Electroencephalogram findings in 10 patients with post-stroke epilepsy:A retrospective study

BACKGROUND Post-stroke epilepsy is a common and easily overlooked complication of acute cerebrovascular disease.Long-term seizures can seriously affect the prognosis and quality of life of patients.Electroencephalogram(EEG)is the simplest way to diagnose epilepsy,and plays an important role in predicting seizures and guiding medication.AIM To explore the EEG characteristics of patients with post-stroke epilepsy and improve the detection rate of inter-seizure epileptiform discharges.METHODS From January 2017 to June 2020,10 patients with post-stroke epilepsy in our hospital were included.The clinical,imaging,and EEG characteristics were collected.The stroke location,seizure type,and ictal and interictal EEG manifestations of the patients with post-stroke epilepsy were then retrospectively analyzed.RESULTS In all 10 patients,epileptiform waves occurred in the side opposite to the stroke lesion during the interictal stage;these manifested as sharp wave,sharp-wave complex,or spike discharges in the anterior head lead of the side opposite to the lesion.CONCLUSION In EEG,epileptiform waves can occur in the side opposite to the stroke lesion in patients with post-stroke epilepsy.

Correlation between human seizure-related gene 6 variants and idiopathic generalized epilepsy in a Southern Chinese Han population

This study sought to analyze the genotype and gene mutations of human seizure-related gene 6 in 98 patients with idiopathic generalized epilepsy （non-febrile seizures）, who were selected from three generations of the Chinese Han population living in Shanghai, Zhejiang Province, Wuxi of Jiangsu Province, and Jiangxi Province of Southern China. Twenty-six patients＇ parents were available as a first-degree relatives group and 100 biologically unrelated healthy controls were collected as the control group. Based on the age of onset and seizure type, the patients were divided into six subgroups. Polymerase chain reaction and DNA direct sequencing analysis showed that the most frequent mutations c. 1249dupC （p.Gly418Argfx31 ） and c.1636A 〉 G （p.Thr546Ala） were detected in some idiopathic generalized epilepsy patients and tl^eir asymptomatic first-degree relatives （30.6% vs. 19.2% and 11.2% vs. 26.9%）. A novel mutation c.1807G 〉A （p.Val603Met） was found in a patient with late-onset idiopathic generalized epilepsy. There was no significant difference in the incidence of these three mutations among the different subgroups of idiopathic generalized epilepsy and controls. Thus, further analysis of a larger population is needed to confirm the assumption that human seizure-related gene 6 is a susceptibility gene for idiopathic generalized epilepsy with various sub-syndromes.

Low-frequency repetitive transcranial magnetic simulation prevents chronic epileptic seizure

Although low-frequency repetitive transcranial magnetic simulation can potentially treat epilepsy, its underlying mechanism remains unclear. This study investigated the influence of low-frequency re-petitive transcranial magnetic simulation on changes in several nonlinear dynamic electroenceph-alographic parameters in rats with chronic epilepsy and explored the mechanism underlying repeti-tive transcranial magnetic simulation-induced antiepileptic effects. An epilepsy model was estab-lished using lithium-pilocarpine intraperitoneal injection into adult Sprague-Dawley rats, which were then treated with repetitive transcranial magnetic simulation for 7 consecutive days. Nonlinear elec-electroencephalographic parameters were obtained from the rats at 7, 14, and 28 days post-stimulation. Results showed significantly lower mean correlation-dimension and Kolmogo-rov-entropy values for stimulated rats than for non-stimulated rats. At 28 days, the complexity and point-wise correlation dimensional values were lower in stimulated rats. Low-frequency repetitive transcranial magnetic simulation has suppressive effects on electrical activity in epileptic rats, thus explaining its effectiveness in treating epilepsy.

