脑磁图对脑功能动态活动的定位作用

脑磁图(magnetoencephalography，MEG)通过无创伤性的方法探测大脑生物电流所产生的磁场变化，具有很高的时间分辨率及空间分辨率，可以与MRI结合形成磁源性影像(MSI)，对脑重要功能区及癫痫灶进行精确定位，用以指导临床医师确定手术方案及指导伽玛刀治疗，以最大范围地切除病变并保留脑的重要功能区，提高患者术后生活质量；可以对轻度脑损伤患者、一过性脑缺血发作患者的脑功能损害提供客观依据。     

脑磁图对脑卒中后脑功能损害的评价作用

目的将近10年来脑磁图用于脑卒中研究的成果做一介绍.方法主要选择被Medline收录的外文文献和在国内核心杂志上发表的有关文献,就其内容进行分析、分类、归纳及总结.结果脑卒中后,其脑损伤部位出现异常低频磁活动,并有相应功能区受损表现.结论脑磁图能够对脑卒中损害的脑组织功能进行监测、定位及评估,并可用于受损神经功能重建和可塑性的研究.     

脑磁图对脑卒中后脑功能损害的评价作用

目的将近10年来脑磁图用于脑卒中研究的成果做一介绍。方法主要选择被Medline收录的外文文献和在国内核心杂志上发表的有关文献,就其内容进行分析、分类、归纳及总结。结果脑卒中后,其脑损伤部位出现异常低频磁活动,并有相应功能区受损表现。结论脑磁图能够对脑卒中损害的脑组织功能进行监测、定位及评估,并可用于受损神经功能重建和可塑性的研究。     

行脑磁图头部位置定位操作的体会

脑磁图（Magnetoencephalography,MEG）是一种应用脑功能图像检测技术对人体实施完全无侵袭、无损伤的大脑研究和临床应用设备。MEG检测过程中测量系统不会发出任何射线、能量或机器噪声,而只是对脑内产生的极其微弱的生物磁场信号进行探测。MEG主要反映神经细胞在不同功能下所产生磁场的变化,因此能相对直接反映神经元的活动状态,     

脑磁图SAM分析法定位皮质运动功能初步探讨

目的利用脑磁图SAM分析法研究健康受试者运动皮质反应及其磁源影像定位价值。方法10例右利手健康受试者给予tone音刺激,受试者听到声音后右手食指触压按键感应器。以运动触发为基点进行平均,选择触发点前后的波形分别用等价电流偶极子(ECD)和合成孔径磁场测量(SAM)进行分析,最终形成三维的脑功能影像图。结果所有10例受试SAM法均定位大脑皮层中央前回,与运动皮层解剖位置一致,ECD法7例定位于中央前回运动中枢,3例定位偏差。结论脑磁图SAM分析方法可以很好地显示皮质运动反应并能对皮层运动功能进行成功定位。     

脑磁图表现对脑卒中患者脑功能损伤程度和区域的评估价值

目的：分析2例出血性脑卒中术后患者的脑磁图表现，探讨脑磁图的研究现状以及在脑血管疾病方面的应用价值。方法：2003-12／2004-01在广东三九脑科医院电生理中心脑磁图室对2例经CT确诊为脑出血并已行引流术的患者进行脑磁图检查。结果：患者于清醒、安静状态下行自发脑磁图检查，在患侧半球发现异常低频磁活动(ALFUA)；手指电刺激所得体感皮质诱发反应，发现患侧半球反应波消失。结论：脑磁图能确定大脑功能损伤的程度和区域，对出血性脑卒中患者脑损伤的诊断及其指导早期康复治疗很有帮助。     

