Amplitude-Integrated Electroencephalography Predicts Outcome in Patients with Coma After Acute Brain Injury

Prognostication of coma patients after brain injury is important, yet challenging. In this study, we evaluated the predictive value of amplitude-integrated electroencephalography （aEEG） for neurological outcomes in coma patients. From January 2013 to January 2016, 128 coma patients after acute brain injury were prospectively enrolled and monitored with aEEG. The 6-month neurological outcome was evaluated using the Cerebral Performance Category Scale. aEEG monitoring commenced at a median of 7.5 days after coma onset. Continuous normal voltage predicted a good 6-month neurological outcome with a sensitivity of 93.6% and specificity of 85.2%. In contrast, continuous extremely low voltage, burst-suppression, or a flat tracing was correlated with poor 6-month neurological outcome with a sensitivity of 76.5% and specificity of 100%. In conclusion, aEEG is a promising predictor of 6-month neurological outcome for coma patients after acute brain injury.

Calculation of compact amplitude-integrated EEG tracing and upper and lower margins using raw EEG data

Amplitude-integrated EEG (aEEG) is a popular method for monitoring cerebral function. Although various commercial aEEG recorders have been produced, a detailed aEEG algorithm currently is not available. The upper and lower margins in the aEEG tracing are the discriminating features for data inspection and tracing classification. However, most aEEG devices require that these margins be measured semi-subjectively. This paper proposes a step-by-step signal-processing method to calculate a compact aEEG tracing and the upper/lower margin using raw EEG data. The high accuracy of the algorithm was verified by comparison with a recognized commercial aEEG device based on a representative testing dataset composed of 72 aEEG data. The introduced digital algorithm achieved compact aEEG tracing with a small data size. Moreover, the algorithm precisely represented the upper and lower margins in the tracing for objective data interpretation. The described method should facilitate aEEG signal processing and further establish the clinical and experimental application of aEEG methods.

视觉对人体姿势控制影响的脑功能网络连接机制

目的研究视觉对人体姿势控制影响及其脑功能网络连接机制。方法以15名健康青年为研究对象,要求受试者分别进行30 s睁眼、闭眼的双腿站立平衡,采集平衡过程中身体压力中心(center of pressure,COP)和脑电。对COP进行样本熵(SampleEn)计算;对脑电θ、α和β频段,计算相位滞后指数(phase lag index,PLI)构建大脑功能网络,并基于图论计算集聚系数(C)、特征路径长度(L)及小世界网络属性(σ)。结果人体在双腿站立平衡过程中,闭眼COPY样本熵显著高于睁眼(P<0.05)。闭眼α频段PLI平均值显著高于睁眼(P<0.05);闭眼α频段C、σ显著高于睁眼,L显著低于睁眼(P<0.05)。闭眼时α频段额区-中央区-顶区之间的网络连接以及中央区和顶区内连接强度显著高于睁眼(P<0.05)。闭眼时α频段PLI平均值以及C值与COPY样本熵中度呈中度负相关(P<0.05)。睁眼时左前额区、左顶区、左枕区α频段PLI平均值与COPY样本熵呈中度负相关;闭眼时左中央区、右枕区α频段PLI平均值则与COPY样本熵呈中度负相关。结论人体在站立平衡时,当没有视觉信息输入时,身体平衡稳定性下降,同时伴随着脑电α频段的脑网络连接增强以及大脑处理信息的效率需提升。人体在不同的视觉条件下进行姿势控制时,大脑会采用不同的神经策略。