Hidden Markov model based epileptic seizure detection using tunable Q wavelet transform

Epilepsy is one of the most prevalent neurological disorders affecting 70 million people worldwide.The present work is focused on designing an efficient algorithm for automatic seizure detection by using electroencephalogram(EEG) as a noninvasive procedure to record neuronal activities in the brain.EEG signals' underlying dynamics are extracted to differentiate healthy and seizure EEG signals.Shannon entropy,collision entropy,transfer entropy,conditional probability,and Hjorth parameter features are extracted from subbands of tunable Q wavelet transform.Efficient decomposition level for different feature vector is selected using the Kruskal-Wallis test to achieve good classification.Different features are combined using the discriminant correlation analysis fusion technique to form a single fused feature vector.The accuracy of the proposed approach is higher for Q=2 and J=10.Transfer entropy is observed to be significant for different class combinations.Proposed approach achieved 100% accuracy in classifying healthy-seizure EEG signal using simple and robust features and hidden Markov model with less computation time.The proposed approach efficiency is evaluated in classifying seizure and non-seizure surface EEG signals.The system has achieved 96.87% accuracy in classifying surface seizure and nonseizure EEG segments using efficient features extracted from different J level.

An Efficient Method for Epileptic Seizure Detection in Long-Term EEG Recordings

Epilepsy is one of the most prevalent neurological disorders with no age, racial, social class, and neither national nor geographic boundaries. There are 50 million sufferers in the world today with 2.4 million new cases occur each year. Electroencephalogram (EEG) has become a traditional procedure to investigate abnormal functioning of brain activity. Epileptic EEG is usually characterized by short transients and sharp waves as spikes. Identification of such event splays a crucial role in epilepsy diagnosis and treatment. The present study proposes a method to detect three epileptic spike types in EEG recordings based mainly on Template Matching Algorithm including multiple signal-processing approaches. The method was applied to real clinical EEG data of epileptic patients and evaluated according to sensitivity, specificity, selectivity and average detection rate. The promising results illuminate that hybrid processing approaches in temporal, frequency and spatial domains can be a real solution to identify fast EEG transients.

Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states

Epileptic seizures are known for their unpredictable nature.However,recent research provides that the transition to seizure event is not random but the result of evidence accumulations.Therefore,a reliable method capable to detect these indications can predict seizures and improve the life quality of epileptic patients.Seizures periods are generally characterized by epileptiform discharges with different changes including spike rate variation according to the shapes,spikes,and the amplitude.In this study,spike rate is used as the indicator to anticipate seizures in electroencephalogram(EEG) signal.Spikes detection step is used in EEG signal during interictal,preictal,and ictal periods followed by a mean filter to smooth the spike number.The maximum spike rate in interictal periods is used as an indicator to predict seizures.When the spike number in the preictal period exceeds the threshold,an alarm is triggered.Using the CHB-MIT database,the proposed approach has ensured92% accuracy in seizure prediction for all patients.

Post-stroke seizures in consecutive elderly stroke patients

This prospective study sought to investigate the clinical, radiological and electroencephalographic （EEG） characteristics of seizures in elderly stroke patients, and their outcomes. Over a 2-year study period, 158 consecutive elderly patients with stroke were examined and followed up. Of these patients, 32 （20%） developed seizures, primarily related to stroke, within a follow up period between 5 months and 2 years. Of these 32 cases, 20 experienced infarctions, and 12 experienced hemorrhages. Involvement of cortical regions was detected in most of the patients exhibiting seizures. In these patients, 44% of the lesions involved cortical areas exclusively or in addition to subcortical areas observed on computed tomography （CT） images. Twenty-five patients （78%） developed early seizures （within 2 weeks after stroke）, and half exhibited immediate post-stroke seizures. None of the patients exhibiting early onset seizures developed recurrent seizures or epilepsy, while 57% of late onset seizures （four cases） developed epilepsy. No specific EEG pattems were apparent in those who later developed epilepsy. Overall, early onset seizures after stroke were found to be relatively common, and did not affect outcome. Late onset seizures were less common, but were associated with chronic epilepsy.

