基于MFc算法的fMRI数据集不平衡问题的处理

在fMRI数据中,因为激活体素(voxel)的数目远小于总的体素数目,由此产生了数据的不平衡性问题.以往解决此问题的方法除了应用大脑本身的生理结构来限制体素的数目外,统计方法常被应用于去掉那些肯定不激活的体素.本文章提出了一种新的解决数据不平衡问题的方法,用改进模糊c均值(MFc)方法将总的数据分成两个子集,而激活的体素总是聚在一个子集中,由此可以将需要进行分析运算的体素数目减至一半,这样不但可以有效的解决fMRI数据存在的不平衡问题,而且也提高了聚类分析的效率.MFc方法与统计方法的最大不同是,它是完全数据驱动的.     

慢性非流畅性失语患者语言加工特征的脑磁图研究

目的:研究慢性非流畅性失语患者大脑在图片命名过程中神经网络活动特征及与受损语言功能的关系.方法:非流畅性失语患者及年龄、性别、学历相匹配的健康成年人各5例,分别作为实验组和对照组.使用西方失语症成套测验评估受试者的言语功能,应用脑磁图(MEG)对受试者图片命名过程中大脑语言加工活动进行检测.结果:比较两组受试者在图片命名过程中相关大脑感兴趣区域(ROIs)在不同时间窗内的激活强度后发现:在图片命名的400-600ms时间窗内非流畅性失语症患者左脑Broca区的激活强度较对照组显著下降(P＜0.05),右脑的Broca同源区、Wemicke同源区、顶下小叶激活强度显著高于对照组(P＜0.05),右Broca同源区的激活强度与患者的失语商(AQ)正相关(r=0.886,n=5,P=-0.045).结论:慢性非流畅性失语患者存在右脑神经网络活动广泛上调,这种泛化在言语输出准备时期最为明显,提示与受损后大脑自发低水平的言语代偿有关.     

电刺激的fMRI的初步研究

目的研究不同频率的电刺激在大脑产生的激活,为理解和发展电刺激治疗疾病的方法提供依据和方向.方法对健康被试者的手腕和肘部内侧进行不同频率的低频电刺激,采用功能磁共振仪进行脑部激活图像的采集.结果表明不同频率的电刺激在大脑中的激活具有差异性,引起了运动皮层和躯体感觉区的明显激活.结论提示不同频率的电刺激可能激活了不同的神经通路,这些神经通路可能服务于中枢神经系统的不同功能,对于在电刺激的康复治疗中,选择恰当的刺激频率有一定的指导意义.     

改进时间簇分析方法对fMRI全脑数据的研究

目的：验证改进时间簇分析方法在处理全脑核磁共振功能数据时对于检测激活脑区时间信息的有效性。材料与方法：8个接受合谷针灸刺激和两个静息扫描的fMRI数据。采用数据驱动的改进时间簇分析方法处理相应的fMRI全脑数据来检测激活脑区的时间曲线。结果：利用改进TCA方法分别得到了与实验设计模型相符的接受针灸刺激8个被试的平均时间变化曲线和没有接受任何刺激静息扫描的2个被试的平均时间曲线。结论：由改进TCA得出的多被试的平均结果来看,改进TCA方法对于处理全脑核磁共振功能数据是非常有效的。     

孤独症谱系障碍儿童脑磁图静息态伽马频带脑功能网络探析

目的:研究孤独症谱系障碍(ASD)儿童静息态脑磁图伽马频带的脑功能网络特征。方法:ASD儿童6名,健康对照9名。采集静息态脑磁图信号和磁共振数据,在信号源水平进行伽马频带信号在大脑皮层的功率谱密度分析,并计算相位转移熵,构建脑网络,用于患儿组和对照组比较。结果:在脑网络节点激活程度方面,与对照组相比,患儿的伽马频带激活程度偏低(均P<0.05),受到显著抑制的脑区主要集中在双侧额叶、双侧颞叶和双侧岛叶,少量分布在右侧边缘叶及右侧顶叶。在脑网络节点间信息传递方面,信息汇集点存在组间差异(均P<0.05),患儿组为左侧角回中部,对照组为右侧枕中回腹部和左侧舌回后部。另外,信息发散点也有组间差异(均P<0.05),患儿组为右侧前眶额回和右侧岛盖部上部以及左侧梭状回前部,对照组则无显著的信息发放核心脑区。结论:ASD儿童大脑静息态伽马频带激活程度较低,提示患儿大脑存在兴奋-抑制失衡。ASD儿童伽马频带脑网络中,信息接收和发放的核心脑区分布模式与对照组存在差异,信息发放失衡。     

