Prediction of rhythmic and periodic EEG patterns and seizures on continuous EEG with early epileptiform discharges.

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Koren, J; Herta, J; Draschtak, S; Pötzl, G; Pirker, S; Fürbass, F; Hartmann, M; Kluge, T; Baumgartner, C

2015-08-01

Continuous EEG (cEEG) is necessary to document nonconvulsive seizures (NCS), nonconvulsive status epilepticus (NCSE), as well as rhythmic and periodic EEG patterns of 'ictal-interictal uncertainty' (RPPIIU) including periodic discharges, rhythmic delta activity, and spike-and-wave complexes in neurological intensive care patients. However, cEEG is associated with significant recording and analysis efforts. Therefore, predictors from short-term routine EEG with a reasonably high yield are urgently needed in order to select patients for evaluation with cEEG. The aim of this study was to assess the prognostic significance of early epileptiform discharges (i.e., within the first 30 min of EEG recording) on the following: (1) incidence of ictal EEG patterns and RPPIIU on subsequent cEEG, (2) occurrence of acute convulsive seizures during the ICU stay, and (3) functional outcome after 6 months of follow-up. We conducted a separate analysis of the first 30 min and the remaining segments of prospective cEEG recordings according to the ACNS Standardized Critical Care EEG Terminology as well as NCS criteria and review of clinical data of 32 neurological critical care patients. In 17 patients with epileptiform discharges within the first 30 min of EEG (group 1), electrographic seizures were observed in 23.5% (n = 4), rhythmic or periodic EEG patterns of 'ictal-interictal uncertainty' in 64.7% (n = 11), and neither electrographic seizures nor RPPIIU in 11.8% (n = 2). In 15 patients with no epileptiform discharges in the first 30 min of EEG (group 2), no electrographic seizures were recorded on subsequent cEEG, RPPIIU were seen in 26.7% (n = 4), and neither electrographic seizures nor RPPIIU in 73.3% (n = 11). The incidence of EEG patterns on cEEG was significantly different between the two groups (p = 0.008). Patients with early epileptiform discharges developed acute seizures more frequently than patients without early epileptiform discharges (p = 0.009). Finally, functional

SCOPE-mTL: A non-invasive tool for identifying and lateralizing mesial temporal lobe seizures prior to scalp EEG ictal onset.

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Lam, Alice D; Maus, Douglas; Zafar, Sahar F; Cole, Andrew J; Cash, Sydney S

2017-09-01

In mesial temporal lobe (mTL) epilepsy, seizure onset can precede the appearance of a scalp EEG ictal pattern by many seconds. The ability to identify this early, occult mTL seizure activity could improve lateralization and localization of mTL seizures on scalp EEG. Using scalp EEG spectral features and machine learning approaches on a dataset of combined scalp EEG and foramen ovale electrode recordings in patients with mTL epilepsy, we developed an algorithm, SCOPE-mTL, to detect and lateralize early, occult mTL seizure activity, prior to the appearance of a scalp EEG ictal pattern. Using SCOPE-mTL, 73% of seizures with occult mTL onset were identified as such, and no seizures that lacked an occult mTL onset were identified as having one. Predicted mTL seizure onset times were highly correlated with actual mTL seizure onset times (r=0.69). 50% of seizures with early mTL onset were lateralizable prior to scalp ictal onset, with 94% accuracy. SCOPE-mTL can identify and lateralize mTL seizures prior to scalp EEG ictal onset, with high sensitivity, specificity, and accuracy. Quantitative analysis of scalp EEG can provide important information about mTL seizures, even in the absence of a visible scalp EEG ictal correlate. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

EEG features of absence seizures in idiopathic generalized epilepsy: Impact of syndrome, age, and state

DEFF Research Database (Denmark)

Sadleir, L.G.; Scheffer, I.E.; Smith, S.

2009-01-01

Purpose: Factors influencing the electroencephalography (EEG) features of absence seizures in newly presenting children with idiopathic generalized epilepsy (IGE) have not been rigorously studied. We examined how specific factors such as state, provocation, age, and epilepsy syndrome affect the EEG...... features of absence seizures. Methods: Children with untreated absence seizures were studied using video-EEG recording. The influence of state of arousal, provocation (hyperventilation, photic stimulation), age, and epilepsy syndrome on specific EEG features was analyzed. Results: Five hundred nine...... seizures were evaluated in 70 children with the following syndromes: childhood absence epilepsy (CAE) 37, CAE+ photoparoxysmal response (PPR) 10, juvenile absence epilepsy (JAE) 8, juvenile myoclonic epilepsy (JME) 6, and unclassified 9. Polyspikes occurred in all syndromes but were more common in JME...

Presurgical EEG-fMRI in a complex clinical case with seizure recurrence after epilepsy surgery

Directory of Open Access Journals (Sweden)

Zhang J

2013-07-01

Full Text Available Jing Zhang,1 Qingzhu Liu,2 Shanshan Mei,2 Xiaoming Zhang,2 Xiaofei Wang,2 Weifang Liu,1 Hui Chen,1 Hong Xia,1 Zhen Zhou,1 Yunlin Li2 1School of Biomedical Engineering, Capital Medical University, Beijing, People's Republic of China; 2Department of Functional Neurology and Neurosurgery, Beijing Haidian Hospital, Beijing, People's Republic of China Abstract: Epilepsy surgery has improved over the last decade, but non-seizure-free outcome remains at 10%–40% in temporal lobe epilepsy (TLE and 40%–60% in extratemporal lobe epilepsy (ETLE. This paper reports a complex multifocal case. With a normal magnetic resonance imaging (MRI result and nonlocalizing electroencephalography (EEG findings (bilateral TLE and ETLE, with more interictal epileptiform discharges [IEDs] in the right frontal and temporal regions, a presurgical EEG-functional MRI (fMRI was performed before the intraoperative intracranial EEG (icEEG monitoring (icEEG with right hemispheric coverage. Our previous EEG-fMRI analysis results (IEDs in the left hemisphere alone were contradictory to the EEG and icEEG findings (IEDs in the right frontal and temporal regions. Thus, the EEG-fMRI data were reanalyzed with newly identified IED onsets and different fMRI model options. The reanalyzed EEG-fMRI findings were largely concordant with those of EEG and icEEG, and the failure of our previous EEG-fMRI analysis may lie in the inaccurate identification of IEDs and wrong usage of model options. The right frontal and temporal regions were resected in surgery, and dual pathology (hippocampus sclerosis and focal cortical dysplasia in the extrahippocampal region was found. The patient became seizure-free for 3 months, but his seizures restarted after antiepileptic drugs (AEDs were stopped. The seizures were not well controlled after resuming AEDs. Postsurgical EEGs indicated that ictal spikes in the right frontal and temporal regions reduced, while those in the left hemisphere became prominent

Psychogenic seizures and frontal disconnection: EEG synchronisation study.

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Knyazeva, Maria G; Jalili, Mahdi; Frackowiak, Richard S; Rossetti, Andrea O

2011-05-01

Psychogenic non-epileptic seizures (PNES) are paroxysmal events that, in contrast to epileptic seizures, are related to psychological causes without the presence of epileptiform EEG changes. Recent models suggest a multifactorial basis for PNES. A potentially paramount, but currently poorly understood factor is the interplay between psychiatric features and a specific vulnerability of the brain leading to a clinical picture that resembles epilepsy. Hypothesising that functional cerebral network abnormalities may predispose to the clinical phenotype, the authors undertook a characterisation of the functional connectivity in PNES patients. The authors analysed the whole-head surface topography of multivariate phase synchronisation (MPS) in interictal high-density EEG of 13 PNES patients as compared with 13 age- and sex-matched controls. MPS mapping reduces the wealth of dynamic data obtained from high-density EEG to easily readable synchronisation maps, which provide an unbiased overview of any changes in functional connectivity associated with distributed cortical abnormalities. The authors computed MPS maps for both Laplacian and common-average-reference EEGs. In a between-group comparison, only patchy, non-uniform changes in MPS survived conservative statistical testing. However, against the background of these unimpressive group results, the authors found widespread inverse correlations between individual PNES frequency and MPS within the prefrontal and parietal cortices. PNES appears to be associated with decreased prefrontal and parietal synchronisation, possibly reflecting dysfunction of networks within these regions.

An epileptic seizures detection algorithm based on the empirical mode decomposition of EEG.

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Orosco, Lorena; Laciar, Eric; Correa, Agustina Garces; Torres, Abel; Graffigna, Juan P

2009-01-01

Epilepsy is a neurological disorder that affects around 50 million people worldwide. The seizure detection is an important component in the diagnosis of epilepsy. In this study, the Empirical Mode Decomposition (EMD) method was proposed on the development of an automatic epileptic seizure detection algorithm. The algorithm first computes the Intrinsic Mode Functions (IMFs) of EEG records, then calculates the energy of each IMF and performs the detection based on an energy threshold and a minimum duration decision. The algorithm was tested in 9 invasive EEG records provided and validated by the Epilepsy Center of the University Hospital of Freiburg. In 90 segments analyzed (39 with epileptic seizures) the sensitivity and specificity obtained with the method were of 56.41% and 75.86% respectively. It could be concluded that EMD is a promissory method for epileptic seizure detection in EEG records.

The probability of seizures during EEG monitoring in critically ill adults.

Science.gov (United States)

Westover, M Brandon; Shafi, Mouhsin M; Bianchi, Matt T; Moura, Lidia M V R; O'Rourke, Deirdre; Rosenthal, Eric S; Chu, Catherine J; Donovan, Samantha; Hoch, Daniel B; Kilbride, Ronan D; Cole, Andrew J; Cash, Sydney S

2015-03-01

To characterize the risk for seizures over time in relation to EEG findings in hospitalized adults undergoing continuous EEG monitoring (cEEG). Retrospective analysis of cEEG data and medical records from 625 consecutive adult inpatients monitored at a tertiary medical center. Using survival analysis methods, we estimated the time-dependent probability that a seizure will occur within the next 72-h, if no seizure has occurred yet, as a function of EEG abnormalities detected so far. Seizures occurred in 27% (168/625). The first seizure occurred early (monitoring) in 58% (98/168). In 527 patients without early seizures, 159 (30%) had early epileptiform abnormalities, versus 368 (70%) without. Seizures were eventually detected in 25% of patients with early epileptiform discharges, versus 8% without early discharges. The 72-h risk of seizures declined below 5% if no epileptiform abnormalities were present in the first two hours, whereas 16h of monitoring were required when epileptiform discharges were present. 20% (74/388) of patients without early epileptiform abnormalities later developed them; 23% (17/74) of these ultimately had seizures. Only 4% (12/294) experienced a seizure without preceding epileptiform abnormalities. Seizure risk in acute neurological illness decays rapidly, at a rate dependent on abnormalities detected early during monitoring. This study demonstrates that substantial risk stratification is possible based on early EEG abnormalities. These findings have implications for patient-specific determination of the required duration of cEEG monitoring in hospitalized patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Epileptic Seizure Detection based on Wavelet Transform Statistics Map and EMD Method for Hilbert-Huang Spectral Analyzing in Gamma Frequency Band of EEG Signals

Directory of Open Access Journals (Sweden)

Morteza Behnam

2015-08-01

Full Text Available Seizure detection using brain signal (EEG analysis is the important clinical methods in drug therapy and the decisions before brain surgery. In this paper, after signal conditioning using suitable filtering, the Gamma frequency band has been extracted and the other brain rhythms, ambient noises and the other bio-signal are canceled. Then, the wavelet transform of brain signal and the map of wavelet transform in multi levels are computed. By dividing the color map to different epochs, the histogram of each sub-image is obtained and the statistics of it based on statistical momentums and Negentropy values are calculated. Statistical feature vector using Principle Component Analysis (PCA is reduced to one dimension. By EMD algorithm and sifting procedure for analyzing the data by Intrinsic Mode Function (IMF and computing the residues of brain signal using spectrum of Hilbert transform and Hilbert – Huang spectrum forming, one spatial feature based on the Euclidian distance for signal classification is obtained. By K-Nearest Neighbor (KNN classifier and by considering the optimal neighbor parameter, EEG signals are classified in two classes, seizure and non-seizure signal, with the rate of accuracy 76.54% and with variance of error 0.3685 in the different tests.

Classifier models and architectures for EEG-based neonatal seizure detection

International Nuclear Information System (INIS)

Greene, B R; Marnane, W P; Lightbody, G; Reilly, R B; Boylan, G B

2008-01-01

Neonatal seizures are the most common neurological emergency in the neonatal period and are associated with a poor long-term outcome. Early detection and treatment may improve prognosis. This paper aims to develop an optimal set of parameters and a comprehensive scheme for patient-independent multi-channel EEG-based neonatal seizure detection. We employed a dataset containing 411 neonatal seizures. The dataset consists of multi-channel EEG recordings with a mean duration of 14.8 h from 17 neonatal patients. Early-integration and late-integration classifier architectures were considered for the combination of information across EEG channels. Three classifier models based on linear discriminants, quadratic discriminants and regularized discriminants were employed. Furthermore, the effect of electrode montage was considered. The best performing seizure detection system was found to be an early integration configuration employing a regularized discriminant classifier model. A referential EEG montage was found to outperform the more standard bipolar electrode montage for automated neonatal seizure detection. A cross-fold validation estimate of the classifier performance for the best performing system yielded 81.03% of seizures correctly detected with a false detection rate of 3.82%. With post-processing, the false detection rate was reduced to 1.30% with 59.49% of seizures correctly detected. These results represent a comprehensive illustration that robust reliable patient-independent neonatal seizure detection is possible using multi-channel EEG

Preictal dynamics of EEG complexity in intracranially recorded epileptic seizure: a case report.

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Bob, Petr; Roman, Robert; Svetlak, Miroslav; Kukleta, Miloslav; Chladek, Jan; Brazdil, Milan

2014-11-01

Recent findings suggest that neural complexity reflecting a number of independent processes in the brain may characterize typical changes during epileptic seizures and may enable to describe preictal dynamics. With respect to previously reported findings suggesting specific changes in neural complexity during preictal period, we have used measure of pointwise correlation dimension (PD2) as a sensitive indicator of nonstationary changes in complexity of the electroencephalogram (EEG) signal. Although this measure of complexity in epileptic patients was previously reported by Feucht et al (Applications of correlation dimension and pointwise dimension for non-linear topographical analysis of focal onset seizures. Med Biol Comput. 1999;37:208-217), it was not used to study changes in preictal dynamics. With this aim to study preictal changes of EEG complexity, we have examined signals from 11 multicontact depth (intracerebral) EEG electrodes located in 108 cortical and subcortical brain sites, and from 3 scalp EEG electrodes in a patient with intractable epilepsy, who underwent preoperative evaluation before epilepsy surgery. From those 108 EEG contacts, records related to 44 electrode contacts implanted into lesional structures and white matter were not included into the experimental analysis.The results show that in comparison to interictal period (at about 8-6 minutes before seizure onset), there was a statistically significant decrease in PD2 complexity in the preictal period at about 2 minutes before seizure onset in all 64 intracranial channels localized in various brain sites that were included into the analysis and in 3 scalp EEG channels as well. Presented results suggest that using PD2 in EEG analysis may have significant implications for research of preictal dynamics and prediction of epileptic seizures.

Patient-Specific Seizure Detection in Long-Term EEG Using Signal-Derived Empirical Mode Decomposition (EMD)-based Dictionary Approach.

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Kaleem, Muhammad; Gurve, Dharmendra; Guergachi, Aziz; Krishnan, Sridhar

2018-06-25

The objective of the work described in this paper is development of a computationally efficient methodology for patient-specific automatic seizure detection in long-term multi-channel EEG recordings. Approach: A novel patient-specific seizure detection approach based on signal-derived Empirical Mode Decomposition (EMD)-based dictionary approach is proposed. For this purpose, we use an empirical framework for EMD-based dictionary creation and learning, inspired by traditional dictionary learning methods, in which the EMD-based dictionary is learned from the multi-channel EEG data being analyzed for automatic seizure detection. We present the algorithm for dictionary creation and learning, whose purpose is to learn dictionaries with a small number of atoms. Using training signals belonging to seizure and non-seizure classes, an initial dictionary, termed as the raw dictionary, is formed. The atoms of the raw dictionary are composed of intrinsic mode functions obtained after decomposition of the training signals using the empirical mode decomposition algorithm. The raw dictionary is then trained using a learning algorithm, resulting in a substantial decrease in the number of atoms in the trained dictionary. The trained dictionary is then used for automatic seizure detection, such that coefficients of orthogonal projections of test signals against the trained dictionary form the features used for classification of test signals into seizure and non-seizure classes. Thus no hand-engineered features have to be extracted from the data as in traditional seizure detection approaches. Main results: The performance of the proposed approach is validated using the CHB-MIT benchmark database, and averaged accuracy, sensitivity and specificity values of 92.9%, 94.3% and 91.5%, respectively, are obtained using support vector machine classifier and five-fold cross-validation method. These results are compared with other approaches using the same database, and the suitability

Amplitude Integrated Electroencephalography Compared With Conventional Video EEG for Neonatal Seizure Detection: A Diagnostic Accuracy Study.

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Rakshasbhuvankar, Abhijeet; Rao, Shripada; Palumbo, Linda; Ghosh, Soumya; Nagarajan, Lakshmi

2017-08-01

This diagnostic accuracy study compared the accuracy of seizure detection by amplitude-integrated electroencephalography with the criterion standard conventional video EEG in term and near-term infants at risk of seizures. Simultaneous recording of amplitude-integrated EEG (2-channel amplitude-integrated EEG with raw trace) and video EEG was done for 24 hours for each infant. Amplitude-integrated EEG was interpreted by a neonatologist; video EEG was interpreted by a neurologist independently. Thirty-five infants were included in the analysis. In the 7 infants with seizures on video EEG, there were 169 seizure episodes on video EEG, of which only 57 were identified by amplitude-integrated EEG. Amplitude-integrated EEG had a sensitivity of 33.7% for individual seizure detection. Amplitude-integrated EEG had an 86% sensitivity for detection of babies with seizures; however, it was nonspecific, in that 50% of infants with seizures detected by amplitude-integrated EEG did not have true seizures by video EEG. In conclusion, our study suggests that amplitude-integrated EEG is a poor screening tool for neonatal seizures.

Clustering of spontaneous recurrent seizures separated by long seizure-free periods: An extended video-EEG monitoring study of a pilocarpine mouse model.

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Lim, Jung-Ah; Moon, Jangsup; Kim, Tae-Joon; Jun, Jin-Sun; Park, Byeongsu; Byun, Jung-Ick; Sunwoo, Jun-Sang; Park, Kyung-Il; Lee, Soon-Tae; Jung, Keun-Hwa; Jung, Ki-Young; Kim, Manho; Jeon, Daejong; Chu, Kon; Lee, Sang Kun

2018-01-01

Seizure clustering is a common and significant phenomenon in patients with epilepsy. The clustering of spontaneous recurrent seizures (SRSs) in animal models of epilepsy, including mouse pilocarpine models, has been reported. However, most studies have analyzed seizures for a short duration after the induction of status epilepticus (SE). In this study, we investigated the detailed characteristics of seizure clustering in the chronic stage of a mouse pilocarpine-induced epilepsy model for an extended duration by continuous 24/7 video-EEG monitoring. A seizure cluster was defined as the occurrence of one or more seizures per day for at least three consecutive days and at least five seizures during the cluster period. We analyzed the cluster duration, seizure-free period, cluster interval, and numbers of seizures within and outside the seizure clusters. The video-EEG monitoring began 84.5±33.7 days after the induction of SE and continued for 53.7±20.4 days. Every mouse displayed seizure clusters, and 97.0% of the seizures occurred within a cluster period. The seizure clusters were followed by long seizure-free periods of 16.3±6.8 days, showing a cyclic pattern. The SRSs also occurred in a grouped pattern within a day. We demonstrate that almost all seizures occur in clusters with a cyclic pattern in the chronic stage of a mouse pilocarpine-induced epilepsy model. The seizure-free periods between clusters were long. These findings should be considered when performing in vivo studies using this animal model. Furthermore, this model might be appropriate for studying the unrevealed mechanism of ictogenesis.

Automatic identification of epileptic seizures from EEG signals using linear programming boosting.

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Hassan, Ahnaf Rashik; Subasi, Abdulhamit

2016-11-01

Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful seizure detection scheme. In this work, the problem of automated epilepsy seizure detection using singe-channel EEG signals has been addressed. At first, segments of EEG signals are decomposed using a newly proposed signal processing scheme, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Six spectral moments are extracted from the CEEMDAN mode functions and train and test matrices are formed afterward. These matrices are fed into the classifier to identify epileptic seizures from EEG signal segments. In this work, we implement an ensemble learning based machine learning algorithm, namely linear programming boosting (LPBoost) to perform classification. The efficacy of spectral features in the CEEMDAN domain is validated by graphical and statistical analyses. The performance of CEEMDAN is compared to those of its predecessors to further inspect its suitability. The effectiveness and the appropriateness of LPBoost are demonstrated as opposed to the commonly used classification models. Resubstitution and 10 fold cross-validation error analyses confirm the superior algorithm performance of the proposed scheme. The algorithmic performance of our epilepsy seizure identification scheme is also evaluated against state-of-the-art works in the literature. Experimental outcomes manifest that the proposed seizure detection scheme performs better than the existing works in terms of accuracy, sensitivity, specificity, and Cohen's Kappa coefficient. It can be anticipated that owing to its use of only one channel of EEG signal, the proposed method will be suitable for device implementation, eliminate the onus of clinicians for analyzing a large bulk of data manually, and

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

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Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.

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Zhang, Zhongnan; Wen, Tingxi; Huang, Wei; Wang, Meihong; Li, Chunfeng

2017-01-01

Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important role in the detection of neurological diseases. However, the process of analyzing EEG to detect neurological diseases is often difficult because the brain electrical signals are random, non-stationary and nonlinear. In order to overcome such difficulty, this study aims to develop a new computer-aided scheme for automatic epileptic seizure detection in EEGs based on multi-fractal detrended fluctuation analysis (MF-DFA) and support vector machine (SVM). New scheme first extracts features from EEG by MF-DFA during the first stage. Then, the scheme applies a genetic algorithm (GA) to calculate parameters used in SVM and classify the training data according to the selected features using SVM. Finally, the trained SVM classifier is exploited to detect neurological diseases. The algorithm utilizes MLlib from library of SPARK and runs on cloud platform. Applying to a public dataset for experiment, the study results show that the new feature extraction method and scheme can detect signals with less features and the accuracy of the classification reached up to 99%. MF-DFA is a promising approach to extract features for analyzing EEG, because of its simple algorithm procedure and less parameters. The features obtained by MF-DFA can represent samples as well as traditional wavelet transform and Lyapunov exponents. GA can always find useful parameters for SVM with enough execution time. The results illustrate that the classification model can achieve comparable accuracy, which means that it is effective in epileptic seizure detection.

Epileptic seizures, coma and EEG burst-suppression from suicidal bupropion intoxication.

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Noda, Anna Hiro; Schu, Ulrich; Maier, Tanja; Knake, Susanne; Rosenow, Felix

2017-03-01

Bupropion, an amphetamine-like dual mechanism drug, is approved and increasingly used for the treatment of major depression, and its use is associated with a dose-dependent risk of epileptic seizures. Suicide attempts are frequent in major depression and often an overdose of the drugs available is ingested. Therefore, it is important to be aware of the clinical course, including EEG and neurological symptoms, as well as treatment and prognosis of bupropion intoxication. We report on the clinical and EEG course of a women who ingested 27 g of bupropion in a suicide attempt. Myoclonic seizures were followed by generalized tonic-clonic seizures and coma associated with EEG burst-suppression and brief tonic seizures. Active carbon and neuro-intensive care treatment, including respiratory support, were given. Within three days, the patient returned to a stable clinical condition with a mildly encephalopathic EEG. In conclusion, bupropion intoxication requires acute intensive care treatment and usually has a good prognosis, however, misinterpretation of the clinical and EEG presentation may lead to errors in management.

LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

Science.gov (United States)

Zhang, Tao; Chen, Wanzhong

2017-08-01

Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs and raw EEG are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.

EEG and CT findings of infant partial seizures

International Nuclear Information System (INIS)

Kajitani, Takashi; Kumanomido, Yoshiaki; Nakamura, Makoto; Ueoka, Kiyotaka

1981-01-01

Examination of EEG and cranial CT were performed in 19 cases of partial seizures with elementary symptomatology (PSES), 6 cases of partial seizures with complex symptomatology (PSCS), and 17 cases of benign focal pilepsy of childhood with Rolandic spikes (BFECRS). The results were as follows. 1) In 16 of 19 cases of PSES (84%), various abnormal CT findings such as localized cerebral atrophy (7 cases), localized cerebral atrophy complicated with porencephaly (4 cases), porencephaly alone (2 cases), and diffuse cerebral atrophy (3 cases) were found. 2) Of 6 cases of PSCS localized cerebral atrophy was found in 3 cases, porencephaly in one case, and localized calcification in one case. Normal CT findings were obtained in one case. 3) In comparison of EEG findings with CT findings in 25 cases of partial seizures CT findings correlated with the basic waves rather than the paroxysmal ones. 4) The fact that CT findings in patients with BFECRS were mostly normal suggests the functional origin of the seizures. 5) CT was valuable in partial seizures for detecting underlying disorders and predicting the prognosis. (Ueda, J.)

Analysis of absence seizure generation using EEG spatial-temporal regularity measures.

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Mammone, Nadia; Labate, Domenico; Lay-Ekuakille, Aime; Morabito, Francesco C

2012-12-01

Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

SVM-Based System for Prediction of Epileptic Seizures from iEEG Signal

Science.gov (United States)

Cherkassky, Vladimir; Lee, Jieun; Veber, Brandon; Patterson, Edward E.; Brinkmann, Benjamin H.; Worrell, Gregory A.