Effects of febrile seizures in mesial temporal lobe epilepsy with hippocampal sclerosis on gene expression using bioinformatical analysis

Background:To investigate the effect of long-term febrile convulsions on gene expression in mesial temporal lobe epilepsy with hippocampal sclerosis(MTLE-HS)and explore the molecular mechanism of MTLE-HS.Methods:Microarray data of MTLE-HS were obtained from the Gene Expression Omnibus database.Differentially expressed genes(DEGs)between MTLE-HS with and without febrile seizure history were screened by the GEO2R software.Pathway enrichment and gene ontology of the DEGs were analyzed using the DAVID online database and FunRich software.Protein–protein interaction(PPI)networks among DEGs were constructed using the STRING database and analyzed by Cytoscape.Results:A total of 515 DEGs were identified in MTLE-HS samples with a febrile seizure history compared to MTLEHS samples without febrile seizure,including 25 down-regulated and 490 up-regulated genes.These DEGs were expressed mostly in plasma membrane and synaptic vesicles.The major molecular functions of those genes were voltage-gated ion channel activity,extracellular ligand-gated ion channel activity and calcium ion binding.The DEGs were mainly involved in biological pathways of cell communication signal transduction and transport.Five genes(SNAP25,SLC32A1,SYN1,GRIN1,and GRIA1)were significantly expressed in the MTLE-HS with prolonged febrile seizures.Conclusion:The pathogenesis of MTLE-HS involves multiple genes,and prolonged febrile seizures could cause differential expression of genes.Thus,investigations of those genes may provide a new perspective into the mechanism of MTLE-HS.

基于人工智能的癫痫发作预测研究综述

癫痫属于神经系统疾病,反复发作和持久倾向将导致机体损伤,因此提前发现癫痫发作有助提升患者的生活质量。为了全面且深入地探究人工智能在预测癫痫发作方面的研究进展及趋势,首先介绍了目前常用的预测癫痫的脑电公开数据集、评价指标和预处理技术,其次将基于人工智能的癫痫发作预测研究划分为基于机器学习和基于深度学习两类,并分别进行分析。分析结果显示,基于深度学习的癫痫发作预测,准确率能达到95%以上。基于以上研究结果得出人工智能应用于癫痫发作预测具有良好的发展前景。

难治性顶叶癫痫患者的临床影像学与神经电生理特点分析

目的探讨难治性顶叶癫痫(PLE)患者的临床影像学与神经电生理特点。方法回顾性分析2021年1月至2023年2月在香港大学深圳医院癫痫中心接受术前评估及手术治疗的9例难治性PLE患者的病历资料,收集患者的人口学、临床症状、脑电图(EEG)、头颅核磁共振(MRI)、正电子发射型计算机断层显像(PET-CT)扫描结果及临床结局等信息,并进行系统分析。结果9例难治性PLE患者的男女比为5∶4,其中6例有失空间感、头晕等先兆症状,其最常见的首发症状分别是愣神和单侧肢体运动。发作间期EEG示,4例患者出现2种形式的放电,即局灶性放电和全导联广泛性尖/棘波/棘慢复合波。尖棘波放电最显著的部位最常出现在双颞区或单侧颞区电极有6例,其次是全导联广泛性棘慢波放电有4例,其后依次是单侧顶枕区、一侧半球等。发作期EEG示,8例为单侧颞叶或单侧顶叶起源,1例患者起源不明。5例MRI为阴性,2例为软化灶,1例为顶叶占位,1例为左侧缘上回皮层增厚。PET-CT结果显示7例为双侧或单侧顶区低代谢。8例行立体定向脑电图(SEEG)植入,1例行硬膜下电极植入。9例中有8例患者接受了热凝毁损术,其中3例患者接受了致痫灶切除,术后病理结果提示分别为中心性血管性胶质瘤、胚胎发育不良性神经上皮肿瘤及致痫灶。9例患者术后疗效均为EngelⅠ级。结论难治性PLE的症状学致痫灶定位特征弱,单纯依靠头皮EEG易误诊,需要结合头颅MRI、PET-CT、颅内EEG及MDT讨论来综合定位致痫灶。经过多学科合作、应用多项技术手段综合定位后,对难治性PLE患者实施手术疗效较好。