应用功能磁共振对臂丛神经损伤健侧颈7移位术后肢体功能康复与大脑皮质激活区的研究

目的:通过对左侧全臂丛根性撕脱伤患者健侧颈7(C7)神经移位后与健康对照组的上肢运动比较,探讨其功能康复与大脑可塑性的关系。方法:选择2001-09/2003-06在华山医院手外科手术或复诊的左侧全臂丛根性撕脱伤患者8例。同期选取健康自愿者8例为对照组。均为右利手。采用1.5T超导磁共振仪检查肢体对应的大脑运动皮层激活的变化。结果:16例患者均进入结果分析。①对照组受检者单侧肢体运动均可在对侧大脑半球初级运动皮质观察到兴奋区,其最大信号像素时间-信号强度曲线与BLOCK模式运动时相一致。②治疗组所有患者健侧上肢运动时,均可在对侧初级运动皮质观察到激活区,出现部位和形态与正常人大致相仿。健侧C7神经移位后,患侧屈腕屈指运动时,对侧皮质运动区M1区的激活体积较正常对照组平均值小。但随着术后功能的恢复,患肢对侧初级运动皮质激活区呈现逐渐增大趋势。功能恢复好,对侧运动皮质激活区区域则大,功能恢复差,对侧运动皮质激活区区域则小。结论:功能性磁共振可描绘出臂丛神经损伤健侧C7神经移位患者的大脑初级运动皮质的改变,术后积极进行损伤肢体的主动锻炼,可加速大脑可塑性的转化,有利于功能康复。     

功能磁共振成像评价动词生成任务中运动前区激活

目的 观察运动前区(PMA)在动词生成任务fMRI试验中的激活情况,探讨其在语言表达功能中的可能作用.方法 对23名受试者接受fMRI试验.试验任务为组块设计的动词生成任务:对照内容为黑色屏幕中心呈现的白色 "+";刺激任务为生成动词,要求受试者根据给出的单字名词,组成一个相关的动词词语.采用SPM2软件进行数据后处理,采用单样本t-检验的组分析方法获得平均脑激活图,观察PMA激活情况.结果 11名符合试验要求的受试者的数据列入组分析,脑激活区包括Broca区、右侧额下回后部、双侧PMC、双侧SMA、左侧顶后皮层、右侧丘脑、左侧基底节区、右侧小脑半球和右侧颞叶后部.全脑最强激活区为左侧PMA.结论 PMA在动词生成任务中具有重要作用,可能涉及语音处理、想象运动、词语提取和信息的高级调控等多个方面.     

缺血性脑卒中患者患手主动运动及被动运动时的功能性磁共振研究

目的观察缺血性脑卒中患者患手执行主动及被动运动时的脑激活模式,探讨主动运动和被动运动治疗脑卒中后手功能障碍的中枢机制。 方法对5例左侧大脑皮质下脑卒中患者患手执行主动及被动抓握-释放动作,执行动作期间采用血氧水平依赖性功能性磁共振（BOLD-fMRI）进行脑扫描,利用SPM5软件对上述患者试验数据进行分析,使用XJVIEW toolbox 8.11版软件得出入选患者在上述两种运动状态下的脑激活区分布图,并对其在不同运动状态下的脑激活模式特点进行分析比较。 结果入选患者患手在执行主动运动时其脑激活部位主要位于对侧感觉运动区(SMC)、运动前区(PMC)、双侧小脑及双侧辅助运动区(SMA),另外同侧SMC及PMC区也有轻度激活;激活脑区主要位于对侧大脑及小脑半球。患手执行被动运动时的脑激活部位主要位于双侧SMC、PMC区、双侧小脑、SMA区;激活脑区平均分布于两侧大脑及小脑半球。与患手主动运动比较,患手被动运动时的脑区激活范围较广泛,激活强度也较高。 结论患手执行主动运动和被动运动均可激活脑卒中患者运动相关脑区,提示对脑卒中患者进行主动运动及被动运动均可促进其脑功能重组。     