2017-01-01

Objective This paper describes a data-analytic modeling approach for prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is widely accepted that statistical characteristics of iEEG signal change prior to seizures, robust seizure prediction remains a challenging problem due to subject-specific nature of data-analytic modeling. Methods Our work emphasizes understanding of clinical considerations important for iEEG-based seizure prediction, and proper translation of these clinical considerations into data-analytic modeling assumptions. Several design choices during pre-processing and post-processing are considered and investigated for their effect on seizure prediction accuracy. Results Our empirical results show that the proposed SVM-based seizure prediction system can achieve robust prediction of preictal and interictal iEEG segments from dogs with epilepsy. The sensitivity is about 90–100%, and the false-positive rate is about 0–0.3 times per day. The results also suggest good prediction is subject-specific (dog or human), in agreement with earlier studies. Conclusion Good prediction performance is possible only if the training data contain sufficiently many seizure episodes, i.e., at least 5–7 seizures. Significance The proposed system uses subject-specific modeling and unbalanced training data. This system also utilizes three different time scales during training and testing stages. PMID:27362758

Non-parametric early seizure detection in an animal model of temporal lobe epilepsy

Science.gov (United States)

Talathi, Sachin S.; Hwang, Dong-Uk; Spano, Mark L.; Simonotto, Jennifer; Furman, Michael D.; Myers, Stephen M.; Winters, Jason T.; Ditto, William L.; Carney, Paul R.

2008-03-01

The performance of five non-parametric, univariate seizure detection schemes (embedding delay, Hurst scale, wavelet scale, nonlinear autocorrelation and variance energy) were evaluated as a function of the sampling rate of EEG recordings, the electrode types used for EEG acquisition, and the spatial location of the EEG electrodes in order to determine the applicability of the measures in real-time closed-loop seizure intervention. The criteria chosen for evaluating the performance were high statistical robustness (as determined through the sensitivity and the specificity of a given measure in detecting a seizure) and the lag in seizure detection with respect to the seizure onset time (as determined by visual inspection of the EEG signal by a trained epileptologist). An optimality index was designed to evaluate the overall performance of each measure. For the EEG data recorded with microwire electrode array at a sampling rate of 12 kHz, the wavelet scale measure exhibited better overall performance in terms of its ability to detect a seizure with high optimality index value and high statistics in terms of sensitivity and specificity.

Detecting interictal discharges in first seizure patients: ambulatory EEG or EEG after sleep deprivation?

NARCIS (Netherlands)

Geut, I.; Weenink, S.; Knottnerus, I.L.H.; van Putten, Michel J.A.M.

2017-01-01

Purpose Uncertainty about recurrence after a first unprovoked seizure is a significant psychological burden for patients, and motivates the need for diagnostic tools with high sensitivity and specificity to assess recurrence risk. As the sensitivity of a routine EEG after a first unprovoked seizure

NeuroKinect: A Novel Low-Cost 3Dvideo-EEG System for Epileptic Seizure Motion Quantification.

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João Paulo Silva Cunha

Full Text Available Epilepsy is a common neurological disorder which affects 0.5-1% of the world population. Its diagnosis relies both on Electroencephalogram (EEG findings and characteristic seizure-induced body movements--called seizure semiology. Thus, synchronous EEG and (2Dvideo recording systems (known as Video-EEG are the most accurate tools for epilepsy diagnosis. Despite the establishment of several quantitative methods for EEG analysis, seizure semiology is still analyzed by visual inspection, based on epileptologists' subjective interpretation of the movements of interest (MOIs that occur during recorded seizures. In this contribution, we present NeuroKinect, a low-cost, easy to setup and operate solution for a novel 3Dvideo-EEG system. It is based on a RGB-D sensor (Microsoft Kinect camera and performs 24/7 monitoring of an Epilepsy Monitoring Unit (EMU bed. It does not require the attachment of any reflectors or sensors to the patient's body and has a very low maintenance load. To evaluate its performance and usability, we mounted a state-of-the-art 6-camera motion-capture system and our low-cost solution over the same EMU bed. A comparative study of seizure-simulated MOIs showed an average correlation of the resulting 3D motion trajectories of 84.2%. Then, we used our system on the routine of an EMU and collected 9 different seizures where we could perform 3D kinematic analysis of 42 MOIs arising from the temporal (TLE (n = 19 and extratemporal (ETE brain regions (n = 23. The obtained results showed that movement displacement and movement extent discriminated both seizure MOI groups with statistically significant levels (mean = 0.15 m vs. 0.44 m, p<0.001; mean = 0.068 m(3 vs. 0.14 m(3, p<0.05, respectively. Furthermore, TLE MOIs were significantly shorter than ETE (mean = 23 seconds vs 35 seconds, p<0.01 and presented higher jerking levels (mean = 345 ms(-3 vs 172 ms(-3, p<0.05. Our newly implemented 3D approach is faster by 87.5% in extracting body

NeuroKinect: A Novel Low-Cost 3Dvideo-EEG System for Epileptic Seizure Motion Quantification.

Science.gov (United States)

Cunha, João Paulo Silva; Choupina, Hugo Miguel Pereira; Rocha, Ana Patrícia; Fernandes, José Maria; Achilles, Felix; Loesch, Anna Mira; Vollmar, Christian; Hartl, Elisabeth; Noachtar, Soheyl

2016-01-01

Epilepsy is a common neurological disorder which affects 0.5-1% of the world population. Its diagnosis relies both on Electroencephalogram (EEG) findings and characteristic seizure-induced body movements--called seizure semiology. Thus, synchronous EEG and (2D)video recording systems (known as Video-EEG) are the most accurate tools for epilepsy diagnosis. Despite the establishment of several quantitative methods for EEG analysis, seizure semiology is still analyzed by visual inspection, based on epileptologists' subjective interpretation of the movements of interest (MOIs) that occur during recorded seizures. In this contribution, we present NeuroKinect, a low-cost, easy to setup and operate solution for a novel 3Dvideo-EEG system. It is based on a RGB-D sensor (Microsoft Kinect camera) and performs 24/7 monitoring of an Epilepsy Monitoring Unit (EMU) bed. It does not require the attachment of any reflectors or sensors to the patient's body and has a very low maintenance load. To evaluate its performance and usability, we mounted a state-of-the-art 6-camera motion-capture system and our low-cost solution over the same EMU bed. A comparative study of seizure-simulated MOIs showed an average correlation of the resulting 3D motion trajectories of 84.2%. Then, we used our system on the routine of an EMU and collected 9 different seizures where we could perform 3D kinematic analysis of 42 MOIs arising from the temporal (TLE) (n = 19) and extratemporal (ETE) brain regions (n = 23). The obtained results showed that movement displacement and movement extent discriminated both seizure MOI groups with statistically significant levels (mean = 0.15 m vs. 0.44 m, p<0.001; mean = 0.068 m(3) vs. 0.14 m(3), p<0.05, respectively). Furthermore, TLE MOIs were significantly shorter than ETE (mean = 23 seconds vs 35 seconds, p<0.01) and presented higher jerking levels (mean = 345 ms(-3) vs 172 ms(-3), p<0.05). Our newly implemented 3D approach is faster by 87.5% in extracting body

Automatic detection of non-convulsive seizures: A reduced complexity approach

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Tazeem Fatma

2016-10-01

Full Text Available Detection of non-convulsive seizures (NCSz is a challenging task because they lack convulsions, meaning no physical visible symptoms are there to detect the presence of a seizure activity. Hence their diagnosis is not easy, also continuous observation of full length EEG for the detection of non-convulsive seizures (NCSz by an expert or a technician is a very exhaustive, time consuming job. A technique for the automatic detection of NCSz is proposed in this paper. The database used in this research was recorded at the All India Institute of Medical Sciences (AIIMS, New Delhi. 13 EEG recordings of 9 subjects consisting of a total 23 seizures of 29.42 min duration were used for analysis. Normalized modified Wilson amplitude is used as a key feature to classify between normal and seizure activity. The main advantage of this study lies in the fact that no classifier is used here and hence algorithm is very simple and computationally fast. With the use of only one feature, all of the seizures under test were detected correctly, and hence the median sensitivity and specificity of 100% and 99.21% were achieved respectively.

Neonatal apneic seizure of occipital lobe origin: continuous video-EEG recording.

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Castro Conde, José Ramón; González-Hernández, Tomás; González Barrios, Desiré; González Campo, Candelaria

2012-06-01

We present 2 term newborn infants with apneic seizure originating in the occipital lobe that was diagnosed by video-EEG. One infant had ischemic infarction in the distribution of the posterior cerebral artery, extending to the cingulate gyrus. In the other infant, only transient occipital hyperechogenicity was observed by using neurosonography. In both cases, although the critical EEG discharge was observed at the occipital level, the infants presented no clinical manifestations. In patient 1, the discharge extended to the temporal lobe first, with subtle motor manifestations and tachycardia, then synchronously to both hemispheres (with bradypnea/hypopnea), and the background EEG activity became suppressed, at which point the infant experienced apnea. In patient 2, background EEG activity became suppressed right at the end of the focal discharge, coinciding with the appearance of apnea. In neither case did the clinical description by observers coincide with video-EEG findings. The existence of connections between the posterior limbic cortex and the temporal lobe and midbrain respiratory centers may explain the clinical symptoms recorded in these 2 cases. The novel features reported here include video-EEG capture of apneic seizure, ischemic lesion in the territory of the posterior cerebral artery as the cause of apneic seizure, and the appearance of apnea when the epileptiform ictal discharge extended to other cerebral areas or when EEG activity became suppressed. To date, none of these clinical findings have been previously reported. We believe this pathology may in fact be fairly common, but that video-EEG monitoring is essential for diagnosis.

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

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Jaiswal, Abeg Kumar; Banka, Haider

2017-01-01

Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure detection is a time-consuming process and may lead to human error; therefore, recently, a number of automated seizure detection frameworks were proposed to replace these traditional methods. Feature extraction and classification are two important steps in these procedures. Feature extraction focuses on finding the informative features that could be used for classification and correct decision-making. Therefore, proposing effective feature extraction techniques for seizure detection is of great significance. Principal Component Analysis (PCA) is a dimensionality reduction technique used in different fields of pattern recognition including EEG signal classification. Global modular PCA (GModPCA) is a variation of PCA. In this paper, an effective framework with GModPCA and Support Vector Machine (SVM) is presented for epileptic seizure detection in EEG signals. The feature extraction is performed with GModPCA, whereas SVM trained with radial basis function kernel performed the classification between seizure and nonseizure EEG signals. Seven different experimental cases were conducted on the benchmark epilepsy EEG dataset. The system performance was evaluated using 10-fold cross-validation. In addition, we prove analytically that GModPCA has less time and space complexities as compared to PCA. The experimental results show that EEG signals have strong inter-sub-pattern correlations. GModPCA and SVM have been able to achieve 100% accuracy for the classification between normal and epileptic signals. Along with this, seven different experimental cases were tested. The classification results of the proposed approach were better than were compared the results of some of the existing methods proposed in literature. It is also found that the time and space

Seizures and EEG features in 74 patients with genetic-dysmorphic syndromes.

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Alfei, Enrico; Raviglione, Federico; Franceschetti, Silvana; D'Arrigo, Stefano; Milani, Donatella; Selicorni, Angelo; Riva, Daria; Zuffardi, Orsetta; Pantaleoni, Chiara; Binelli, Simona

2014-12-01

Epilepsy is one of the most common findings in chromosome aberrations. Types of seizures and severity may significantly vary both between different conditions and within the same aberration. Hitherto specific seizures and EEG patterns are identified for only few syndromes. We studied 74 patients with defined genetic-dysmorphic syndromes with and without epilepsy in order to assess clinical and electroencephalographic features, to compare our observation with already described electro-clinical phenotypes, and to identify putative electroencephalographic and/or seizure characteristics useful to address the diagnosis. In our population, 10 patients had chromosomal disorders, 19 microdeletion or microduplication syndromes, and 32 monogenic syndromes. In the remaining 13, syndrome diagnosis was assessed on clinical grounds. Our study confirmed the high incidence of epilepsy in genetic-dysmorphic syndromes. Moreover, febrile seizures and neonatal seizures had a higher incidence compared to general population. In addition, more than one third of epileptic patients had drug-resistant epilepsy. EEG study revealed poor background organization in 42 patients, an excess of diffuse rhythmic activities in beta, alpha or theta frequency bands in 34, and epileptiform patterns in 36. EEG was completely normal only in 20 patients. No specific electro-clinical pattern was identified, except for inv-dup15, Angelman, and Rett syndromes. Nevertheless some specific conditions are described in detail, because of notable differences from what previously reported. Regarding the diagnostic role of EEG, we found that--even without any epileptiform pattern--the generation of excessive rhythmic activities in different frequency bandwidths might support the diagnosis of a genetic syndrome. © 2014 Wiley Periodicals, Inc.

Automatic seizure detection based on the combination of newborn multi-channel EEG and HRV information

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Mesbah, Mostefa; Balakrishnan, Malarvili; Colditz, Paul B.; Boashash, Boualem

2012-12-01

This article proposes a new method for newborn seizure detection that uses information extracted from both multi-channel electroencephalogram (EEG) and a single channel electrocardiogram (ECG). The aim of the study is to assess whether additional information extracted from ECG can improve the performance of seizure detectors based solely on EEG. Two different approaches were used to combine this extracted information. The first approach, known as feature fusion, involves combining features extracted from EEG and heart rate variability (HRV) into a single feature vector prior to feeding it to a classifier. The second approach, called classifier or decision fusion, is achieved by combining the independent decisions of the EEG and the HRV-based classifiers. Tested on recordings obtained from eight newborns with identified EEG seizures, the proposed neonatal seizure detection algorithms achieved 95.20% sensitivity and 88.60% specificity for the feature fusion case and 95.20% sensitivity and 94.30% specificity for the classifier fusion case. These results are considerably better than those involving classifiers using EEG only (80.90%, 86.50%) or HRV only (85.70%, 84.60%).

Multifractal detrended cross-correlation analysis for epileptic patient in seizure and seizure free status

International Nuclear Information System (INIS)

Ghosh, Dipak; Dutta, Srimonti; Chakraborty, Sayantan

2014-01-01

Highlights: • We analyze EEG of patients during seizure and in seizure free interval. • Data from different sections of the brain and seizure activity was analyzed. • Assessment of cross-correlation in seizure and seizure free interval using MF-DXA technique. - Abstract: This paper reports a study of EEG data of epileptic patients in terms of multifractal detrended cross-correlation analysis (MF-DXA). The EEG clinical data were obtained from the EEG Database available with the Clinic of Epileptology of the University Hospital of Bonn, Germany. The data sets (C, D, and E) were taken from five epileptic patients undergoing presurgical evaluations. The data sets consist of intracranial EEG recordings during seizure-free intervals (interictal periods) from within the epileptogenic zone (D) and from the hippocampal formation of the opposite hemisphere of the epileptic patients’ brain, respectively (C). The data set (E) was recorded during seizure activity (ictal periods). MF-DXA is a very rigorous and robust tool for assessment of cross-correlation among two nonlinear time series. The study reveals the degree of cross-correlation is more among seizure and seizure free interval in epileptogenic zone. These data are very significant for diagnosis, onset and prognosis of epileptic patients

Seizure classification in EEG signals utilizing Hilbert-Huang transform

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Abdulhay Enas W

2011-05-01

Full Text Available Abstract Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG signals. Method Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. Results The t-test results in a P-value Conclusion An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool.

Seizure classification in EEG signals utilizing Hilbert-Huang transform.

Science.gov (United States)

Oweis, Rami J; Abdulhay, Enas W

2011-05-24

Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. The t-test results in a P-value with respect to its fast response and ease to use. An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool.

Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.

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Stamoulis, Catherine; Schomer, Donald L; Chang, Bernard S

2013-08-01

How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution (Andrade-Valenca et al., 2011; Stamoulis et al., 2012). However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤ 100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤ 100 Hz, at least in some seizures. Copyright © 2013 Elsevier B.V. All rights reserved.

Patients with epilepsy and patients with psychogenic non-epileptic seizures: video-EEG, clinical and neuropsychological evaluation.

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Turner, Katherine; Piazzini, Ada; Chiesa, Valentina; Barbieri, Valentina; Vignoli, Aglaia; Gardella, Elena; Tisi, Giuseppe; Scarone, Silvio; Canevini, Maria Paola; Gambini, Orsola

2011-11-01

The incidence of psychogenic non-epileptic seizures (PNES) is 4.9/100,000/year and it is estimated that about 20-30% of patients referred to tertiary care epilepsy centers for refractory seizures have both epilepsy and PNES. The purpose of our study is to evaluate psychiatric disorders and neuropsychological functions among patients with PNES, patients with epilepsy associated with PNES and patients with epilepsy. We evaluated 66 consecutive in-patients with video-EEG recordings: 21 patients with epilepsy, 22 patients with PNES and 10 patients with epilepsy associated with PNES; 13 patients were excluded (8 because of mental retardation and 5 because they did not present seizures or PNES during the recording period). All patients with PNES had a psychiatric diagnosis (100%) vs. 52% of patients with epilepsy. Cluster B personality disorders were more common in patients with PNES. We observed fewer mood and anxiety disorders in patients with PNES compared with those with epilepsy. We did not find statistically significant differences in neuropsychological profiles among the 3 patient groups. This study can help to contribute to a better understanding of the impact of PNES manifestations, in addition to the occurrence of seizures, in order to provide patients with more appropriate clinical, psychological and social care. Copyright © 2011 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

ABC optimized RBF network for classification of EEG signal for epileptic seizure identification

Directory of Open Access Journals (Sweden)

Sandeep Kumar Satapathy

2017-03-01

Full Text Available The brain signals usually generate certain electrical signals that can be recorded and analyzed for detection in several brain disorder diseases. These small signals are expressly called as Electroencephalogram (EEG signals. This research work analyzes the epileptic disorder in human brain through EEG signal analysis by integrating the best attributes of Artificial Bee Colony (ABC and radial basis function networks (RBFNNs. We have used Discrete Wavelet Transform (DWT technique for extraction of potential features from the signal. In our study, for classification of these signals, in this paper, the RBFNNs have been trained by a modified version of ABC algorithm. In the modified ABC, the onlooker bees are selected based on binary tournament unlike roulette wheel selection of ABC. Additionally, kernels such as Gaussian, Multi-quadric, and Inverse-multi-quadric are used for measuring the effectiveness of the method in numerous mixtures of healthy segments, seizure-free segments, and seizure segments. Our experimental outcomes confirm that RBFNN with inverse-multi-quadric kernel trained with modified ABC is significantly better than RBFNNs with other kernels trained by ABC and modified ABC.

The effects of lossy compression on diagnostically relevant seizure information in EEG signals.

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Higgins, G; McGinley, B; Faul, S; McEvoy, R P; Glavin, M; Marnane, W P; Jones, E

2013-01-01

This paper examines the effects of compression on EEG signals, in the context of automated detection of epileptic seizures. Specifically, it examines the use of lossy compression on EEG signals in order to reduce the amount of data which has to be transmitted or stored, while having as little impact as possible on the information in the signal relevant to diagnosing epileptic seizures. Two popular compression methods, JPEG2000 and SPIHT, were used. A range of compression levels was selected for both algorithms in order to compress the signals with varying degrees of loss. This compression was applied to the database of epileptiform data provided by the University of Freiburg, Germany. The real-time EEG analysis for event detection automated seizure detection system was used in place of a trained clinician for scoring the reconstructed data. Results demonstrate that compression by a factor of up to 120:1 can be achieved, with minimal loss in seizure detection performance as measured by the area under the receiver operating characteristic curve of the seizure detection system.

Autism Spectrum Disorder: Correlation between aberrant behaviors, EEG abnormalities and seizures

Directory of Open Access Journals (Sweden)

Michelle Elena Hartley-McAndrew

2010-04-01

Full Text Available The relationship between epilepsy, epileptiform discharges, cognitive, language and behavioral symptoms is not clearly understood. Since difficulties with socialization and maladaptive behaviors are found in children with Autism Spectrum Disorder (ASD, we inquired whether epileptiform activity and seizures are associated with adverse behavioral manifestations in this population. We reviewed our EEG database between 1999-2006, and identified 123 children with ASD. EEG abnormalities were found in 39 children (31%. A control group of age and gender matched ASD children with normal EEG’s was obtained. Packets of questionnaires including the Vineland Adaptive Behavior Scale II (VABS, Aberrant Behavior Checklist (ABC and the Childhood Autism Rating Scale (CARS were sent by mail. Out of 21 packets received, 11 had normal and 10 had abnormal EEG’s. There were no statistically significant differences in behavior between the two groups. Statistical analysis of discharge location and frequency did not reveal a significant trend. However, children with ASD and seizures had statistically significant lower scores in VABS daily living (P=0.009 and socialization (P=0.007 as compared to those without seizures. ASD children with seizures had higher ABC levels of hyperactivity and irritability. Differences in irritability scores nearly reached statistical significance (P=0.058. There was no significant difference in the degree of CARS autism rating between the groups. Our study did not reveal statistically significant differences in behaviors between ASD children with and without EEG abnormalities. However, ASD children with seizures revealed significantly worse behaviors as compared to counterparts without seizures.

Diagnosing psychogenic nonepileptic seizures: Video-EEG monitoring, suggestive seizure induction and diagnostic certainty.

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Popkirov, Stoyan; Jungilligens, Johannes; Grönheit, Wenke; Wellmer, Jörg

2017-08-01

Psychogenic nonepileptic seizures (PNES) can remain undiagnosed for many years, leading to unnecessary medication and delayed treatment. A recent report by the International League Against Epilepsy Nonepileptic Seizures Task Force recommends a staged approach to the diagnosis of PNES (LaFrance, et al., 2013). We aimed to investigate its practical utility, and to apply the proposed classification to evaluate the role of long-term video-EEG monitoring (VEEG) and suggestive seizure induction (SSI) in PNES workup. Using electronic medical records, 122 inpatients (mean age 36.0±12.9years; 68% women) who received the diagnosis of PNES at our epilepsy center during a 4.3-year time period were included. There was an 82.8% agreement between diagnostic certainty documented at discharge and that assigned retroactively using the Task Force recommendations. In a minority of cases, having used the Task Force criteria could have encouraged the clinicians to give more certain diagnoses, exemplifying the Task Force report's utility. Both VEEG and SSI were effective at supporting high level diagnostic certainty. Interestingly, about one in four patients (26.2%) had a non-diagnostic ("negative") VEEG but a positive SSI. On average, this subgroup did not have significantly shorter mean VEEG recording times than VEEG-positive patients. However, VEEG-negative/SSI-positive patients had a significantly lower habitual seizure frequency than their counterparts. This finding emphasizes the utility of SSI in ascertaining the diagnosis of PNES in patients who do not have a spontaneous habitual event during VEEG due to, for example, low seizure frequency. Copyright © 2017 Elsevier Inc. All rights reserved.

Seizure and EEG patterns in Wolf-Hirschhorn (4p-) syndrome.

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Battaglia, Agatino; Carey, John C

2005-08-01

Wolf-Hirschhorn syndrome (WHS) is a well-characterized chromosomal disorder that occurs due to partial deletion of the short arm of chromosome 4 (4p-). Although, about 300 cases have been reported to date, limited data are available on electroclinical findings. Information given to parents at the time of diagnosis tends to be skewed to the extreme negative. To delineate the natural history of seizures and EEG patterns in WHS, and obtain better information on diagnosis or outcome in a clinical setting, we reviewed the available literature on electroclinical findings of WHS. 4p- syndrome is characterized by distinctive seizure and EEG patterns that facilitate the early diagnosis and management of such patients.

Persistent seizures following failed surgery - Ictal SPECT and correlation with video EEG and follow-up

International Nuclear Information System (INIS)

Raja, S.; Gupta, A.; Kotagal, P.

2002-01-01

Introduction: A significant proportion (30-70%) of seizure patients (pts) have recurrent seizures post surgically. Up to 40-60% of these pts may benefit from re-evaluation and repeat surgical resections. Follow-up MRI is generally not useful in these patients due to post-surgical changes. Recently, ictal SPECT (IC) has been shown to be useful for the localization of seizure focus. We retrospectively analyzed the utility of IC in patients with unsuccessful surgical resections. Methods: Review of medical charts of all pts with IC from 1995 to 2001 was performed to identify pts with recurrent seizures who had IC studies. A total of 15 pts (male = 6, female 9; mean age = 17.9 yrs., range 6-31 yr.) were identified. All pts received 74-140 MBq of Tc-99m ECD each within 30 sec (range 14-81 sec) of seizure onset and were imaged within 6 hr post injection. For the inter-ictal (INT) scan, they received a similar dose and were imaged within 15 min post-injection on a triple-head gamma camera (Triad Trionix, Twinsburg, Ohio). The reconstructed transverse images were co-registered and normalized to the total counts of the INT. Greater than 10% increase in counts on the IC compared to the INT was considered positive for ictally-enhanced perfusion. The ICs were classified as localizable, lateralizable, or discordant with respect to vEEG. Results: Ictal SPECT and vEEG were concordant and lateralized the seizure focus in 14/15 pts, while both modalities were concordant and localized the foci in 7/15 pts, they were discordant for laterialization in 1 pt, and for localization in 8 pts. The MRI in 13/15 pts prior to the IC, revealed post surgical changes at the resection site, while in two pts MRI showed residual/recurrent tumor. Repeat resections and post-surgical follow-up (30 days to > 2 yrs) were available in 6/15 pts, 5 of these pts with repeat surgical resections of concordantly localized seizure foci by IC and vEEG, had good post-surgical outcome (Engel's I/II), while in the

Persistent lactic acidosis in neonatal hypoxic-ischaemic encephalopathy correlates with EEG grade and electrographic seizure burden.

