异丙酚对家兔EEGδ频段的影响

目的 :观察异丙酚对家兔EEGδ频段的影响。方法 :应用定量药物EEG(QPEEG)功率谱分析法 ,分析静注异丙酚前后家兔脑电活动的变化。结果 :异丙酚 2 .5mg/kg对δ频段的功率百分比无明显影响 :5mg/kg使δ频段的功率百分比增大一倍以上 ,但未达显著性水平 (P >0 .0 5 ) ;10mg/kg使各脑区使δ频段功率百分比在 2 0s至 5min内均显著增大 (P <0 .0 1,P <<0 .0 5 ) ,且与行为变化平行 ,δ频段的改变与异丙酚剂量在 5min内均呈显著相关 (r=0 6 2～ 0 95 ,P <0 0 1)。结论 :异丙酚以剂量依赖方式增大家兔EEGδ频段的功率百分比 ,提示δ频段可能成为监测麻醉深度的指标     

基于Granger因果性的功能磁共振成像对内侧颞叶癫痫活动的研究

在内侧颞叶癫痫(mTLE)中,内侧颞叶与皮层及皮层下结构参与了癫痫活动的起源与传播.基于Granger因果性(GC)检验方法,对脑电联合功能磁共振(EEG-fMRI)数据进行分析,研究内侧颞叶在mTLE中的作用.以内侧颞叶激活区域为参考区域,计算参考区域与大脑其余每个体素点之间的Granger因果关系,并映射到全脑,形成Granger因果图(GCM).结果表明,内侧颞叶将癫痫活动传播到外侧颞叶、额叶、顶叶及丘脑等区域,同时受到脑岛、壳核以及丘脑等区域脑活动的影响,提示内侧颞叶在mTLE痫样发放的传播环路中具有关键作用.     

脑功能信号的Granger因果性分析方法

脑是如何选择和调整分布于全脑的神经活动以实现其功能的?为解决这个问题,近年来人们将推测变量间信息因果流向的Granger因果分析引入脑功能研究.首先介绍了Granger因果分析的基本原理及其在处理脑功能信号时的拓展算法——结构向量自回归模型(SVAR);综述了在对脑功能信号进行Granger因果分析时的技术问题;最后,...     

颞叶癫痫病人睡眠EEG放电规律的探讨

目的：探讨颞叶癫痫患者昼与夜的脑电图痫样放电特点。方法：对２０例颞叶癫痫患者及同年龄、性别的对照组进行连续４８ｈＥＥＧ监测，就其临床发作频率、睡眠各期痫样放电的频率、时程进行分析。结果：ＥＥＧ监测期间共发生１３次临床发作。其中清醒时６次，睡眠中７次；２０例病人均检出痫样放电，１８例出现于清醒和睡眠时，１例仅出现于睡眠中，另一例仅出现于清醒时。痫样放电出现于非眼快动睡眠相（ＮＲＥＭ）１期１６例，２期１８例，３期３例，４期４例，出现于眼快动睡眠相（ＲＥＭ）１２例。结论：颞叶癫痫的临床发作频率和痫样放电频率在清醒和睡眠时期基本相等。痫样放电在ＮＲＥＭ的１、２期和ＲＥＭ期明显增加     

应用因果分析方法对癫痫发作间期头皮脑电信号进行致痫灶定侧

目的利用因果分析方法对癫痫发作间期的头皮脑电信号进行致痫灶定侧。方法在频域因果分析方法——自适应直接传递函数（ADTF）的基础上提出功率谱加权ADTF（psADTF）法,以给定频段内信号的功率谱对ADTF的标准化做加权,以适应不同癫痫波频域信息不同的特点。利用该方法对2组共30例患者的头皮脑电信号进行分析,含组1癫痫手术患者15例,组2门诊癫痫患者15例。其中组1患者共截取癫痫波样本数104个,组2患者共截取癫痫波样本数98个。结果组1患者通过psADTF分析对致痫灶定侧与手术侧一致的有96个,平均单个癫痫波致痫灶定侧准确率可达92％;组2患者通过psADTF分析对致痫灶定侧与专家判读结果一致的有94个,平均单个癫痫波致痫灶定侧准确率达96％。结论发作间期头皮脑电癫痫波信号的psADTF分析能够很好地辅助临床致痫灶定侧。     