电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响

背景:创伤性脑损伤是由头部受到撞击、打击而导致大脑正常功能被破坏的疾病,目前需要寻找有效治疗方式和客观指标,帮助医生判别损伤状况及恢复患者脑功能。目的:探究电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响。方法:将40只6周龄SPF级雄性SD大鼠随机分为假手术组、模型组、电针组、低频经颅超声刺激组和联合组(n=8),后4组采用Feeney自由落体法造模,假手术组只开骨窗而不打击。各干预组均于造模后1 d开始实施干预,电针组进行电针干预,低频经颅超声刺激组进行低频经颅超声刺激干预,联合组进行两者联合干预,共干预7 d。造模后8 h,用改良神经功能缺损评分评定大鼠神经功能缺损情况;干预7 d后观察大鼠Y迷宫自发轮流行为百分比,而后采集脑电信号,利用快速傅里叶变换分解出α、β、θ和δ波段,计算各频段振荡幅值、能量占比百分比以及Lempel-Ziv复杂度、样本熵。结果与结论:①造模后8 h,模型组、电针组、低频经颅超声刺激组和联合组的改良神经功能缺损评分显著高于假手术组(P<0.05);②造模后第7天,模型组的α波、δ波频带振荡幅值、δ波能量占比百分比显著高于假手术组(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Ziv复杂度、样本熵显著低于假手术组(P<0.05);③与模型组比较,联合组的α波、δ波频带振荡幅值显著下降(P<0.05),电针组、低频经颅超声刺激组、联合组的α波、β波频带能量占比百分比显著升高(P<0.05),δ波能量占比百分比显著下降(P<0.05);④与电针组和低频经颅超声刺激组相比,联合组的δ波能量占比百分比显著降低(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Zi复杂度、样本熵显著升高(P<0.05);⑤结果显示,创伤性脑损伤大鼠出现脑电信号异常,而电针联合低频经颅超声刺激干预后可以改善大鼠脑电信号的异常情况,提示脑电频域特征和非线性特征可用来评估创伤性脑损伤情况。

巅峰式神经反馈训练提升射击表现效果和无应答者特性分析

为探索神经反馈训练在提升射击表现方面的应用效果和训练过程中的无应答者特性,开展一项用于提升射击表现的神经反馈训练(neurofeedback training for sport performance,SP-NFT)实验研究,招募20名受试者,进行2周4次的“巅峰”范式SP-NFT,采集受试者前、后测隐显目标射击表现和相关脑电(electroencephalograph,EEG)数据,检验SP-NFT对射击表现的提升效果、静息态EEG特征、SP-NFT期间正常组和无应答组EEG特性变化情况。结果表明:受试者后测射击成绩显著高于前测(P<0.01),静息态theta频带功率显著降低(P<0.01);相对正常受试者,无应答者在SP-NFT期间的努力程度更高,theta频段功率和SMR功率的变化程度更低,SP-NFT能够有效提升受试者射击表现,进一步揭示了无应答者的相关生理机制。研究成果为用于提升射击表现的SP-NFT技术进一步发展提供理论支撑和实验证据。

脑电生物反馈结合学习任务训练治疗注意缺陷多动障碍

目的分析脑电生物反馈治疗结合学习任务训练治疗注意缺陷多动障碍(ADHD)患儿临床疗效。方法选取68例注意缺陷多动障碍患儿,随机分为对照组与观察组,各34例。对照组给予脑电生物反馈治疗,观察组给予脑电生物反馈治疗结合学习任务训练治疗,比较2组临床疗效结果。结果观察组临床总有效率(94.12%,32/34)高于对照组(76.47%,26/34)(P<0.05)。治疗后,2组β波均高于治疗前,观察组高于对照组(P<0.05);2组θ波、SMR波均低于治疗前,观察组低于对照组(均P<0.05);2组Conners父母用量表(PSQ)评分低于治疗前,观察组低于对照组(均P<0.05);2组持续性注意力测试指标水平均低于治疗前,观察组低于对照组(均P<0.05)。结论脑电生物反馈治疗结合学习任务训练治疗注意缺陷多动障碍患儿,改善患儿注意力缺陷症状、脑电活动,疗效明显。

基于脑电微状态特征的正常老年人大脑网络特性研究

采用脑电(EEG)微状态方法,分析了94名受试者静息闭眼61通道脑电数据。基于脑电微状态时间序列、微状态转移概率提出微状态变化率与微状态转移熵计算方法,用于评估大脑功能网络动态信息交流特性及其复杂程度。结果显示,2组均得到A、B、C、D这4种经典微状态,相较于青年人,老年人微状态A、B特征及两者之间的转移概率均增加,而微状态C、D特征和微状态变化率以及微状态转移熵均降低。利用线性回归分析发现,脑电微状态特征与大脑内不同节律波能量相关,预示了正常老年人大脑动态特性发生改变,脑网络动态信息交流减弱,可能与老年人大脑内高频信号增加有关。