LENUS (Irish Health Repository)

Murray, D M

2012-02-03

BACKGROUND: Predicting at birth which infants with perinatal hypoxic-ischaemic injury will progress to significant encephalopathy remains a challenge. OBJECTIVE: To determine whether lactic acidosis at birth in asphyxiated neonates could predict the grade of EEG encephalopathy by examining the relationship between time taken for the normalisation of lactate, severity of encephalopathy and seizure burden. METHODS: Continuous early video-EEG monitoring was performed in babies at risk for hypoxic-ischaemic encephalopathy. Encephalopathy was graded from the EEG data. Total seizure burden (seconds) was calculated for each baby. Initial blood gas measurements of pH, base deficit and lactate were taken within 30 minutes of delivery. Time to normal serum lactate was determined in hours from birth for each infant. RESULTS: All 50 term infants had raised initial serum lactate (median (lower, upper quartiles) 11.7 (10.2, 14.9)). There were no significant differences between the initial serum lactate, pH and base deficit in infants with normal\\/mildly abnormal (n = 24), moderately abnormal (n = 14), severely abnormal (n = 5) and inactive EEGs (n = 7). Time to normal lactate varied significantly with EEG grade (median (lower, upper quartile) 6.0 (4.1, 9.5) for mild\\/normal EEG, 13.5 (6.8, 23.5) moderate EEG, 41.5 (30.0, 55.5) severe group, 12.0 (8.1, 21.5) inactive group; p<0.001). Time to normal lactate correlated significantly with EEG seizure burden (seconds; R = 0.446, p = 0.002). Mean (SD) time to normal lactate was 10.0 (7.2) hours in infants who did not have seizures and 27.3 (19.0) hours in the 13 infants with electrographic seizures (p = 0.002). CONCLUSIONS: Serum lactate levels in the first 30 minutes of life do not predict the severity of the ensuing encephalopathy. In contrast, sustained lactic acidosis is associated with severe encephalopathy on EEG and correlates with seizure burden.

Evaluation of a novel median power spectrogram for seizure detection by non-neurophysiologists.

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Yan, Peter; Melman, Tamar; Yan, Sherry; Otgonsuren, Munkhzul; Grinspan, Zachary

2017-08-01

(1) To evaluate how well resident physicians use a novel EEG spectral analysis tool (the median power spectrogram; MPS) to detect seizures. (2) To assess the capability of the MPS to identify different seizure types. 120 EEG records from children with intractable seizures were converted to MPS by taking the median power across leads and using multi-taper spectral estimation. Twelve blinded neurology residents were trained to interpret the spectrogram with a five-minute video tutorial and post-test. Two residents independently assessed each set for presence of seizures. Their performance was compared to seizures identified using conventional EEG. Two blinded neurologists separately reviewed the EEGs and spectrograms to independently categorize the seizures. Their results were used to determine the spectrogram's capability to reveal seizures and visualize different seizure types for the user. Three key MPS features distinguished seizures from inter-ictal background: power difference relative to background, down-sloping resonance bands, and power in high frequencies. Using these features, residents identified seizures with 77% sensitivity and 72% specificity. 86% (51/59) of focal seizures and 81% (22/27) of generalized seizures were detected by at least one resident. Missed seizures included brief (seizures, tonic seizures, seizures with predominant delta (0-4Hz) activity, and seizures evident primarily in supplementary low temporal leads. The MPS is a novel qEEG modality that requires minimal training to interpret. It enables physicians without extensive neurophysiology training to identify seizures with sensitivity and specificity comparable to more complex multi-modal qEEG displays. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Feasibility of Seizure Prediction from intracranial EEG Recordings

DEFF Research Database (Denmark)

Henriksen, Jonas; Kjær, Troels; Thomsen, Carsten E.

2009-01-01

Purpose: The current project evaluated the feasibility of providing an algorithm that could warn a patient of a forthcoming seizure based on iEEG recordings. Method: The mean phase coherence (MPC) feature (Mormann F et al. Phys Nonlinear Phenom 2000;3-4:358-369.) was implemented and tested...... in a rigorously, out-of-sample manner. The MPC-feature is based on the synchronization measure, explained through the analytic signal approach where the Hilbert transform is used to find the instantaneous phase of an arbitrary signal. By a relative comparison between two different iEEG channels the phase...

Continuous EEG Monitoring in Aneurysmal Subarachnoid Hemorrhage

DEFF Research Database (Denmark)

Kondziella, Daniel; Friberg, Christian Kærsmose; Wellwood, Ian

2015-01-01

BACKGROUND: Continuous EEG (cEEG) may allow monitoring of patients with aneurysmal subarachnoid hemorrhage (SAH) for delayed cerebral ischemia (DCI) and seizures, including non-convulsive seizures (NCSz), and non-convulsive status epilepticus (NCSE). We aimed to evaluate: (a) the diagnostic...

Prognostic value of non-reactive burst suppression EEG pattern associated to early neonatal seizures Valor prognóstico do EEG com padrão de surto-supressão não reativo associado a convulsões neonatais precoces

Directory of Open Access Journals (Sweden)

Magda Lahorgue Nunes

2005-03-01

Full Text Available ABSTRACT Seizures are the most frequent neurological event in newborns and clinical data suggest that etiology is the dominant factor in long term outcome. However, there are consistent background EEG abnormalities associated to neonatal seizures that are usually related to unfavorable outcome as the burst - suppression pattern. OBJECTIVE: The objective of this study was to correlate clinical and EEG features associated to long - term outcome of newborns with non - reactive burst - suppression (BS EEG. METHOD: Newborns included in the study were selected from our database and had conceptional age (at the time of first EEG >37 weeks, EEG recordings with non - reactive BS available for review and clinical follow up. RESULTS: 12 newborns met inclusion criteria, 50% had seizures in the first day of life. Seizures became refractory to treatment in all of them. In 50% the etiology of seizures was considered cryptogenic, 33% had inborn errors of metabolism and 17% had clinical history and neuroimage suggestive of hypoxic-ischemic encephalopathy. The follow-up showed that 7/12 infants deceased, 3 during the first year of life, and one in the neonatal period. All the survivors had severe developmental delay and multifocal neurological impairment. 92% developed refractory epilepsy, 58% were latter diagnosed with West syndrome. CONCLUSION: The non-reactive BS pattern may appear related to many neonatal neurological disorders and is associated with early and refractory neonatal seizures. It is clearly associated with elevated morbidity and mortality and to the development of post-neonatal epilepsy.RESUMO Convulsões representam o evento neurológico mais freqüente no período neonatal e a etiologia das crises parece ser o aspecto clínico mais associado ao prognóstico a longo prazo. Entretanto, existem padrões anormais de EEG, que de forma consistente relacionam-se a prognóstico, entre eles o padrão de surto - supressão. OBJETIVO: Este estudo teve

Seizure-Onset Mapping Based on Time-Variant Multivariate Functional Connectivity Analysis of High-Dimensional Intracranial EEG: A Kalman Filter Approach.

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Lie, Octavian V; van Mierlo, Pieter

2017-01-01

The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach.

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

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Tsiouris, Κostas Μ; Pezoulas, Vasileios C; Zervakis, Michalis; Konitsiotis, Spiros; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I

2018-05-17

The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic seizure prediction using EEG signals, expanding the use of deep learning algorithms with convolutional neural networks (CNN). A pre-analysis is initially performed to find the optimal architecture of the LSTM network by testing several modules and layers of memory units. Based on these results, a two-layer LSTM network is selected to evaluate seizure prediction performance using four different lengths of preictal windows, ranging from 15 min to 2 h. The LSTM model exploits a wide range of features extracted prior to classification, including time and frequency domain features, between EEG channels cross-correlation and graph theoretic features. The evaluation is performed using long-term EEG recordings from the open CHB-MIT Scalp EEG database, suggest that the proposed methodology is able to predict all 185 seizures, providing high rates of seizure prediction sensitivity and low false prediction rates (FPR) of 0.11-0.02 false alarms per hour, depending on the duration of the preictal window. The proposed LSTM-based methodology delivers a significant increase in seizure prediction performance compared to both traditional machine learning techniques and convolutional neural networks that have been previously evaluated in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

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Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

99mTc-HMPAO Brain SPECT in Seizure Disorder: Comparison Brain SPECT, MRI / CT and EEG

International Nuclear Information System (INIS)

Yang, Hyung In; Im, Ju Hyuk; Choi, Chang Woon; Lee, Dong Soo; Chung, June Key; No, Jae Kyu; Lee, Myung Chul; Koh, Chang Soon

1994-01-01

We studied 115 patients with seizure who had been performed brain SPECT brain MRI of CT and EEG. To evaluate the pattern of brain SPECT in seizure patients 28 of them had secondary epilepsies, 87 had primary epilepsies. In primary epilepsies, 42 were generalized seizure and 45 were partial seizure. The causes of secondary epilepsies were congenital malformation, cerebromalacia, cerebral infarction ultiple sclerosis, AV-malformation. granuloma and etc, in order. In 28 secondary epilepsies, 25 of them, brain SPECT lesions was concordant with MRI or CT lesions. 3 were disconcordant. The brain SPECT findings of generalized seizure were normal in 22 patients, diffuse irregular decreased perfusion in 8, decreased in frontal cortex in 4. temporal in 5 and frontotemporal in 3. In 45 partial seizure, 19 brain SPECT were concordant with EEG (42.4%).

Fast automatic analysis of antenatal dexamethasone on micro-seizure activity in the EEG

International Nuclear Information System (INIS)

Rastin, S.J.; Unsworth, C.P.; Bennet, L.

2010-01-01

Full text: In this work wc develop an automatic scheme for studying the effect of the antenatal Dexamethasone on the EEG activity. To do so an FFT (Fast Fourier Transform) based detector was designed and applied to the EEG recordings obtained from two groups of fetal sheep. Both groups received two injections with a time delay of 24 h between them. However the applied medicine was different for each group (Dex and saline). The detector developed was used to automatically identify and classify micro-seizures that occurred in the frequency bands corresponding to the EEG transients known as slow waves (2.5 14 Hz). For each second of the data recordings the spectrum was computed and the rise of the energy in each predefined frequency band then counted when the energy level exceeded a predefined corresponding threshold level (Where the threshold level was obtained from the long term average of the spectral points at each band). Our results demonstrate that it was possible to automatically count the micro-seizures for the three different bands in a time effective manner. It was found that the number of transients did not strongly depend on the nature of the injected medicine which was consistent with the results manually obtained by an EEG expert. Tn conclusion, the automatic detection scheme presented here would allow for rapid micro-seizure event identification of hours of highly sampled EEG data thus providing a valuable time-saving device.

Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection.

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Mathieson, Sean R; Livingstone, Vicki; Low, Evonne; Pressler, Ronit; Rennie, Janet M; Boylan, Geraldine B

2016-10-01

Phenobarbital increases electroclinical uncoupling and our preliminary observations suggest it may also affect electrographic seizure morphology. This may alter the performance of a novel seizure detection algorithm (SDA) developed by our group. The objectives of this study were to compare the morphology of seizures before and after phenobarbital administration in neonates and to determine the effect of any changes on automated seizure detection rates. The EEGs of 18 term neonates with seizures both pre- and post-phenobarbital (524 seizures) administration were studied. Ten features of seizures were manually quantified and summary measures for each neonate were statistically compared between pre- and post-phenobarbital seizures. SDA seizure detection rates were also compared. Post-phenobarbital seizures showed significantly lower amplitude (pphenobarbital reduces both the amplitude and propagation of seizures which may help to explain electroclinical uncoupling of seizures. The seizure detection rate of the algorithm was unaffected by these changes. The results suggest that users should not need to adjust the SDA sensitivity threshold after phenobarbital administration. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Preictal Dynamics of EEG Complexity in Intracranially Recorded Epileptic Seizure

Czech Academy of Sciences Publication Activity Database

Bob, P.; Roman, R.; Světlák, M.; Kukleta, M.; Chládek, Jan; Brázdil, M.

2014-01-01

Roč. 93, č. 23 (2014), el151:1-4 ISSN 0025-7974 R&D Projects: GA MŠk(CZ) LO1212 Institutional support: RVO:68081731 Keywords : EEG * epileptic Seizure Subject RIV: FS - Medical Facilities ; Equipment Impact factor: 5.723, year: 2014

Seizure phenotypes, periodicity, and sleep-wake pattern of seizures in Kcna-1 null mice.

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Wright, Samantha; Wallace, Eli; Hwang, Youngdeok; Maganti, Rama

2016-02-01

This study was undertaken to describe seizure phenotypes, natural progression, sleep-wake patterns, as well as periodicity of seizures in Kcna-1 null mutant mice. These mice were implanted with epidural electroencephalography (EEG) and electromyography (EMG) electrodes, and simultaneous video-EEG recordings were obtained while animals were individually housed under either diurnal (LD) condition or constant darkness (DD) over ten days of recording. The video-EEG data were analyzed to identify electrographic and behavioral phenotypes and natural progression and to examine the periodicity of seizures. Sleep-wake patterns were analyzed to understand the distribution and onset of seizures across the sleep-wake cycle. Four electrographically and behaviorally distinct seizure types were observed. Regardless of lighting condition that animals were housed in, Kcna-1 null mice initially expressed only a few of the most severe seizure types that progressively increased in frequency and decreased in seizure severity. In addition, a circadian periodicity was noted, with seizures peaking in the first 12h of the Zeitgeber time (ZT) cycle, regardless of lighting conditions. Interestingly, seizure onset differed between lighting conditions where more seizures arose out of sleep in LD conditions, whereas under DD conditions, the majority occurred out of the wakeful state. We suggest that this model be used to understand the circadian pattern of seizures as well as the pathophysiological implications of sleep and circadian disturbances in limbic epilepsies. Copyright © 2015 Elsevier Inc. All rights reserved.

{sup 99m}Tc-HMPAO Brain SPECT in Seizure Disorder: Comparison Brain SPECT, MRI / CT and EEG

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Yang, Hyung In [Kyunghee University Hospital, Seoul (Korea, Republic of); Im, Ju Hyuk; Choi, Chang Woon; Lee, Dong Soo; Chung, June Key; No, Jae Kyu; Lee, Myung Chul; Koh, Chang Soon [Seoul National University Hospital, Seoul (Korea, Republic of)

1994-03-15

We studied 115 patients with seizure who had been performed brain SPECT brain MRI of CT and EEG. To evaluate the pattern of brain SPECT in seizure patients 28 of them had secondary epilepsies, 87 had primary epilepsies. In primary epilepsies, 42 were generalized seizure and 45 were partial seizure. The causes of secondary epilepsies were congenital malformation, cerebromalacia, cerebral infarction ultiple sclerosis, AV-malformation. granuloma and etc, in order. In 28 secondary epilepsies, 25 of them, brain SPECT lesions was concordant with MRI or CT lesions. 3 were disconcordant. The brain SPECT findings of generalized seizure were normal in 22 patients, diffuse irregular decreased perfusion in 8, decreased in frontal cortex in 4. temporal in 5 and frontotemporal in 3. In 45 partial seizure, 19 brain SPECT were concordant with EEG (42.4%).

Correlation of Tc-99m HMPAO SPECT with surface EEG, MR, and CT for noninvasive localization of seizure foci

International Nuclear Information System (INIS)

Engelstad, B.L.; Laxer, K.D.; Dickson, H.S.; Cooper, K.E.; Huberty, J.P.; White, D.L.

1987-01-01

Some patients with refractory seizure disorders are candidates for surgical management. Correct preoperative lateralization is essential. Of 19 patients with seizure disorders who underwent Tc-99m HMPAO SPECT, 14 were considered to have ultimately had definitive localization by other means: consistently abnormal surface electroencephalogram (EEG), subdural or deep electrode EEG, EEG response to resection, abnormal histopatholgy, or grossly abnormal MR image. Lateralization with SPECT was (1) focal or regional hypoperfusion (11 patients) or (2) discrete focal hyperperfusion (one patient). Correct lateralization was obtained in ten of 14 with SPECT, nine of 14 with surface EEG, seven of 12 with MR, and one of eight with CT. Preoperative evaluation of patients with medically refractory seizures can be aided by Tc-99m HMPAO SPECT

Cortical network dysfunction in musicogenic epilepsy reflecting the role of snowballing emotional processes in seizure generation: an fMRI-EEG study.

Science.gov (United States)

Diekmann, Volker; Hoppner, Anselm Cornelius

2014-03-01

Patients suffering from musicogenic epilepsy have focal seizures triggered by auditory stimuli. In some of these patients, the emotions associated with the music appear to play a role in the process triggering the seizure, however, the significance of these emotions and the brain regions involved are unclear. In order to shed some light on this, we conducted fMRI and EEG in a case of musicogenic epilepsy. In a 32-year-old male patient with seizures induced by a specific piece of Russian music, we performed video-EEG monitoring as well as simultaneous fMRI and EEG registration. Video-EEG monitoring revealed a left temporo-frontal epileptogenic focus. During fMRI-EEG co-registration, BOLD signal alterations were not only found in the epileptogenic focus but also in areas known for their role in the processing of emotions. Prior to a seizure in some of these areas, BOLD contrasts exponentially increased or decreased. These results suggest that in our case, dysfunction of the regulation processes of the musically-induced emotions, and not the musical stimulus itself, led to the seizures.

Emotional stimuli-provoked seizures potentially misdiagnosed as psychogenic non-epileptic attacks: A case of temporal lobe epilepsy with amygdala enlargement

Directory of Open Access Journals (Sweden)

Hidetaka Tamune

Full Text Available The association between emotional stimuli and temporal lobe epilepsy (TLE is largely unknown. Here, we report the case of a depressed, 50-year-old female complaining of episodes of a “spaced out” experience precipitated by emotional stimuli. Psychogenic non-epileptic attacks were suspected. However, video-EEG coupled with emotional stimuli-provoked procedures and MRI findings of amygdala enlargement, led to the diagnosis of left TLE. Accurate diagnosis and explanation improved her subjective depression and seizure frequency. This case demonstrated that emotional stimuli can provoke seizures in TLE and suggested the involvement of the enlarged amygdala and the modulation of emotion-related neural circuits. Keywords: Video-EEG, Psychogenic non-epileptic attacks, Temporal lobe epilepsy, Amygdala enlargement, Reflex seizure, Provoked seizure

Predicting seizure by modeling synaptic plasticity based on EEG signals - a case study of inherited epilepsy

Science.gov (United States)

Zhang, Honghui; Su, Jianzhong; Wang, Qingyun; Liu, Yueming; Good, Levi; Pascual, Juan M.

2018-03-01

This paper explores the internal dynamical mechanisms of epileptic seizures through quantitative modeling based on full brain electroencephalogram (EEG) signals. Our goal is to provide seizure prediction and facilitate treatment for epileptic patients. Motivated by an earlier mathematical model with incorporated synaptic plasticity, we studied the nonlinear dynamics of inherited seizures through a differential equation model. First, driven by a set of clinical inherited electroencephalogram data recorded from a patient with diagnosed Glucose Transporter Deficiency, we developed a dynamic seizure model on a system of ordinary differential equations. The model was reduced in complexity after considering and removing redundancy of each EEG channel. Then we verified that the proposed model produces qualitatively relevant behavior which matches the basic experimental observations of inherited seizure, including synchronization index and frequency. Meanwhile, the rationality of the connectivity structure hypothesis in the modeling process was verified. Further, through varying the threshold condition and excitation strength of synaptic plasticity, we elucidated the effect of synaptic plasticity to our seizure model. Results suggest that synaptic plasticity has great effect on the duration of seizure activities, which support the plausibility of therapeutic interventions for seizure control.

Seizure classification in EEG signals utilizing Hilbert-Huang transform

OpenAIRE

Oweis, Rami J; Abdulhay, Enas W

2011-01-01

Abstract Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Method Discrimination in this ...

Cerebral blood flow during paroxysmal EEG activation induced by sleep in patients with complex partial seizures

International Nuclear Information System (INIS)

Gozukirmizi, E.; Meyer, J.S.; Okabe, T.; Amano, T.; Mortel, K.; Karacan, I.

1982-01-01

Cerebral blood flow (CBF) measurements were combined with sleep polysomnography in nine patients with complex partial seizures. Two methods were used: the 133Xe method for measuring regional (rCBF) and the stable xenon CT method for local (LCBF). Compared to nonepileptic subjects, who show diffuse CBF decreases during stages I-II, non-REM sleep onset, patients with complex partial seizures show statistically significant increases in CBF which are maximal in regions where the EEG focus is localized and are predominantly seen in one temporal region but are also propagated to other cerebral areas. Both CBF methods gave comparable results, but greater statistical significance was achieved by stable xenon CT methodology. CBF increases are more diffuse than predicted by EEG paroxysmal activity recorded from scalp electrodes. An advantage of the 133Xe inhalation method was achievement of reliable data despite movement of the head. This was attributed to the use of a helmet which maintained the probes approximated to the scalp. Disadvantages were poor resolution (7 cm3) and two-dimensional information. The advantage of stable xenon CT method is excellent resolution (80 mm3) in three dimensions, but a disadvantage is that movement of the head in patients with seizure disorders may limit satisfactory measurements

Confirming psychogenic nonepileptic seizures with video-EEG: sex matters.

Science.gov (United States)

Noe, Katherine H; Grade, Madeline; Stonnington, Cynthia M; Driver-Dunckley, Erika; Locke, Dona E C

2012-03-01

The influence of gender on psychogenic nonepileptic seizures (PNES) diagnosis was examined retrospectively in 439 subjects undergoing video-EEG (vEEG) for spell classification, of whom 142 women and 42 men had confirmed PNES. The epileptologist's predicted diagnosis was correct in 72% overall. Confirmed epilepsy was correctly predicted in 94% men and 88% women. In contrast, confirmed PNES was accurately predicted in 86% women versus 61% men (p=0.003). Sex-based differences in likelihood of an indeterminate admission were not observed for predicted epilepsy or physiologic events, but were for predicted PNES (39% men, 12% women, p=0.0002). More frequent failure to record spells in men than women with predicted PNES was not explained by spell frequency, duration of monitoring, age, medication use, or personality profile. PNES are not only less common in men, but also more challenging to recognize in the clinic, and even when suspected more difficult to confirm with vEEG. Copyright © 2012 Elsevier Inc. All rights reserved.

EEG epileptiform abnormalities at admission to a rehabilitation department predict the risk of seizures in disorders of consciousness following a coma.

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Bagnato, Sergio; Boccagni, Cristina; Sant'Angelo, Antonino; Prestandrea, Caterina; Virgilio, Vittorio; Galardi, Giuseppe

2016-03-01

Seizures affect about a quarter of patients with disorders of consciousness (DOC) after a coma. We investigated whether the presence of epileptiform abnormalities (EAs) in the electroencephalogram (EEG) of patients with DOC may predict the occurrence of seizures. Moreover, we evaluated whether EAs have a prognostic role in these patients. This was a retrospective single-center cohort study of patients hospitalized between January 2005 and December 2014 in a rehabilitation department (mean time from acute brain injury: 46.1 days). We analyzed 30-minute EEGs at admittance for 112 patients with unresponsive wakefulness syndrome (UWS) or in a minimally conscious state (MCS), then compared occurrence of seizures over the following three months across patients with absent, unilateral, and bilateral EAs (generalized or bilateral independent). Outcomes at three months were assessed in the same groups using the Coma Recovery Scale Revised. Epileptiform abnormalities were observed in 38 patients (33.9%). Of these, 25 were unilateral, and 13 were bilateral. Seizures occurred in 84.6% of patients with bilateral EAs, which was significantly higher than in patients without EAs (10.8%, p<0.001) or with unilateral EAs (24%, p=0.001). The presence of EAs was not related to etiology or different DOC and did not significantly affect outcomes at three months. Patients with EAs at admission to a rehabilitation department have an increased risk of seizures. Specifically, most patients with bilateral EAs had seizures within the following 3 months. Evaluation of EAs in EEGs of patients with DOC may give valuable information in the management of antiepileptic drug treatment. Copyright © 2015 Elsevier Inc. All rights reserved.

Two cases of childhood narcolepsy mimicking epileptic seizures in video-EEG/EMG.

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Yanagishita, Tomoe; Ito, Susumu; Ohtani, Yui; Eto, Kaoru; Kanbayashi, Takashi; Oguni, Hirokazu; Nagata, Satoru

2018-06-06

Narcolepsy is characterized by excessive sleepiness, hypnagogic hallucinations, and sleep paralysis, and can occur with or without cataplexy. Here, we report two children with narcolepsy presenting with cataplexy mimicking epileptic seizures as determined by long-term video-electroencephalography (EEG) and electromyography (EMG) monitoring. Case 1 was a 15-year-old girl presenting with recurrent episodes of "convulsions" and loss of consciousness, who was referred to our hospital with a diagnosis of epilepsy showing "convulsions" and "complex partial seizures". The long-term video-polygraph showed a clonic attack lasting for 15 s, which corresponded to 1-2 Hz with interruption of mentalis EMG discharges lasting for 70-300 ms without any EEG changes. Narcolepsy was suspected due to the attack induced by hearty laughs and the presence of sleep attacks, and confirmed by low orexin levels in cerebrospinal fluid (CSF). Case 2 was an 11-year-old girl presenting with recurrent episodes of myoclonic attacks simultaneously with dropping objects immediately after hearty laughs, in addition to sleep attacks, hypnagogic hallucinations, and sleep paralysis. The long-term video-polygraph showed a subtle attack, characterized by dropping chopsticks from her hand, which corresponded to an interruption of ongoing deltoid EMG discharges lasting 140 ms without any EEG changes. A diagnosis of narcolepsy was confirmed by the low orexin levels in CSF. These cases demonstrate that children with narcolepsy may have attacks of cataplexy that resemble clonic or myoclonic seizures. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Analyzing large data sets acquired through telemetry from rats exposed to organophosphorous compounds: an EEG study.

