基于信号特征的功能磁共振成像数据分析方法

概述了基于功能磁共振成像(functionalmagneticresonanceimages,fMRI)信号本身统计特征的数据驱动型分析方法主成分分析、独立分量分析以及典型分析等方法的原理、特点和进展,特别强调了这些方法针对fMRI数据分析特点所做的改进。     

BOLD-fMRI联合DTI技术在神经解剖学中的应用

<正>1基本原理1.1 BOLD-fMRI成像原理功能磁共振成像(functional magnetic resonance imaging,fMRI)是以血氧水平依赖效应(blood oxygenation level dependent,BOLD)为核心检测和定位脑功能的一种成像技术。它是利用内源性血红蛋白作为对比剂,通过血氧饱和度的变化实现的成像方法,反映了神     

一种基于静息态功能磁共振成像的快速丘脑分割算法

目的 探讨基于静息态功能磁共振成像(fMRI)的快速有效的丘脑分割方法.方法 静息态fMRI技术是通过测量血氧水平依赖(BOLD)信号的变化间接反映神经元的活动情况.利用丘脑内部的BOLD信号相关并结合聚类分析算法将丘脑进行功能性分割.结果 丘脑被划分为7个区域,同一区域内信号相似度高.此分割结果与利用丘脑-大脑皮层的功能连接强度所得的分割结果相似.结论 静息态fMRI不仅可以分析丘脑-大脑皮层之间的功能连接,还可分析丘脑内部的功能特征.仅利用丘脑内部信息分割丘脑具有运算量小、计算速度快的优点.     

脑功能成像研究进展

功能磁共振成像、正电子发射计算机断层显像、单光子发射机断层显像和内禀光学成像等断层影像技术能直视活体脑的解剖和功能变化,能在屏幕上看到人脑的思维活动,从而将我们推向了绘制人类思维图像(mapping the human mind)的时代。 1 常用的脑功能成像技术 1.1 功能磁共振成像(functional magnetic resonance imaging,fMRI);依成像原理,fMRI可分为三类:第一类,灌注基础上的fMRI,以示踪剂在脑内的时间过程来计算脑血流。第二类,血流基础上的fMRI,可探查大血管里的血流变化。第三类,磁敏感对照基础上的fMRI,如血氧水平依赖性(blood oxygenation level dependent,BOLD)方法。BOLD fMRI对神经元活动的敏感性是第一、二类fMRI的2～3     

一种基于独立成份分析的fMRI时-空模型数据处理方法

独立成份分析(ICA)是信号处理领域中斯近发展起来的一种很有应用前景的方法，而脑功能磁共振(fMRI)信号的有效分离与识别是一个正在研究和试验之中的技术领域。因此，发展基于ICA的fMRI数据处理方法具有明显的理论价值和应用前景。本文首先介绍了ICA原理，分析了现行ICA—fMRI方法采用的信号与噪声的空域分布相互独立的信号模型所存在的明显不足，然后提出了微域中的信号与噪声的时域过程相互独立的fMRI信号模型，从而建立了一种新的fMRI数据处理方法：邻域独立成份相关法。合理的fMRI实验数据处理结果验证了新方法的合理性。     

空间ICA在fMRI数据上的应用与分析

独立成分分析(ICA)技术试图将多维数据分解成若干个相互统计独立的分量。时间ICA和空间ICA都可以用于分析功能核磁共振成像(fMRI)数据。但由于fMRI数据空间维数远远大于时间维数，为计算方便，在分析fMRI数据时。则更多的使用空间ICA方法。本文在单任务激励实验中，利用ICA方法从fMRI数据中分离出若干个与任务相关的独立分量，其中包括与任务相关的恒定分量(CTR)和与任务相关的暂态分量(TTR)；通过将这些独立分量进行空间映射，得到了与任务相关的脑部激活区域。将此结果与SPM的分析比较，得到了一致的结果。在对结果的分析中，我们进一步指出了ICA方法的特点和局限性。     