脑磁图在癫痫致痫灶及灶周脑功能区定位中的作用

目的：脑磁图是通过测定神经元兴奋产生的电流所伴随的磁场变化来确定异常放电的部位，了解其在癫痫致痫灶和痫灶周围脑功能区定位中的作用。资料来源：应用计算机检索Medline1998-07／2004-11与脑磁图和癫痫相关文章，检索词“Epilepsy，Magnetoencephalography，localization”，并限定文章语言种类为English。计算机检索VIP和CJFD1999／2004与脑磁图和癫痫相关的中文文章，检索词“癫痫，脑磁图，定位”。资料选择：对资料进行初审，纳入标准；①回顾性研究，无论是否设有对照组。②研究为随机抽样。开始查找全文，未排除是否为盲法。资料提炼：共收集到91篇相关文献（英文84篇，中文7篇）。54篇符合纳入标准。排除的37篇文章中34篇系重复研究，3篇为Meta分析。资料综合：54篇文章中14篇从偶极子定位方面阐述，13篇涉及脑磁图对癫痫患者手术前后评估，16篇与其他定位技术比较证明脑磁图的作用。11篇采取个案报道的形式证实脑磁图的定位价值。从中选取13篇有代表性的文献进行综述，认为作为无创性检测技术，脑磁图可检测到直径〈3．0mm的癫痫病理灶，分辨时相高达1．0ms，可以发现癫痫原发病灶与对侧对称位置出现的类似信号，即“镜像灶”，还能分辨发作间期一侧大脑半球的多个癫痫灶。脑磁图可用于癫痫发作期和发作间期致痫源的定位，还可对痫灶周围脑功能区进行定位，与脑电图比较，其使用更方便，更敏感。结论：脑磁图对各类癫痫的诊断，致痫灶、灶周脑功能区的定位，癫痫镜像灶的辨别具有明显的优势和广泛的应用前景。     

自主吞咽运动早期人大脑皮质活动的脑磁图研究

在研究吞咽的神经解剖关系时,通常使用无创的检测方法,如功能性磁共振(fMRI)和正电子发射断层扫描(PET).脑磁图(magnetoencephalography,MEG)是一项新型的无创检查技术,通过记录并分析大脑神经细胞活动时产生的微弱磁场变化来了解大脑生理活动和病理变化;其关键部件是其中的磁场检测线圈,又称"超导量子干涉仪"(SQUID),在检测时置于受检者头部.MEG的时间分辨率(大约1ms)远优于PET和fMRI,而空间分辨率与之相当,因此,其优势在于可以观察神经元的"活动"状况,而不仅是静态图像.     

脑磁图在癫痫致痫灶及灶周脑功能区定位中的作用

目的:脑磁图是通过测定神经元兴奋产生的电流所伴随的磁场变化来确定异常放电的部位,了解其在癫痫致痫灶和痫灶周围脑功能区定位中的作用。资料来源:应用计算机检索Medline1998-07/2004-11与脑磁图和癫痫相关文章,检索词“Epilepsy,Magnetoencephalography,localization”,并限定文章语言种类为English。计算机检索VIP和CJFD1999/2004与脑磁图和癫痫相关的中文文章,检索词“癫痫,脑磁图,定位”。资料选择:对资料进行初审,纳入标准:①回顾性研究,无论是否设有对照组。②研究为随机抽样。开始查找全文,未排除是否为盲法。资料提炼:共收集到91篇相关文献(英文84篇,中文7篇)。54篇符合纳入标准。排除的37篇文章中34篇系重复研究,3篇为Meta分析。资料综合:54篇文章中14篇从偶极子定位方面阐述,13篇涉及脑磁图对癫痫患者手术前后评估,16篇与其他定位技术比较证明脑磁图的作用,11篇采取个案报道的形式证实脑磁图的定位价值。从中选取13篇有代表性的文献进行综述,认为作为无创性检测技术,脑磁图可检测到直径<3.0mm的癫痫病理灶,分辨时相高达1.0ms,可以发现癫痫原发病灶与对侧对称位置出现的类似信号,即“镜像灶”,还能分辨发作间期一侧大脑半球的多个癫痫灶。脑磁图可用于癫痫发作期和发作间期致痫源的定位,还可对痫灶周围脑功能区进行定位,与脑电图比较,其使用更方便,更敏感。结论:脑磁图对各类癫痫的诊断,致痫灶、灶周脑功能区的定位,癫痫镜像灶的辨别具有明显的优势和广泛的应用前景。     

