精神分裂症患者的自发脑电地形图

对32例精神分裂症及40例正常对照者的 BEAM—EEG 各脑区各频域的功率值作了分析。显著性概率图显示精神分裂症的脑电功率值在额、中央、颞、顶及枕等7个脑区,都有0频域功率增加,α和β频域功率减少。     

精神分裂症阴性阳性症状的脑电地形图

本研究表明,除阴性和阳性症状 BEAM 改变的共同点外,阴性症状组的δ功率增强范围更大,0峰值频率显著偏慢,后侧α功率降低更甚,F_3、C_3区θ/α值升高更著。阳性症状组α功率前移,β和α对称性指数明显降低。     

肺癌性脑损害患者的脑电地形图分析

本文报道６３例肺癌患者脑损害的临床表现，头颅ＣＴ、ＥＥＧ和ＢＥＡＭ检查结果，其中３１例出现肺癌性非转移性脑损害；３２例发现脑转移，分子了肺癌脑损害的脑电变化特点。结果表明，头颅ＣＴ可以确定脑转移病灶的存在，ＥＥＧ和ＢＥＡＭ既可显示肺癌脑转移病灶的脑电变化，还可显示非转移性肺癌性脑损害的存在。     

氯氮平治疗中脑电图与脑电地形图的改变

精神药物可以引起脑电活动改变,国内外屡有报道而有关精神药物对脑电地形图(BEAM)的影响则报道甚少。本文就94例精神分裂症患者服用氯氮平治疗前后的脑电地形图以及同步描记的脑电图(EEG)变化进行了对比研究。材料与方法所有94例患者均符合 CCMD—2精神分裂症标准。其中男性61例,女性33例。年龄     

脑电地形图在神经科中的应用

本文着重对70年代发展起来的新型成像技术——脑电地形图对癲痫、颅内占位病变以及脑血管病进行了临床应用的评价.并对其概念及基本原理、脑电图α节律起步点研究作了简要的介绍.认为在当今医学科学技术迅速发展的年代,脑电地形图仍不失为研究脑部功能病变的一种无创伤性、直观性的最佳手段之一.     

Interictal epileptiform discharges vary across age groups

ObjectiveTo investigate whether the occurrence and morphology of interictal epileptiform discharges (IEDs) in scalp-EEG change by age.Methods10,547 patients who had a standard or sleep deprived EEG recording reported using the SCORE standard were included. 875 patients had at least one EEG with focal IEDs. Focal IED morphology was analyzed by age using quantitative measures in EEGLAB and by visual classification based on the SCORE standard. We present distributions of IED measures by age group, with medians, interquartiles, 5th and 95th percentiles.ResultsFocal IEDs occurred most frequently in children and elderly. IED morphology and localization depended on age (p < 0.001). IEDs had higher amplitudes, sharper peaks, larger slopes, shorter durations, larger slow-wave areas and wider distributions in children. These morphological characteristics diminished and the IEDs became more lateralized with increasing age. Spike asymmetry was stable across all age groups.ConclusionsIEDs have age-dependent characteristics. A spike detector, human or computer, should not operate with the same set of thresholds for patients at various age. With increasing age, focal IEDs are less sharp, have lower amplitudes, have less prominent slow-waves and they become more lateralized. Our findings can help EEG readers in detecting and correctly describing IEDs in patients of various age.SignificanceEEG readers should always consider patient age when interpreting interictal epileptiform discharges.     

Risk for developing epilepsy and epileptiform discharges on EEG in patients with febrile seizures

Purpose: The aim of the present study was to investigate the correlation between epileptiform discharges on EEGs after febrile seizures and the prognosis of patients in terms of the development of epilepsy and recurrence of febrile seizures. This study also evaluated the characteristics of epileptiform discharges and EEG changes on follow-up examination. Methods: This study consisted of 36 children who presented to our hospital with febrile seizures and whose electroencephalograms (EEG) showed epileptiform discharges. The development of epilepsy and the recurrence of febrile seizures were compared between the study group (n = 36) and the control group (n = 87), which included children with febrile seizure but with normal EEG findings. Results: No significant correlation was detected between the recurrence rate of febrile seizures in patients with normal EEG (23 out of 87, 26.4%) findings and that of patients whose EEGs showed epileptiform discharges (12 out of 36, 33.3%) [adjusted OR 0.67 (0.26–1.68)]. However, 9 (25.0%) out of 36 patients with epileptiform discharges on EEG had epilepsy compared to 2 patients (2.3%) in the control group. The correlation was statistically significant [crude OR 10.88 (2.47–47.88) and adjusted OR 8.75 (1.49–51.6)]. Conclusion: Epileptiform discharges on the EEGs of patients with febrile seizures are important predictive risk factors of the development of epilepsy.     

Deep learning for detection of focal epileptiform discharges from scalp EEG recordings

Objective

Visual assessment of the EEG still outperforms current computer algorithms in detecting epileptiform discharges. Deep learning is a promising novel approach, being able to learn from large datasets. Here, we show pilot results of detecting epileptiform discharges using deep neural networks.