Science.gov (United States)

de Araujo Furtado, Marcio; Zheng, Andy; Sedigh-Sarvestani, Madineh; Lumley, Lucille; Lichtenstein, Spencer; Yourick, Debra

2009-10-30

The organophosphorous compound soman is an acetylcholinesterase inhibitor that causes damage to the brain. Exposure to soman causes neuropathology as a result of prolonged and recurrent seizures. In the present study, long-term recordings of cortical EEG were used to develop an unbiased means to quantify measures of seizure activity in a large data set while excluding other signal types. Rats were implanted with telemetry transmitters and exposed to soman followed by treatment with therapeutics similar to those administered in the field after nerve agent exposure. EEG, activity and temperature were recorded continuously for a minimum of 2 days pre-exposure and 15 days post-exposure. A set of automatic MATLAB algorithms have been developed to remove artifacts and measure the characteristics of long-term EEG recordings. The algorithms use short-time Fourier transforms to compute the power spectrum of the signal for 2-s intervals. The spectrum is then divided into the delta, theta, alpha, and beta frequency bands. A linear fit to the power spectrum is used to distinguish normal EEG activity from artifacts and high amplitude spike wave activity. Changes in time spent in seizure over a prolonged period are a powerful indicator of the effects of novel therapeutics against seizures. A graphical user interface has been created that simultaneously plots the raw EEG in the time domain, the power spectrum, and the wavelet transform. Motor activity and temperature are associated with EEG changes. The accuracy of this algorithm is also verified against visual inspection of video recordings up to 3 days after exposure.

Proepileptic patterns in EEG of WAG/Rij rats

Science.gov (United States)

Grubov, Vadim V.; Sitnikova, Evgenia Yu.; Nedaivozov, Vladimir O.; Koronovskii, Alexey A.

2018-04-01

In this paper we study specific oscillatory patterns on EEG signals of WAG/Rij rats. These patterns are known as proepileptic because they occur in time period during the development of absence-epilepsy before fully-formed epileptic seizures. In the paper we analyze EEG signals of WAG/Rij rats with continuous wavelet transform and empirical mode decomposition in order to find particular features of epileptic spike-wave discharges and nonepileptic sleep spindles. Then we introduce proepileptic activity as patterns that combine features of epileptic and non-epileptic activity. We analyze proepileptic activity in order to specify its features and time-frequency structure.

Epileptiform discharges in EEG and seizure risk in adolescent children of women with epilepsy.

Science.gov (United States)

Samuel, Joseph; Jose, Manna; Nandini, V S; Thomas, Sanjeev V

2017-09-01

We aimed to study the epileptiform discharges (ED) and seizure risk in EEG of 12-18-year-old children of women with epilepsy (WWE). Children of WWE who were prospectively followed up in the Kerala registry of epilepsy and pregnancy (KREP), aged 12-16years (n=92; males 48, females 44) underwent clinical evaluation and a 30-min digital 18-channel EEG. The EEG showed epileptiform discharges in 13 children (5 males and 8 females). The EDs were generalized in 9 and focal in 4 (occipital 2, frontal 1, and centroparietal 1). They had significantly higher risk of ED (odds ratio 4.02, 95% CI 1.04-15.51) when compared to published prevalence of ED in healthy children. There were 2 children with epilepsy (one with localization-related epilepsy and the other generalized epilepsy). The children under study had a trend towards higher prevalence of epilepsy (odds ratio 3.39, 95% CI 0.82-13.77) when compared to age specific prevalence of epilepsy from community surveys in same region. Children of WWE showed increased risk of ED in EEG and trend towards increased seizure risk when compared to healthy children. Copyright © 2017 Elsevier Inc. All rights reserved.

Early seizure detection in an animal model of temporal lobe epilepsy

Science.gov (United States)

Talathi, Sachin S.; Hwang, Dong-Uk; Ditto, William; Carney, Paul R.

2007-11-01

The performance of five seizure detection schemes, i.e., Nonlinear embedding delay, Hurst scaling, Wavelet Scale, autocorrelation and gradient of accumulated energy, in their ability to detect EEG seizures close to the seizure onset time were evaluated to determine the feasibility of their application in the development of a real time closed loop seizure intervention program (RCLSIP). The criteria chosen for the performance evaluation were, high statistical robustness as determined through the predictability index, the sensitivity and the specificity of a given measure to detect an EEG seizure, the lag in seizure detection with respect to the EEG seizure onset time, as determined through visual inspection and the computational efficiency for each detection measure. An optimality function was designed to evaluate the overall performance of each measure dependent on the criteria chosen. While each of the above measures analyzed for seizure detection performed very well in terms of the statistical parameters, the nonlinear embedding delay measure was found to have the highest optimality index due to its ability to detect seizure very close to the EEG seizure onset time, thereby making it the most suitable dynamical measure in the development of RCLSIP in rat model with chronic limbic epilepsy.

Non-invasive imaging of epileptic seizures in vivo using photoacoustic tomography

Energy Technology Data Exchange (ETDEWEB)

Zhang Qizhi; Carney, Paul R; Yuan Zhen; Jiang Huabei [J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611 (United States); Liu Zhao [Department of Pediatrics, Division of Pediatric Neurology, University of Florida, Gainesville, FL 32610 (United States); Chen Huanxin; Roper, Steven N [Department of Neurosurgery, University of Florida, Gainesville, FL 32610-0265 (United States)], E-mail: hjiang@bme.ufl.edu

2008-04-07

Non-invasive laser-induced photoacoustic tomography (PAT) is an emerging imaging modality that has the potential to image the dynamic function of the brain due to its unique ability of imaging biological tissues with high optical contrast and ultrasound resolution. Here we report the first application of our finite-element-based PAT for imaging of epileptic seizures in an animal model. In vivo photoacoustic images were obtained in rats with focal seizures induced by microinjection of bicuculline, a GABA{sub A} antagonist, into the neocortex. The seizure focus was accurately localized by PAT as confirmed with gold-standard electroencephalogram (EEG). Compared to the existing neuroimaging modalities, PAT not only has the unprecedented advantage of high spatial and temporal resolution in a single imaging modality, but also is portable and low in cost, making it possible to bring brain imaging to the bedside.

Early seizure propagation from the occipital lobe to medial temporal structures and its surgical implication.

Science.gov (United States)

Usui, Naotaka; Mihara, Tadahiro; Baba, Koichi; Matsuda, Kazumi; Tottori, Takayasu; Umeoka, Shuichi; Nakamura, Fumihiro; Terada, Kiyohito; Usui, Keiko; Inoue, Yushi

2008-12-01

Intracranial EEG documentation of seizure propagation from the occipital lobe to medial temporal structures is relatively rare. We retrospectively analyzed intracranial EEG recorded with electrodes implanted in the medial temporal lobe in patients who underwent occipital lobe surgery. Four patients with occipital lesions, who underwent intracranial EEG monitoring with intracerebral electrodes implanted in the medial temporal lobe prior to occipital lobe surgery, were studied. Subdural electrodes were placed over the occipital lobe and adjacent areas. Intracerebral electrodes were implanted into bilateral hippocampi and the amygdala in three patients, and in the hippocampus and amygdala ipsilateral to the lesion in one. In light of the intracranial EEG findings, the occipital lobe was resected but the medial temporal lobe was spared in all patients. The follow-up period ranged from six to 16 years, and seizure outcome was Engel Class I in all patients. Sixty six seizures were analyzed. The majority of the seizures originated from the occipital lobe. In complex partial seizures, ictal discharges propagated to the medial temporal lobe. No seizures originating from the temporal lobe were documented. In some seizures, the ictal-onset zone could not be identified. In these seizures, very early propagation to the medial temporal lobe was observed. Interictal spikes were recorded in the medial temporal lobe in all cases. Intracranial EEG revealed very early involvement of the medial temporal lobe in some seizures. Seizure control was achieved without resection of the medial temporal structures.

Electroencephalography after a single unprovoked seizure.

Science.gov (United States)

Debicki, Derek B

2017-07-01

Electroencephalography (EEG) is an essential diagnostic tool in the evaluation of seizure disorders. In particular, EEG is used as an additional investigation for a single unprovoked seizure. Epileptiform abnormalities are related to seizure disorders and have been shown to predict recurrent unprovoked seizures (i.e., a clinical definition of epilepsy). Thus, the identification of epileptiform abnormalities after a single unprovoked seizure can inform treatment options. The current review addresses the relationship between EEG abnormalities and seizure recurrence. This review also addresses factors that are found to improve the yield of recording epileptiform abnormalities including timing of EEG relative to the new-onset seizure, use of repeat studies, use of sleep deprivation and prolonged recordings. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Effect of carbamazepine (Tegretol) on seizure and EEG patterns in monkeys with alumina-induced focal motor and hippocampal foci.

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David, J; Grewal, R S

1976-12-01

Qualitative and quantitative aspects of chronic carbamazepine (Tegretol) medication on focal seizures and associated interictal EEG abnormalities in Rhesus monkeys with alumina-induced foci in either the sensorimotor cortex or the hipocampus was investigated. In both groups of animals, carbamazepine produced qualitative control of visible seizures and reduced intracortical spike propagation, but did not cause complete normalization of the background EEG; quantitative indices, such as spike density and amount of paroxysmal discharge representative of abnormal EEG activity, were significantly reduced with respect to predrug values during medication and after cessation as well. Threshold to pentylenetetrazol was elevated by carbamazepine in both groups of epileptic monkeys. Aggressivity and other clinical manifestations in monekys with hippocampal foci were markedly reduced by carbamazepine.

On seeing the trees and the forest: single-signal and multisignal analysis of periictal intracranial EEG.

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Schindler, Kaspar; Gast, Heidemarie; Goodfellow, Marc; Rummel, Christian

2012-09-01

Epileptic seizures are associated with a dysregulation of electrical brain activity on many different spatial scales. To better understand the dynamics of epileptic seizures, that is, how the seizures initiate, propagate, and terminate, it is important to consider changes of electrical brain activity on different spatial scales. Herein we set out to analyze periictal electrical brain activity on comparatively small and large spatial scales by assessing changes in single intracranial electroencephalography (EEG) signals and of averaged interdependences of pairs of EEG signals. Single and multiple EEG signals are analyzed by combining methods from symbolic dynamics and information theory. This computationally efficient approach is chosen because at its core it consists of analyzing the occurrence of patterns and bears analogy to classical visual EEG reading. Symbolization is achieved by first mapping the EEG signals into bit strings, that is, long sequences of zeros and ones, depending solely on whether their amplitudes increase or decrease. Bit strings reflect relational aspects between consecutive values of the original EEG signals, but not the values themselves. For each bit string the relative frequencies of the different constituent short bit patterns are then determined and used to compute two information theoretical measures: (1) redundancy (R) of single bit strings characterizes electrical brain activity on a comparatively small spatial scale represented by a single EEG signal and (2) averaged pair-wise mutual information with all other bit strings (M), which allows tracking of larger-scale EEG dynamics. We analyzed 20 periictal intracranial EEG recordings from five patients with pharmacoresistant temporal lobe epilepsy. At seizure onset, R first strongly increased and then decreased toward seizure termination, whereas M gradually increased throughout the seizure. Bit strings with maximal R were always derived from EEG signals recorded from the visually

Seizure semiology and electroencephalography in young children with lesional temporal lobe epilepsy.

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Lv, Rui-Juan; Sun, Zhen-Rong; Cui, Tao; Shao, Xiao-Qiu

2014-02-01

This study aimed to discuss the clinical features of seizure semiology and electroencephalography (EEG) in young children with lesional temporal lobe epilepsy (TLE). Children with lesional TLE received presurgical evaluation for intractable epilepsy. They were followed up for more than one year after temporal lobectomy. We reviewed the medical history and video-EEG monitoring of children with TLE to analyze the semiology of seizures and EEG findings and compared the semiology of seizures and EEG findings of childhood TLE and adult TLE. A total of 84 seizures were analyzed in 11 children (aged 23-108 months). The age of seizure onset was from 1 month to 26 months (a mean of 17.6 months). All of the patients exhibited prominent motor manifestations including epileptic spasm, tonic seizure, and unilateral clonic seizure. Seven children manifested behavioral arrest similar to an automotor seizure in adult TLE but with a shorter duration and higher frequency. The automatisms were typically orofacial, whereas manual automatisms were rarely observed. The EEG recordings revealed that diffuse discharge patterns were more common in younger children, whereas focal or unilateral patterns were more typical in older children. All of the patients were seizure-free after temporal lobectomy with more than one-year follow-up. All of the children had a mental development delay or regression; however, there was improvement after surgery, especially in those with surgery performed early. In contrast to TLE in adults, young children with lesional TLE probably represent a distinct nosological and probably less homogeneous syndrome. Although they had generalized clinical and electrographic features, resective epilepsy surgery should be considered as early as possible to obtain seizure control and improvement in mental development. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Sleep disruption increases seizure susceptibility: Behavioral and EEG evaluation of an experimental model of sleep apnea.

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Hrnčić, Dragan; Grubač, Željko; Rašić-Marković, Aleksandra; Šutulović, Nikola; Šušić, Veselinka; Bjekić-Macut, Jelica; Stanojlović, Olivera

2016-03-01

Sleep disruption accompanies sleep apnea as one of its major symptoms. Obstructive sleep apnea is particularly common in patients with refractory epilepsy, but causing factors underlying this are far from being resolved. Therefore, translational studies regarding this issue are important. Our aim was to investigate the effects of sleep disruption on seizure susceptibility of rats using experimental model of lindane-induced refractory seizures. Sleep disruption in male Wistar rats with implanted EEG electrodes was achieved by treadmill method (belt speed set on 0.02 m/s for working and 0.00 m/s for stop mode, respectively). Animals were assigned to experimental conditions lasting 6h: 1) sleep disruption (sleep interrupted, SI; 30s working and 90 s stop mode every 2 min; 180 cycles in total); 2) activity control (AC, 10 min working and 30 min stop mode, 9 cycles in total); 3) treadmill chamber control (TC, only stop mode). Afterwards, the animals were intraperitoneally treated with lindane (L, 4 mg/kg, SI+L, AC+L and TC+L groups) or dimethylsulfoxide (DMSO, SIc, ACc and TCc groups). Convulsive behavior was assessed by seizure incidence, latency time to first seizure, and its severity during 30 min after drug administration. Number and duration of ictal periods were determined in recorded EEGs. Incidence and severity of lindane-induced seizures were significantly increased, latency time significantly decreased in animals undergoing sleep disruption (SI+L group) compared with the animals from TC+L. Seizure latency was also significantly decreased in SI+L compared to AC+L groups. Number of ictal periods were increased and duration of it presented tendency to increase in SI+L comparing to AC+L. No convulsive signs were observed in TCc, ACc and SIc groups, as well as no ictal periods in EEG. These results indicate sleep disruption facilitates induction of epileptic activity in rodent model of lindane-epilepsy enabling translational research of this phenomenon. Copyright �

Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG.

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van Mierlo, Pieter; Lie, Octavian; Staljanssens, Willeke; Coito, Ana; Vulliémoz, Serge

2018-04-26

We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25-35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred.

CLINICAL AND RADIOLOGICAL EVALUATION OF NEW - ONSET EPILETIC SEIZURES IN A TERTIARY CARE HOSPITAL

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Chalapathi Rao

2015-09-01

Full Text Available BACKGROUND: Epilepsy is one of the most familiar neurological disorders which can cause bodily injury and death from inadequately treated or untreated cases. The imaging and EEG of new onset seizures is done with different indications, to identify an acute illness as the underline course for the seizure and possible neurological deficit. To this purpose we have evaluated new onset seizures in adult patients in correlation with their clinical profile, Electroencephalography (EEG and Computerized tomography (CT imaging of brain. METHODS: This cro ss sectional study was studied in 100 adult patients, presenting with seizures attending the Emergency department, General Medicine and Neurology wards and OPD of Tertiary care teaching hospital during the period of March 2006 to March 2008. All the patien ts were examined clinically and subjected to CT imaging of brain and EEG. Other necessary blood investigations were also done. Correlation between various seizures and CT scan brain and EEG were studied. Descriptive statistics were used to analyze the data . RESULTS: 63% of patients were in the age group of 20 - 39 years, 63% were males and 37% were females. 65% presented with GTCS, 35% with partial seizures. CT scan was found abnormal in 49.2% patients in GTCS, 71.4% in partial seizures. EEG showed abnormal p attern in 39% patients. 40% of the patients with partial seizures had epileptic form discharges. 33% patients had focal lesions on CT brain with normal EEG. CONCLUSION: Generalized Tonic clonic seizures were the commonest type of seizures was present, seen mostly in male patients. CT scan brain was abnormal in 57% of the patients. Neurocysticercosis and calcified granuloma were the commonest causes for seizures up to 3 rd decade of life. Majority of the patients with focal lesions on CT scan brain had epileptic form discharges on EEG which indicate a strong correlation of EEG with CT findings. Initiating the treatment with antiepileptic drugs was

Analysis of routine EEG usage in a general adult ICU.

LENUS (Irish Health Repository)

McHugh, J C

2009-09-01

Non-convulsive seizures and status epilepticus are common in brain-injured patients in intensive care units. Continuous electroencephalography (cEEG) monitoring is the most sensitive means of their detection. In centres where cEEG is unavailable, routine EEG is often utilized for diagnosis although its sensitivity is lower.

Hidden pattern discovery on epileptic EEG with 1-D local binary patterns and epileptic seizures detection by grey relational analysis.

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Kaya, Yılmaz

2015-09-01

This paper proposes a novel approach to detect epilepsy seizures by using Electroencephalography (EEG), which is one of the most common methods for the diagnosis of epilepsy, based on 1-Dimension Local Binary Pattern (1D-LBP) and grey relational analysis (GRA) methods. The main aim of this paper is to evaluate and validate a novel approach, which is a computer-based quantitative EEG analyzing method and based on grey systems, aimed to help decision-maker. In this study, 1D-LBP, which utilizes all data points, was employed for extracting features in raw EEG signals, Fisher score (FS) was employed to select the representative features, which can also be determined as hidden patterns. Additionally, GRA is performed to classify EEG signals through these Fisher scored features. The experimental results of the proposed approach, which was employed in a public dataset for validation, showed that it has a high accuracy in identifying epileptic EEG signals. For various combinations of epileptic EEG, such as A-E, B-E, C-E, D-E, and A-D clusters, 100, 96, 100, 99.00 and 100% were achieved, respectively. Also, this work presents an attempt to develop a new general-purpose hidden pattern determination scheme, which can be utilized for different categories of time-varying signals.

Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model.

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Zwanenburg, Alex; Andriessen, Peter; Jellema, Reint K; Niemarkt, Hendrik J; Wolfs, Tim G A M; Kramer, Boris W; Delhaas, Tammo

2015-03-01

Seizures below one minute in duration are difficult to assess correctly using seizure detection algorithms. We aimed to improve neonatal detection algorithm performance for short seizures through the use of trend templates for seizure onset and end. Bipolar EEG were recorded within a transiently asphyxiated ovine model at 0.7 gestational age, a common experimental model for studying brain development in humans of 30-34 weeks of gestation. Transient asphyxia led to electrographic seizures within 6-8 h. A total of 3159 seizures, 2386 shorter than one minute, were annotated in 1976 h-long EEG recordings from 17 foetal lambs. To capture EEG characteristics, five features, sensitive to seizures, were calculated and used to derive trend information. Feature values and trend information were used as input for support vector machine classification and subsequently post-processed. Performance metrics, calculated after post-processing, were compared between analyses with and without employing trend information. Detector performance was assessed after five-fold cross-validation conducted ten times with random splits. The use of trend templates for seizure onset and end in a neonatal seizure detection algorithm significantly improves the correct detection of short seizures using two-channel EEG recordings from 54.3% (52.6-56.1) to 59.5% (58.5-59.9) at FDR 2.0 (median (range); p seizures by EEG monitoring at the NICU.

Diagnostic decision-making after a first and recurrent seizure in adults

NARCIS (Netherlands)

Askamp, Jessica; van Putten, Michel Johannes Antonius Maria

2013-01-01

Purpose The role of EEG after a first seizure has been debated. Epileptiform EEG activity is a good predictor of seizure recurrence, but is reported in only 8-50% of first-seizure adult patients. Even if the EEG is abnormal, the opinions about treatment after a first seizure differ. The role of EEG

Validation of an automated seizure detection algorithm for term neonates

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Mathieson, Sean R.; Stevenson, Nathan J.; Low, Evonne; Marnane, William P.; Rennie, Janet M.; Temko, Andrey; Lightbody, Gordon; Boylan, Geraldine B.

2016-01-01

Objective The objective of this study was to validate the performance of a seizure detection algorithm (SDA) developed by our group, on previously unseen, prolonged, unedited EEG recordings from 70 babies from 2 centres. Methods EEGs of 70 babies (35 seizure, 35 non-seizure) were annotated for seizures by experts as the gold standard. The SDA was tested on the EEGs at a range of sensitivity settings. Annotations from the expert and SDA were compared using event and epoch based metrics. The effect of seizure duration on SDA performance was also analysed. Results Between sensitivity settings of 0.5 and 0.3, the algorithm achieved seizure detection rates of 52.6–75.0%, with false detection (FD) rates of 0.04–0.36 FD/h for event based analysis, which was deemed to be acceptable in a clinical environment. Time based comparison of expert and SDA annotations using Cohen’s Kappa Index revealed a best performing SDA threshold of 0.4 (Kappa 0.630). The SDA showed improved detection performance with longer seizures. Conclusion The SDA achieved promising performance and warrants further testing in a live clinical evaluation. Significance The SDA has the potential to improve seizure detection and provide a robust tool for comparing treatment regimens. PMID:26055336

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

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Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adeli, Hojjat

2017-09-27

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epileptiform abnormalities. This technique can be time-consuming, limited by technical artifact, provides variable results secondary to reader expertise level, and is limited in identifying abnormalities. Therefore, it is essential to develop a computer-aided diagnosis (CAD) system to automatically distinguish the class of these EEG signals using machine learning techniques. This is the first study to employ the convolutional neural network (CNN) for analysis of EEG signals. In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes. The proposed technique achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Contribution of EEG in transient neurological deficits.

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Lozeron, Pierre; Tcheumeni, Nadine Carole; Turki, Sahar; Amiel, Hélène; Meppiel, Elodie; Masmoudi, Sana; Roos, Caroline; Crassard, Isabelle; Plaisance, Patrick; Benbetka, Houria; Guichard, Jean-Pierre; Houdart, Emmanuel; Baudoin, Hélène; Kubis, Nathalie

2018-01-01

Identification of stroke mimics and 'chameleons' among transient neurological deficits (TND) is critical. Diagnostic workup consists of a brain imaging study, for a vascular disease or a brain tumour and EEG, for epileptiform discharges. The precise role of EEG in this diagnostic workup has, however, never been clearly delineated. However, this could be crucial in cases of atypical or incomplete presentation with consequences on disease management and treatment. We analysed the EEG patterns on 95 consecutive patients referred for an EEG within 7 days of a TND with diagnostic uncertainty. Patients were classified at the discharge or the 3-month follow-up visit as: 'ischemic origin', 'migraine aura', 'focal seizure', and 'other'. All patients had a brain imaging study. EEG characteristics were correlated to the TND symptoms, imaging study, and final diagnosis. Sixty four (67%) were of acute onset. Median symptom duration was 45 min. Thirty two % were 'ischemic', 14% 'migraine aura', 19% 'focal seizure', and 36% 'other' cause. EEGs were recorded with a median delay of 1.6 day after symptoms onset. Forty EEGs (42%) were abnormal. Focal slow waves were the most common finding (43%), also in the ischemic group (43%), whether patients had a typical presentation or not. Epileptiform discharges were found in three patients, one with focal seizure and two with migraine aura. Non-specific EEG focal slowing is commonly found in TND, and may last several days. We found no difference in EEG presentation between stroke mimics and stroke chameleons, and between other diagnoses.

Conversation analysis can help to distinguish between epilepsy and non-epileptic seizure disorders: a case comparison.

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Plug, Leendert; Sharrack, Basil; Reuber, Markus

2009-01-01

Factual items in patients' histories are of limited discriminating value in the differential diagnosis of epilepsy and non-epileptic seizures (NES). A number of studies using a transcript-based sociolinguistic research method inspired by Conversation Analysis (CA) suggest that it is helpful to focus on how patients talk. Previous reports communicated these findings by using particularly clear examples of diagnostically relevant interactional, linguistic and topical features from different patients. They did not discuss the sequential display of different features although this is crucially important from a conversation analytic point of view. This case comparison aims to show clinicians how the discriminating features are displayed by individual patients over the course of a clinical encounter. CA-inspired brief sequential analysis of two first 30-min doctor-patient encounters by a linguist blinded to all medical information. A gold standard diagnosis was made by the recording of a typical seizure with video-EEG. The patient with epilepsy volunteered detailed first person accounts of seizures. The NES patient exhibited resistance to focusing on individual seizure episodes and only provided a detailed seizure description after repeated prompting towards the end of the interview. Although both patients also displayed some linguistic features favouring the alternative diagnosis, the linguist's final diagnostic hypothesis matched the diagnosis made by video-EEG in both cases. This study illustrates the importance of the time point at which patients share information with the doctor. It supports the notion that close attention to how patients communicate can help in the differential diagnosis of seizures.

Video-EEG recording: a four-year clinical audit.

