BG-RSN. We compared the data obtained in patients with epilepsy with that in healthy controls (HC). Functional magnetic resonance imaging (fMRI) was performed in 10 HC and 24 patients with epilepsy: 14 patients with extratemporal epilepsy (PE) and 10 patients with temporal epilepsy (PT). Resting state fMRI data was obtained using the 1.5 T Siemens Symphony scanner. The Group ICA of fMRI Toolbox (GIFT) program was used for independent component analysis. The component representing the DMN was chosen according to a spatial correlation with a mask typical for DMN. The FC between the putamen and the primary somatomotor cortex was studied to assess the connectivity of the putamen within the BG-RSN. A second-level analysis was calculated to evaluate differences among the groups using SPM software. In patients with epilepsy as compared to HC, the magnitude of anti-correlation between the putamen and brain regions engaged in the DMN was significantly lower. In fact, the correlation changed the connectivity direction from negative in HC to positive in PE and PT. The disturbed FC of the BG in patients with epilepsy as compared with HC was further illustrated by a significant decrease in connectivity between the left/right putamen and the left/right somatomotor cortex, i.e. between regions that are engaged in the BG-RSN. The FC between the putamen and the cortex is disturbed in patients with epilepsy. This may reflect an altered function of the BG in epilepsy.     

Changes of functional connectivity of the motor network in the resting state in Parkinson's disease

We used functional MRI (fMRI) and a network model based on graph theory to measure functional connectivity of brain motor network in the resting state in patients with Parkinson's disease (PD). FMRIs were acquired in 22 PD patients before and after levodopa administration, and in age- and sex-matched normal controls. The total connectivity degree of each region within the motor network was calculated and compared between patients and controls. We found that PD patients at off state had significantly decreased functional connectivity in the supplementary motor area, left dorsal lateral prefrontal cortex and left putamen, and had increased functional connectivity in the left cerebellum, left primary motor cortex, and left parietal cortex compared to normal subjects. Administration of levodopa relatively normalized the pattern of functional connectivity in PD patients. The functional connectivity in most of regions in the motor network correlated with the Unified Parkinson's Disease Rating Scale motor score in the patients. Our findings demonstrate that the pattern of functional connectivity of the motor network in the resting state is disrupted in PD. This change is secondary to dopamine deficiency, and related to the severity of the disease. We postulate that this abnormal functional connectivity of motor network in the baseline state is possibly an important factor contributing to some motor deficits in PD, e.g. akinesia.     

Detecting Functional Connectivity in fMRI Using PCA and Regression Analysis

A fMRI connectivity analysis approach combining principal component analysis (PCA) and regression analysis is proposed to detect functional connectivity between the brain regions. By first using PCA to identify clusters within the vectors of fMRI time series, more energy and information features in the signal can be maintained than using averaged values from brain regions of interest. Then, regression analysis can be applied to the extracted principal components in order to further investigate functional connectivity. Finally, t-test is applied and the patterns with t-values lager than a threshold are considered as functional connectivity mappings. The validity and reliability of the presented method were demonstrated with both simulated data and human fMRI data obtained during behavioral task and resting state. Compared to the conventional functional connectivity methods such as average signal based correlation analysis, independent component analysis (ICA) and PCA, the proposed method achieves competitive performance with greater accuracy and true positive rate (TPR). Furthermore, the ‘default mode’ and motor network results of resting-state fMRI data indicate that using PCA may improve upon application of existing regression analysis methods in study of human brain functional connectivity.     

Normal aging decreases regional homogeneity of the motor areas in the resting state

Our knowledge about aging modulation of the central motor system remains sparse and contradictory. In the current study, we used functional MRI (fMRI) to study the aging influence on regional homogeneity of the motor-related brain areas in the resting state. We found that regional homogeneity in extensive motor regions, like the cingulate motor area, cerebellum, primary motor cortex, premotor area, supplementary motor area, thalamus, globus pallidus and putamen was significantly decreased in aged subjects. Our study indicates that normal aging process may disrupt the function of motor areas in the resting state, which may contribute to the declined motor ability in aged population.     

Basal ganglia circuits changes in Parkinson's disease patients

Functional changes in basal ganglia circuitry are responsible for the major clinical features of Parkinson's disease (PD). Current models of basal ganglia circuitry can only partially explain the cardinal symptoms in PD. We used functional MRI to investigate the causal connectivity of basal ganglia networks from the substantia nigra pars compacta (SNc) in PD in the movement and resting state. In controls, SNc activity predicted increased activity in the supplementary motor area, the default mode network, and dorsolateral prefrontal cortex, but, in patients, activity predicted decreases in the same structures. The SNc had decreased connectivity with the striatum, globus pallidus, subthalamic nucleus, thalamus, supplementary motor area, dorsolateral prefrontal cortex, insula, default mode network, temporal lobe, cerebellum, and pons in patients compared to controls. Levodopa administration partially normalized the pattern of connectivity. Our findings show how the dopaminergic system exerts influences on widespread brain networks, including motor and cognitive networks. The pattern of basal ganglia network connectivity is abnormal in PD secondary to dopamine depletion, and is more deviant in more severe disease. Use of functional MRI with network analysis appears to be a useful method to demonstrate basal ganglia pathways in vivo in human subjects.     

State-dependent functional connectivity of rat olfactory system assessed by fMRI

Functional connectivity between the piriform cortex and limbic and neocortical areas was assessed using functional magnetic resonance imaging (fMRI) of urethane anesthetized rats that spontaneously cycled between slow-wave and fast-wave states. Slow-wave and fast-wave states were determined indirectly through monitoring of respiration rate, which was confirmed to co-vary with state as determined by electrophysiological recordings. Previous electrophysiological data have suggested that the piriform cortex shifts between responsiveness to afferent odor input during fast-wave states and enhanced functional connectivity with limbic areas during slow-wave state. The present results demonstrate that fMRI-based resting state functional connectivity between the piriform cortex and both limbic and neocortical areas is enhanced during slow-wave state compared to fast-wave state using respiration as an indirect measure of state in urethane anesthetized rats. This state-dependent shift in functional connectivity may be important for sleep-dependent odor memory consolidation.     

慢性失眠患者大脑蓝斑的异常静息态功能连接

目的:利用功能连接方法观察慢性失眠患者静息态下蓝斑的异常功能连接。方法:采集49例慢性失眠患者以及47例性别年龄和受教育程度相匹配的健康对照组的功能磁共振图像,以蓝斑为感兴趣区域,与全脑其他体素进行功能连接分析,得到两组之间功能连接的差异脑区,再对异常连接脑区的功能连接值与临床量表分数做相关分析。结果:与对照组相比,慢性失眠患者蓝斑与右楔前叶皮质、右后扣带回皮质、左颞中回皮质、左距状沟周围皮质、右眶部额上回皮质之间的功能连接增强（P<0.05, FDR校正）,并且蓝斑与左颞中回皮质之间功能连接值与抑郁自评量表呈正相关（P=0.021）。结论:慢性失眠患者蓝斑与多个脑区（主要是默认模式网络）出现的异常功能连接,可能有助于更好地理解慢性失眠的神经生物学机制,可能为失眠的高度唤醒假说提供新的影像学证据。