血氧水平依赖脑功能磁共振在精神障碍疾病中的应用

脑功能磁共振成像(fMRI)最主要的形式是血氧水平依赖磁共振成像(】BOLD-fMRI),根据神经元兴奋后局部氧耗与血流增幅不一致,用BOLD效应机制成像,间接显示神经元活动。BOLD-fMRI通过静息态和任务态两种模式,对精神疾病的研究已经不仅局限于研究特定脑区激活程度的差异,更逐渐关注分析各脑区间的神经环路和功能网络连接的变化。本文综述BOLD-fMRI成像原理、应用模式及在研究精神分裂症等常见精神障碍疾病脑区神经活动的相关性及功能连接。     

大脑功能磁共振成像基础研究进展

大脑功能区的定位一直是基础研究学者研究的热点，近年来功能磁共振成像(fMRI)作为一种新型无损伤技术，为大脑功能的基础研究提供了一个新的途径。fMRI以其高分辨成像技术适时反应脑神经活动时的功能变化，藉以了解在生命状态下大脑不同区域的主要功能和疾病时的功能改变。这是目前人们所掌握的唯一无侵入、无创伤、可精确定位人脑高级功能的研究手段：广义上fMRI方法包括脑血流测定技术、脑代谢测定技术、     

基于空间约束的时间独立成分分析方法分析fMRI数据

首先采用相关分析初步检测可能的功能激活区域,并以初步检测的功能激活区域作为空间约束条件,对fMRI数据进行时间模式的独立成分分析,然后利用功能实验设计时序信息,通过典型相关分析方法对独立成分排序,自动识别与功能实验设计相关的功能信号成分,最后以识别的功能信号成分作为参考函数,重新利用相关分析自适应地分析fMRI数据。通过对实际的fMRI数据分析验证了提出方法的有效性及可靠性。     

血氧水平依赖功能磁共振成像的基本原理及方法学应用

功能磁共振成像(functional magnetic resonance imaging,fMRI)是研究脑功能的一种强有力的方法,具有无创定位、高空间分辨率和时间分辨率的特点。最基本的fMRI的成像技术是血氧水平依赖功能磁共振成像(blood oxygen level dependent fMRI,BOLD-fMRI)。概述了BOLD-fMRI的基本原理以及在方法学上的应用。     

一种基于独立成分分析的功能磁共振数据处理方法

独立成分分析（ICA）是统计信号处理中的一项新技术，用来从混合信号的多维观测中提取具有统计独立性的成分。我们针对功能磁共振数据处理，采用先对相邻的两体元信号作ICA分离，然后与参考信号进行相关，把相关系数大于一定阈值的体元作为刺激引起兴奋的体元，从而实现刺激的功能定位。经实际脑功能磁共振数据试验，初步证明了方法的有效性。     

Analysis of fMRI data by blind separation of data in a tiny spatial domain into independent temporal component

Independent Component Analysis (ICA) is a promising tool for the analysis of functional magnetic resonance imaging (fMRI) time series. In these studies, mostly assumed is a spatially independent component map of fMRI data (spatial ICA). In this paper, we assume that the temporal courses of the signal and noises are independent within a Tiny spatial domain (temporal ICA). Then with fast-ICA algorithm, spatially neighboring fMRI data were blindly separated into several temporal courses and were preassumed to be formed by a signal time course and several noise time courses where the signal has the largest correlation coefficient with the reference signal. The final functional imaging was completed for the signals obtained from each voxel. Simulations showed that compared with the spatial ICA method, the new temporal ICA method is more effective than the spatial ICA in detecting weak signal in a fMRI dataset. As background noise, the simulations include simulated Gaussian noise and fMRI data without stimulation. Finally, vivo fMRI tests showed that the excited areas evoked by a visual stimuli are mainly in the region of the primary visual cortex and that evoked by auditory stimuli are mainly in the region of the primary temporal cortex.     