LENUS (Irish Health Repository)

O'Rourke, K

2012-02-03

In the setting of a regional neurological unit without an epilepsy surgery service as in our case, video-EEG telemetry is undertaken for three main reasons; to investigate whether frequent paroxysmal events represent seizures when there is clinical doubt, to attempt anatomical localization of partial seizures when standard EEG is unhelpful, and to attempt to confirm that seizures are non-epileptic when this is suspected. A clinical audit of all telemetry performed over a four-year period was carried out, in order to determine the clinical utility of this aspect of the service and to determine means of improving effectiveness in the unit. Analysis of the data showed a high rate of negative studies with no attacks recorded. Of the positive studies approximately 50% showed non-epileptic attacks. Strategies for improving the rate of positive investigations are discussed.

Assessment of seizure liability of Org 306039, a 5-HT2c agonist, using hippocampal brain slice and rodent EEG telemetry.

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Markgraf, Carrie G; DeBoer, Erik; Zhai, Jin; Cornelius, Lara; Zhou, Ying Ying; MacSweeney, Cliona

2014-01-01

Evaluation of the seizure potential for a CNS-targeted pharmaceutical compound before it is administered to humans is an important part of development. The current in vitro and in vivo studies were undertaken to characterize the seizure potential of the potent and selective 5-HT2c agonist Org 306039. Rat hippocampal slices (n=5) were prepared and Org 306039 was applied over a concentration range of 0-1000μM. Male Sprague-Dawley rats, implanted with telemetry EEG recording electrodes received either vehicle (n=4) or 100mg/kg Org 306039 (n=4) by oral gavage daily for 10days. EEG was recorded continuously for 22±1h post-dose each day. Post-dose behavior observations were conducted daily for 2h. Body temperature was measured at 1 and 2h post-dose. On Day 7, blood samples were drawn for pharmacokinetic analysis of Org 306039. In hippocampal slice, Org 306039 elicited a concentration-dependent increase in population spike area and number recorded from CA1 area, indicating seizure-genic potential. In telemetered rats, Org 306039 was associated with a decrease in body weight, a decrease in body temperature and the appearance of seizure-related behaviors and pre-seizure waveforms on EEG. One rat exhibited an overt seizure. Plasma concentrations of Org 306039 were similar among the 4 rats in the Org-treated group. Small group size made it difficult to determine a PK-PD relationship. These results indicate that the in vitro and in vivo models complement each other in the characterization of the seizure potential of CNS-targeted compounds such as the 5-HT2c agonist Org 306039. Copyright © 2014 Elsevier Inc. All rights reserved.

Mozart K.448 listening decreased seizure recurrence and epileptiform discharges in children with first unprovoked seizures: a randomized controlled study.

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Lin, Lung-Chang; Lee, Mei-Wen; Wei, Ruey-Chang; Mok, Hin-Kiu; Yang, Rei-Cheng

2014-01-13

Increasing numbers of reports show the beneficial effects of listening to Mozart music in decreasing epileptiform discharges as well as seizure frequency in epileptic children. There has been no effective method to reduce seizure recurrence after the first unprovoked seizure until now. In this study, we investigated the effect of listening to Mozart K.448 in reducing the seizure recurrence rate in children with first unprovoked seizures. Forty-eight children who experienced their first unprovoked seizure with epileptiform discharges were included in the study. They were randomly placed into treatment (n = 24) and control (n = 24) groups. Children in the treatment group listened to Mozart K.448 daily before bedtime for at least six months. Two patients in the treatment group were excluded from analysis due to discontinuation intervention. Finally, forty-six patients were analyzed. Most of these patients (89.1%) were idiopathic in etiology. Seizure recurrence rates and reduction of epileptiform discharges were compared. The average follow-up durations in the treatment and control groups were 18.6 ± 6.6 and 20.1 ± 5.1 months, respectively. The seizure recurrence rate was estimated to be significantly lower in the treatment group than the control group over 24 months (37.2% vs. 76.8%, p = 0.0109). Significant decreases in epileptiform discharges were also observed after 1, 2, and 6 months of listening to Mozart K.448 when compared with EEGs before listening to music. There were no significant differences in gender, mentality, seizure type, and etiology between the recurrence and non-recurrence groups. Although the case number was limited and control music was not performed in this study, the study revealed that listening to Mozart K.448 reduced the seizure recurrence rate and epileptiform discharges in children with first unprovoked seizures, especially of idiopathic etiology. We believe that Mozart K.448 could be a promising alternative treatment in patients with

Usefulness of a simple sleep-deprived EEG protocol for epilepsy diagnosis in de novo subjects.

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Giorgi, Filippo S; Perini, Daria; Maestri, Michelangelo; Guida, Melania; Pizzanelli, Chiara; Caserta, Anna; Iudice, Alfonso; Bonanni, Enrica

2013-11-01

In case series concerning the role of EEG after sleep deprivation (SD-EEG) in epilepsy, patients' features and protocols vary dramatically from one report to another. In this study, we assessed the usefulness of a simple SD-EEG method in well characterized patients. Among the 963 adult subjects submitted to SD-EEG at our Center, in the period 2003-2010, we retrospectively selected for analysis only those: (1) evaluated for suspected epileptic seizures; (2) with a normal/non-specific baseline EEG; (3) still drug-free at the time of SD-EEG; (4) with an MRI analysis; (5) with at least 1 year follow-up. SD-EEG consisted in SD from 2:00 AM and laboratory EEG from 8:00 AM to 10:30 AM. We analyzed epileptic interictal abnormalities (IIAs) and their correlations with patients' features. Epilepsy was confirmed in 131 patients. SD-EEG showed IIAs in 41.2% of all patients with epilepsy, and a 91.1% specificity for epilepsy diagnosis; IIAs types observed during SD-EEG are different in generalized versus focal epilepsies; for focal epilepsies, the IIAs yield in SD-EEG is higher than in second routine EEG. This simple SD-EEG protocol is very useful in de novo patients with suspected seizures. This study sheds new light on the role of SD-EEG in specific epilepsy populations. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Inter-modality comparisons of seizure focus lateralization in complex partial seizures

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Meyer, P.T.; Cortes-Blanco, A.; Pourdehnad, M.; Desiderio, L.; Jang, S.; Alavi, A.; Levy-Reis, I.

2001-01-01

Anterior temporal lobectomy offers a high chance of seizure-free outcome in patients suffering from drug-refractory complex partial seizure (CPS) originating from the temporal lobe. Other than EEG, several functional and morphologic imaging methods are used to define the spatial seizure origin. The present study was undertaken to compare the merits of fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET), magnetic resonance imaging (MRI) and single-voxel proton MR spectroscopy (MRS) for the lateralization of temporal lobe seizure foci. The clinical charts and imaging data of 43 consecutive CPS patients were reviewed. Based on surface EEG, 31 patients were classified with temporal lobe epilepsy (TLE; 25 lateralized, 6 not lateralized) and 12 with non-temporal lobe epilepsy. All were examined by FDG-PET, MRS and MRI within 6 weeks. FDG-PET and MRI were interpreted visually, while the N-acetyl-aspartate to creatine ratio was used for MRS interpretation. One FDG-PET scan was invalid due to seizure activity post injection. The MR spectra could not be evaluated in five cases bilaterally and three cases unilaterally for technical reasons. A total of 15 patients underwent anterior temporal lobectomy. All showed a beneficial postoperative outcome. When the proportions of agreement between FDG-PET (0.77), MRI (0.58) and MRS (0.56) and surface EEG in TLE cases were compared, there were no significant differences (P>0.10). However, FDG-PET showed a significantly higher agreement (0.93) than MRI (0.60; P=0.03) with the side of successful temporal lobectomy. The concordance of MRS with the side of successful temporal lobectomy was intermediate (0.75). When the results of functional and morphologic imaging were combined, no significant differences were found between the rates of agreement of FDG-PET/MRI and MRS/MRI with EEG (0.80 vs 0.68; P=0.50) and with the side of successful temporal lobectomy (0.87 vs 0.92; P=0.50) in TLE cases. However, MRS/MRI showed

Inter-modality comparisons of seizure focus lateralization in complex partial seizures

Energy Technology Data Exchange (ETDEWEB)

Meyer, P.T.; Cortes-Blanco, A.; Pourdehnad, M.; Desiderio, L.; Jang, S.; Alavi, A. [Pennsylvania Univ., Philadelphia, PA (United States). Dept. of Radiology; Levy-Reis, I. [Pennsylvania Univ., Philadelphia, PA (United States). Dept. of Neurology

2001-10-01

Anterior temporal lobectomy offers a high chance of seizure-free outcome in patients suffering from drug-refractory complex partial seizure (CPS) originating from the temporal lobe. Other than EEG, several functional and morphologic imaging methods are used to define the spatial seizure origin. The present study was undertaken to compare the merits of fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET), magnetic resonance imaging (MRI) and single-voxel proton MR spectroscopy (MRS) for the lateralization of temporal lobe seizure foci. The clinical charts and imaging data of 43 consecutive CPS patients were reviewed. Based on surface EEG, 31 patients were classified with temporal lobe epilepsy (TLE; 25 lateralized, 6 not lateralized) and 12 with non-temporal lobe epilepsy. All were examined by FDG-PET, MRS and MRI within 6 weeks. FDG-PET and MRI were interpreted visually, while the N-acetyl-aspartate to creatine ratio was used for MRS interpretation. One FDG-PET scan was invalid due to seizure activity post injection. The MR spectra could not be evaluated in five cases bilaterally and three cases unilaterally for technical reasons. A total of 15 patients underwent anterior temporal lobectomy. All showed a beneficial postoperative outcome. When the proportions of agreement between FDG-PET (0.77), MRI (0.58) and MRS (0.56) and surface EEG in TLE cases were compared, there were no significant differences (P>0.10). However, FDG-PET showed a significantly higher agreement (0.93) than MRI (0.60; P=0.03) with the side of successful temporal lobectomy. The concordance of MRS with the side of successful temporal lobectomy was intermediate (0.75). When the results of functional and morphologic imaging were combined, no significant differences were found between the rates of agreement of FDG-PET/MRI and MRS/MRI with EEG (0.80 vs 0.68; P=0.50) and with the side of successful temporal lobectomy (0.87 vs 0.92; P=0.50) in TLE cases. However, MRS/MRI showed

Change in illness perception is associated with short-term seizure burden outcome following video-EEG confirmation of psychogenic nonepileptic seizures.

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Chen, David K; Majmudar, Shirine; Ram, Aarthi; Rutherford, Holly C; Fadipe, Melissa; Dunn, Callie B; Collins, Robert L

2018-04-27

We aimed to evaluate whether potential changes in the patient's illness perception can significantly influence short-term seizure burden following video-electroencephalography (EEG) confirmation/explanation of psychogenic nonepileptic seizures (PNES). Patients with PNES were dichotomized to two groups based on a five-point Symptom Attribution Scale: (a) those who prior to diagnosis perceived their seizures to be solely ("5") or mainly ("4") physical in origin (physical group) and (b) the remainder of patients with PNES (psychological group). The physical group (n=32), psychological group (n=40), and group with epilepsy (n=26) also completed the Brief Illness Perception Questionnaire (BIPQ) prior to diagnosis, and were followed up at 3months as well as at 6months postdiagnosis. At 3months postdiagnosis, the physical group experienced significantly greater improvement in seizure intensity (p=0.002) and seizure frequency (p=0.016) when compared with the psychological group. The physical group was significantly more likely to have modified their symptom attribution toward a greater psychological role to their seizures (p=0.002), and their endorsement on the BIPQ item addressing "consequences" (How much do your seizures affect your life?) was significantly less severe (p'=0.014) when compared with that of the psychological group and the group with epilepsy. At 6months postdiagnosis, the physical group continued to experience significantly greater improvement in seizure intensity (p=0.007) while their seizure frequency no longer reached significant difference (p=0.078) when compared with the psychological group. The physical group continued to be significantly more likely to have modified their symptom attribution toward a greater psychological role to their seizures (p=0.005), and their endorsement on the BIPQ item addressing "consequences" remained significantly less severe (p'=0.037) when compared with the psychological group and the group with epilepsy. Among

Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice

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Federico Chella

2017-05-01

Full Text Available Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz, the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST. The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of

Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

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Jiang, Yizhang; Wu, Dongrui; Deng, Zhaohong; Qian, Pengjiang; Wang, Jun; Wang, Guanjin; Chung, Fu-Lai; Choi, Kup-Sze; Wang, Shitong

2017-12-01

Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the classification accuracy is usually not satisfactory for two main reasons: the distributions of the data used for training and testing may be different, and the amount of training data may not be enough. In addition, most machine learning approaches generate black-box models that are difficult to interpret. In this paper, we integrate transductive transfer learning, semi-supervised learning and TSK fuzzy system to tackle these three problems. More specifically, we use transfer learning to reduce the discrepancy in data distribution between the training and testing data, employ semi-supervised learning to use the unlabeled testing data to remedy the shortage of training data, and adopt TSK fuzzy system to increase model interpretability. Two learning algorithms are proposed to train the system. Our experimental results show that the proposed approaches can achieve better performance than many state-of-the-art seizure classification algorithms.

A case-control study of wicket spikes using video-EEG monitoring.

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Vallabhaneni, Maya; Baldassari, Laura E; Scribner, James T; Cho, Yong Won; Motamedi, Gholam K

2013-01-01

To investigate clinical characteristics associated with wicket spikes in patients undergoing long-term video-EEG monitoring. A case-control study was performed in 479 patients undergoing video-EEG monitoring, with 3 age- (±3 years) and gender-matched controls per patient with wicket spikes. Logistic regression was utilized to investigate the association between wicket spikes and other factors, including conditions that have been previously associated with wicket spikes. Wicket spikes were recorded in 48 patients. There was a significantly higher prevalence of dizziness/vertigo (p=0.002), headaches (p=0.005), migraine (p=0.015), and seizures (p=0.016) in patients with wickets. The majority of patients with wicket spikes did not exhibit epileptiform activity on EEG; however, patients with history of seizures were more likely to have wickets (p=0.017). There was no significant difference in the prevalence of psychogenic non-epileptic seizures between the groups. Wickets were more common on the left, during sleep, and more likely to be first recorded on day 1-2 of monitoring. Patients with wicket spikes are more likely to have dizziness/vertigo, headaches, migraine, and seizures. Patients with history of seizures are more likely to have wickets. The prevalence of psychogenic non-epileptic seizures is not significantly higher in patients with wickets. Copyright © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

An Automatic Prediction of Epileptic Seizures Using Cloud Computing and Wireless Sensor Networks.

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Sareen, Sanjay; Sood, Sandeep K; Gupta, Sunil Kumar

2016-11-01

Epilepsy is one of the most common neurological disorders which is characterized by the spontaneous and unforeseeable occurrence of seizures. An automatic prediction of seizure can protect the patients from accidents and save their life. In this article, we proposed a mobile-based framework that automatically predict seizures using the information contained in electroencephalography (EEG) signals. The wireless sensor technology is used to capture the EEG signals of patients. The cloud-based services are used to collect and analyze the EEG data from the patient's mobile phone. The features from the EEG signal are extracted using the fast Walsh-Hadamard transform (FWHT). The Higher Order Spectral Analysis (HOSA) is applied to FWHT coefficients in order to select the features set relevant to normal, preictal and ictal states of seizure. We subsequently exploit the selected features as input to a k-means classifier to detect epileptic seizure states in a reasonable time. The performance of the proposed model is tested on Amazon EC2 cloud and compared in terms of execution time and accuracy. The findings show that with selected HOS based features, we were able to achieve a classification accuracy of 94.6 %.

Cerebrospinal fluid findings after epileptic seizures.

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Chatzikonstantinou, Anastasios; Ebert, Anne D; Hennerici, Michael G

2015-12-01

We aimed to evaluate ictally-induced CSF parameter changes after seizures in adult patients without acute inflammatory diseases or infectious diseases associated with the central nervous system. In total, 151 patients were included in the study. All patients were admitted to our department of neurology following acute seizures and received an extensive work-up including EEG, cerebral imaging, and CSF examinations. CSF protein elevation was found in most patients (92; 60.9%) and was significantly associated with older age, male sex, and generalized seizures. Abnormal CSF-to-serum glucose ratio was found in only nine patients (5.9%) and did not show any significant associations. CSF lactate was elevated in 34 patients (22.5%) and showed a significant association with focal seizures with impaired consciousness, status epilepticus, the presence of EEG abnormalities in general and epileptiform potentials in particular, as well as epileptogenic lesions on cerebral imaging. Our results indicate that non-inflammatory CSF elevation of protein and lactate after epileptic seizures is relatively common, in contrast to changes in CSF-to-serum glucose ratio, and further suggest that these changes are caused by ictal activity and are related to seizure type and intensity. We found no indication that these changes may have further-reaching pathological implications besides their postictal character.

Seizure semiology identifies patients with bilateral temporal lobe epilepsy.

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Loesch, Anna Mira; Feddersen, Berend; Tezer, F Irsel; Hartl, Elisabeth; Rémi, Jan; Vollmar, Christian; Noachtar, Soheyl

2015-01-01

Laterality in temporal lobe epilepsy is usually defined by EEG and imaging results. We investigated whether the analysis of seizure semiology including lateralizing seizure phenomena identifies bilateral independent temporal lobe seizure onset. We investigated the seizure semiology in 17 patients in whom invasive EEG-video-monitoring documented bilateral temporal seizure onset. The results were compared to 20 left and 20 right consecutive temporal lobe epilepsy (TLE) patients who were seizure free after anterior temporal lobe resection. The seizure semiology was analyzed using the semiological seizure classification with particular emphasis on the sequence of seizure phenomena over time and lateralizing seizure phenomena. Statistical analysis included chi-square test or Fisher's exact test. Bitemporal lobe epilepsy patients had more frequently different seizure semiology (100% vs. 40%; p<0.001) and significantly more often lateralizing seizure phenomena pointing to bilateral seizure onset compared to patients with unilateral TLE (67% vs. 11%; p<0.001). The sensitivity of identical vs. different seizure semiology for the identification of bilateral TLE was high (100%) with a specificity of 60%. Lateralizing seizure phenomena had a low sensitivity (59%) but a high specificity (89%). The combination of lateralizing seizure phenomena and different seizure semiology showed a high specificity (94%) but a low sensitivity (59%). The analysis of seizure semiology including lateralizing seizure phenomena adds important clinical information to identify patients with bilateral TLE. Copyright © 2014 Elsevier B.V. All rights reserved.

Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

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Varatharajah, Yogatheesan; Berry, Brent; Cimbalnik, Jan; Kremen, Vaclav; Van Gompel, Jamie; Stead, Matt; Brinkmann, Benjamin; Iyer, Ravishankar; Worrell, Gregory

2018-08-01

An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between 90 min and 2 h are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

EEG (Electroencephalogram)

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... in diagnosing brain disorders, especially epilepsy or another seizure disorder. An EEG might also be helpful for diagnosing ... Sometimes seizures are intentionally triggered in people with epilepsy during the test, but appropriate medical care is ...

Using recurrence plot for determinism analysis of EEG recordings in genetic absence epilepsy rats.

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Ouyang, Gaoxiang; Li, Xiaoli; Dang, Chuangyin; Richards, Douglas A

2008-08-01

Understanding the transition of brain activity towards an absence seizure is a challenging task. In this paper, we use recurrence quantification analysis to indicate the deterministic dynamics of EEG series at the seizure-free, pre-seizure and seizure states in genetic absence epilepsy rats. The determinism measure, DET, based on recurrence plot, was applied to analyse these three EEG datasets, each dataset containing 300 single-channel EEG epochs of 5-s duration. Then, statistical analysis of the DET values in each dataset was carried out to determine whether their distributions over the three groups were significantly different. Furthermore, a surrogate technique was applied to calculate the significance level of determinism measures in EEG recordings. The mean (+/-SD) DET of EEG was 0.177+/-0.045 in pre-seizure intervals. The DET values of pre-seizure EEG data are significantly higher than those of seizure-free intervals, 0.123+/-0.023, (Pdeterminism in EEG epochs was present in 25 of 300 (8.3%), 181 of 300 (60.3%) and 289 of 300 (96.3%) in seizure-free, pre-seizure and seizure intervals, respectively. Results provide some first indications that EEG epochs during pre-seizure intervals exhibit a higher degree of determinism than seizure-free EEG epochs, but lower than those in seizure EEG epochs in absence epilepsy. The proposed methods have the potential of detecting the transition between normal brain activity and the absence seizure state, thus opening up the possibility of intervention, whether electrical or pharmacological, to prevent the oncoming seizure.

Behavioral and electroencephalographic evaluation of the anticonvulsive activity of Moringa oleifera leaf non-polar extracts and one metabolite in PTZ-induced seizures.

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González-Trujano, María Eva; Martínez-González, Claudia Lizbeth; Flores-Carrillo, Maricela; Luna-Nophal, Sara Ibeth; Contreras-Murillo, Gerardo; Magdaleno-Madrigal, Víctor Manuel

2018-01-15

Moringa oleifera Lamarck is a species that has long been used in high demand in folk medicine, including for the treatment of epilepsy. Nevertheless, scientific studies demonstrating its anticonvulsant properties and the nature of the bioactive constituents are lacking. The aim of this study was to evaluate the anticonvulsant activities of the Moringa oleifera leaves in non-polar vs. polar extracts using behavioral and electroencephalographic (EEG) analyses in rodents. First, PTZ (80 mg/kg, i.p.)-induced tonic-clonic seizures were assayed via a dose-response (100, 200 and 300 mg/kg, i.p.) evaluation in mice. Then, a dosage of the extracts (100 or 300 mg/kg) and one metabolite (30 mg/kg, i.p.) was selected to evaluate its effect on PTZ (35 mg/kg, i.p.)-induced EEG paroxystic activities in rats compared to the effects of ethosuximide (reference anticonvulsant drug, 100 mg/kg, i.p.). Latent onset of the first paroxystic spike, first seizure and frequency as well as seizure severity, were determined using Racine's scale. Moringa oleifera ethanol and hexane extracts produced a delay in the seizure latency in mice and rats; this effect was improved in the presence of the hexane extract containing the active metabolite hexadecanoic acid. The anticonvulsant effects were corroborated in the spectral analysis by the potency of the EEG due to a reduction in the spike frequency and amplitude, as well as in the duration and severity of the seizures. The effects of the hexane extract resembled those observed in the reference antiepileptic drug ethosuximide. Moringa oleifera leaves possess anticonvulsant activities due to the complementary of the non-polar and polar constituents. However, the non-polar constituents appear to exert an important influence via the partial participation of fatty acids, providing evidence of the effects of this plant in epilepsy therapy. Copyright © 2017. Published by Elsevier GmbH.

Acute confusional state of unknown cause in the elderly: a study with continuous EEG monitoring.

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Naeije, Gilles; Gaspard, Nicolas; Depondt, Chantal; Pepersack, Thierry; Legros, Benjamin

2012-03-01

Acute confusional state (ACS) is a frequent cause of emergency consultation in the elderly. Many causes of ACS are also risk factors for seizures. Both non-convulsive seizures and status epilepticus can cause acute confusion. The yield of routine EEG may not be optimal in case of prolonged post-ictal confusion. We thus, sought to evaluate the yield of CEEG in identifying seizures in elderly patients with ACS of unknown origin. We reviewed our CEEG database for patients over 75 years with ACS and collected EEG, CEEG and clinical information. Thirty-one percent (15/48) of the CEEG performed in elderly patients were done for ACS. Routine EEG did not reveal any epileptic anomalies in 7/15 patients. Among those, CEEG identified interictal epileptiform discharges (IED) in 2 and NCSE in 1. In 8/15 patients, routine EEG revealed epileptiform abnormalities: 3 with IED (including 1 with periodic lateralized discharges), 3 with non-convulsive seizures (NCSz) and 2 with non-convulsive status epilepticus (NCSE). Among patients with only IED, CEEG revealed NCSz in 1 and NCSE in 2. This retrospective study suggests that NCSz and NCSE may account for more cases of ACS than what was previously thought. A single negative routine EEG does not exclude this diagnosis. Continuous EEG (CEEG) monitoring is more revealing than routine EEG for the detection of NCSE and NCSz in confused elderly. The presence of IED in the first routine EEG strongly suggests concomitant NCSz or NCSE. Prospective studies are required to further determine the role of CEEG monitoring in the assessment of ACS in the elderly and to establish the incidence of NCSz and NCSE in this setting. Copyright © 2012 Elsevier Inc. All rights reserved.

Causality within the Epileptic Network: An EEG-fMRI Study Validated by Intracranial EEG.

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Vaudano, Anna Elisabetta; Avanzini, Pietro; Tassi, Laura; Ruggieri, Andrea; Cantalupo, Gaetano; Benuzzi, Francesca; Nichelli, Paolo; Lemieux, Louis; Meletti, Stefano

2013-01-01

Accurate localization of the Seizure Onset Zone (SOZ) is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI) has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical work-up. However, fMRI maps related to interictal epileptiform activities (IED) often show multiple regions of signal change, or "networks," rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modeling (DCM) applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here, we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of blood oxygenation level dependent (BOLD) signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favored a model corresponding to the left dorso-lateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a) the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI), and "psycho-physiological interaction" analysis; (b) the failure of a first surgical intervention limited to the fronto-polar region; (c) the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

Causality within the epileptic network: an EEG-fMRI study validated by intracranial EEG.

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Anna Elisabetta eVaudano

2013-11-01

Full Text Available Accurate localization of the Seizure Onset Zone (SOZ is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical workup. However, fMRI maps related to interictal epileptiform activities (IED often show multiple regions of signal change, or networks, rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modelling (DCM applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of BOLD signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favoured a model corresponding to the left dorsolateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI, and psychophysiological interaction analysis (PPI; (b the failure of a first surgical intervention limited to the fronto-polar region; (c the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

Imaging seizure activity: a combined EEG/EMG-fMRI study in reading epilepsy.