脑磁图表现对脑卒中患者脑功能损伤程度和区域的评估价值

目的:分析2例出血性脑卒中术后患者的脑磁图表现,探讨脑磁图的研究现状以及在脑血管疾病方面的应用价值。方法:2003-12/2004-01在广东三九脑科医院电生理中心脑磁图室对2例经CT确诊为脑出血并已行引流术的患者进行脑磁图检查。结果:患者于清醒、安静状态下行自发脑磁图检查,在患侧半球发现异常低频磁活动(ALFMA);手指电刺激所得体感皮质诱发反应,发现患侧半球反应波消失。结论:脑磁图能确定大脑功能损伤的程度和区域,对出血性脑卒中患者脑损伤的诊断及其指导早期康复治疗很有帮助。     

A graphical model for estimating stimulus-evoked brain responses from magnetoencephalography data with large background brain activity

This paper formulates a novel probabilistic graphical model for noisy stimulus-evoked MEG and EEG sensor data obtained in the presence of large background brain activity. The model describes the observed data in terms of unobserved evoked and background factors with additive sensor noise. We present an expectation maximization (EM) algorithm that estimates the model parameters from data. Using the model, the algorithm cleans the stimulus-evoked data by removing interference from background factors and noise artifacts and separates those data into contributions from independent factors. We demonstrate on real and simulated data that the algorithm outperforms benchmark methods for denoising and separation. We also show that the algorithm improves the performance of localization with beamforming algorithms.     

Spatiotemporal patterns of language-specific brain activity in patients with chronic aphasia after stroke using magnetoencephalography

Six participants with chronic aphasia secondary to first-ever ischemic stroke within the middle cerebral artery (MCA) distribution of the left hemisphere and six neurologically intact controls of similar age were given a running recognition memory task for words while the magnetic flux normal to the scalp surface was measured with a whole-head neuromagnetometer. This task had been previously shown to be valid for the localization and lateralization of brain activity specific to receptive language function. As expected, patients exhibited relatively decreased activation in areas known to be involved in receptive language function, including superior temporal gyrus (STG) in the left hemisphere, as well as increased activation of areas outside of the left STG that might potentially support language function. Decreased activation within left STG was associated with a reduction in receptive language in patients, as was increased activation outside of left STG. Results support hypotheses suggesting that peri-lesional areas outside premorbid language areas may assume receptive language function after aphasia secondary to stroke, but that better recovery occurs when putative premorbid language areas are able to normalize.     

Localization of primary auditory cortex in humans by magnetoencephalography

Brief auditory stimuli activate the primary auditory cortex (PAC) earlier than any other cortical area so, within a certain latency range, the PAC is the only cortical source contributing to the auditory evoked field (AEF). Nevertheless, there is no AEF component specific to PAC that can be reliably detected in all individuals. The present study suggests that a peak in the first temporal derivative of the magnetic field at about 20 ms (dP20m) is a genuine correlate of PAC activity. AEFs in response to clicks presented to the right ear were recorded with a 37-channel axial gradiometer system positioned over the left hemisphere in nine normal-hearing subjects. More than 8500 stimuli were presented in each of two independent sessions at a rate of approximately 3/s. The dipole coordinates for the dP20m derived from the two sessions typically differed by only a few millimeters. Coregistration of the dipoles with structural magnetic resonance images suggests that dP20m arises from an area close to the retroinsular origin of Heschl's gyrus. Although the dP20m is simply the point of steepest slope on the well-known middle-latency peak, P30m or Pam, it would appear that dP20m and P30m do not have the same cortical origin. Evidence is provided that P30m receives major contributions from at least two distinct cortical areas, only one of which is PAC.     

Localization of abnormal discharges causing insular epilepsy by magnetoencephalography

