静息态脑功能成像评价平衡针对正常人的中枢作用

目的:应用静息态脑功能磁共振成像技术,探讨平衡针的中枢作用机制.方法:选择10名健康志愿者,于针刺平衡针前后分别进行磁共振腩功能成像扫描,应用功能连接方法处理功能磁共振(fMRI)成像数据,针刺前后两组数据采用组间配对t检验统计分析.结果:针刺后的双侧颞中回、双侧眶上同、双侧尾状核头、双侧岛叶、左侧腹背侧核、双侧额上回...     

静息状态脑活动及其脑功能成像

目前应用无创性磁共振功能成像技术的脑功能成像研究常把无任务的静息状态作为对照,特定的脑功能区活动是任务状态脑活动与对照状态相减所得.但是近年来研究发现,所谓静息状态时大脑也存在功能活动.显然这种脑活动将会影响与目的任务相关的脑功能成像结果以及对这种结果的解释.因此理解静息状态脑活动及其生理意义,对解释脑功能成像的结果以及全面了解大脑功能具有重要意义.文中就静态脑活动的研究背景、存在证据、活动特点、生理意义及其功能成像研究进展做简要评述.     

磁共振成像技术在颅脑疾病临床中的应用

通过对磁共振成像技术的系统分析，综合介绍了脑功能成像技术在颅脑临床研究中的应用，提出fMRI在临床中的应用目前正在逐步开发。并且对未来提高外科手术质量和病人的生存质量具有巨大的作用。     

任务背景下腹侧注意功能网络的fMRI研究

基于静息状态的功能磁共振成像(functional MRI,fMRI)已经成为当前人脑功能研究的重要手段之一,本研究采用任务背景来获取一种更为"纯净"的静息状态,其中脑区的"任务背景"被定义为那些不会激活感兴趣脑区的任务.由于到目前为止还不清楚在"任务背景"下人脑除默认网络外的其他"高级"功能网络内部是否被中断,本文研究了人脑听觉背景下腹侧注意网络内部的功能连接.结果表明在听觉背景下该网络内部存在显著的功能连接,这一结果说明简单的感觉任务不会中断人脑的腹侧注意网络.本研究首次证明在任务背景下,除默认网络之外,人脑还有一些高级功能网络内部存在显著功能连接.     

脑功能网络建模及分析研究进展

大脑是一种典型的复杂系统,理解大脑的结构以及运作机制对生命科学、医药工程、人工智能等领域重大问题的研究具有重要意义.功能核磁共振成像(fMRI)等技术可以实现比较精细的大脑神经活动信号的无创采集,是观察和分析大脑功能活动的重要辅助技术;同时,复杂网络理论与方法则为探索大脑的工作机制提供了重要的理论和技术基础.本文回顾了近年来基于fMRI等大脑神经活动信号采集技术进行脑功能网络建模与分析的研究进展,包括脑功能连接的相关性、因果性分析,白质纤维束投射连接分析,脑活动状态空间的能量图景分析等.文中介绍了这些方法的原理、适用性及局限性.目前基于数据分析的脑网络建模研究已经取得了丰硕的成果,然而,随着神经影像技术的不断发展及高质量神经活动数据的不断积累,复杂系统理论在脑科学领域的应用仍然具有广阔的前景.     

基于Granger因果检验和PCA的脑网络效应连接方法

为了提高脑功能效应连接网络检测的可靠性,提出了一种基于Granger因果关系检验和主成分分析(PCA)的功能磁共振(fMRI)数据效应连接方法.该方法首先通过PCA提取感兴趣区域内fMRI信号的时间主成分,以此特征作为时间参考信息,然后计算参考信息与大脑其余每个体素之间的Granger因果关系,并映射到全脑,形成Granger因果图(GCM).理论推导阐明了所提方法的有效性.采用该方法研究人脑运动功能脑区在手动任务下的效应连接GCM,结果验证了运动功能神经网络理论.     

记忆与执行功能及有关精神健康的认知神经科学研究

中国科学技术大学1999年建立了脑功能与医学成像联合实验室, 其主要研究方向是:以认知心理学、脑功能成像(fMRI、ERP)等认知神经科学的方法,研究高级认知功能(工作记忆、选择性注意、执行控制、决策等);及相关的认知障碍和精神健康,如老年人和神经内分泌疾病病人的记忆功能、网络游戏成瘾等.在这些方面已经获得了一些有意义的结果. 今后将进一步关注积极心理学中的重要问题,如情绪及幸福感的认知神经机制等.     