Paradoxical correlation between signal in functional magnetic resonance imaging and deoxygenated haemoglobin content in capillaries: a new theoretical explanation

Signal increases in functional magnetic resonance imaging (fMRI) are believed to be a result of decreased paramagnetic deoxygenated haemoglobin (deoxyHb) content in the neural activation area. However, discrepancies in this canonical blood oxygenation level dependent (BOLD) theory have been pointed out in studies using optical techniques, which directly measure haemoglobin changes. To explain the discrepancies, we developed a new theory bridging magnetic resonance (MR) signal and haemoglobin changes. We focused on capillary influences, which have been neglected in most previous fMRI studies and performed a combined fMRI and near-infrared spectroscopy (NIRS) study using a language task. Paradoxically, both the MR signal and deoxyHb content increased in Broca's area. On the other hand, fMRI activation in the auditory area near large veins correlated with a mirror-image decrease in deoxyHb and increase in oxygenated haemoglobin (oxyHb), in agreement with canonical BOLD theory. All fMRI signal changes correlated consistently with changes in oxyHb, the diamagnetism of which is insensitive to MR. We concluded that the discrepancy with the canonical BOLD theory is caused by the fact that the BOLD theory ignores the effect of the capillaries. Our theory explains the paradoxical phenomena of the oxyHb and deoxyHb contributions to the MR signal and gives a new insight into the precise haemodynamics of activation by analysing fMRI and NIRS data.     

Quantitative Analysis of Asymmetrical Cortical Activity Based on Power Spectrum Changes

The present study intends to quantitatively analyze power changes in blood oxygenation level-dependent (BOLD) signals, and to investigate functional asymmetry of cortical activity in motor areas during sequential finger movements. A power spectrum method was employed, mainly in contrast with the signal magnitude analysis, to investigate functional asymmetry of motor area cortical activity. Six right-handed subjects were included in the functional magnetic resonance imaging (fMRI) experiments. Both bi-handed and single-handed movements were analyzed. The power spectrum method demonstrated that right-handed subjects exhibited a larger power difference in BOLD signals between task and rest states in the right motor area than in the left motor area. These results showed that more nerve cells were evoked in the right motor area of right-handed subjects. In addition, the power spectrum method was confirmed to be a valid quantitative-analysis method for brain asymmetry analyses.     

Quantitative functional imaging of the brain: towards mapping neuronal activity by BOLD fMRI.

Quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) measurements of energy metabolism (i.e. cerebral metabolic rate of oxygen consumption, CMR(O2)), blood circulation (i.e. cerebral blood flow, CBF, and volume, CBV), and functional MRI (fMRI) signal over a wide range of neuronal activity and pharmacological treatments are used to interpret the neurophysiologic basis of blood oxygenation level dependent (BOLD) image-contrast at 7 T in glutamatergic neurons of rat cerebral cortex. Multi-modal MRI and MRS measurements of CMR(O2), CBF, CBV and BOLD signal (both gradient-echo and spin-echo) are used to interpret the neuroenergetic basis of BOLD image-contrast. Since each parameter that can influence the BOLD image-contrast is measured quantitatively and separately, multi-modal measurements of changes in CMR(O2), CBF, CBV, BOLD fMRI signal allow calibration and validation of the BOLD image-contrast. Good agreement between changes in CMR(O2) calculated from BOLD theory and measured by (13)C MRS, reveals that BOLD fMRI signal-changes at 7 T are closely linked with alterations in neuronal glucose oxidation, both for activation and deactivation paradigms. To determine the neurochemical basis of BOLD, pharmacological treatment with lamotrigine, which is a neuronal voltage-dependent Na(+) channel blocker and neurotransmitter glutamate release inhibitor, is used in a rat forepaw stimulation model. Attenuation of the functional changes in CBF and BOLD with lamotrigine reveals that the fMRI signal is associated with release of glutamate from neurons, which is consistent with a link between neurotransmitter cycling and energy metabolism. Comparisons of CMR(O2) and CBF over a wide dynamic range of neuronal activity provide insight into the regulation of energy metabolism and oxygen delivery in the cerebral cortex. The current results reveal the energetic and physiologic components of the BOLD fMRI signal and indicate the required steps towards mapping neuronal activity quantitatively by fMRI at steady-state. Consequences of these results from rat brain for similar calibrated BOLD fMRI studies in the human brain are discussed.     

Neural correlates of sensory and decision processes in auditory object identification

Physiological studies of auditory perception have not yet clearly distinguished sensory from decision processes. In this experiment, human participants identified speech sounds masked by varying levels of noise while blood oxygenation signals in the brain were recorded with functional magnetic resonance imaging (fMRI). Accuracy and response time were used to characterize the behavior of sensory and decision components of this perceptual system. Oxygenation signals in a cortical subregion just anterior and lateral to primary auditory cortex predicted accuracy of sound identification, whereas signals in an inferior frontal region predicted response time. Our findings provide neurophysiological evidence for a functional distinction between sensory and decision mechanisms underlying auditory object identification. The present results also indicate a link between inferior frontal lobe activation and response-selection processes during auditory perception tasks.     