临床下痫样放电对青少年癫痫患者认知功能影响的研究

目的探讨临床下痛样放电对青少年癫痫患者认知功能的影响。方法以全身强直阵挛性发作（GTCS）为临床表现的特发性癫痫患者65例,无临床发作均超过3个月,其中35例动态脑电图或普通脑电图显示有痫样放电,30例患者动态脑电图均正常。65例患者均服用左乙拉西坦治疗,随访6个月,服药前后分别进行基本认知能力测试,分析两组患者6个月前后认知功能的变化。结果63例完成本实验,两组实验前后IQ均在正常范围且差异不明显。但6个月后有痛样放电组认知功能明显下降（P〈0．01）,具体表现在数字鉴别（P〈0．01）、汉字快速比较（P〈0．01）、汉字旋转（P〈0．01）、图形再认（P〈0．01）等方面,而脑电图正常组认知功能无明显变化（P〉0．05）。结论临床下痫样放电可损害患者的认知能力,应受到重视,采取适当的干预措施。     

EEG autoregressive modeling analysis: A diagnostic tool for patients with epilepsy without epileptiform discharges

ObjectiveNumerous types of nonepileptic paroxysmal events, such as syncopes and psychogenic nonepileptic seizures, may imitate epileptic seizures and lead to diagnostic difficulty. Such misdiagnoses may lead to inappropriate treatment in patients that can considerably affect their lives. Electroencephalogram (EEG) is a commonly used tool in assisting diagnosis of epilepsy. Although the appearance of epileptiform discharges (EDs) in EEG recordings is specific for epilepsy diagnosis, only 25%–56% of patients with epilepsy show EDs in their first EEG examination.MethodsIn this study, we developed an autoregressive (AR) model prediction error–based EEG classification method to distinguish EEG signals between controls and patients with epilepsy without EDs. Twenty-three patients with generalized epilepsy without EDs in their EEG recordings and 23 age-matched controls were enrolled. Their EEG recordings were classified using AR model prediction error–based EEG features.ResultsAmong different classification methods, XGBoost achieved the highest performance in terms of accuracy and true positive rate. The results showed that the accuracy, area under the curve, true positive rate, and true negative rate were 85.17%, 87.54%, 89.98%, and 81.81%, respectively.ConclusionsOur proposed method can help neurologists in the early diagnosis of epilepsy in patients without EDs and might help in differentiating between nonepileptic paroxysmal events and epilepsy.SignificanceEEG AR model prediction errors could be used as an alternative diagnostic marker of epilepsy.     

Isolation of epileptiform discharges from unaveraged EEG by independent component analysis.

OBJECTIVE: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different waveforms and spatial distributions. METHODS: The separation employs independent component analysis (ICA) and is not based on any assumption regarding generator model. A simulation study was performed by generating ten EEG data matrices by computer: each matrix included real background activity from a normal subject to which was added an array of simulated unaveraged EDs. Each discharge was a summation of two transients having slightly different potential field distributions and small jitters in time and amplitude. Real EEG data were also obtained from three epileptic patients. RESULTS: Through ICA, we could isolate the two epileptiform transients in every simulation matrix, and the retrieved transients were almost identical as the originals, especially in their spatial distributions. Two epileptic components were isolated by ICA in all patients. Each estimated epileptic component had a consistent time course. CONCLUSION: ICA appears promising for the separation of unaveraged spikes from the EEG background and their decomposition in independent spatio-temporal components.     

Periodic lateralized epileptiform discharges in neurosyphilis

We report two patients of neurosyphilis with periodic lateralized epileptiform discharges (PLEDs) in the EEG. Patient 1, a 32-yr-old man manifested with rapidly progressive cognitive decline and abnormal behavior and recurrent generalized tonic-clonic seizures. EEG revealed periodic epileptiform discharges arising from the anterior temporal and frontal region, predominantly from the right. Diffusion weighted MRI of brain did not show any focal restricted diffusion. Patient 2, a 33-yr-old woman presented with 2-year history of behavioral abnormalities, generalized tonic-clonic seizures and unconcerned urinary incontinence. EEG revealed PLEDS arising from the left anterior temporal region. Her CT scan showed gross cerebral atrophy. Both the patients improved partially with treatment and PLEDs resolved completely. PLEDs may be recorded in EEG of patients with neurosyphilis without imageological evidence of focal cerebral lesion.     