基于近似熵静息态fMRI的大脑功能性别差异研究

引入度量时间序列复杂度的近似熵(ApEn)方法探讨健康年轻成人静息态下大脑功能性别差异.利用功能磁共振成像(fMRI)技术对74名健康年轻成人(其中:男36名,女38名)进行扫描以获取静息态fMRI数据,使用DPABI软件进行数据预处理,采用ApEn方法比较健康男女大脑功能活动,确定健康男女大脑功能活动的差异区域.结果发现,较男性健康组,女性健康组在右侧枕中回、右侧角回、右侧颞中回及双侧楔前叶的ApEn值更高;较女性健康组,男性健康组在右侧梭状回、右侧枕下回、右侧舌回、左侧额中回及左侧背外侧额上回的ApEn值更高.该结果表明,静息态下大脑功能活动存在性别差异,尽管差异区域与以往线性方法得到的结果并不完全一致,但都一致认为这些差异可能与大脑结构以及行为和认知上的性别差异有关.     

大脑皮层对飞机飞越噪声的认知机制

为了研究人类大脑皮层对飞机飞越噪声的表达机制,采用功能磁共振成像(fMRI)技术,选择25例正常健康受试者,观察在飞机飞越噪声刺激时大脑功能区的激活情况,通过对数据进行统计学处理以及脑功能区定位,结果表明:25例受试者在飞机飞越噪声刺激时大脑显著激活了视觉联合皮层、前额叶皮层、初级运动皮层以及与认知记忆相关的脑区等.飞机飞越噪声刺激下,大脑皮层听觉区域不仅参与了听觉处理,可能还涉及消极情绪、认知、注意、记忆等区域反应.     

ICA+DMN方法在抑郁症诊断中的应用

功能磁共振成像(fMRI)作为一种工具,用于预测临床信息,如疾病的诊断及预测等,然而由于fMRI数据的高维性使得对其进行数据分析成为一个重要的研究课题,独立成分分析算法(ICA)常用于任务态下的fMRI数据的处理.本文提出将独立成分分析和默认模式脑网络(DMN)结合的方法,并将其应用于静息态的fMRI数据,可以根据大脑静息态下fMRI数据诊断出是否患有抑郁症,实验结果表明,此方法对处理静息态的fMRI数据的处理有一定的效果,正确率达到73.68%,可以为抑郁症患者提供辅助诊断治疗方法.     

静息态脑区的活动特征研究

静息态脑区的活动处于一种相对稳定的状态。但是,静息态机能性磁共振成像(functional Magnetic Resonance Imaging,fMRI)实验中,被试者可能会受到各种噪声的影响,因此,统计分析所得到的静息态脑区的活动强度和体素数都可能受此影响。为了更进一步研究静息态脑区的活动特点,分别对16名被试采集了8′14″的静息态fMRI数据,将这些数据按照时间等分为5个部分,对每个部分分别采用低频振幅方法进行分析。实验结果显示:楔前叶和后扣带皮层包含活动体素的个数随时间变化较小,处于一种相对稳定的状态;额内侧皮层和顶下小叶中活动体素个数随时间变化差异较大,处于不是很稳定的状态。实验结果表明,静息态脑区中,楔前叶和后扣带皮层对于外界噪声的干扰不敏感,额内侧皮层和顶下小叶对于外界噪声比较敏感。     

What we can do and what we cannot do with fMRI

Functional magnetic resonance imaging (fMRI) is currently the mainstay of neuroimaging in cognitive neuroscience. Advances in scanner technology, image acquisition protocols, experimental design, and analysis methods promise to push forward fMRI from mere cartography to the true study of brain organization. However, fundamental questions concerning the interpretation of fMRI data abound, as the conclusions drawn often ignore the actual limitations of the methodology. Here I give an overview of the current state of fMRI, and draw on neuroimaging and physiological data to present the current understanding of the haemodynamic signals and the constraints they impose on neuroimaging data interpretation.     

Recent advances in the data analysis method of functional magnetic resonance imaging and its applications in neuroimaging

Functional magnetic resonance imaging (fMRI) has opened a new area to explore the human brain. The fMRI can reveal the deep insights of spatial and temporal changes underlying a broad range of brain function, such as motor, vision, memory and emotion, all of which are helpful in the clinical investigation. In this paper, we introduce some recent-developed algorithms for fMRI signal detection such as model-driven method (general linear model, deconvolution model, non-linear model, etc.) and data-driven method (principle component analysis, independent component analysis, self-organization mapping, clustered constrained non-negative matrix factorization, etc.). We also propose several important applications of neuroimaging and point out their shortcomings and future perspectives.     

Visualizing columnar architectures using high-field fMRI

Among the many neuroimaging tools available for studying human brain functions, functional magnetic resonance imaging (fMRI) is the most widely used today. One advantage of fMRI over other imaging techniques is its relatively high spatial resolution. High-resolution fMRI, with its superb signal-to-noise ratio and improved tissue-vessel specificity, has strengthened the capability of fMRI and allowed mapping of fine cortical architectures in the human brain. In this review, I will first explain the factors limiting the spatial specificity of the blood oxygenation level-dependent (BOLD) effect, based on which most of fMRI experiments are conducted, and the measures dealing with these factors, and then briefly introduce several high-resolution (sub-millimeter) studies on the functional organization of human primary visual cortex (V1), including mapping of ocular dominance columns, mapping of temporal frequency dependent domains and direct demonstration of tuning to stimulus orientation.     