Wavelet Analysis as a Tool for Investigating Movement-Related Cortical Oscillations in EEG-fMRI Coregistration

Electroencephalography combined with functional magnetic resonance imaging (EEG-fMRI) identifies blood oxygenation level dependent (BOLD) signal changes associated with physiological and pathological EEG events. In this study we used EEG-fMRI to determine the possible correlation between topographical movement-related EEG changes in brain oscillatory activity recorded from EEG electrodes over the scalp and fMRI cortical responses in motor areas during finger movement. Thirty-two channels of EEG were recorded in 12 subjects during eyes-closed condition inside a three T magnetic resonance (MR) scanner using an MR-compatible EEG recording system. Off-line MRI artifact subtraction software was applied to obtain continuous EEG data during fMRI acquisition. For EEG data analysis we used a time–frequency approach to measure time by varying the energy in a signal at a given frequency band by the convolution of the EEG signal with a wavelet family in the alpha and beta bands. The correlation between the BOLD signal associated with the EEG regressor provides that sensory motor region is a source of the EEG. We conclude that combined EEG-fMRI can be used to investigate movement-related oscillations of the human brain inside an MRI scanner and wavelet analysis adds further details on the EEG changes. The movement-related changes in the EEG signals are useful to identify the brain activation sources responsible for BOLD-signal changes.     

Spectrally resolved neurophotonics: a case report of hemodynamics and vascular components in the mammalian brain

We developed a spectral technique that is independent of the light transport modality (diffusive or nondiffusive) to separate optical changes in scattering and absorption in the cat's brain due to the hemodynamic signal following visual stimulation. We observe changes in oxyhemoglobin and deoxyhemoglobin concentration signals during visual stimulation reminiscent of the functional magnetic resonance imaging (fMRI) blood oxygenation level dependence (BOLD) effect. Repeated measurements at different locations show that the observed changes are local rather than global. We also determine that there is an apparent large decrease in the water concentration and scattering coefficient during stimulation. We model the apparent change in water concentration on the separation of the optical signal from two tissue compartments. One opaque compartment is featureless (black), due to relatively large blood vessels. The other compartment is the rest of the tissue. When blood flow increases due to stimulation, the opaque compartment increases in volume, resulting in an overall decrease of tissue transmission. This increase in baseline absorption changes the apparent relative proportion of all tissue components. However, due to physiological effects, the deoxyhemoglobin is exchanged with oxyhemoglobin resulting in an overall increase in the oxyhemoglobin signal, which is the only component that shows an apparent increase during stimulation.     

Quantitative evaluation of activation state in functional brain imaging

Neuronal activity can evoke the hemodynamic change that gives rise to the observed functional magnetic resonance imaging (fMRI) signal. These increases are also regulated by the resting blood volume fraction (V (0)) associated with regional vasculature. The activation locus detected by means of the change in the blood-oxygen-level-dependent (BOLD) signal intensity thereby may deviate from the actual active site due to varied vascular density in the cortex. Furthermore, conventional detection techniques evaluate the statistical significance of the hemodynamic observations. In this sense, the significance level relies not only upon the intensity of the BOLD signal change, but also upon the spatially inhomogeneous fMRI noise distribution that complicates the expression of the results. In this paper, we propose a quantitative strategy for the calibration of activation states to address these challenging problems. The quantitative assessment is based on the estimated neuronal efficacy parameter [Formula: see text] of the hemodynamic model in a voxel-by-voxel way. It is partly immune to the inhomogeneous fMRI noise by virtue of the strength of the optimization strategy. Moreover, it is easy to incorporate regional vascular information into the activation detection procedure. By combining MR angiography images, this approach can remove large vessel contamination in fMRI signals, and provide more accurate functional localization than classical statistical techniques for clinical applications. It is also helpful to investigate the nonlinear nature of the coupling between synaptic activity and the evoked BOLD response. The proposed method might be considered as a potentially useful complement to existing statistical approaches.