认知知觉功能障碍训练在男性精神分裂症患者中的应用效果

目的:探讨在男性精神分裂症患者中采取认知知觉功能障碍训练联合脑电生物反馈治疗的作用。方法:采用随机数字表法将2021年9月—2023年9月赣州市第三人民医院收治的精神分裂症患者102例分为两组。对照组(n=51)行脑电生物反馈治疗,观察组(n=51)在脑电生物反馈治疗基础上采取认知知觉功能障碍训练,两组均持续干预1个月。比较两组精神症状、认知功能及社会功能。结果:干预1个月后观察组简明精神病评定量表(BPRS)中激活性、敌对性、缺乏活力、思维障碍、焦虑忧郁评分均较对照组低,差异均有统计学意义(P<0.05);干预1个月后观察组简易精神状态检查量表(MMSE)中定向力、记忆力、回忆能力、语言功能、计算力评分均较对照组高,差异均有统计学意义(P<0.05);干预1个月后观察组住院精神病人社会功能评定量表(SSPI)中动性和交往情况、日常生活能力、社会性活动能力评分均较对照组高,差异均有统计学意义(P<0.05)。结论:认知知觉功能障碍训练配合脑电生物反馈治疗可减轻男性精神分裂症患者精神症状,促进其认识功能提升,有效改善患者社会功能。

左乙拉西坦联合奥卡西平治疗小儿部分性发作癫痫对患儿认知能力及脑电图指标的影响

目的观察左乙拉西坦联合奥卡西平治疗小儿部分性发作癫痫对患儿认知能力及脑电图指标的影响。方法选取2023年3月—2024年5月永州市第三人民医院收治的部分性发作癫痫患儿82例,采用随机数字表法分为观察组和对照组,各41例。对照组单纯予奥卡西平片治疗,观察组在对照组基础上联合左乙拉西坦口服溶液治疗,2组均连续治疗18周。比较2组治疗效果,治疗前及治疗18周后脑电图指标(δ、θ、α、β波段的相对功率)、认知功能[智商(FIQ)、操作智商(PIQ)、言语智商(VIQ)]变化及不良反应。结果观察组患儿治疗总有效率为95.12%,高于对照组的73.17%(χ^(2)=7.405,P=0.007);治疗18周后,2组α、β波段相对功率及FIQ、PIQ、VIQ评分均较治疗前升高,δ、θ波段相对功率较治疗前降低,且观察组高/低于对照组(P均<0.05);观察组与对照组不良反应总发生率(24.39%vs.19.51%)比较差异无统计学意义(χ^(2)=0.285,P=0.594)。结论左乙拉西坦联合奥卡西平治疗小儿部分性发作癫痫效果肯定,对患儿认知能力及脑电图指标均有积极影响,且安全性较高。

脑电生物反馈联合酒石酸唑吡坦片治疗急性缺血性卒中后睡眠障碍临床观察

目的:观察脑电生物反馈联合酒石酸唑吡坦片治疗急性缺血性卒中后睡眠障碍的临床疗效。方法:选取2022年2月1日至2023年8月31日福建省老年医院神经内科收治的急性缺血性卒中后睡眠障碍患者77例作为研究对象进行回顾性调查。根据治疗方案分为对照组(n=42)和观察组(n=35),对照组采用酒石酸唑吡坦片口服治疗,观察组采用脑电生物反馈联合酒石酸唑吡坦片治疗。2组均治疗2周,比较2组干预前后匹兹堡睡眠质量指数(PSQI)评分及睡眠时间、觉醒次数及觉醒时间,并评定临床疗效。结果:治疗后2组PSQI评分、睡眠时间、觉醒次数及觉醒时间均较本组治疗前改善(P<0.05),且观察组治疗后改善优于对照组(P<0.05);观察组总有效率高于对照组(P<0.05)。结论:脑电生物反馈联合酒石酸唑吡坦片显著改善急性缺血性卒中后睡眠质量,疗效肯定。