不出声与出声图片命名任务神经激活机制差异的功能磁共振成像

目的 采用功能磁共振成像(fMRI)技术观察执行不出声和出声图片命名任务时大脑活动的差异.方法 在10名健康志愿者(24～27岁)分别进行不出声和出声图片命名时,同时采集其脑部的fMRI数据,通过分析处理获得执行不同任务时的头动结果及脑功能区统计激活图.结果 不出声任务的平均头动和最大头动低于出声任务,但差异无统计学意义(P=0.23).不出声图片命名的神经激活网络包括双侧枕回及小脑、双侧辅助运动区、中央后回、双侧额下回和前扣带回.出声图片命名时除在上述不出声时的激活区有更强激活外,还激活了双侧中央前回(BA4)、双侧后上颞回、左侧前上颞回、双侧丘脑及基底节区、左侧岛叶.结论 不出声和出声图片命名的神经处理网络及环节互不相同,两种任务不能相互替代.     

头针丛刺结合强制性运动疗法对脑梗死后手运动障碍疗效的功能性磁共振评价

目的采用血氧水平依赖性功能磁共振成像（BOLD-fMRI）观察急性期脑梗死患者经头针丛刺及强制性运动疗法（CIMT）治疗前、后其手运动中枢激活体积、激活强度变化。 方法采用随机数字表法将30例急性期（发病至入组时间≤3d）脑梗死患者分为试验组及对照组。2组患者均给予常规药物治疗，试验组同时辅以头针丛刺及CIMT治疗，对照组则辅以体针及一般康复治疗。于入院当天及治疗14d后进行fMRI检查，观察其大脑手运动功能区改善情况，并采用Fugl-Meyer运动功能量表（FMA）上肢部分测定患者肢体功能改善情况。另外本研究同时选取15例年龄、性别相匹配的健康志愿者行单次fMRI检查，观察其相同任务下脑区激活体积与强度，并与患者组进行比较。 结果所有患者经治疗后其患肢运动时患侧感觉-运动皮质（SMC）激活体积、FMA评分均较治疗前增大（P<0.05）；试验组治疗前、后患侧手运动激活对侧SMC体积及激活强度均较对照组更明显（P<0.05）。 结论在脑梗死急性期采用头针丛刺结合CIMT治疗能进一步促进患侧大脑感觉-运动皮质功能恢复，改善患者运动功能，该联合疗法值得临床推广、应用。     

利用多层受约束一范数优化检测功能磁共振成像中神经活动

本研究提出利用fMRI中神经信号内在的稀疏性,通过积分器转换,最大期望算法优化对脑fMRI中血流动力学变化建立多层神经信号模型,将检测脑fMRI中神经活动转化为受约束的一范数优化问题.利用空间自适应滤波器,优化结果可以准确地检测出fMRI中神经活动.通过与目前主流检测方法时间聚类分析、最大相关性方法及图模型推理法对比,本文提出的方法能够以较小的计算复杂度得出精确的结果.     

Functional inferences vary with the method of analysis in fMRI.

Neuroanatomic substrates of specific cognitive functions have been inferred from anatomic distributions of activated pixels during fMRI studies. With declarative memory tasks, interest has focused on the extent to which various medial temporal lobe anatomic structures are activated while subjects encode new information. The aim of this project was to examine how commonly used variations in fMRI data processing methods affect the distribution of activation in anatomically defined medial temporal lobe regions of interest (ROIs) during a complex scene-encoding task. ROIs were drawn on an MRI anatomic template formed from 3D SPGR scans of eight subjects combined in Talairach space. Separate ROIs were drawn for the posterior and anterior hippocampal formation, parahippocampal gyrus, and entorhinal cortex. Twelve different activation maps were created for each subject by using four correlation coefficients and three cluster volumes. Friedman's two-way ANOVA by ranks was used to test the hypothesis that the distribution of activated pixels among defined anatomic ROIs varied as a function of the data processing method. By simply varying the combination of correlation coefficient and cluster volume, significantly different distributions of activation within named medial temporal lobe structures were obtained from the same fMRI datasets (P < 0.015; P < 0.001). The number of subjects studied (n = 8) is in a range commonly found in the literature yet this clearly resulted in spurious associations between processing parameter variations and activation distribution. Using data processing methods that are independent of the arbitrary selection of cutoff values for thresholding activation maps may reduce the likelihood of obtaining spurious results.     