癫痫发作类型与EEG的相关性

目的：分析各种发作类型癫痫及其与脑电图（EEG）表现的关系。方法：对352例确诊癫痫患者行规范的病史询问及长程EEG监测（描记时间10～15h）,并按照1981年ILAE分类和名词委员会推荐的癫痫发作的分类方案进行发作症状的分类,按照1989年II,AE推荐的癫痫和癫痫综合征的分类作出诊断,分析其发作类型和EEG之间的相关性。结果：在352例中,EEG异常246例,异常率为69．9％,24例（6．8％）记录到临床发作。EEG异常率与发作频率相关,每月发作大于4次者较每月发作少于4次者EEG异常率显著升高（P=0．014）。部分性发作和全面性发作的患者异常率比较差异无显著意义（P=0．929）,但前者更多表现为EEG局限性异常（P=0．014）。结论：规范的长程EEG检查异常率较高,EEG异常率与发作频率相关,不同癫痫发作类型患者的EEG表现有差异。     

基于多分辨Tsallis熵的癫痫EEG分析

利用多分辨率Tsallis熵的方法,识别癫痫脑电中的棘波,把EEG信号分解成小波级数,在各个尺度上利用多分辨率Tsallis熵来检测棘波,和申农熵相比,多分辨率Tsallis熵能给出更详细的信息。通过对6位患者的EEG信号进行处理,发现这种方法能够比较准确的检测EEG中的棘波,具有较好的临床应用价值。     

基于改进的伪Wigner分布检测癫痫EEG棘波的方法

本文提出了一种新的检测癫痫EEG棘波的方法,采用改进的伪Wigner分布对脑电信号进行时频变换,这种时频分布不仅能够有效地消除交叉项,而且可以快速实现,在时频平面上,以每个时间点上的中心频率划分背景脑电和癫痫样瞬态特征,通过一个镜像滤波器提取瞬态分量,最后,利用瞬态分量的能量局部极值检测棘波,临床应用表明,这种方法能够快速有效地从背景脑电中提取癫痫样瞬态特征。     

阴性颞叶癫痫患者静息态脑功能连接网络特征融合策略的分析

静息态功能磁共振成像(rfMRI)的功能连接(FC)可为阴性颞叶癫痫提供脑功能异常指标,但冗余特征影响了精准性。为此,本研究提出结合特异性指数模型与判别相关分析(DCA)的特征融合策略以改善识别效果。将20位患者与20位健康人的rfMRI数据预处理后,以健康人为对照组,构建两类特异性指数模型以量化FC和脑网络FC;采用最小冗余最大相关(mRMR)及独立样本t检验去除冗余特征,应用DCA融合2类FC特异性指标;将融合特征分别输入到K近邻、支持向量机和逻辑回归分类器中,并以嵌套10次10折交叉验证与嵌套10次5折分层交叉验证的平均分类精度来评估算法有效性。结果表明,融合特征识别率达到了91.25%～92.50%,高于非融合方案的识别水平。所提出的特征融合策略可有效地处理冗余信息,增强特征判别能力,为精准识别阴性颞叶癫痫提供了新思路。     

基于EEG模糊相似性的癫痫发作预测

本研究提出基于EEG序列模糊相似性指数方法预测癫痫发作.首先,结合复自相关法和Cao法对EEG序列进行了相空间重构;然后,计算相关积分时用Gaussian函数代替Heavyside函数,克服了Heavyside函数的刚性边界问题,使得计算相似性指数更加准确和可靠;最后,分析大鼠癫痫EEG信号,检测癫痫发作前期状态.分析结果表明模糊相似性指数方法能够比动态相似性指数方法获得更长的预测时间和更低的错误预测率.     

Investigation of the effective connectivity of resting state networks in Alzheimer's disease: a functional MRI study combining independent components analysis and multivariate Granger causality analysis

Recent neuroimaging studies have shown that the cognitive and memory decline in patients with Alzheimer's disease (AD) is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses in small‐world attributes. However, the causal interactions among the spatially isolated, but functionally related, resting state networks (RSNs) are still largely unexplored. In this study, we first identified eight RSNs by independent components analysis from resting state functional MRI data of 18 patients with AD and 18 age‐matched healthy subjects. We then performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that patients with AD exhibited decreased causal interactions among the RSNs in both intensity and quantity relative to normal controls. Results from mGCA indicated that the causal interactions involving the default mode network and auditory network were weaker in patients with AD, whereas stronger causal connectivity emerged in relation to the memory network and executive control network. Our findings suggest that the default mode network plays a less important role in patients with AD. Increased causal connectivity of the memory network and self‐referential network may elucidate the dysfunctional and compensatory processes in the brain networks of patients with AD. These preliminary findings may provide a new pathway towards the determination of the neurophysiological mechanisms of AD. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluation of the effective connectivity of the dominant primary motor cortex during bimanual movement using Granger causality