Generation of Febrile Seizures and Subsequent Epileptogenesis

Febrile seizures（FSs） occur commonly in children aged from 6 months to 5 years. Complex（repetitive or prolonged） FSs, but not simple FSs, can lead to permanent brain modification. Human infants and immature rodents that have experienced complex FSs have a high risk of subsequent temporal lobe epilepsy. However, the causes of FSs and the mechanisms underlying the subsequent epileptogenesis remain unknown. Here, we mainly focus on two major questions concerning FSs： how fever triggers seizures, and how epileptogenesis occurs after FSs. The risk factors responsible for the occurrence of FSs and the epileptogenesis after prolonged FSs are thoroughly summarized and discussed. An understanding of these factors can provide potential therapeutic targets for the prevention of FSs and also yield biomarkers for identifying patients at risk of epileptogenesis following FSs.

Gender difference in acquired seizure susceptibility in adult rats after early complex febrile seizures

Gender differences are involved in many neurological disorders including epilepsy. However, little is known about the effect of gender difference on the risk of epilepsy in adults with a specific early pathological state such as complex febrile seizures（FSs） in infancy. Here we used a well-established complex FS model in rats and showed that：（1） the susceptibility to seizures induced by hyperthermia, pentylenetetrazol（PTZ）, and maximal electroshock（MES） was similar in male and female rat pups, while males were more susceptible to PTZ- and MES-induced seizures than age-matched females in normal adult rats;（2） adult rats with complex FSs in infancy acquired higher seizure susceptibility than normal rats; importantly, female FS rats were more susceptible to PTZ and MES than male FS rats; and（3） the protein expression of interleukin-1β, an infl ammatory factor associated with seizure susceptibility, was higher in adult FS females than in males, which may reflect a gender-difference phenomenon of seizure susceptibility. Our results provide direct evidence that the acquired seizure susceptibility after complex FSs is gender-dependent.

Brain Rattled, Heart Shackled: Ictal Asystole in a Patient without Prior History of Epilepsy or Arrhythmia

We present a case of ictal asystole in an 81-year-old female, with no prior history of epileptic activity, or cardiac history suggestive of arrhythmia, who suffered several seemingly unrelated epileptic and asystolic episodes prior to finally having a witnessed seizure followed by an asystolic event. Following this event, all atrioventricular (AV) nodal blockers, and medications with potential seizure threshold lowering activity were stopped, and anti-epileptic medication was optimized. Due to the wishes of the patient’s family, no invasive interventions were pursued.However, the patient continued to be medically treated with anti-epileptic therapy and had no further asystolic events. Unfortunately, the patient’s overall clinical status deteriorated, and she subsequently passed during her hospital stay after being made do not resuscitate and do not intubate (DNR/DNI) by the family and then subsequently comfort care. Prior to her passing, however, she had remained free of epileptic events for 10 days and free of asystolic events for 21 days.

检测脑电癫痫的多头自注意力机制神经网络

癫痫是一种危及生命且具有挑战性的神经系统疾病,目前基于脑电图(EEG)的癫痫检测方法依然存在很多挑战,脑电图信号是不稳定的,不同的病人表现出的癫痫发作模式不同,检测脑电信号耗时费力,不仅会给医务人员带来沉重的负担,还容易造成误检情况的发生。因此,研究高效的跨多患者的癫痫自动检测技术是非常有必要的。提出了一种基于多头自注意力机制神经网络的癫痫脑电检测方法(CABLNet),利用卷积层捕获脑电时序信号的短期时间模式和各通道之间的局部依赖关系,使用多头自注意力机制进一步捕获具有时序关系的短期时间模式特征向量的长距离依赖关系和时间动态相关性,将上下文表示送入双向长短时记忆网络(BiLSTM)提取前后方向的信息,用logsoftmax函数进行训练和分类。实验使用CHB-MIT头皮脑电数据库数据,灵敏度、特异性、准确率、F1-score分别为96.18%、97.04%、96.61%、96.59%,结果表明,提出的方法优于现有方法,在癫痫检测性能方面有显著提高,对癫痫的辅助诊断具有重要意义。