Clustering of cytokine genes on mouse chromosome 11

The presence of positionally conserved amino acid residues suggests that the mouse proteins TCA3, P500, MIP1-alpha, MIP1-beta, and JE are members of a single gene family. These proteins are activation specific and can be expressed by both myeloid and lymphoid cells. MIP1-alpha/MIP1-beta and MCAF (the putative human homologue of JE) act as chemotactic and activating agents for neutrophils and macrophages, respectively. The functions of TCA3 and P500 are unknown. We have used interspecies somatic cell hybrids and recombinant inbred mouse strains to show that the genes encoding TCA3, MIP1-alpha, MIP1-beta, and JE (provisionally termed Tca3, Mip-1a, Mip-1b, and Sigje, respectively) map as a cluster on the distal portion of mouse chromosome 11 near the Hox-2 gene complex. DNA sequence analysis indicates that the P500 and TCA3 proteins are encoded by alternative splicing products of one genomic gene. Additionally, the genes encoding TCA3 and JE are found to be strikingly similar with respect to the positions of intron-exon boundaries. Together, these data support the model that the cytokines TCA3, P500, MIP1-alpha, MIP1-beta, and JE are encoded by a single cluster of related genes. The gene encoding IL-5 (Il-5), which acts as a T cell-replacing factor, a B cell growth factor, and an eosinophil differentiation factor, is also mapped to mouse chromosome 11.Il-5 maps approximately 25 cM proximal to the Tca-3 gene and appears tightly linked to a previously described gene cluster that includes Il-3, Il-4, and Csfgm. We discuss the potential relevance of the two cytokine gene clusters described here with particular attention to specific human hematologic malignancies associated with chromosomal aberrations at corresponding locations on human chromosomes 5 and 17.     

Loss of reliable temporal structure in event-related averaging of naturalistic stimuli

To separate neural signals from noise, brain responses measured in neuroimaging are routinely averaged across space and time. However, such procedures may obscure some properties of neural activity. Recently, multi-voxel pattern analysis methods have demonstrated that patterns of activity across voxels contain valuable information that is concealed by spatial averaging. Here we show that temporal patterns of neural activity contain information that can discriminate different stimuli, even within brain regions that show no net activation to that stimulus class. Furthermore, we find that in many brain regions, responses to natural stimuli are highly context dependent. In such cases, prototypical event-related responses do not even exist for individual stimuli, so that averaging responses to the same stimulus within different contexts may worsen the effective signal-to-noise. As a result, analysis of the temporal structures of single events can reveal aspects of neural dynamics which cannot be detected using standard event-related averaging methods.     

On multivariate spectral analysis of fMRI time series

Most of functional magnetic resonance imaging (fMRI) time series analysis is based on single voxel data evaluation using parametric statistical tests. The result of such an analysis is a statistical parametric map. Voxels with a high significance value in the parametric test are interpreted as activation regions stimulated by the experimental task. However, for the investigation of functional connectivities it would be interesting to get some detailed information about the temporal dynamics of the blood oxygen level-dependent (BOLD) signal. For investigating that behavior, a method for fMRI data analysis has been developed that is based on Wiener theory of spectral analysis for multivariate time series. Spectral parameters such as coherence measure and phase lead can be estimated. The resulting maps give detailed information on brain regions that belong to a network structure and also show the temporal behavior of the BOLD response function. This paper describes the method and presents a visual fMRI experiment as an example to demonstrate the results.     

An arc-clustering-based phase ambiguity estimation method for persistent scatterer interferometry

The reliability of persistent scatterer interferometry (PSI) is directly related to the accurate phase unwrapping (PU) of the 3-D (2-D space and time) sparse data stack. Phase ambiguities estimated using temporal phase unwrapping (TPU) are crucially exploited in most 3-D PU algorithms. However, most TPU methods are not noise-robust owing to the independent processing of each arc in the persistent scatterer network. To solve this problem, the cluster-analysis-based PU method for digital elevation model (DEM) construction is adapted to the phase ambiguity estimation problem for PSI in this letter. First, for each arc, the interior relation among phase ambiguities in multiple interferograms is derived to be linear and can be represented by an intercept vector. Subsequently, arcs with the same ambiguities are clustered according to their intercept vectors because arcs with identical phase ambiguities are verified to have the same intercept vectors. Moreover, a more reliable intercept vector can be calculated for each arc cluster by combining the intercept vectors within the cluster. Finally, more precise phase differences are estimated for each cluster using the corresponding intercept vector so that all the arcs are better unwrapped. Both the simulated and real experiments indicate the effectiveness and superiority of the proposed algorithm.     