Granger causality analysis of the whole brain, voxel-by-voxel, was applied to six right-handed subjects performing a classic bimanual movement, to describe the effective connectivity between the activated voxels in the left primary motor cortex (PMC) and other parts of the brain, by choosing the left PMC as a reference region. The results demonstrated that the left and right PMC interact during bimanual movement, and Granger causality mapping implied a possible cause–effect relationship. The supplementary motor area (SMA) and cerebellum were pre-activated during bimanual movement relative to the left PMC, confirming the prior qualitative results concerning the functions of the SMA and cerebellum in hand movements.     

基于多变量格兰杰因果关系的运动想象因效网络构建

运动想象神经活动规律的探索为脑损伤肢体瘫痪患者康复训练新方法研发等提供理论指导。基于格兰杰因果关系构建的因效网络是分析运动想象神经活动状态的重要工具,但是格兰杰因果关系只能反映两个变量之间的相互作用,而一个简单的运动想象过程也需要多个神经节点参与,针对该问题,本研究引入可反映一个集群中多个变量之间相互作用的多变量格兰杰因果分析,优化运动想象因效网络构建方法。针对4位受试者,利用多变量及传统格兰杰因果关系,分别构建同一人两种不同运动想象模式的因效网络,并提取网络特征进行运动想象模式分类。结果表明,基于多变量格兰杰因效网络进行4位受试者运动想象模式分类的正确率分别为90.4%、88.8%、91.1%、90.3%,基于格兰杰因效网络的正确率为88.5%、89.3%、90.2%、89.7%。与传统格兰杰因果关系相比,基于多变量格兰杰因果关系构建因效网络,能更准确地反映运动想象神经活动特征状态。     

Functional connectivity and infant spatial working memory: a frequency band analysis

The limited research on the functional meaning of infant EEG frequency bands has used measures of EEG power. The purpose of this study was to examine task‐related changes in frontal EEG coherence measures for three infant EEG frequency bands (2–5 Hz, 6–9 Hz, 10–13 Hz) during a spatial working memory task. Eight‐month‐olds exhibited baseline‐to‐task changes in frontal EEG coherence for all infant frequency bands. Both the 2–5 Hz and the 10–13 Hz bands differentiated frontal functional connectivity during the distinct processing stages, but each band provided unique information. The 10–13 Hz band, however, was the only frequency band to distinguish frontal EEG coherence values during correct and incorrect responses. These data reveal valuable information concerning frontal functional connectivity and the functional meaning of three different infant EEG frequency bands during working memory processing.     

A comparison of multivariate causality based measures of effective connectivity

During the past several years a variety of methods have been developed to estimate the effective connectivity of neural networks from measurements of brain activity in an attempt to study causal interactions among distinct brain areas. Understanding the relative strengths and weaknesses of these methods, the assumptions they rely on, the accuracy they provide, and the computation time they require is of paramount importance in selecting the optimal method for a particular experimental task and for interpreting the results obtained. In this paper, the accuracy of the six most commonly used techniques for calculating effective connectivity are compared, namely directed transfer function, partial directed coherence, squared partial directed coherence, full frequency directed transfer function, direct directed transfer function, and Granger causality. These measures are derived from the coefficients and error terms of autoregressive models calculated using the dynamic autoregressive neuromagnetic causal imaging (DANCI) algorithm. These techniques were evaluated using magnetoencephalography recordings as well as several synthetic datasets that simulate neurophysiological signals, which varied on several parameters, including network size, signal-to-noise ratio, and network complexity, etc. The results show that Granger causality is the most accurate method across all experimental conditions explored and suggest that large multisensor data sets can be accurately analyzed using Granger causality with the DANCI algorithm.     