The modulation of brain functional connectivity with manual acupuncture in healthy subjects:An electroencephalograph case study

Manual acupuncture is widely used for pain relief and stress control.Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions.To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level,we acupuncture at ST36 of a right leg to obtain electroencephalograph（EEG） signals.By coherence estimation,we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states.The resulting synchronization matrices are converted into functional networks by applying a threshold,and the clustering coefficients and path lengths are computed as a function of threshold.The results show that acupuncture can increase functional connections and synchronizations between different brain areas.For a wide range of thresholds,the clustering coefficient during acupuncture and postacupuncture period is higher than that during the pre-acupuncture control period,whereas the characteristic path length is shorter.We provide further support for the presence of ＂small-world＂ network characteristics in functional networks by using acupuncture.These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture,which could contribute to the understanding of the effects of acupuncture on the entire brain,as well as the neurophysiological mechanisms underlying acupuncture.Moreover,the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.

Modulation of electroencephalograph activity by manual acupuncture stimulation in healthy subjects:An autoregressive spectral analysis

To investigate whether and how manual acupuncture（MA） modulates brain activities,we design an experiment where acupuncture at acupoint ST36 of the right leg is used to obtain electroencephalograph（EEG） signals in healthy subjects.We adopt the autoregressive（AR） Burg method to estimate the power spectrum of EEG signals and analyze the relative powers in delta（0 Hz-4 Hz）,theta（4 Hz-8 Hz）,alpha（8 Hz-13 Hz）,and beta（13 Hz-30 Hz） bands.Our results show that MA at ST36 can significantly increase the EEG slow wave relative power（delta band） and reduce the fast wave relative powers（alpha and beta bands）,while there are no statistical differences in theta band relative power between different acupuncture states.In order to quantify the ratio of slow to fast wave EEG activity,we compute the power ratio index.It is found that the MA can significantly increase the power ratio index,especially in frontal and central lobes.All the results highlight the modulation of brain activities with MA and may provide potential help for the clinical use of acupuncture.The proposed quantitative method of acupuncture signals may be further used to make MA more standardized.

Characteristics analysis of acupuncture electroencephalograph based on mutual information Lempel-Ziv complexity

As a convenient approach to the characterization of cerebral cortex electrical information, electroencephalograph （EEG） has potential clinical application in monitoring the acupuncture effects. In this paper, a method composed of the mutual information method and Lempel-Ziv complexity method （MILZC） is proposed to investigate the effects of acupuncture on the complexity of information exchanges between different brain regions based on EEGs. In the experiments, eight subjects are manually acupunctured at ＇Zusanli＇ acupuncture point （ST-36） with different frequencies （i.e., 50, 100, 150, and 200 times/min） and the EEGs are recorded simultaneously. First, MILZC values are compared in general. Then average brain connections are used to quantify the effectiveness of acupuncture under the above four frequencies. Finally, significance index P values are used to study the spatiality of the acupuncture effect on the brain. Three main findings are obtained： （i） MILZC values increase during the acupuncture; （ii） manual acupunctures （MAs） with 100 times/rain and 150 times/min are more effective than with 50 times/min and 200 times/rain; （iii） contralateral hemisphere activation is more prominent than ipsilateral hemisphere＇s. All these findings suggest that acupuncture contributes to the increase of brain information exchange complexity and the MILZC method can successfully describe these changes.

Electroencephalographic Correlates of Psychometry

Berger＇s ＂window on the mind＂ [1] has, with modem computing power, become a possibility. A portable electroencephalograph was used to demonstrate a correlation of personality with brain waves. In principle, this could make it as useful a clinical tool for psychiatrists as the stethoscope is for physicians. Besides clinical use, the method could be a cheap, efficient way of investigating the effects ofpsychopharmaceutical drugs.