高热惊厥患儿额颞叶区脑电图特点与癫痫的发生及神经发育不良的关系

目的:探讨高热惊厥(FS)患儿额颞叶区脑电图特点与癫痫的发生及神经发育不良的关系。方法:将我院2017年1月-2019年12月间收治的100例符合入组标准的FS患儿分为EEG正常组和EEG异常组。所有患者均在入组后采用脑电图仪进行EEG检查;随访1年,详细记录癫痫情况,参照《中国修订韦氏儿童智力量表手册》认知功能评定标准对患儿的神经发育功能进行评估。结果:EEG正常组和EEG异常组两组患儿性别、热性惊厥持续时间、热性惊厥再发次数、热性惊厥再发、惊厥类型、热性惊厥家族病史、发病年龄、癫痫家族病史例等临床资料无明显差异(P>0.05);癫痫组FS患儿EEG异常发生率明显高于无癫痫组,差异有统计学意义(P<0.05);神经发育不良组FS患儿EEG异常发生率明显高于神经发育正常组,差异有统计学意义(P<0.05);EEG异常与FS患儿癫痫和神经发育不良均存显著正相关关系(P<0.05);EEG异常是影响FS患儿癫痫和神经发育不良发生的独立性威胁因素(P<0.05)。结论:高热惊厥患儿额颞叶区脑电图异常与癫痫和神经发育不良均存显著正相关关系,且是影响FS患儿癫痫和神经发育不良发生的独立性威胁因素。

儿童热性惊厥遗传学研究进展

热性惊厥是婴幼儿时期最常见的疾病之一,部分热性惊厥患儿在疾病后期进展为癫痫。目前热性惊厥的发病机制尚不明确,近年来研究显示,热性惊厥具有明显的家族遗传倾向,其发病与钠离子通道基因、钾离子通道基因、氯离子通道基因、细胞因子基因、富含脯氨酸的跨膜蛋白2基因、突触融合蛋白1B基因的突变相关。

26例儿童发热感染相关性癫痫综合征的脑电图分析

目的探讨儿童发热感染相关性癫痫综合征(febrile infection-related epilepsy syndrome,FIRES)的脑电图特征及演变,有助于该病的诊治。方法回顾性分析2017年5月-2021年12月收治的26例FIRES患儿的临床资料。结果26例(100%)患儿病初均有发热,病程早期出现抽搐,很快演变为惊厥持续状态,22例(85%)需要呼吸机辅助通气。全部患儿急性期脑电图正常背景活动消失,发作间期为弥漫性慢波和多灶性棘慢波;发作期表现为游走性局灶性低波幅快节律起始的特征性发作模式。慢性期脑电图背景活动逐渐恢复,异常波相对局限;发作期表现为局灶性慢波节律起始的图形。4例(15%)患儿监测到极度δ刷。结论FIRES患儿的急性期、慢性期脑电图存在特征性表现,对疾病诊断和分期有一定提示意义。极度δ刷可能是FIRES患儿特征性标志之一。