Association between the M129V variant allele of PRNP gene and mild temporal lobe epilepsy in women

Specific variations in the prion protein gene (PRNP) are associated with, and prevalent in patients with intractable temporal lobe epilepsy (TLE) and influence the surgical outcome. We investigated whether or not the PRNP gene is a susceptibility gene in temporal lobe epileptic patients with mild epilepsy. We systematically screened the entire open reading frame of the PRNP gene and evaluated the genetic contribution of the functional PRNP M129V polymorphism in 289 patients with mild TLE compared with a neurologically unaffected age and sex matched control group (n=272). Statistical analysis revealed a moderate difference in the distribution at codon 129 of the PRNP gene between sporadic mild TLE patients and healthy controls (p=0.036; OR=1.30; 95% CI=1.01-1.68). Although, there was no statistically significant difference in the genotype distribution within the study groups (p=0.101), a further analysis showed that the 129V allele was highly represented only in women with TLE compared with control group (p=0.006, OR=1.632; 95%CI=1.15-2.31). This is the first publication of data that support the hypothesis that the common methionine/valine polymorphism at codon 129 of the PRNP gene may modify the susceptibility of women to mild TLE.     

Correlation of electrocorticographic to clinical seizure onset and interhemispheric propagation times in temporal lobe epilepsy

This study was performed to test the hypothesis that, in human temporal lobe epilepsy, electrocorticographic time factors involved in the ictal EEG to clinical ictal transition (electrocorticographic to clinical seizure onset time, ECOT) and the interhemispheric propagation of epileptic activity (interhemispheric propagation time, IHPT), which are independently correlated with temporal lobe epileptogenicity and predictive of seizure-free outcome following temporal lobectomy, are correlated with one another in a quantitative fashion. A series of 37 patients with medically intractable temporal lobe seizures was studied with long-term subdural videoelectroencephalographic monitoring. Temporal lobe seizure interhemispheric propagation time (IHPT) was found to be a negative, exponential function of electrocorticographic to clinical seizure onset time (ECOT) (f(x) = 8.201 × 10^−0.016x, r = 0.347, d.f. = 35, t = 2.19, p < 0.05, where f(x) = IHPT and x = ECOT). A small increase in ECOT was associated with a substantial decrease in IHPT and vice versa. The results suggest the electrophysiological time factor, ECOT, involved in the transition from ictal EEG seizure onset to clinical seizure onset, may determine the speed of interhemispheric propagation of established epileptic activity. The results suggest the interesting hypothesis that, in human temporal lobe epilepsy and, perhaps, under non-pathological circumstances, the human temporal lobe might possess a “time-labeling” function amenable to quantitative analysis.     

Functional connectivity analysis of steady-state visual evoked potentials

In this paper, functional connectivity of steady-state visual evoked potential (SSVEP) was investigated. Directed transfer function (DTF) was applied to cortical signals recorded from electroencephalography (EEG) in order to obtain connectivity patterns. Flow gain was proposed to assess the role of the specific brain region involved in the information transmission process. We found network connections exist in many regions beyond occipital region. Flow gain mapping both in 8–12 Hz and 13–30 Hz showed that parietal region seemed to serve as the sole hub of information transmission. Further studies of flow gain obtained from channel Pz showed two distinct peaks centered at about 12 Hz low frequency and 20 Hz medium frequency respectively. The low frequency region had a larger value of flow gain. The present study introduced functional connectivity into SSVEP. Furthermore, we put forward the concept of flow gain for the first time to explore the exchange and processing of brain information during SSVEP.     

Mutations in GABRA1, GABRA5, GABRG2 and GABRD receptor genes are not a major factor in the pathogenesis of familial focal epilepsy preceded by febrile seizures

GABA(A) receptors mutations have been reported in few epilepsy families with febrile seizures (FS) followed by generalized epilepsy. It is not known if such mutations may underlie FS followed by partial epilepsy, which is a more common type of epilepsy. We searched for disease-causing mutations in the genes of the alpha1, alpha5, gamma2 and delta subunits of the GABA-A receptor that were previously shown to contain epilepsy-causing mutations or epilepsy susceptibility polymorphisms. All coding and untranslated exons of these four GABA(A) subunit genes were screened in 74 unrelated patients with familial partial epilepsy preceded by FS. Most patients had temporal lobe epilepsy (TLE). We did not detect any disease-causing mutations that would be consistent with missense, nonsense or splice site mutations in any of the four analyzed genes. We conclude that these genes are not a major genetic factor in familial TLE preceded by FS.