fMRI visualization of transient activations in the rat olfactory bulb using short odor stimulations

Odor-evoked activity in the olfactory bulb displays both spatial and temporal organization. The difficulty when assessing spatio-temporal dynamics of olfactory representation is to find a method that reconciles the appropriate resolution for both dimensions. Imaging methods based on optical recordings can reach high temporal and spatial resolution but are limited to the observation of the accessible dorsal surface. Functional magnetic resonance imaging (fMRI) may be useful to overcome this limitation as it allows recording from the whole brain. In this study, we combined ultra fast imaging sequence and short stimulus duration to improve temporal resolution of odor-evoked BOLD responses. Short odor stimulations evoked high amplitude BOLD responses and patterns of activation were similar to those obtained in previous studies using longer stimulations. Moreover, short odor exposures prevented habituation processes. Analysis of the BOLD signal time course in the different areas of activation revealed that odorant response maps are not static entities but rather are temporally dynamic as reported by recent studies using optical imaging. These data demonstrated that fMRI is a non-invasive method which could represent a powerful tool to study not only the spatial dimension of odor representation but also the temporal dimension of information processing.     

Regional Variation in the Incidence of Symptomatic Pesticide Exposures: Applications of Geographic Information Systems

Objective: To evaluate the epidemiology of symptomatic human pesticide exposures using poison control center data and geographic information systems. Methods: All symptomatic human pesticide exposures reported to the poison center during the period from January 1 to December 31, 2000 were included for analysis using geographic information systems. A space–time scan statistic was utilized to evaluate for clustering of symptomatic human exposures. Results: Of 322 symptomatic pesticide exposures, 297 (92%) contained spatial identifiers that could be further analyzed using geographic information systems. A spatial and temporal cluster of symptomatic pesticide exposures was identified during the period from April 1 to August 31, 2000, covering a large geographic area of eastern and predominantly rural regions of the state. The relative risk of reporting a symptomatic pesticide exposure among individuals living within this geographic area was 1.8 (log likelihood ratio=18.5, P=0.0005). Conclusions: Geographic information systems can be effectively utilized by poison control centers to study regional and temporal variation in the incidence of human pesticide exposures. With the collection of more specific spatial identifiers, geographic information systems may have many additional applications in the surveillance and prevention of pesticide and other sentinel event exposures.     

Interindividual differences of medial temporal lobe activation during encoding in an elderly population studied by fMRI

Functional MRI (fMRI) is used to study medial temporal lobe (MTL) activation during encoding of new information into memory. In most studies, fMRI data of different subjects are averaged in standard coordinate space. However, interindividual differences in activation can be extensive, reflecting functional heterogeneity. Further, anatomical differences in brain structure cause additional variance and loss of registration accuracy. Such differences in structural and functional MTL characteristics may interfere with the efficiency of averaging data across subjects, and may become more significant with aging and dementia. The current study concerns the analysis of individual differences in MTL activation associated with episodic encoding.Twenty-nine healthy elderly men between 60 and 70 years old performed a simple face encoding task during fMRI scanning. Individual data were analyzed in native space, and compared to the group average in standard space (Talairach and Tournoux).MTL volumes between subjects varied between 6.34 and 11.27 cm(3), and had considerable variation when mapped to standard space. Eighteen of the 29 subjects showed MTL activity and activation patterns varied both in location and size (ranging from 0.11 to 1.78 cm(3)), with the strongest activation in the left posterior part of the MTL. In standard space, no region was significantly activated on a group level at a comparable alpha level. We conclude that while the majority of elderly subjects show MTL activation during episodic encoding of faces, there is considerable structural and functional variability between subjects. Group analysis in standard space may not be appropriate for studies of a complex structure such as the MTL, particularly not in aging and dementia.