NSE、HMGB1、H2S联合检测在重症热性惊厥伴癫痫患儿中的诊断价值

目的探讨血清神经元特异性烯醇化酶(NSE)、高迁移率族蛋白B1(HMGB1)与硫化氢(H_(2)S)联合检测在重症热性惊厥伴癫痫患儿中的诊断价值。方法选择2020年2月—2022年3月于广安市人民医院收治的102例重症热性惊厥患儿作为观察组,将所有患儿依照半年随访是否出现癫痫分为癫痫组43例和非癫痫组59例,同期选择50例健康体检者作为对照组。比较各组血清NSE、HMGB1与H_(2)S水平。采用Logistic回归模型分析多指标联合应用预测继发癫痫的联合应用模型,并绘制工作者受试特征曲线分析各指标单独及联合应用预测患者癫痫发作的价值。结果观察组血清NSE和HMGB1水平均高于对照组,H_(2)S水平低于对照组,差异有统计学意义(P<0.05)。癫痫组血清NSE和HMGB1水平均高于非癫痫组,H_(2)S水平低于非癫痫组,差异有统计学意义(P<0.05)。NSE、HMGB1、H_(2)S联合应用预测重症热性惊厥患儿癫痫发作的模型为Log(P)=0.653×NSE+0.619×HMGB1-0.638×H_(2)S+0.839。各指标联合应用预测重症热性惊厥患儿癫痫发作的AUC均高于各指标单独应用,差异有统计学意义(P<0.05)。结论重症热性惊厥患儿血清NSE、HMGB1与H_(2)S水平呈现明显的异常状态,且3项指标联合应用具有较高预测患者癫痫发作的价值。

热性惊厥儿童脑电图特点及异常部位对后期癫痫发生的影响

目的:研究热性惊厥儿童脑电图特点及异常部位对后期癫痫发生的影响。方法:选取河南大学淮河医院2018年1月至2022年6月收治的116例热性惊厥儿童作为研究对象。脑电图检查正常儿童76例(脑电图正常组),脑电图异常儿童40例(脑电图异常组)。比较脑电图正常及异常儿童临床病理因素,分析不同部位脑电图异常儿童的癫痫发生率。结果:两组热性惊厥儿童脑电图表现在性别、年龄、热性惊厥家族史、惊厥类型上比较,差异无统计学意义(P>0.05);两组热性惊厥儿童在热性惊厥持续时间、热性惊厥再发次数、初次发作年龄、热性惊厥表现上比较,差异具有统计学意义(P<0.05),脑电图异常组热性惊厥儿童热性惊厥持续时间、热性惊厥再发次数及全身抽搐比例显著高于脑电图正常组儿童,差异具有统计学意义(P<0.05),初次发作年龄显著低于脑电图正常组儿童,差异具有统计学意义(P<0.05)。40例脑电图异常热性惊厥儿童中弥漫性异常23例(57.5%)、额颞叶区异常8例(20.0%)及顶枕叶区异常9例(22.5%),弥漫性异常显著高于额颞叶区及顶枕叶区,差异具有统计学意义(P<0.05)。本组116例热性惊厥儿童中癫痫患儿14例(12.1%),均发生在脑电图异常组儿童,脑电图额颞叶区异常儿童癫痫发生率显著高于弥漫性异常及顶枕叶区异常儿童,差异具有统计学意义(P<0.05)。结论:热性惊厥儿童脑电图异常与热性惊厥持续时间、热性惊厥再发次数、初次发作年龄、热性惊厥表现有关,脑电图额颞叶区异常儿童癫痫发生率显著升高,临床上对脑电图额颞叶区异常儿童应密切监测以改善其预后。

热性惊厥患儿视频脑电图特点及其与预后的关系探究

目的:探究热性惊厥(FS)患儿视频脑电图(VEEG)特点及其与预后的关系。方法:回顾性分析2019年1月-2021年1月收治的78例FS患儿,分为预后良好组与预后不良组,采用Logistic回归分析探究FS患儿VEEG与预后的关系。结果:两组发作类型、持续时间、发作次数、VEEG类型比较差异具有统计学意义(P<0.05);多因素Logistic回归模型显示:VEEG类型:PPMD、异常为患儿预后不良的影响因素(P<0.05)。结论:VEEG表现为PPMD、异常为FS患儿预后不良的影响因素,临床应针对性干预以减少其遗留神经系统并发症发生情况。