Epileptic Encephalopathies in Infants and Children: Study of Clinico-Electroencephalographic Spectrum in a Tertiary Hospital in Bangladesh

Background: The epileptic encephalopathies collectively exact an immense personal, medical, and financial toll on the affected children, their families, and the healthcare system. Objective: This study was aimed to delineate the clinical spectrum of patients with Epileptic encephalopathies (EEs) and classify them under various epileptic syndromes. Methods: This was a cross-sectional study that was carried out in the department of Neurophysiology of the National Institute of Neurosciences and Hospital, Bangladesh from July 2016 to June 2019. Children with recurrent seizures which were difficult to control and associated with developmental arrest or regression in absence of a progressive brain pathology were considered to be suffering from EE. Children under 12 years of age fulfilling the inclusion criteria were enrolled in the study. These patients were evaluated clinically and Electroencephalography (EEG) was done in all children at presentation. Based on the clinical profile and EEG findings the patients were categorized under various epileptic syndromes according to International League Against Epilepsy (ILAE) classification 2010. Results: A total of 1256 children under 12 years of age were referred to the Neurophysiology Department. Among them, 162 (12.90%) fulfilled the inclusion criteria. Most of the patients were male (64.2%) and below 1 year (37.7%) of age. The majority (56.8%) were delivered at the hospital and 40.1% had a history of perinatal asphyxia. Development was age-appropriate before the onset of a seizure in 38.9% of cases. Most (53.7%) of the patients had seizure onset within 3 months of age. Categorization of Epileptic syndromes found that majority had West Syndrome (WS) (37.65%) followed by Lennox-Gastaut syndrome (LGS) (22.22%), Otahara syndrome (11.73%), Continuous spike-and-wave during sleep (CSWS) (5.66%), Myoclonic astatic epilepsy (MAE) (4.94%), Early myoclonic encephalopathy (EME) (3.7%), Dravet syndrome (3.7%) and Landau-Kleffner syndrome (LKS) (1.23%). 9.26% of syndromes were unclassified. Conclusion: EEG was found to be a useful tool in the evaluation of Epileptic encephalopathies. The clinico-electroencephalographic features are age-related. Their recognition and appropriate management are critical.

不同年龄段癫痫患儿的脑电图特征分析

目的:探究不同年龄段癫痫患儿的脑电图特征分析。方法:选择2020年3月—2021年3月赣州市人民医院神经内科脑电生理室收治的72例癫痫患儿作为研究对象,对不同年龄段的患儿进行脑电图监测,分析具体的脑电图特征,及存在的异常情况。结果:8~14岁共36例癫痫患儿,9例正常,27例异常(75.00%);4~8岁共18例癫痫患儿,3例正常,15例异常(83.33%);1~4岁共8例癫痫患儿,1例正常,7例异常(87.50%);2个月~1岁共10例癫痫患儿,1例正常,9例异常(90.00%)。经对比脑电图异常情况,发现不同年龄段患儿,差异无统计学意义(P>0.05);相较于1~14岁癫痫患儿,2个月~1岁的暴发性抑制概率3例(33.33%)显著升高,差异有统计学意义(P<0.05),但是不同年龄段患儿棘波、尖(棘)慢综合波、散发或阵发慢波增多、双侧显著不对称、尖波的异常情况发生率,差异无统计学意义(χ^(2)=0.3750、0.774、0.1846、2.8966、0.0591,P>0.05)。结论:针对神经内科脑电生理室的癫痫患儿,通过脑电图诊断监测的方式,发现不同年龄段患儿异常发生无差异,其中1岁以下患儿较多发暴发性抑制,临床上应当按照脑电图特征等给予针对性的对症干预,临床应用价值较好。

基于CNN-LSTM模型的癫痫脑电信号识别方法

为提高癫痫脑电图(electroencephalography,EEG)信号识别的准确率,提出了一种将一维卷积神经网络(convolutional neural network,CNN)与长短期记忆网络(long short-term memory network,LSTM)相结合的新模型(CNN-LSTM模型)。首先采用3个卷积块来搭建CNN,用于提取EEG序列的局部内在特征;然后利用LSTM学习长期序列依赖关系;最后利用具有Softmax激活函数的全连接神经网络实现癫痫EEG信号的自动识别。采用德国波恩大学癫痫研究室的癫痫数据库中的数据进行实验分析。结果表明,CNN-LSTM模型具有良好的分类性能,平均分类准确率达到99.1%。