The insula, one of the five cerebral lobes of the brain, is located deep within the brain and lies mainly beneath the temporal lobe. Insular epilepsy can be easily confused and misdiagnosed as temporal lobe epilepsy (TLE) because of the similar clinical symptoms and scalp electroencephalography (EEG) findings due to the insula location and neuronal connections with the temporal lobe. Magnetoencephalography (MEG) has higher sensitivity and spatial resolution than scalp EEG, and thus can often identify epileptic discharges not revealed by scalp EEG. Simultaneous scalp EEG and MEG were performed to detect and localize epileptic discharges in two patients known to have insular epilepsy associated with cavernous angioma in the insula. Epileptic discharges were detected as abnormal spikes in the EEG and MEG findings. In Patient 1, the sources of all MEG spikes detected simultaneously by EEG and MEG (E/M-spikes) were localized in the anterior temporal lobe, similar to TLE. In contrast, the sources of all MEG spikes detected only by MEG (M-spikes) were adjacent to the insular lesion. In Patient 2, the sources of all MEG spikes detected simultaneously by EEG and MEG (E/M-spikes) were localized in the anterior temporal lobe. These findings indicate that MEG allows us to detect insular activity that is undetectable by scalp EEG. In conclusion, simultaneous EEG and MEG are helpful for detecting spikes and obtaining additional information about the epileptic origin and propagation in patients with insular epilepsy.     

Changes in brain network activity during working memory tasks: a magnetoencephalography study

In this study, we elucidate the changes in neural oscillatory processes that are induced by simple working memory tasks. A group of eight subjects took part in modified versions of the N-back and Sternberg working memory paradigms. Magnetoencephalography (MEG) data were recorded, and subsequently processed using beamformer based source imaging methodology. Our study shows statistically significant increases in θ oscillations during both N-back and Sternberg tasks. These oscillations were shown to originate in the medial frontal cortex, and further to scale with memory load. We have also shown that increases in θ oscillations are accompanied by decreases in β and γ band oscillations at the same spatial coordinate. These decreases were most prominent in the 20-40 Hz frequency range, although spectral analysis showed that γ band power decrease extends up to at least 80 Hz. β/γ Power decrease also scales with memory load. Whilst θ increases were predominately observed in the medial frontal cortex, β/γ decreases were associated with other brain areas, including nodes of the default mode network (for the N-back task) and areas associated with language processing (for the Sternberg task). These observations are in agreement with intracranial EEG and fMRI studies. Finally, we have shown an intimate relationship between changes in β/γ band oscillatory power at spatially separate network nodes, implying that activity in these nodes is not reflective of uni-modal task driven changes in spatially separate brain regions, but rather represents correlated network activity. The utility of MEG as a non-invasive means to measure neural oscillatory modulation has been demonstrated and future studies employing this technology have the potential to gain a better understanding of neural oscillatory processes, their relationship to functional and effective connectivity, and their correspondence to BOLD fMRI.     

Human fetal brain imaging by magnetoencephalography: verification of fetal brain signals by comparison with fetal brain models

Fetal magnetoencephalogram (fMEG) is measured in the presence of a large interference from maternal and fetal magnetocardiograms (mMCG and fMCG). This cardiac interference can be successfully removed by orthogonal projection of the corresponding spatial vectors. However, orthogonal projection redistributes the fMEG signal among channels. Such redistribution can be readily accounted for in the forward solution, and the signal topography can also be corrected. To assure that the correction has been done properly, and also to verify that the measured signal originates from within the fetal head, we have modeled the observed fMEG by two extreme models where the fetal head is assumed to be either electrically transparent or isolated from the abdominal tissue. Based on the measured spontaneous, sharp wave, and flash-evoked fMEG signals, we have concluded that the model of the electrically isolated fetal head is more appropriate for fMEG analysis. We show with the help of this model that the redistribution due to projection was properly corrected, and also, that the measured fMEG is consistent with the known position of the fetal head. The modeling provides additional confidence that the measured signals indeed originate from within the fetal head.     

Localization of interictal delta and epileptiform EEG activity associated with focal epileptogenic brain lesions

The present study was aimed at investigating the accuracy of electric source reconstruction in the presurgical evaluation of epilepsy patients. Spontaneous EEG activity of 14 patients with focal intracerebral epileptogenic lesions was analyzed by source reconstruction based on high-resolution EEG (64-channel system) and a boundary element method head model accounting for the individual head anatomy. Equivalent dipole modeling was applied to focal delta and interictal epileptiform activity. The localization results were validated quantitatively by comparison with the sites of the structural lesions. In 6 of 9 patients with focal delta activity, the maximum of dipole concentration was closer than 10 mm to the nearest lesion margin and mostly at the border or within pathologically altered cortical tissue. In all 11 patients showing interictal epileptiform activity, the localization results were found in the same lobe as the lesion. In almost half of them, they were closer than 10 mm to the lesion margin. Patients with larger distances (22-36 mm) mostly had hippocampal atrophy or sclerosis. Their dipole locations did not appear in the affected hippocampus, but in the adjacent temporal neocortex. In conclusion, electric source reconstruction applied to both abnormal slow and interictal epileptiform EEG activity seems to be a valuable additional noninvasive component in the multimodal presurgical evaluation of epilepsy patients.     