Visualizing columnar architectures using high-field fMRI

Among the many neuroimaging tools available for studying human brain functions, functional magnetic resonance imaging (fMRI) is the most widely used today. One advantage of fMRI over other imaging techniques is its relatively high spatial resolution. High-resolution fMRI, with its superb signal-to-noise ratio and improved tissue-vessel specificity, has strengthened the capability of fMRI and allowed mapping of fine cortical architectures in the human brain. In this review, I will first explain the factors limiting the spatial specificity of the blood oxygenation level-dependent (BOLD) effect, based on which most of fMRI experiments are conducted, and the measures dealing with these factors, and then briefly introduce several high-resolution (sub-millimeter) studies on the functional organization of human primary visual cortex (V1), including mapping of ocular dominance columns, mapping of temporal frequency dependent domains and direct demonstration of tuning to stimulus orientation.     

Neurophysiological investigation of the basis of the fMRI signal.

Functional magnetic resonance imaging (fMRI) is widely used to study the operational organization of the human brain, but the exact relationship between the measured fMRI signal and the underlying neural activity is unclear. Here we present simultaneous intracortical recordings of neural signals and fMRI responses. We compared local field potentials (LFPs), single- and multi-unit spiking activity with highly spatio-temporally resolved blood-oxygen-level-dependent (BOLD) fMRI responses from the visual cortex of monkeys. The largest magnitude changes were observed in LFPs, which at recording sites characterized by transient responses were the only signal that significantly correlated with the haemodynamic response. Linear systems analysis on a trial-by-trial basis showed that the impulse response of the neurovascular system is both animal- and site-specific, and that LFPs yield a better estimate of BOLD responses than the multi-unit responses. These findings suggest that the BOLD contrast mechanism reflects the input and intracortical processing of a given area rather than its spiking output.     

A template of rat brain based on fMRI T_2~* imaging

Thedevelopmentofnoninvasivefunctionalneu roimagingmethodshasmadeitpossibletoinvestigatelarge scaleactivationpatternsofbrain.FMRI,arep resentativeinhemodynamictechniques,hasbeen usedextensivelyinthestudiesofthephysiology,pathologyandpsychologyofbrains[1—3],foritslessinvasiveproperty,superiorresolution,andlowercost comparedtoPETtechniques.Itisimportanttopointoutthatcommonimage analysissoftwaressuchasstatisticalparametricmap ping(SPM),analysesoffunctionalneuroimages(AFNI),createdatabydoinga…     

A template of rat brain based on fMRI T*2 imaging

The development of functional magnetic resonance imaging (fMRI) technology has made it possible to carry out functional brain imaging experiments in small animals. Usually, group data is required to form the assessment of population, which can not only increase the sensitivity of the overall experiment, but also allow the generalization of the conclusion to the whole population. In order to average the signals of functional brain images from different subjects, it is necessary to put all the mapping images into the same standard space (template image). However, up to now, most animal brain templates remain unavailable and it must be done by ourselves. In this study, a template image based on the brains of eight male Wistar rats is obtained, and it is successfully used in our present Alzheimer disease (AD)-like rat model studies as template for spatially normalizing images to the same stereotaxical space. The fMRI results processed with statistical parametric mapping (SPM99) software are in agreement with the results from immunohistochemical experiment, which proves that this method is universally applicable to the pathologic models of other small animals and to human brain lesion studies.     

基于β估计校正值的低场功能磁共振成像分析方法

针对低场功能磁共振成像(fMRI)非脑组织信号变化的影响,提出一种有效的图像分析方法以改进大脑功能定位的结果.综合利用基于形变模型的图像分割算法和基于像素形态测量学(voxel-basedmorphometry,VBM)的统计分析方法提取脑组织,生成显式掩模,并构建分析掩模图像以修正一般线性模型的β参数估计值,使得VBM的统计推断只针对大脑组织,消除了非脑组织信号变化的影响.应用实例表明,这种方法可有效去除背景、头骨及头皮信号变化引起的伪激活区,提高了低场fMRI分析的可靠性和准确性.     

Deactivations during the numerical processing

Deactivation has been encountered frequently in functional brain imaging researches. However, the deactivations during the numerical processing have not been reported yet. In this study, the functional magnetic resonance imaging (fMRI) was employed to investigate the pattern of the deactivation in the brain of 15 healthy subjects during the numerical addition task. Analyses revealed significant deactivations in several brain regions, including the posterior cingulate, precuneus, anterior cingulate and prefrontal cortex. Especially, we found notable deactivation in bilateral insula. Accounting for the cognitive functions of these regions participating in a combinated way, we discuss their contributions in sustaining the brain activity during conscious resting state, and indicate that the insula is an important area of gathering auditory information from the external world.