基于脑电多视图混合神经网络的时空半监督睡眠分期

睡眠分期是评价睡眠质量的必要基础,现阶段的工作大部分采用全监督学习和单一维度视图信息进行,这不仅需要技师进行大量的睡眠数据标注,还可能因特征提取不充分而导致分期准确率受限的问题.利用半监督学习策略,实现对脑电无标注数据的学习.提出一种多视图混合神经网络,首先用多通道视图时频域机制分别提取时域信号特征和空域信号特征,实现多视图特征提取;再通过注意力机制加强对显著性特征的提取;最后将上述混合特征融合并分类.在三个公开数据集和一个私有数据集中与全监督学习进行了对比评估,半监督学习取得平均准确率为81.0%,卡帕值为73.2%.结果表明,本文模型可以与全监督学习的睡眠分期模型相媲美,同时显著减少技师标注数据的工作量.

利培酮联合脑电生物反馈对精神分裂症患者认知功能、日常行为能力及睡眠脑电活动的影响观察

目的:观察利培酮联合脑电生物反馈治疗精神分裂症的临床疗效,以及对患者认知功能、日常行为能力及睡眠脑电活动的影响。方法:选择本院收治的80例精神分裂症患者为研究对象,按治疗方式不同分为对照组和研究组,每组各40例。对照组予以利培酮治疗,研究组予以利培酮联合脑电生物反馈法治疗。记录两组患者治疗前、治疗6周后临床症状评定[简明精神病量表(BPRS)]、日常行为能力和社会能力[日常生活能力量表(ADL)、社会功能评定量表(SSPI)]、认知功能[简单视觉空间记忆测验(BVMT-R)]及睡眠脑电活动[多导睡眠监测(PSG)]。结果:治疗6周后,两组患者BPRS、ADL、睡眠N1期水平均低于治疗前,且研究组低于对照组(P<0.05);两组患者SSPI、BVMT-R、TST、SE、睡眠N3期水平高于治疗前,除BVMT-R(2)、SE外,研究组均高于对照组(P<0.05)。结论:利培酮联合脑电生物反馈治疗可以帮助精神分裂症患者改善症状,调节患者睡眠质量,有一定临床推广应用价值。

基于多模态特征组合的真实驾驶疲劳状态识别

对驾驶员在驾驶过程中的疲劳状态进行实时准确的预判,可减少由于驾驶疲劳引发的交通事故。首先,通过无线体域网采集了12名驾驶员在真实驾驶过程中的多模态特征,提取了脑电、肌电、呼吸等3种生理信号的特征参数近似熵,其中基于畸变能密度理论(DED)确定肌电信号的采集位置为颈6棘突旁开2 cm处的上斜方肌;然后,通过模糊C聚类方法分析了3种特征参数组合对疲劳状态的反映效果;最后,建立基于马氏距离理论的真实驾驶疲劳判别模型。研究结果表明,驾驶员颈6部位比颈7部位肌电信号的ApEn值显著下降(P<0.05),表明颈6处肌肉比颈7处肌肉对驾驶员的疲劳状态反映更为敏感,实际检测结果与畸变能密度理论计算结果一致,证明了该位置提取肌电信号的正确性和准确性;脑、肌、呼吸这3种生理信号的ApEn值均随驾驶时间的延长呈递减变化,驾驶约90 min时递减趋势变缓,表明驾驶员进入疲劳状态;通过模糊C聚类分析可知,当脑电与肌电ApEn组合时,清醒与疲劳的概率分布界限清晰,可有效反映驾驶疲劳状态;以脑电和肌电近似熵为自变量,基于马氏距离理论建立真实驾驶过程的疲劳判别模型,其测试集准确率达90.92%,表明该模型能够比较准确的判别出驾驶员的疲劳状态。