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Salek-Haddadi, Afraim; Mayer, Thomas; Hamandi, Khalid; Symms, Mark; Josephs, Oliver; Fluegel, Dominique; Woermann, Friedrich; Richardson, Mark P; Noppeney, Uta; Wolf, Peter; Koepp, Matthias J

2009-02-01

To characterize the spatial relationship between activations related to language-induced seizure activity, language processing, and motor control in patients with reading epilepsy. We recorded and simultaneously monitored several physiological parameters [voice-recording, electromyography (EMG), electrocardiography (ECG), electroencephalography (EEG)] during blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in nine patients with reading epilepsy. Individually tailored language paradigms were used to induce and record habitual seizures inside the MRI scanner. Voxel-based morphometry (VBM) was used for structural brain analysis. Reading-induced seizures occurred in six out of nine patients. One patient experienced abundant orofacial reflex myocloni during silent reading in association with bilateral frontal or generalized epileptiform discharges. In a further five patients, symptoms were only elicited while reading aloud with self-indicated events. Consistent activation patterns in response to reading-induced myoclonic seizures were observed within left motor and premotor areas in five of these six patients, in the left striatum (n = 4), in mesiotemporal/limbic areas (n = 4), in Brodmann area 47 (n = 3), and thalamus (n = 2). These BOLD activations were overlapping or adjacent to areas physiologically activated during language and facial motor tasks. No subtle structural abnormalities common to all patients were identified using VBM, but one patient had a left temporal ischemic lesion. Based on the findings, we hypothesize that reflex seizures occur in reading epilepsy when a critical mass of neurons are activated through a provoking stimulus within corticoreticular and corticocortical circuitry subserving normal functions.

The early electroclinical manifestations of infantile spasms: A video EEG study

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Mary Iype

2016-01-01

Full Text Available Purpose: Infantile spasms are described as flexor extensor and mixed; but more features of their semiology and ictal electroencephalography (EEG changes are sparse in the literature. The purpose of the study was to describe the clinical and ictal video-EEG characteristics of consecutive cases with infantile spasms and to try to find an association with the etiology. Materials and Methods: The clinical phenomenology and EEG characteristics on video-EEG were analyzed in 16 babies with infantile spasms. Results: A total of 869 spasms were reviewed. Nine (56.3% showed focal seizures at least once during the recording and 1 (6.3% had multifocal myoclonus in addition to the spasms. The duration of the cluster and interval between spasms was totally variable in all patients. Lateralizing phenomena were present in at least some of the spasms in all patients. Unilateral manual automatism in the form of holding the pinna was noted in three patients following the spasm. The ictal EEG activity in the majority (75% was the slow wave. Four (25% showed fast generalized spindle-like ictal discharges. Spikes, spike and wave activity, or electrodecremental pattern alone during the ictus was seen in none. On bivariate analysis, no factor noted on the video EEG had association with the etiology. Conclusion: Infantile spasms could be associated with focal and other seizures, has unique, non-uniform and variable semiology from patient to patient. The ictal EEG manifestation in the majority (75% of our patients was the slow wave transient with 25% showing generalized fast spindle-like activity.

Scale invariance properties of intracerebral EEG improve seizure prediction in mesial temporal lobe epilepsy.

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Kais Gadhoumi

Full Text Available Although treatment for epilepsy is available and effective for nearly 70 percent of patients, many remain in need of new therapeutic approaches. Predicting the impending seizures in these patients could significantly enhance their quality of life if the prediction performance is clinically practical. In this study, we investigate the improvement of the performance of a seizure prediction algorithm in 17 patients with mesial temporal lobe epilepsy by means of a novel measure. Scale-free dynamics of the intracerebral EEG are quantified through robust estimates of the scaling exponents--the first cumulants--derived from a wavelet leader and bootstrap based multifractal analysis. The cumulants are investigated for the discriminability between preictal and interictal epochs. The performance of our recently published patient-specific seizure prediction algorithm is then out-of-sample tested on long-lasting data using combinations of cumulants and state similarity measures previously introduced. By using the first cumulant in combination with state similarity measures, up to 13 of 17 patients had seizures predicted above chance with clinically practical levels of sensitivity (80.5% and specificity (25.1% of total time under warning for prediction horizons above 25 min. These results indicate that the scale-free dynamics of the preictal state are different from those of the interictal state. Quantifiers of these dynamics may carry a predictive power that can be used to improve seizure prediction performance.

Screening EEG in Aircrew Selection: Clinical Aerospace Neurology Perspective

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Clark, Jonathan B.; Riley, Terrence

2001-01-01

As clinical aerospace neurologists we do not favor using screening EEG in pilot selection on unselected and otherwise asymptomatic individuals. The role of EEG in aviation screening should be as an adjunct to diagnosis, and the decision to disqualify a pilot should never be based solely on the EEG. Although a policy of using a screening EEG in an unselected population might detect an individual with a potentially increased relative risk, it would needlessly exclude many applicants who would probably never have a seizure. A diagnostic test performed on an asymptomatic individual without clinical indications, in a population with a low prevalence of disease (seizure) may be of limited or possibly detrimental value. We feel that rather than do EEGs on all candidates, a better approach would be to perform an EEG for a specific indication, such as family history of seizure, single convulsion (seizure) , history of unexplained loss of consciousness or head injury. Routine screening EEGs in unselected aviation applications are not done without clinical indication in the U.S. Air Force, Navy, or NASA. The USAF discontinued routine screening EEGs for selection in 1978, the U.S. Navy discontinued it in 1981 , and NASA discontinued it in 1995. EEG as an aeromedical screening tool in the US Navy dates back to 1939. The US Navy routinely used EEGs to screen all aeromedical personnel from 1961 to 1981. The incidence of epileptiform activity on EEG in asymptomatic flight candidates ranges from 0.11 to 2.5%. In 3 studies of asymptomatic flight candidates with epileptiform activity on EEG followed for 2 to 15 years, 1 of 31 (3.2%), 1 of 30 (3.3%), and 0 of 14 (0%) developed a seizure, for a cumulative risk of an individual with an epileptiform EEG developing a seizure of 2.67% (2 in 75). Of 28,658 student naval aviation personnel screened 31 had spikes and/or slow waves on EEG, and only 1 later developed a seizure. Of the 28,627 who had a normal EEG, 4 later developed seizures, or

A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals

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Quintero-Rincón, Antonio; Pereyra, Marcelo; D'Giano, Carlos; Batatia, Hadj; Risk, Marcelo

2016-04-01

Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which result from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical signal processing. In this work we propose a new algorithm for seizure onset detection and spread estimation in epilepsy patients. The algorithm is based on a multilevel 1-D wavelet decomposition that captures the physiological brain frequency signals coupled with a generalized gaussian model. Preliminary experiments with signals from 30 epilepsy crisis and 11 subjects, suggest that the proposed methodology is a powerful tool for detecting the onset of epilepsy seizures with his spread across the brain.

Exploring the capability of wireless near infrared spectroscopy as a portable seizure detection device for epilepsy patients.

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Jeppesen, Jesper; Beniczky, Sándor; Johansen, Peter; Sidenius, Per; Fuglsang-Frederiksen, Anders

2015-03-01

Near infrared spectroscopy (NIRS) has proved useful in measuring significant hemodynamic changes in the brain during epileptic seizures. The advance of NIRS-technology into wireless and portable devices raises the possibility of using the NIRS-technology for portable seizure detection. This study used NIRS to measure changes in oxygenated (HbO), deoxygenated (HbR), and total hemoglobin (HbT) at left and right side of the frontal lobe in 33 patients with epilepsy undergoing long-term video-EEG monitoring. Fifteen patients had 34 focal seizures (20 temporal-, 11 frontal-, 2 parietal-lobe, one unspecific) recorded and analyzed with NIRS. Twelve parameters consisting of maximum increase and decrease changes of HbO, HbR and HbT during seizures (1 min before- to 3 min after seizure-onset) for left and right side, were compared with the patients' own non-seizure periods (a 2-h period and a 30-min exercise-period). In both non-seizure periods 4 min moving windows with maximum overlapping were applied to find non-seizure maxima of the 12 parameters. Detection was defined as positive when seizure maximum change exceeded non-seizure maximum change. When analyzing the 12 parameters separately the positive seizure detection was in the range of 6-24%. The increase in hemodynamics was in general better at detecting seizures (15-24%) than the decrease in hemodynamics (6-18%) (P=0.02). NIRS did not seem to be a suitable technology for generic seizure detection given the device, settings, and methods used in this study. There are still several challenges to overcome before the NIRS-technology can be used as a home-monitoring seizure detection device. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Seizures Induced by Music

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A. O. Ogunyemi

1993-01-01

Full Text Available Musicogenic epilepsy is a rare disorder. Much remains to be learned about the electroclinical features. This report describes a patient who has been followed at our institution for 17 years, and was investigated with long-term telemetered simultaneous video-EEG recordings. She began to have seizures at the age of 10 years. She experienced complex partial seizures, often preceded by elementary auditory hallucination and complex auditory illusion. The seizures occurred in relation to singing, listening to music or thinking about music. She also had occasional generalized tonic clonic seizures during sleep. There was no significant antecedent history. The family history was negative for epilepsy. The physical examination was unremarkable. CT and MRI scans of the brain were normal. During long-term simultaneous video-EEG recordings, clinical and electrographic seizure activities were recorded in association with singing and listening to music. Mathematical calculation, copying or viewing geometric patterns and playing the game of chess failed to evoke seizures.

Seizure ending signs in patients with dyscognitive focal seizures.

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Gavvala, Jay R; Gerard, Elizabeth E; Macken, Mícheál; Schuele, Stephan U

2015-09-01

Signs indicating the end of a focal seizure with loss of awareness and/or responsiveness but without progression to focal or generalized motor symptoms are poorly defined and can be difficult to determine. Not recognizing the transition from ictal to postictal behaviour can affect seizure reporting accuracy by family members and may lead to delayed or a lack of examination during EEG monitoring, erroneous seizure localization and inadequate medical intervention for prolonged seizure duration. Our epilepsy monitoring unit database was searched for focal seizures without secondary generalization for the period from 2007 to 2011. The first focal seizure in a patient with loss of awareness and/or responsiveness and/or behavioural arrest, with or without automatisms, was included. Seizures without objective symptoms or inadequate video-EEG quality were excluded. A total of 67 patients were included, with an average age of 41.7 years. Thirty-six of the patients had seizures from the left hemisphere and 29 from the right. All patients showed an abrupt change in motor activity and resumed contact with the environment as a sign of clinical seizure ending. Specific ending signs (nose wiping, coughing, sighing, throat clearing, or laughter) were seen in 23 of 47 of temporal lobe seizures and 7 of 20 extra-temporal seizures. Seizure ending signs are often subtle and the most common finding is a sudden change in motor activity and resumption of contact with the environment. More distinct signs, such as nose wiping, coughing or throat clearing, are not specific to temporal lobe onset. A higher proportion of seizures during sleep went unexamined, compared to those during wakefulness. This demonstrates that seizure semiology can be very subtle and arousals from sleep during monitoring should alert staff. Patient accounts of seizure frequency appear to be unreliable and witness reports need to be taken into account. [Published with video sequences].

Dynamics of large-scale brain activity in normal arousal states and epileptic seizures

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Robinson, P. A.; Rennie, C. J.; Rowe, D. L.

2002-04-01

Links between electroencephalograms (EEGs) and underlying aspects of neurophysiology and anatomy are poorly understood. Here a nonlinear continuum model of large-scale brain electrical activity is used to analyze arousal states and their stability and nonlinear dynamics for physiologically realistic parameters. A simple ordered arousal sequence in a reduced parameter space is inferred and found to be consistent with experimentally determined parameters of waking states. Instabilities arise at spectral peaks of the major clinically observed EEG rhythms-mainly slow wave, delta, theta, alpha, and sleep spindle-with each instability zone lying near its most common experimental precursor arousal states in the reduced space. Theta, alpha, and spindle instabilities evolve toward low-dimensional nonlinear limit cycles that correspond closely to EEGs of petit mal seizures for theta instability, and grand mal seizures for the other types. Nonlinear stimulus-induced entrainment and seizures are also seen, EEG spectra and potentials evoked by stimuli are reproduced, and numerous other points of experimental agreement are found. Inverse modeling enables physiological parameters underlying observed EEGs to be determined by a new, noninvasive route. This model thus provides a single, powerful framework for quantitative understanding of a wide variety of brain phenomena.

Electroencephalography findings in patients presenting to the ED for evaluation of seizures.

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Kadambi, Pooja; Hart, Kimberly W; Adeoye, Opeolu M; Lindsell, Christopher J; Knight, William A

2015-01-01

Status epilepticus is a life-threatening, time-sensitive emergency. Acquiring an electroencephalogram (EEG) in the emergency department (ED) could impact therapeutic and disposition decisions for patients with suspected status epilepticus. The objective of this study is to estimate the proportion of EEGs diagnostic for seizures in patients presenting to an ED with a complaint of seizures. This retrospective chart review included adults presenting to the ED of an urban, academic, tertiary care hospital with suspected seizures or status epilepticus, who received an EEG within 24 hours of hospital admission. Data abstraction was performed by a single, trained, nonblinded abstractor. Seizures were defined as an epileptologist's diagnosis of either seizures or status epilepticus on EEG. The proportion of patients with seizures is given with confidence interval95 (CI95). Of 120 included patients, 67 (56%) had a history of epilepsy. Mean age was 52 years (SD, 16), 58% were White, and 61% were male. Within 24 hours, 3% had an EEG diagnostic for seizures. Electroencephalogram was obtained in the ED in 32 (27%) of 120 (CI95, 19%-35%), and 2 (6%) of 32 (CI95, 1%-19%) had seizures. Electroencephalogram was performed inpatient for 88 (73%) of 120 (CI95, 65%-81%), and 2 (2%) of 88 (CI95, 0.5%-7.1%) had seizures. Only 3% of ED patients with suspected seizures or status epilepticus had EEG confirmation of seizures within 24 hours. Early EEG acquisition in the ED may identify a group of patients amenable to ED observation and subsequent discharge from the hospital. Copyright © 2014 Elsevier Inc. All rights reserved.

Seizures in E200K familial and sporadic Creutzfeldt-Jakob disease.

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Appel, S; Chapman, J; Cohen, O S; Rosenmann, H; Nitsan, Z; Blatt, I

2015-03-01

Although seizures (other than myoclonus) are frequently reported in Creutzfeldt-Jakob disease (CJD), their frequency, clinical manifestations, and effect on the disease course is unknown. To characterize the frequency of seizures in E200K familial and sporadic CJD, to describe its semiology, EEG and MRI findings. In this retrospective study, we reviewed all patients with CJD who were seen in the Sheba Medical Center between the years 2003-2012 and underwent clinical evaluation, genetic testing, EEG and MRI studies. The diagnosis of seizures was carried out based on documentation of episodes consistent with seizures or episode of unresponsiveness correlated with ictal activity in EEG. Sixty-four probable patients with CJD were included in the study, 57 (89%) with E200K familial (fCJD) and 7 (11%) with sporadic (sCJD). Seizures occurred in 8 patients: 3 of 7 (43%) in patients with sCJD compared to 5/57 (9%) in patients with E200K fCJD (P = 0.04, chi-square test). Two of E200K fCJD patients with seizures had other non-prion etiologies for seizures (brain metastasis, known history of temporal lobe epilepsy which started 44 years before the diagnosis of CJD). Seizures occurred late in the course of the disease with an average of 12 days between the onset of seizures and death. Seizures in E200K fCJD were infrequent and occurred late in the disease course. This difference suggests that E200K fCJD represents a separate subtype of the disease with distinct clinical characteristics. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Coprolalia as a manifestation of epileptic seizures.

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Massot-Tarrús, Andreu; Mousavi, Seyed Reza; Dove, Carin; Hayman-Abello S, Susan; Hayman-Abello, Brent; Derry, Paul A; Diosy, David C; McLachlan, Richard S; Burneo, Jorge G; Steven, David A; Mirsattari, Seyed M

2016-07-01

The aim of this study was to investigate the lateralizing and localizing value of ictal coprolalia and brain areas involved in its production. A retrospective search for patients manifesting ictal coprolalia was conducted in our EMU database. Continuous video-EEG recordings were reviewed, and EEG activity before and during coprolalia was analyzed using independent component analysis (ICA) technique and was compared to the seizures without coprolalia among the same patients. Nine patients were evaluated (five women), eight with intracranial video-EEG recordings (icVEEG). Four had frontal or temporal lesions, and five had normal MRIs. Six patients showed impairment in the language functions and five in the frontal executive tasks. Two hundred six seizures were reviewed (60.7% from icVEEG). Ictal coprolalia occurred in 46.6% of them, always associated with limbic auras or automatisms. They arose from the nondominant hemisphere in five patients, dominant hemisphere in three, and independently from the right and left hippocampus-parahippocampus in one. Electroencephalographic activity always involved orbitofrontal and/or mesial temporal regions of the nondominant hemisphere when coprolalia occurred. Independent component analysis of 31 seizures in seven patients showed a higher number of independent components in the nondominant hippocampus-parahippocampus before and during coprolalia and in the dominant lateral temporal region in those seizures without coprolalia (p=0.009). Five patients underwent surgery, and all five had an ILAE class 1 outcome. Ictal coprolalia occurs in both males and females with temporal or orbitofrontal epilepsy and has a limited lateralizing value to the nondominant hemisphere but can be triggered by seizures from either hemisphere. It involves activation of the paralimbic temporal-orbitofrontal network. Copyright © 2016 Elsevier Inc. All rights reserved.

A computerised EEG-analyzing system for small laboratory animals

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Kropveld, D.; Chamuleau, R. A.; Popken, R. J.; Smith, J.

1983-01-01

The experimental setup, including instrumentation and software packaging, is described for the use of a minicomputer as an on-line analyzing system of the EEG in rats. Complete fast Fourier transformation of the EEG sampled in 15 episodes of 10 s each is plotted out within 7 min after the start of

GABAergic Neuron-Specific Loss of Ube3a Causes Angelman Syndrome-Like EEG Abnormalities and Enhances Seizure Susceptibility.

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Judson, Matthew C; Wallace, Michael L; Sidorov, Michael S; Burette, Alain C; Gu, Bin; van Woerden, Geeske M; King, Ian F; Han, Ji Eun; Zylka, Mark J; Elgersma, Ype; Weinberg, Richard J; Philpot, Benjamin D

2016-04-06

Loss of maternal UBE3A causes Angelman syndrome (AS), a neurodevelopmental disorder associated with severe epilepsy. We previously implicated GABAergic deficits onto layer (L) 2/3 pyramidal neurons in the pathogenesis of neocortical hyperexcitability, and perhaps epilepsy, in AS model mice. Here we investigate consequences of selective Ube3a loss from either GABAergic or glutamatergic neurons, focusing on the development of hyperexcitability within L2/3 neocortex and in broader circuit and behavioral contexts. We find that GABAergic Ube3a loss causes AS-like increases in neocortical EEG delta power, enhances seizure susceptibility, and leads to presynaptic accumulation of clathrin-coated vesicles (CCVs)-all without decreasing GABAergic inhibition onto L2/3 pyramidal neurons. Conversely, glutamatergic Ube3a loss fails to yield EEG abnormalities, seizures, or associated CCV phenotypes, despite impairing tonic inhibition onto L2/3 pyramidal neurons. These results substantiate GABAergic Ube3a loss as the principal cause of circuit hyperexcitability in AS mice, lending insight into ictogenic mechanisms in AS. Copyright © 2016 Elsevier Inc. All rights reserved.

Channel selection for automatic seizure detection

DEFF Research Database (Denmark)

Duun-Henriksen, Jonas; Kjaer, Troels Wesenberg; Madsen, Rasmus Elsborg

2012-01-01

Objective: To investigate the performance of epileptic seizure detection using only a few of the recorded EEG channels and the ability of software to select these channels compared with a neurophysiologist. Methods: Fifty-nine seizures and 1419 h of interictal EEG are used for training and testing...... of an automatic channel selection method. The characteristics of the seizures are extracted by the use of a wavelet analysis and classified by a support vector machine. The best channel selection method is based upon maximum variance during the seizure. Results: Using only three channels, a seizure detection...... sensitivity of 96% and a false detection rate of 0.14/h were obtained. This corresponds to the performance obtained when channels are selected through visual inspection by a clinical neurophysiologist, and constitutes a 4% improvement in sensitivity compared to seizure detection using channels recorded...

Seizure-related factors and non-verbal intelligence in children with epilepsy. A population-based study from Western Norway.

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Høie, B; Mykletun, A; Sommerfelt, K; Bjørnaes, H; Skeidsvoll, H; Waaler, P E

2005-06-01

To study the relationship between seizure-related factors, non-verbal intelligence, and socio-economic status (SES) in a population-based sample of children with epilepsy. The latest ILAE International classifications of epileptic seizures and syndromes were used to classify seizure types and epileptic syndromes in all 6-12 year old children (N=198) with epilepsy in Hordaland County, Norway. The children had neuropediatric and EEG examinations. Of the 198 patients, demographic characteristics were collected on 183 who participated in psychological studies including Raven matrices. 126 healthy controls underwent the same testing. Severe non-verbal problems (SNVP) were defined as a Raven score at or Raven percentile group, whereas controls were highly over-represented in the higher percentile groups. SNVP were present in 43% of children with epilepsy and 3% of controls. These problems were especially common in children with remote symptomatic epilepsy aetiology, undetermined epilepsy syndromes, myoclonic seizures, early seizure debut, high seizure frequency and in children with polytherapy. Seizure-related characteristics that were not usually associated with SNVP were idiopathic epilepsies, localization related (LR) cryptogenic epilepsies, absence and simple partial seizures, and a late debut of epilepsy. Adjusting for socio-economic status factors did not significantly change results. In childhood epilepsy various seizure-related factors, but not SES factors, were associated with the presence or absence of SNVP. Such deficits may be especially common in children with remote symptomatic epilepsy aetiology and in complex and therapy resistant epilepsies. Low frequencies of SNVP may be found in children with idiopathic and LR cryptogenic epilepsy syndromes, simple partial or absence seizures and a late epilepsy debut. Our study contributes to an overall picture of cognitive function and its relation to central seizure characteristics in a childhood epilepsy population

Occipital lobe seizures and epilepsies.

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Adcock, Jane E; Panayiotopoulos, Chrysostomos P

2012-10-01

Occipital lobe epilepsies (OLEs) manifest with occipital seizures from an epileptic focus within the occipital lobes. Ictal clinical symptoms are mainly visual and oculomotor. Elementary visual hallucinations are common and characteristic. Postictal headache occurs in more than half of patients (epilepsy-migraine sequence). Electroencephalography (EEG) is of significant diagnostic value, but certain limitations should be recognized. Occipital spikes and/or occipital paroxysms either spontaneous or photically induced are the main interictal EEG abnormalities in idiopathic OLE. However, occipital epileptiform abnormalities may also occur without clinical relationship to seizures particularly in children. In cryptogenic/symptomatic OLE, unilateral posterior EEG slowing is more common than occipital spikes. In neurosurgical series of symptomatic OLE, interictal EEG abnormalities are rarely strictly occipital. The most common localization is in the posterior temporal regions and less than one-fifth show occipital spikes. In photosensitive OLE, intermittent photic stimulation elicits (1) spikes/polyspikes confined in the occipital regions or (2) generalized spikes/polyspikes with posterior emphasis. In ictal EEG, a well-localized unifocal rhythmic ictal discharge during occipital seizures is infrequent. A bioccipital field spread to the temporal regions is common. Frequency, severity, and response to treatment vary considerably from good to intractable and progressive mainly depending on underlying causes.

A brief history of typical absence seizures - Petit mal revisited.

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Brigo, Francesco; Trinka, Eugen; Lattanzi, Simona; Bragazzi, Nicola Luigi; Nardone, Raffaele; Martini, Mariano

2018-03-01

In this article, we have traced back the history of typical absence seizures, from their initial clinical description to the more recent nosological position. The first description of absence seizures was made by Poupart in 1705 and Tissot in 1770. In 1824, Calmeil introduced the term "absences", and in 1838, Esquirol for the first time used the term petit mal. Reynolds instead used the term "epilepsia mitior" (milder epilepsy) and provided a comprehensive description of absence seizures (1861). In 1854, Delasiauve ranked absences as the seizure type with lower severity and introduced the concept of idiopathic epilepsy. Otto Binswanger (1899) discussed the role of cortex in the pathophysiology of "abortive seizures", whereas William Gowers (1901) emphasized the importance of a detailed clinical history to identify nonmotor seizures or very mild motor phenomena which otherwise may go unnoticed or considered not epileptic. At the beginning of the 20th Century, the term pyknolepsy was introduced, but initially was not universally considered as a type of epilepsy; it was definitely recognized as an epileptic entity only in 1945, based on electroencephalogram (EEG) recordings. Hans Berger, the inventor of the EEG, made also the first EEG recording of an atypical absence (his results were published only in 1933), whereas the characteristic EEG pattern was reported by neurophysiologists of the Harvard Medical School in 1935. The discovery of EEG made it also possible to differentiate absence seizures from so called "psychomotor" seizures occurring in temporal lobe epilepsy. Penfield and Jasper (1938) considered absences as expression of "centrencephalic epilepsy". Typical absences seizures are now classified by the International League Against Epilepsy among generalized nonmotor (absence) seizures. Copyright © 2018 Elsevier Inc. All rights reserved.

Predicting epileptic seizures in advance.

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Negin Moghim

Full Text Available Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling, is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance.