Hemodynamic correlates of epileptiform discharges: an EEG-fMRI study of 63 patients with focal epilepsy

Using continuous EEG-correlated fMRI, we investigated the Blood Oxygen Level Dependent (BOLD) signal correlates of interictal epileptic discharges (IEDs) in 63 consecutively recruited patients with focal epilepsy. Semi-automated spike detection and advanced modeling strategies are introduced to account for different EEG event types, and to minimize false activations from uncontrolled motion. We show that: (1) significant hemodynamic correlates were detectable in over 68% of patients in whom discharges were captured and were highly, but not entirely, concordant with site(s) of presumed seizure generation where known; (2) deactivations were less concordant and may non-specifically reflect the consequential or downstream effects of IEDs on brain activity; (3) a striking pattern of retrosplenial deactivation was observed in 7 cases mainly with focal discharges; (4) the basic hemodynamic response to IEDs is physiological; (5) incorporating information about different types of IEDs, their durations and saturation effects resulted in more powerful models for the detection of fMRI correlates; (6) focal activations were more likely when there was good electroclinical localization, frequent stereotyped spikes, less head motion and less background EEG abnormality, but were also seen in patients in whom the electroclinical focus localization was uncertain. These findings provide important new information on the optimal use and interpretation of EEG-fMRI in focal epilepsy and suggest a possible role for EEG-fMRI in providing new targets for invasive EEG monitoring.     

Effects of two different cycles of vagus nerve stimulation on interictal epileptiform discharges

PURPOSE: To evaluate the effects of two cycles of vagus nerve stimulation (VNS), 30 s/5 min and 7 s/18 s on the interictal epileptiform discharges (IEDs). METHODS: Twenty patients were studied, 12 with generalized and 8 with partial seizures. An EEG of 120 channels was performed during 3 different conditions, each one lasting 30 min: basal state (BS), 30 s/5 min and 7 s/18 s VNS cycles. The number and duration of IEDs, time of IEDs in 1 min (TIEDM), IEDs/NIEDs index and the spike-free period (SFP) were determined. RESULTS: In 16 patients (80%), IED decreased during 30 s/5 min cycle (Group 1) and increased in 4 (Group 2). In Group 1, during the 30 s/5 min cycle the following variables showed a decrease: TIEDM, from 12.64 s to 9.62 s (p=0.001); IED/NIED index, from 0.53 to 0.31 (p=0.021), and IED duration, from 1.57 s to 1.05 s (p=0.015); whereas SFP duration increased from 20.06 s to 37.73 s (p=0.008). The decrease in IED was 41% and the increase in SFP 88%. In the 7s/18s cycle, only SFP had an increase, 72% (p<0.043). In Group 2, an increase in IED during both cycles was found. In the 30 s/5 min cycle, TIEDM increased 56% (p=0.042) and IED/NIED index 259% (p=0.040). CONCLUSION: VNS modifies IED in an acute form, in 80% of patients the 30 s/5 min cycle decreases the epileptiform activity and it is not modified by 7 s/18 s cycle. In 20% of patients, both cycles increase the epileptiform activity.     

Intracranial EEG-fMRI analysis of focal epileptiform discharges in humans

Purpose: Combining intracranial electroencephalography (iEEG) with functional magnetic resonance imaging (fMRI) is of interest in epilepsy studies as it would allow the detection of much smaller interictal epileptiform discharges than can be recorded using scalp EEG‐fMRI. This may help elucidate the spatiotemporal mechanisms underlying the generation of interictal discharges. To our knowledge, iEEG‐fMRI has never been performed at 3 Tesla (3T) in humans. We report our findings relating to spike‐associated blood oxygen level–dependent (BOLD) signal changes in two subjects. Methods: iEEG‐fMRI at 3T was performed in two subjects. Twelve channels of iEEG were recorded from subdural strips implanted on the left posterior temporal and middle frontal lobes in a 20‐year‐old female with bilateral periventricular gray matter heterotopia. Twenty channels of iEEG were recorded bilaterally from two subdural strips laid anterior–posterior along mesial temporal surfaces in a 29‐year‐old woman with bilateral temporal seizures and mild left amygdalar enlargement on MRI. Functional MRI (fMRI) statistical maps were generated and thresholded at p = 0.01. Key Findings: No adverse events were noted. A total of 105 interictal discharges were recorded in the posterior middle temporal gyrus of Subject 1. In Subject 2, 478 discharges were recorded from both mesial temporal surfaces (n = 194 left, 284 right). The right and left discharges were modeled separately, as they were independent. Subject 1 showed spike‐associated BOLD signal increases in the left superior temporal region, left middle frontal gyrus, and right parietal lobe. BOLD decreases were seen in the right frontal and parietal lobes. In Subject 2, BOLD signal increases were seen in both mesial temporal lobes, which when left and right spikes were modeled independently, were greater on the side of the discharge. In addition, striking BOLD signal decreases were observed in the thalamus and posterior cingulate gyrus. Significance: iEEG‐fMRI can be performed at 3T with low risk. Notably, runs of only 5 or 10 min of EEG‐fMRI were performed as part of our implementation protocol, yet a significant number of epileptiform discharges were recorded, allowing meaningful analyses. With these studies, we have shown that deactivation can be seen in individual subjects with focal epileptiform discharges. These preliminary observations suggest a novel mechanism through which focal interictal discharges may have widespread cortical and subcortical influences.