Learning arbitrary visuomotor associations: temporal dynamic of brain activity.

Primates can give behavioral responses on the basis of arbitrary, context-dependent rules. When sensory instructions and behavioral responses are associated by arbitrary rules, these rules need to be learned. This study investigates the temporal dynamics of functional segregation at the basis of visuomotor associative learning in humans, isolating specific learning-related changes in neurovascular activity across the whole brain. We have used fMRI to measure human brain activity during performance of two tasks requiring the association of visual patterns with motor responses. Both tasks were learned by trial and error, either before (visuomotor control) or during (visuomotor learning) the scanning session. Epochs of tasks performance ( approximately 30 s) were alternated with a baseline period over the whole scanning session ( approximately 50 min). We have assessed both linear and nonlinear modulations in the differential signal between tasks, independently from overall task differences. The performance indices of the visuomotor learning task smoothly converged onto the values of a steady-state control condition, according to nonlinear timecourses. Specific visuomotor learning-related activity has been found over a distributed cortical network, centred on a temporo-prefrontal circuit. These cortical time-modulated activities were supported early in learning by the hippocampal/parahippocampal complex, and late in learning by the basal ganglia system. These findings suggest the inferior temporal and the ventral prefrontal cortex are critical neural nodes for integrating perceptual information with executive processes.     

Verification of fetal brain responses by coregistration of fetal ultrasound and fetal magnetoencephalography data

Fetal magnetoencephalography (fMEG) is used to study neurological functions of the developing fetus by measuring magnetic signals generated by electrical sources within the fetal brain. For this aim either auditory or visual stimuli are presented and evoked brain activity or spontaneous activity is measured at the sensor level. However a limiting factor of this approach is the low signal to noise ratio (SNR) of recorded signals. To overcome this limitation, advanced signal processing techniques such as spatial filters (e.g., beamformer) can be used to increase SNR. One crucial aspect of this technique is the forward model and, in general, a simple spherical head model is used. This head model is an integral part of a model search approach to analyze the data due to the lack of exact knowledge about the location of the fetal head. In the present report we overcome this limitation by a coregistration of volumetric ultrasound images with fMEG data. In a first step we validated the ultrasound to fMEG coregistration with a phantom and were able to show that the coregistration error is below 2 cm. In the second step we compared the results gained by the model search approach to the exact location of the fetal head determined on pregnant mothers by ultrasound. The results of this study clearly show that the results of the model search approach are in accordance with the location of the fetal head.     

Detection of event-related hemodynamic response to neuroactivation by dynamic modeling of brain activity

This paper presents a state-space hemodynamic model by which any event-related hemodynamic prediction function (i.e., the basis function of the design matrix in the general linear model) is obtained as an output of the model. To model the actual event-related behavior during a task period (intra-activity dynamics) besides the contrasting behavior among the different task periods and against the rest periods (inter-activity dynamics), the modular system is investigated by parametric subspace-based state-space modeling of actual hemodynamic response to an impulse stimulus. This model provides a simple and computationally efficient way to generate the event-related basis function for an experiment by just convolving the developed hemodynamic model with the impulse approximation of the experimental stimuli. The demonstration of the stated findings is carried out by conducting finger-related experiments with slow- and fast-sampling near-infrared spectroscopy instruments to model and validate the cortical hemodynamic responses. The generated basis functions of the finger-related experiments are adapted from real data to validate the incorporation of non-delayed and real-time event-related features and to effectively demonstrate a dynamic-modeling-based online framework. The proposed method demonstrates potential in estimating event-related intra- and inter-activation dynamics and thereby outperforms the classical Gaussian approximation method.