Seizure characteristics in multiple sclerosis patients

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Vahid Shaygannejad

2013-01-01

Full Text Available Background: To evaluate seizure characteristic among multiple sclerosis patients with coexistent seizure activity compared to control group. Materials and Methods : This study is a cross-sectional study which was conducted by reviewing the clinical records of patients with definite diagnosis of MS according to McDonald′s criteria from March 2007 to June 2011, who referred to the MS clinic of the university. Results : A total of 920 patients with a diagnosis of MS were identified, among whom 29 patients (3.15% with seizure activity (case due to MS with the mean age of 32.6 ± 6.23 years were analyzed. Also, fifty MS patients without any seizure occurrence with the mean age of 33.7 ± 7.4 years were used as our control group. In case group, seizure was general tonic clonic in 23 patients (79.3%, complex partial in four (13.8%, and simple partial in two (5.9%. The 26 available interictal EEGs in MS patients showed abnormal EEG pattern in 22 (84.6% of them, including focal epileptic form discharge or focal slowing in 10 (38.5%, generalized discharge (spike-wave, polyspike, or general paroxysmal fast activity in 10 (38.5%, and general slowing activity in 10 record (38.5%. MRI reviews of the 26 available brain MRIs showed subcortical white mater lesions in 22 (84.6% of patients with seizure. All MRIs were performed within one month after the first seizure episode. Amongst 48 available MRIs in our control group, 91.7% (44 cases showed periventricular lesions and in 8.3% (4 cases subcortical white matter lesions were reported. Conclusion : The result of this study demonstrated the higher rate of subcortical whit matter lesion in MS patients with seizure occurrence compared to control group.

Phenomenology and psychiatric origin of psychogenic nonepileptic seizures

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Ristić Aleksandar J.

2004-01-01

Full Text Available INTRODUCTION Psychogenic nonepileptic seizure (PNES is a sudden change in a person's behavior, perception, thinking, or feeling that is usually time limited and resembles, or is mistaken for, epilepsy but does not have the characteristic electroencephalographic (EEG changes that accompanies a true epileptic seizure [1]. It is considered that PNES is a somatic manifestation of mental distress, in response to a psychological conflict or other Stressors [2]. A wide spectrum of clinical presentation includes syncope, generalized tonic-clonic seizure, simple and complex partial seizure, myoclonic seizure, frontal lobe seizures and status epilepticus [3]. Coexistence of epilepsy and PNES is seen in approximately 9% of cases [5]. Between 25-30% of patients referred to tertiary centers and initially diagnosed as refractory epilepsy were on further examination diagnosed as PNES [6,7]. In DSM-IV [12] PNES are usually categorized under conversion disorder with seizures or convulsions. However, psychiatric basis of PNES may be anxiousness (panic attack, somatization or factitious disorder, simulation, dissociative disorders and psychosis [1]. AIM The aim of the study was to establish clinical phenomenology and EEG characteristics as well as basic psychiatric disorder in patients with PNES. METHOD In a retrospective study covering the period from January 1st 1999 till April 31 st 2003, 24 patients (22 female, 2 male treated at the Institute of Neurology in Belgrade were analyzed. PNES were defined as sudden change in behavior incoherent with epileptiform activity registered on EEG. Possible PNES were determined on the basis of history data and clinical examination during the attack but definitive confirmation was established only by the finding of no ictal EEG changes during typical seizure of each patient. Patients with coexisting epilepsy were included in the study, too. At least two standard EEG (range 2-6, median 4 were performed at the beginning of

EEG dynamical correlates of focal and diffuse causes of coma.

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Kafashan, MohammadMehdi; Ryu, Shoko; Hargis, Mitchell J; Laurido-Soto, Osvaldo; Roberts, Debra E; Thontakudi, Akshay; Eisenman, Lawrence; Kummer, Terrance T; Ching, ShiNung

2017-11-15

Rapidly determining the causes of a depressed level of consciousness (DLOC) including coma is a common clinical challenge. Quantitative analysis of the electroencephalogram (EEG) has the potential to improve DLOC assessment by providing readily deployable, temporally detailed characterization of brain activity in such patients. While used commonly for seizure detection, EEG-based assessment of DLOC etiology is less well-established. As a first step towards etiological diagnosis, we sought to distinguish focal and diffuse causes of DLOC through assessment of temporal dynamics within EEG signals. We retrospectively analyzed EEG recordings from 40 patients with DLOC with consensus focal or diffuse culprit pathology. For each recording, we performed a suite of time-series analyses, then used a statistical framework to identify which analyses (features) could be used to distinguish between focal and diffuse cases. Using cross-validation approaches, we identified several spectral and non-spectral EEG features that were significantly different between DLOC patients with focal vs. diffuse etiologies, enabling EEG-based classification with an accuracy of 76%. Our findings suggest that DLOC due to focal vs. diffuse injuries differ along several electrophysiological parameters. These results may form the basis of future classification strategies for DLOC and coma that are more etiologically-specific and therefore therapeutically-relevant.

Source and sink nodes in absence seizures.

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Rodrigues, Abner C; Machado, Birajara S; Caboclo, Luis Otavio S F; Fujita, Andre; Baccala, Luiz A; Sameshima, Koichi

2016-08-01

As opposed to focal epilepsy, absence seizures do not exhibit a clear seizure onset zone or focus since its ictal activity rapidly engages both brain hemispheres. Yet recent graph theoretical analysis applied to absence seizures EEG suggests the cortical focal presence, an unexpected feature for this type of epilepsy. In this study, we explore the characteristics of absence seizure by classifying the nodes as to their source/sink natures via weighted directed graph analysis based on connectivity direction and strength estimation using information partial directed coherence (iPDC). By segmenting the EEG signals into relatively short 5-sec-long time windows we studied the evolution of coupling strengths from both sink and source nodes, and the network dynamics of absence seizures in eight patients.

Seizure detection using dynamic warping for patients with intellectual disability

NARCIS (Netherlands)

Wang, L.; Arends, J.B.A.M.; Long, X.; Wu, Y.; Cluitmans, P.J.M.

2016-01-01

Electroencephalography (EEG) is paramount for both retrospective analysis and real-time monitoring of epileptic seizures. Studies have shown that EEG-based seizure detection is very difficult for a specific epileptic population with intellectual disability due to the cerebral development disorders.

Temporal lobe origin is common in patients who have undergone epilepsy surgery for hypermotor seizures.

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Arain, Amir M; Azar, Nabil J; Lagrange, Andre H; McLean, Michael; Singh, Pradumna; Sonmezturk, Hasan; Konrad, Peter; Neimat, Joseph; Abou-Khalil, Bassel

2016-11-01

Hypermotor seizures are most often reported from the frontal lobe but may also have temporal, parietal, or insular origin. We noted a higher proportion of patients with temporal lobe epilepsy in our surgical cohort who had hypermotor seizures. We evaluated the anatomic localization and surgical outcome in patient with refractory hypermotor seizures who had epilepsy surgery in our center. We identified twenty three patients with refractory hypermotor seizures from our epilepsy surgery database. We analyzed demographics, presurgical evaluation including semiology, MRI, PET scan, interictal/ictal scalp video-EEG, intracranial recording, and surgical outcomes. We evaluated preoperative variables as predictors of outcome. Most patients (65%) had normal brain MRI. Intracranial EEG was required in 20 patients (86.9%). Based on the presurgical evaluation, the resection was anterior temporal in fourteen patients, orbitofrontal in four patients, cingulate in four patients, and temporoparietal in one patient. The median duration of follow-up after surgery was 76.4months. Fourteen patients (60%) had been seizure free at the last follow up while 3 patients had rare disabling seizures. Hypermotor seizures often originated from the temporal lobe in this series of patients who had epilepsy surgery. This large proportion of temporal lobe epilepsy may be the result of a selection bias, due to easier localization and expected better outcome in temporal lobe epilepsy. With extensive presurgical evaluation, including intracranial EEG when needed, seizure freedom can be expected in the majority of patients. Copyright © 2016. Published by Elsevier Inc.

Electroencephalographic characterization of seizure activity in the synapsin I/II double knockout mouse

DEFF Research Database (Denmark)

Etholm, Lars; Lindén, Henrik; Eken, Torsten

2011-01-01

We present a detailed comparison of the behavioral and electrophysiological development of seizure activity in mice genetically depleted of synapsin I and synapsin II (SynDKO mice), based on combined video and surface EEG recordings. SynDKO mice develop handling-induced epileptic seizures...... at the age of 2months. The seizures show a very regular behavioral pattern, where activity is initially dominated by truncal muscle contractions followed by various myoclonic elements. Whereas seizure behavior goes through clearly defined transitions, cortical activity as reflected by EEG recordings shows...... a more gradual development with respect to the emergence of different EEG components and the frequency of these components. No EEG pattern was seen to define a particular seizure behavior. However, myoclonic activity was characterized by more regular patterns of combined sharp waves and spikes. Where...

Ictal time-irreversible intracranial EEG signals as markers of the epileptogenic zone.

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Schindler, Kaspar; Rummel, Christian; Andrzejak, Ralph G; Goodfellow, Marc; Zubler, Frédéric; Abela, Eugenio; Wiest, Roland; Pollo, Claudio; Steimer, Andreas; Gast, Heidemarie

2016-09-01

To show that time-irreversible EEG signals recorded with intracranial electrodes during seizures can serve as markers of the epileptogenic zone. We use the recently developed method of mapping time series into directed horizontal graphs (dHVG). Each node of the dHVG represents a time point in the original intracranial EEG (iEEG) signal. Statistically significant differences between the distributions of the nodes' number of input and output connections are used to detect time-irreversible iEEG signals. In 31 of 32 seizure recordings we found time-irreversible iEEG signals. The maximally time-irreversible signals always occurred during seizures, with highest probability in the middle of the first seizure half. These signals spanned a large range of frequencies and amplitudes but were all characterized by saw-tooth like shaped components. Brain regions removed from patients who became post-surgically seizure-free generated significantly larger time-irreversibilities than regions removed from patients who still had seizures after surgery. Our results corroborate that ictal time-irreversible iEEG signals can indeed serve as markers of the epileptogenic zone and can be efficiently detected and quantified in a time-resolved manner by dHVG based methods. Ictal time-irreversible EEG signals can help to improve pre-surgical evaluation in patients suffering from pharmaco-resistant epilepsies. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Clinical profile of patients with nascent alcohol related seizures

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P Sandeep

2013-01-01

Full Text Available Aim: The aim of this study is to characterize the clinical profile of patients with alcohol related seizures (ARS and to identify the prevalence of idiopathic generalized epilepsy (IGE in the same. Materials and Methods: 100 consecutive male patients presenting to a tertiary care center in South India with new onset ARS were analyzed with alcohol use disorders identification test (AUDIT score. All underwent 19 channel digital scalp electroencephalography (EEG and at least computed tomography (CT scan. Results: A total of 27 patients (27% who had cortical atrophy on CT had a mean duration of alcohol intake of 23.62 years compared with 14.55 years in patients with no cortical atrophy (P < 0.001. Twenty-two patients (22% had clustering in the current episode of whom 18 had cortical atrophy. Nearly, 88% patients had generalized tonic clonic seizures while 12% who had partial seizures underwent magnetic resonance imaging (MRI, which identified frontal focal cortical dysplasia in one. Mean lifetime duration of alcohol intake in patients presenting with seizures within 6 hours (6H-gp of intake of alcohol was significantly lower (P = 0.029. One patient in the 6H-gp with no withdrawal symptoms had EEG evidence for IGE and had a lower AUDIT score compared with the rest. Conclusion: CT evidence of cortical atrophy is related to the duration of alcohol intake and portends an increased risk for clustering. Partial seizures can be a presenting feature of ARS and those patients may benefit from MRI to identify underlying symptomatic localization related epilepsy (8.3% of partial seizures. IGE is more likely in patients presenting with ARS within first 6 hours especially if they do not have alcohol withdrawal symptoms and scalp EEG is helpful to identify this small subgroup (~1% who may require long-term anti-epileptic medication.

Emotion-induced myoclonic absence-like seizures in a patient with inv-dup(15) syndrome: a clinical, EEG, and molecular genetic study.

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Aguglia, U; Le Piane, E; Gambardella, A; Messina, D; Russo, C; Sirchia, S M; Porta, G; Quattrone, A

1999-09-01

We have described a clinical EEG and molecular genetic study of a 9-year-old boy with inv-dup(15) syndrome in whom seizures were induced by emotionally gratifying stimuli. The reflex seizures began 5-20 s after the onset of repeated cheek-kissing from his mother or after viewing of pleasant or funny events. They were characterized by bilateral discharges involving mainly the temporal regions and evolving into myoclonic absence-like seizures. Nonemotional stimuli, such as a pinch, sucking or rubbing his cheeks, or the sound of the kiss alone, failed to provoke seizures. The seizures were resistant to antiepileptic (AED) treatments. Molecular genetic investigations revealed a correct methylation pattern of the chromosomes 15, and three copies (two maternal and one paternal) of the segment 15q11-q13, including the GABRb3 gene. We hypothesize that an overexpression of cerebral gamma-aminobutyric acid (GABA)-mediated inhibition accounts for the severe epilepsy that we observed in this patient.

The EEG, CT and Tc-99m HMPAO SPECT study in patients with epilepsy

International Nuclear Information System (INIS)

Tovuudorj, A.; Tsagaankhuu, G.; Onkhuudai, P.; Tsevelmaa, L.; Sereegotov, E.; Enkhtuya, B.

2007-01-01

Full text: We have put an objective of studying the EEG and neuroimaging diagnostic indexes (CT, SPECT) in patients with partial seizures during interictal period. Methods: In our study a total of 35 cases were included (20 male and 15 females). In EEG studies we used the diagnostics methodology elaborated by L.R.Zenkov (1996) and in SPECT study by Payne JK (1991) and in CT investigation by Chermissan V.M (2001). Results: By EEG study the cases of interictal period of partial seizure were mostly revealed in the form of sharp waves in temporal lobe (47.62.5%). By CT study the 18 (51.4 ± 2.5 %) cases of partial seizure with normal index, 12 (34.3 ± 1.8 %) cases with dilatation of ventricles and 5 (14.3 ± 2.1%) cases of cerebral atrophy. In SPECT investigation we identified 8 (22.81.8%) cases with normal brain blood flow supply and 27 (77.2 2.0%) cases with variable degrees of hypoperfusion (AI) in the temporal lobe was reaching 233.9% (p<0.01). Conclusion: 1. On EEG analysis during interictal period of partial seizures, there were prevailing sharp-waves (47.6 ± 2.5%) at temporal location of a hemispheres. 2. The brain CT investigation during epilepsy mostly revealed the normal indexes 3. By analyzing brain SPECT during the interictal period of seizures, there were prevailing hypoperfusion degrees (AI) of blood flow to reach 23.0 ± 3.9%. (author)

Examinations with computerized cranial axial tomography carried out on patients with epileptic seizures, taking into consideration the EEG and the clinical picture

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Geiser, R.

1982-01-01

204 patients suffering from epileptic seizures were examined with the help of computerized cranial X-ray tomography; the results were compared with anamnestic, clinical, and EEC-findings. In good agreement with results published in literature, in 54% of the patients pathologic CT's such as tumours, attack scars, changes in ventricles and arachnoid spaces etc. were found. A pathological CT is very likely to appear in male patients who are 30 or even 50 years of age, having partial attacks with elementary symptoms, focal diagnosis in the EEG and a neurological unilateral finding. Especially noteworthy is the tumour detecting rate achieved by CT and the fact that in nearly 5% of the cases CT detected a cerebral lesion which has not been suspected, neither clinically nor in the EEG (4 tumours). This shows clearly that CT represents a heighly valuable diagnostic help, especially for patients with epileptic seizures. (orig./MG) [de

The FNS-based analyzing the EEG to diagnose the bipolar affective disorder

International Nuclear Information System (INIS)

Panischev, Yu; Panischeva, S N; Demin, S A

2015-01-01

Here we demonstrate a capability of method based on the Flicker-Noise Spectroscopy (FNS) in analyzing the manifestation bipolar affective disorder (BAD) in EEG. Generally EEG from BAD patient does not show the visual differences from healthy EEG. Analyzing the behavior of FNS-parameters and the structure of 3D-cross correlators allows to discover the differential characteristics of BAD. The cerebral cortex electric activity of BAD patients have a specific collective dynamics and configuration of the FNS-characteristics in comparison with healthy subjects. (paper)

Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data.

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Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios

2014-01-01

To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Benign occipital lobe seizures: Natural progression and atypical evolution

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Prithika Chary

2013-01-01

Full Text Available Benign occipital seizure syndromes are benign childhood epilepsy syndromes and are mainly of two types, Panayiotopoulos syndrome, an autonomic epilepsy and idiopathic childhood occipital epilepsy of Gastaut (ICOE-G including the idiopathic photosensitive occipital lobe epilepsy. Although both these types are categorized as occipital seizures, they are distinct in presentation and management. They can also be tricky to diagnose as visual symptoms may not always be the presenting feature and it is also not very easy to elicit visual hallucinations during history taking. These seizures have a good response to treatment; however, there could be atypical evolution and refractoriness to treatment especially with ICOE-G. We describe three children who presented with visual and non-visual symptoms and the electroencephalography (EEG in all the three cases showed occipital paroxysms. We have emphasized the clues in the clinical history and EEG leading to the diagnosis of these distinct epilepsy syndromes. We have also discussed the natural course of these epilepsy syndromes with some atypical evolution, which clinicians need to be aware of during treatment of these children.

Benign occipital lobe seizures: Natural progression and atypical evolution.

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Chary, Prithika; Rajendran, Bhuvaneshwari

2013-10-01

Benign occipital seizure syndromes are benign childhood epilepsy syndromes and are mainly of two types, Panayiotopoulos syndrome, an autonomic epilepsy and idiopathic childhood occipital epilepsy of Gastaut (ICOE-G) including the idiopathic photosensitive occipital lobe epilepsy. Although both these types are categorized as occipital seizures, they are distinct in presentation and management. They can also be tricky to diagnose as visual symptoms may not always be the presenting feature and it is also not very easy to elicit visual hallucinations during history taking. These seizures have a good response to treatment; however, there could be atypical evolution and refractoriness to treatment especially with ICOE-G. We describe three children who presented with visual and non-visual symptoms and the electroencephalography (EEG) in all the three cases showed occipital paroxysms. We have emphasized the clues in the clinical history and EEG leading to the diagnosis of these distinct epilepsy syndromes. We have also discussed the natural course of these epilepsy syndromes with some atypical evolution, which clinicians need to be aware of during treatment of these children.

The effect of propofol-remifentanil anesthesia on selected seizure quality indices in electroconvulsive therapy.

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Dinwiddie, Stephen H; Glick, David B; Goldman, Morris B

2012-07-01

Use of a short-acting opiate to potentiate anesthetic induction agents has been shown to increase seizure duration in electroconvulsive therapy (ECT), but little is known of the effect of this combination on indices of seizure quality. To determine whether anesthetic modality affects commonly provided indices of seizure quality. Twenty-five subjects were given propofol 2 mg/kg body weight for their first ECT session, at which time seizure threshold was titrated. Subjects thereafter alternated between that anesthetic regimen or propofol 0.5 mg/kg plus remifentanil 1 mcg/kg. Linear mixed models with random subject effect, adjusting for electrode placement, electrical charge, and number of treatments, were fit to estimate effect of anesthesia on seizure duration and several standard seizure quality indices (average seizure energy, time to peak electroencephalography (EEG) power, maximum sustained power, interhemispheric coherence, early and midictal EEG amplitude, and maximum sustained interhemispheric EEG coherence). Propofol-remifentanil anesthesia significantly lengthened seizure duration and was associated with longer time to reach maximal EEG power and coherence as well as maximal degree of interhemispheric EEG coherence. No effect was seen on early ictal amplitude or average seizure energy index. Propofol-remifentanil anesthesia prolongs seizure duration and has a significant effect on some, but not all, measures of seizure quality. This effect may be of some benefit in cases where adequate seizures are otherwise difficult to elicit. Varying anesthetic technique may allow more precise investigation of the relationships between and relative impacts of commonly used seizure quality indices on clinical outcomes and ECT-related cognitive side effects. Copyright © 2012 Elsevier Inc. All rights reserved.

Etiology and Outcome of Neonatal Seizures

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J Gordon Millichap

2006-04-01

Full Text Available The prognostic value of seizure etiology, neurologic examination, EEG, and neuroimaging in the neurodevelopmental outcome of 89 term infants with neonatal seizures was determined at the Children’s Hospital and Harvard Medical School, Boston, MA.

The influence of the anesthesia-to-stimulation time interval on seizure quality parameters in electroconvulsive therapy

DEFF Research Database (Denmark)

Jorgensen, A; Christensen, S J; Jensen, A E K

2018-01-01

BACKGROUND: Electroconvulsive therapy (ECT) continues to be the most efficacious treatment for severe depression and other life-threatening acute psychiatric conditions. Treatment efficacy is dependent upon the induced seizure quality, which may be influenced by a range of treatment related factors....... Recently, the time interval from anesthesia to the electrical stimulation (ASTI) has been suggested to be an important determinant of seizure quality. METHODS: We measured ASTI in 73 ECT sessions given to 22 individual patients, and analyzed its influence on five seizure quality parameters (EEG seizure...

Clinical and eeg analysis of mesial and lateral temporal lobe seizures Análise clínica e eletrencefalográfica de crises epilépticas temporais de origem mesial e lateral

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FÁBIO GALVÃO DANTAS

1998-09-01

Full Text Available The analysis of the temporal lobe seizures through video-EEG systems shows that they often consist of a sequence of clinical and EEG features which may suggest the localization and the lateralization of the epileptogenic lobe. We analyzed clinical and EEG features of 50 temporal lobe seizures which were separated in group 1 with 25 patients (related to mesial temporal sclerosis and group 2 with 25 patients (other neocortical temporal lesions. Among the auras, the epigastric type was the most frequent and predominated in group 1. There were differences between the two groups, considering dystonic and tonic posturing and versive head and eye movements. Dystonic posturing was always contralateral to the ictal onset and was considered the most useful lateralizing clinical feature. Ictal speech, spitting and blinking automatisms, prolonged disorientation for place and a greatest percentage of postictal language preservation occurred in right temporal seizures. Postictal aphasia and global disorientation predominated in left temporal seizures. EEG was important for lateralizing the epileptogenic lobe, specially considering rhythmic ictal activity and postictal findings.As crises epilépticas do lobo temporal tendem a seguir uma sequência previsível de eventos clínicos e eletrencefalográficos, cuja análise, preferencialmente através de sistemas de vídeo-EEG, sugere a localização e a lateralização do lobo epileptogênico. Para este estudo, foram analisadas 50 crises epilépticas do lobo temporal, do ponto de vista clínico e eletrencefalográfico, sendo 25 relacionadas a esclerose mesial (grupo 1 e 25 a patologias neocorticais (grupo 2. Auras abdominais foram as mais frequentes, predominando no grupo 1. Houve diferenças entre os dois grupos, quanto à instalação e duração da postura distônica, à postura tônica e à versão oculocefálica. Postura distônica unilateral foi o mais importante fenômeno clínico lateralizatório, sempre

Dextromethorphan in the treatment of early myoclonic encephalopathy evolving into migrating partial seizures in infancy

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Yin-Hsuan Chien

2012-05-01

Full Text Available Epileptic encephalopathy with suppression-burst in electroencephalography (EEG can evolve into a few types of epileptic syndromes. We present here an unusual case of early myoclonic encephalopathy that evolved into migrating partial seizures in infancy. A female neonate initially had erratic myoclonus movements, hiccups, and a suppression-burst pattern in EEG that was compatible with early myoclonic encephalopathy. The seizures were controlled with dextromethorphan (20 mg/kg, and a suppression-burst pattern in EEG was reverted to relatively normal background activity. However, at 72 days of age, alternating focal tonic seizures, compatible with migrating partial seizures in infancy, were demonstrated by the 24-hour EEG recording. The seizures responded poorly to dextromethorphan. To our knowledge, this is the first reported case of early myoclonic encephalopathy evolving into migrating partial seizure in infancy. Whether it represents another age-dependent epilepsy evolution needs more clinical observation.

Mapping cortical haemodynamics during neonatal seizures using diffuse optical tomography: A case study

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Harsimrat Singh

2014-01-01

Full Text Available Seizures in the newborn brain represent a major challenge to neonatal medicine. Neonatal seizures are poorly classified, under-diagnosed, difficult to treat and are associated with poor neurodevelopmental outcome. Video-EEG is the current gold-standard approach for seizure detection and monitoring. Interpreting neonatal EEG requires expertise and the impact of seizures on the developing brain remains poorly understood. In this case study we present the first ever images of the haemodynamic impact of seizures on the human infant brain, obtained using simultaneous diffuse optical tomography (DOT and video-EEG with whole-scalp coverage. Seven discrete periods of ictal electrographic activity were observed during a 60 minute recording of an infant with hypoxic–ischaemic encephalopathy. The resulting DOT images show a remarkably consistent, high-amplitude, biphasic pattern of changes in cortical blood volume and oxygenation in response to each electrographic event. While there is spatial variation across the cortex, the dominant haemodynamic response to seizure activity consists of an initial increase in cortical blood volume prior to a large and extended decrease typically lasting several minutes. This case study demonstrates the wealth of physiologically and clinically relevant information that DOT–EEG techniques can yield. The consistency and scale of the haemodynamic responses observed here also suggest that DOT–EEG has the potential to provide improved detection of neonatal seizures.

Neonatal Seizure Detection Using Deep Convolutional Neural Networks.

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Ansari, Amir H; Cherian, Perumpillichira J; Caicedo, Alexander; Naulaers, Gunnar; De Vos, Maarten; Van Huffel, Sabine

2018-04-02

Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not be optimal. The main goal of the present paper is using deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification. The input of the proposed classifier is raw multi-channel EEG and the output is the class label: seizure/nonseizure. By training this network, the required features are optimized, while fitting a nonlinear classifier on the features. After training the network with EEG recordings of 26 neonates, five end layers performing the classification were replaced with a random forest classifier in order to improve the performance. This resulted in a false alarm rate of 0.9 per hour and seizure detection rate of 77% using a test set of EEG recordings of 22 neonates that also included dubious seizures. The newly proposed CNN classifier outperformed three data-driven feature-based approaches and performed similar to a previously developed heuristic method.

Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation.

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Yuan, Shasha; Zhou, Weidong; Wu, Qi; Zhang, Yanli

2016-05-01

Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

Automatic Epileptic Seizure Onset Detection Using Matching Pursuit

DEFF Research Database (Denmark)

Sorensen, Thomas Lynggaard; Olsen, Ulrich L.; Conradsen, Isa

2010-01-01

. The combination of Matching Pursuit and SVM for automatic seizure detection has never been tested before, making this a pilot study. Data from red different patients with 6 to 49 seizures are used to test our model. Three patients are recorded with scalp electroencephalography (sEEG) and three with intracranial...... electroencephalography (iEEG). A sensitivity of 78-100% and a detection latency of 5-18s has been achieved, while holding the false detection at 0.16-5.31/h. Our results show the potential of Matching Pursuit as a feature xtractor for detection of epileptic seizures....

Influence of vigilance state on physiological consequences of seizures and seizure-induced death in mice.

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Hajek, Michael A; Buchanan, Gordon F

2016-05-01

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in patients with refractory epilepsy. SUDEP occurs more commonly during nighttime sleep. The details of why SUDEP occurs at night are not well understood. Understanding why SUDEP occurs at night during sleep might help to better understand why SUDEP occurs at all and hasten development of preventive strategies. Here we aimed to understand circumstances causing seizures that occur during sleep to result in death. Groups of 12 adult male mice were instrumented for EEG, EMG, and EKG recording and subjected to seizure induction via maximal electroshock (MES) during wakefulness, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Seizure inductions were performed with concomitant EEG, EMG, and EKG recording and breathing assessment via whole body plethysmography. Seizures induced via MES during sleep were associated with more profound respiratory suppression and were more likely to result in death. Despite REM sleep being a time when seizures do not typically occur spontaneously, when seizures were forced to occur during REM sleep, they were invariably fatal in this model. An examination of baseline breathing revealed that mice that died following a seizure had increased baseline respiratory rate variability compared with those that did not die. These data demonstrate that sleep, especially REM sleep, can be a dangerous time for a seizure to occur. These data also demonstrate that there may be baseline respiratory abnormalities that can predict which individuals have higher risk for seizure-induced death.

EEG controls for detecting the recurrence of supratentorial gliomas

International Nuclear Information System (INIS)

Leblhuber, F.; Olschowski, A.; Deisenhammer, E.; Hammer, B.; Knauer, W.

1984-01-01

The purpose of this study was to find out the value of postoperative EEG controls in the early detection of recurrence of supratentorial gliomas (the majority being astrocytomas, stage II to IV). 29 cases with verified tumour recurrence were examined and in all but one the EEG showed a reactivation of the focus in accordance with the development of the glioma. At least one of the following parameters had to be established: 1. a further spreading of the focal changes, 2. a reduction in frequency, 3. an increase in amplitudes and 4. focal depression and amplitudes. At least 3 postoperative EEG controls were made in each case. The duration of tumour treatment was 3 to 59 months. In 3 cases temporary focus activation was found without evidence of tumour recurrence; in one of these cases the activation was preceded by an epileptic seizure. Epileptic seizures, thus, seem to have a focus activating effect. Focus activation as a result of radiotherapy or cytostatic treatment was not observed. On the basis of our findings it appears that regularly conducted postoperative EEG controls seem to be highly suited as a non-invasive and economical method for the early detection of recurrence of this type of tumour. In the case of malignant types of gliomas involving rapid growth EEG controls should be made monthly. (Author)

Standardized computer-based organized reporting of EEG

DEFF Research Database (Denmark)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C.

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE....... In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE...

Tantrums, Emotion Reactions and Their EEG Correlates in Childhood Benign Rolandic Epilepsy vs. Complex Partial Seizures: Exploratory Observations.

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Potegal, Michael; Drewel, Elena H; MacDonald, John T

2018-01-01

We explored associations between EEG pathophysiology and emotional/behavioral (E/B) problems of children with two types of epilepsy using standard parent questionnaires and two new indicators: tantrums recorded by parents at home and brief, emotion-eliciting situations in the laboratory. Children with Benign Rolandic epilepsy (BRE, N = 6) reportedly had shorter, more angry tantrums from which they recovered quickly. Children with Complex Partial Seizures (CPS, N = 13) had longer, sadder tantrums often followed by bad moods. More generally, BRE correlated with anger and aggression; CPS with sadness and withdrawal. Scores of a composite group of siblings ( N = 11) were generally intermediate between the BRE and CPS groups. Across all children, high voltage theta and/or interictal epileptiform discharges (IEDs) correlated with negative emotional reactions. Such EEG abnormalities in left hemisphere correlated with greater social fear, right hemisphere EEG abnormalities with greater anger. Right hemisphere localization in CPS was also associated with parent-reported problems at home. If epilepsy alters neural circuitry thereby increasing negative emotions, additional assessment of anti-epileptic drug treatment of epilepsy-related E/B problems would be warranted.

White matter abnormalities in the anterior temporal lobe suggest the side of the seizure foci in temporal lobe epilepsy

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Adachi, Y.; Yagishita, A. [Tokyo Metropolitan Neurological Hospital, Department of Neuroradiology, Fuchu, Tokyo (Japan); Arai, N. [Tokyo Metropolitan Neurological Institute, Department of Clinical Neuropathology, Fuchu, Tokyo (Japan)

2006-07-15

White matter abnormalities in the anterior temporal lobe (WAATL) are sometimes observed on magnetic resonance (MR) images of patients with temporal lobe epilepsy (TLE). Our purpose was to determine whether WAATL could indicate if the seizure foci are ipsilateral on electroencephalograms (EEG) in TLE patients. We reviewed 112 consecutive patients with medically intractable TLE. We compared the side of seizure foci on EEG (preoperative and intraoperative) and MR images. Both loss of gray-white matter demarcation and increased signal intensity changes in the anterior white matter (positive WAATL) were observed in 54 of 112 patients (48.2%) with TLE. WAATL were present on the same side as the seizure foci on preoperative intracranial EEG with subdural electrodes (iEEG) and on intraoperative electrocorticography (ECG) in all the patients. In 47 patients, MR images showed WAATL and focal lesions that were possibly epileptogenic for TLE. In 2 of the 47 patients, the seizure foci on iEEG and ECG were contralateral to the focal lesion; in the remaining 45 patients, the seizure foci on surface EEG (sEEG) and ECG and the focal lesion were on the same side. In three patients, no focal lesions were seen but WAATL were present on the same side as the seizure foci on sEEG and ECG. In four patients, MR images showed focal lesions for which epileptogenicity was questionable, and WAATL on the same side as the seizure foci on EEG. WAATL are clinically useful because they indicate the side of the seizure foci. (orig.)

White matter abnormalities in the anterior temporal lobe suggest the side of the seizure foci in temporal lobe epilepsy

International Nuclear Information System (INIS)

Adachi, Y.; Yagishita, A.; Arai, N.

2006-01-01

White matter abnormalities in the anterior temporal lobe (WAATL) are sometimes observed on magnetic resonance (MR) images of patients with temporal lobe epilepsy (TLE). Our purpose was to determine whether WAATL could indicate if the seizure foci are ipsilateral on electroencephalograms (EEG) in TLE patients. We reviewed 112 consecutive patients with medically intractable TLE. We compared the side of seizure foci on EEG (preoperative and intraoperative) and MR images. Both loss of gray-white matter demarcation and increased signal intensity changes in the anterior white matter (positive WAATL) were observed in 54 of 112 patients (48.2%) with TLE. WAATL were present on the same side as the seizure foci on preoperative intracranial EEG with subdural electrodes (iEEG) and on intraoperative electrocorticography (ECG) in all the patients. In 47 patients, MR images showed WAATL and focal lesions that were possibly epileptogenic for TLE. In 2 of the 47 patients, the seizure foci on iEEG and ECG were contralateral to the focal lesion; in the remaining 45 patients, the seizure foci on surface EEG (sEEG) and ECG and the focal lesion were on the same side. In three patients, no focal lesions were seen but WAATL were present on the same side as the seizure foci on sEEG and ECG. In four patients, MR images showed focal lesions for which epileptogenicity was questionable, and WAATL on the same side as the seizure foci on EEG. WAATL are clinically useful because they indicate the side of the seizure foci. (orig.)

Generalized Hurst exponent estimates differentiate EEG signals of healthy and epileptic patients

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Lahmiri, Salim

2018-01-01

The aim of our current study is to check whether multifractal patterns of the electroencephalographic (EEG) signals of normal and epileptic patients are statistically similar or different. In this regard, the generalized Hurst exponent (GHE) method is used for robust estimation of the multifractals in each type of EEG signals, and three powerful statistical tests are performed to check existence of differences between estimated GHEs from healthy control subjects and epileptic patients. The obtained results show that multifractals exist in both types of EEG signals. Particularly, it was found that the degree of fractal is more pronounced in short variations of normal EEG signals than in short variations of EEG signals with seizure free intervals. In contrary, it is more pronounced in long variations of EEG signals with seizure free intervals than in normal EEG signals. Importantly, both parametric and nonparametric statistical tests show strong evidence that estimated GHEs of normal EEG signals are statistically and significantly different from those with seizure free intervals. Therefore, GHEs can be efficiently used to distinguish between healthy and patients suffering from epilepsy.

Using of the interictal EEGs for epilepsy diagnosing

International Nuclear Information System (INIS)

Panischev, O Yu; Demin, S A; Zinatullin, E M

2015-01-01

In this work we apply a new method to determine the differences in characteristics of the cortical electroencephalographic (EEG) activity, measured during interictal stage (i.e., period between seizures), between healthy subjects and patients with epilepsy. To analyze the dynamical and spectral properties of bioelectric activity we use power spectra and phase portraits which are introduced on the basis of the Memory Function Formalism (MFF). We discover the significant differences in the types of power spectra of the EEG for healthy subjects and patients. We reveal the cerebral cortex areas for which the EEG activity of considered groups of subjects has a different structure of the phase portraits. The proposed approach can be used as an additional method for diagnosis of epilepsy during interictal stage. (paper)

Photogenic partial seizures.

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Hennessy, M J; Binnie, C D

2000-01-01

To establish the incidence and symptoms of partial seizures in a cohort of patients investigated on account of known sensitivity to intermittent photic stimulation and/or precipitation of seizures by environmental visual stimuli such as television (TV) screens or computer monitors. We report 43 consecutive patients with epilepsy, who had exhibited a significant EEG photoparoxysmal response or who had seizures precipitated by environmental visual stimuli and underwent detailed assessment of their photosensitivity in the EEG laboratory, during which all were questioned concerning their ictal symptoms. All patients were considered on clinical grounds to have an idiopathic epilepsy syndrome. Twenty-eight (65%) patients reported visually precipitated attacks occurring initially with maintained consciousness, in some instances evolving to a period of confusion or to a secondarily generalized seizure. Visual symptoms were most commonly reported and included positive symptoms such as coloured circles or spots, but also blindness and subjective symptoms such as "eyes going funny." Other symptoms described included nonspecific cephalic sensations, deja-vu, auditory hallucinations, nausea, and vomiting. No patient reported any clear spontaneous partial seizures, and there were no grounds for supposing that any had partial epilepsy excepting the ictal phenomenology of some or all of the visually induced attacks. These findings provide clinical support for the physiological studies that indicate that the trigger mechanism for human photosensitivity involves binocularly innervated cells located in the visual cortex. Thus the visual cortex is the seat of the primary epileptogenic process, and the photically triggered discharges and seizures may be regarded as partial with secondary generalization.

Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier.

Science.gov (United States)

Sriraam, N; Raghu, S

2017-09-02

Identifying epileptogenic zones prior to surgery is an essential and crucial step in treating patients having pharmacoresistant focal epilepsy. Electroencephalogram (EEG) is a significant measurement benchmark to assess patients suffering from epilepsy. This paper investigates the application of multi-features derived from different domains to recognize the focal and non focal epileptic seizures obtained from pharmacoresistant focal epilepsy patients from Bern Barcelona database. From the dataset, five different classification tasks were formed. Total 26 features were extracted from focal and non focal EEG. Significant features were selected using Wilcoxon rank sum test by setting p-value (p z > 1.96) at 95% significance interval. Hypothesis was made that the effect of removing outliers improves the classification accuracy. Turkey's range test was adopted for pruning outliers from feature set. Finally, 21 features were classified using optimized support vector machine (SVM) classifier with 10-fold cross validation. Bayesian optimization technique was adopted to minimize the cross-validation loss. From the simulation results, it was inferred that the highest sensitivity, specificity, and classification accuracy of 94.56%, 89.74%, and 92.15% achieved respectively and found to be better than the state-of-the-art approaches. Further, it was observed that the classification accuracy improved from 80.2% with outliers to 92.15% without outliers. The classifier performance metrics ensures the suitability of the proposed multi-features with optimized SVM classifier. It can be concluded that the proposed approach can be applied for recognition of focal EEG signals to localize epileptogenic zones.

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy - A comparison with scalp EEG monitoring.

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Zibrandtsen, I C; Kidmose, P; Christensen, C B; Kjaer, T W

2017-12-01

Ear-EEG is recording of electroencephalography from a small device in the ear. This is the first study to compare ictal and interictal abnormalities recorded with ear-EEG and simultaneous scalp-EEG in an epilepsy monitoring unit. We recorded and compared simultaneous ear-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal spikes. There were no differences in sensitivity or specificity for seizure detection. Mean correlation coefficient between ear-EEG and nearest scalp electrode was above 0.6 with a statistically significant decreasing trend with increasing distance away from the ear. Ictal morphology and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance. Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Headache as an Aura of Epilepsy: Video-EEG Monitoring Study.

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Kim, Dong Wook; Sunwoo, Jun-Sang; Lee, Sang Kun

2016-04-01

Headache can be associated with epilepsy as a pre-ictal, ictal, or post-ictal phenomenon; however, studies of patients with headache as an epileptic aura are scarce. We performed the present study to investigate the incidence and characteristics of headache as an epileptic aura, via confirmation of electroencephalography (EEG) changes by video-EEG monitoring. Data of aura and clinical seizure episodes of 831 consecutive patients who undertook video-EEG monitoring were analyzed retrospectively. For patients who had headache as an aura, information on the detailed features of headache was acquired, including location, nature, duration, and the presence of accompanying symptoms. Video-recorded clinical seizures, EEG findings, and neuroimaging data were used to determine the ictal onset areas in the patients. Six out of 831 (0.7%) patients experienced headache as aura (age range, 25-52 years), all of whom had partial seizures. The incidence of pre-ictal headache was 6.3% (25/831), and post-ictal headache was 30.9% (257/831). In patients with headache as aura, five patients described headache as the most frequent aura, and headache was the second most frequent aura in one patient. The characteristics of headache were hemicrania epileptica in two patients, tension-type headache in another two patients, and migraine-like headache in the remaining two patients. No patient met the diagnostic criteria of ictal epileptic headache or migraine aura-triggered seizure. Our study showed that headache as an aura is uncommon in adult patients with epilepsy, and that headache can present as diverse features, including hemicrania epileptica, tension-type headache, and migraine-like headache. Further studies are necessary to characterize the features of headache as an epileptic aura in adult patients with epilepsy. © 2016 American Headache Society.

Frequency of seizures and epilepsy in neurological HIV-infected patients.

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Kellinghaus, C; Engbring, C; Kovac, S; Möddel, G; Boesebeck, F; Fischera, M; Anneken, K; Klönne, K; Reichelt, D; Evers, S; Husstedt, I W

2008-01-01

Infection with the human immunodeficiency virus (HIV) is associated both with infections of the central nervous system and with neurological deficits due to direct effects of the neurotropic virus. Seizures and epilepsy are not rare among HIV-infected patients. We investigated the frequency of acute seizures and epilepsy of patients in different stages of HIV infection. In addition, we compared the characteristics of patients who experienced provoked seizures only with those of patients who developed epilepsy. The database of the Department of Neurology, University of Münster, was searched for patients with HIV infection admitted between 1992 and 2004. Their charts were reviewed regarding all available sociodemographic, clinical, neurophysiological, imaging and laboratory data, therapy and outcome. Stage of infection according to the CDC classification and the epileptogenic zone were determined. Of 831 HIV-infected patients treated in our department, 51 (6.1%) had seizures or epilepsy. Three of the 51 patients (6%) were diagnosed with epilepsy before the onset of the HIV infection. Fourteen patients (27%) only had single or few provoked seizures in the setting of acute cerebral disorders (eight patients), drug withdrawal or sleep withdrawal (two patients), or of unknown cause (four patients). Thirty-four patients (67%) developed epilepsy in the course of their HIV infection. Toxoplasmosis (seven patients), progressive multifocal leukencephalopathy (seven patients) and other acute or subacute cerebral infections (five patients) were the most frequent causes of seizures. EEG data of 38 patients were available. EEG showed generalized and diffuse slowing only in 9 patients, regional slowing in 14 patients and regional slowing and epileptiform discharges in 1 patient. Only 14 of the patients had normal EEG. At the last contact, the majority of the patients (46 patients=90%) were on highly active antiretroviral therapy (HAART). Twenty-seven patients (53%) were on

Predictors and incidence of posttraumatic seizures in children and adolescents after brain injury

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Athanasios K. Petridis

2012-06-01

Full Text Available The present study evaluates the incidence of early and late seizures after head injury in patients under 18 years old. Factors correlating with a high risk of developing posttraumatic seizures were identified. Such risk factors were the severity of the head trauma and a Glasgow Coma Scale of 3-8. In contrast to many studies, we observed that the incidence of posttraumatic seizures was significantly higher in patients older than 12 years old (12-16 and 12-18. Most of the late seizures were paroxysmal electroencephalography (EEG discharges diagnosed on a snapshot-EEG during the follow-up examination of the patients without clinical symptoms. We suppose that EEG-examination in head injured children is important to identify patients with epileptic potentials without clinical symptoms. Epileptic patterns of the EEG could worsen the diagnosis and clinical outcome of the children in accordance to studies performed in the adult population.

Seizure outcomes of temporal lobe epilepsy surgery in patients with normal MRI and without specific histopathology.

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Ivanovic, Jugoslav; Larsson, Pål G; Østby, Ylva; Hald, John; Krossnes, Bård K; Fjeld, Jan G; Pripp, Are H; Alfstad, Kristin Å; Egge, Arild; Stanisic, Milo

2017-05-01

Seizure outcome following surgery in pharmacoresistant temporal lobe epilepsy patients with normal magnetic resonance imaging and normal or non-specific histopathology is not sufficiently presented in the literature. In a retrospective design, we reviewed data of 263 patients who had undergone temporal lobe epilepsy surgery and identified 26 (9.9%) who met the inclusion criteria. Seizure outcomes were determined at 2-year follow-up. Potential predictors of Engel class I (satisfactory outcome) were identified by logistic regression analyses. Engel class I outcome was achieved in 61.5% of patients, 50% being completely seizure free (Engel class IA outcome). The strongest predictors of satisfactory outcome were typical ictal seizure semiology (p = 0.048) and localised ictal discharges on scalp EEG (p = 0.036). Surgery might be an effective treatment choice for the majority of these patients, although outcomes are less favourable than in patients with magnetic resonance imaging-defined lesional temporal lobe epilepsy. Typical ictal seizure semiology and localised ictal discharges on scalp EEG were predictors of Engel class I outcome.

Automatic multimodal detection for long-term seizure documentation in epilepsy.

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Fürbass, F; Kampusch, S; Kaniusas, E; Koren, J; Pirker, S; Hopfengärtner, R; Stefan, H; Kluge, T; Baumgartner, C

2017-08-01

This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Panayiotopoulos syndrome and symptomatic occipital lobe epilepsy of childhood: a clinical and EEG study.

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Tata, Gulten; Guveli, Betul Tekin; Dortcan, Nimet; Cokar, Ozlem; Kurucu, Hatice; Demirbilek, Veysi; Dervent, Aysin

2014-06-01

Panayiotopoulos syndrome (PS) is an age-related seizure susceptibility syndrome that affects the central autonomic system. Although the majority of the few ictal recordings obtained so far suggest an occipital origin, semiological and interictal EEG data appear to favour more extensive involvement. In this study, the characteristics (including those based on semiology and EEG) of children with Panayiotopoulos syndrome (n=24) and those with lesion-related, symptomatic occipital lobe epilepsy (SOLE) (n=23) were compared. Detailed semiological information and EEG parameters including the localisation, distribution, density (n/sec), reactivity, and morphological characteristics of spike-wave foci and their relationship with different states of vigilance were compared between the two groups. The age at seizure onset was significantly younger in patients with symptomatic occipital lobe epilepsy than in those with PS (mean age at onset: 3.4 versus 5.6 years, respectively; p=0.044). Autonomic seizures (p=0.001) and ictal syncope (p=0.055) were more frequent in PS than in symptomatic occipital lobe epilepsy (87.5% and 37.5% versus 43.5% and 13%, respectively). The interictal spike-wave activity increased significantly during non-rapid eye movement (non-REM) sleep in both groups. The spike waves in non-REM seen in PS tended to spread mainly to central and centro-temporal regions. The results indicate that although common features do exist, Panayiotopoulos syndrome differs from symptomatic occipital lobe epilepsy and has a unique low epileptogenic threshold related to particular brain circuits.

A novel seizure detection algorithm informed by hidden Markov model event states

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Baldassano, Steven; Wulsin, Drausin; Ung, Hoameng; Blevins, Tyler; Brown, Mesha-Gay; Fox, Emily; Litt, Brian

2016-06-01

Objective. Recently the FDA approved the first responsive, closed-loop intracranial device to treat epilepsy. Because these devices must respond within seconds of seizure onset and not miss events, they are tuned to have high sensitivity, leading to frequent false positive stimulations and decreased battery life. In this work, we propose a more robust seizure detection model. Approach. We use a Bayesian nonparametric Markov switching process to parse intracranial EEG (iEEG) data into distinct dynamic event states. Each event state is then modeled as a multidimensional Gaussian distribution to allow for predictive state assignment. By detecting event states highly specific for seizure onset zones, the method can identify precise regions of iEEG data associated with the transition to seizure activity, reducing false positive detections associated with interictal bursts. The seizure detection algorithm was translated to a real-time application and validated in a small pilot study using 391 days of continuous iEEG data from two dogs with naturally occurring, multifocal epilepsy. A feature-based seizure detector modeled after the NeuroPace RNS System was developed as a control. Main results. Our novel seizure detection method demonstrated an improvement in false negative rate (0/55 seizures missed versus 2/55 seizures missed) as well as a significantly reduced false positive rate (0.0012 h versus 0.058 h-1). All seizures were detected an average of 12.1 ± 6.9 s before the onset of unequivocal epileptic activity (unequivocal epileptic onset (UEO)). Significance. This algorithm represents a computationally inexpensive, individualized, real-time detection method suitable for implantable antiepileptic devices that may considerably reduce false positive rate relative to current industry standards.

Multi-modal intelligent seizure acquisition (MISA) system--a new approach towards seizure detection based on full body motion measures.

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Conradsen, Isa; Beniczky, Sandor; Wolf, Peter; Terney, Daniella; Sams, Thomas; Sorensen, Helge B D

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG) and audio and video recording. The results showed that a non-subject specific MISA system developed on data from the modalities: accelerometer (ACM), gyroscope and EMG is able to detect 98% of the simulated seizures and at the same time mistakes only 4 of the normal movements for seizures. If the system is individualized (subject specific) it is able to detect all simulated seizures with a maximum of 1 false positive. Based on the results from the simulated seizures and normal movements the MISA system seems to be a promising approach to seizure detection.

Characteristics of seizure-induced signal changes on MRI in patients with first seizures.

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Kim, Si Eun; Lee, Byung In; Shin, Kyong Jin; Ha, Sam Yeol; Park, JinSe; Park, Kang Min; Kim, Hyung Chan; Lee, Joonwon; Bae, Soo-Young; Lee, Dongah; Kim, Sung Eun

2017-05-01

The aim of this study was to investigate the predictive factors and identify the characteristics of the seizure-induced signal changes on MRI (SCM) in patients with first seizures. We conducted a retrospective study of patients with first seizures from March 2010 to August 2014. The inclusion criteria for this study were patients with 1) first seizures, and 2) MRI and EEG performed within 24h of the first seizures. The definition of SCM was hyper-intensities in the brain not applying to cerebral arterial territories. Multivariate logistic regression was performed with or without SCM as a dependent variable. Of 431 patients with seizures visiting the ER, 69 patients met the inclusion criteria. Of 69 patients, 11 patients (15.9%) had SCM. Epileptiform discharge on EEG (OR 29.7, 95% CI 1.79-493.37, p=0.018) was an independently significant variable predicting the presence of SCM in patients with first seizures. In addition, the topography of SCM was as follows; i) ipsilateral hippocampus, thalamus and cerebral cortex (5/11), ii) unilateral cortex (4/11), iii) ipsilateral thalamus and cerebral cortex (1/11), iv) bilateral hippocampus (1/11). Moreover, 6 out of 7 patients who underwent both perfusion CT and MRI exhibited unilateral cortical hyperperfusion with ipsilateral thalamic involvement reflecting unrestricted vascular territories. There is an association between epileptiform discharges and SCM. Additionally, the involvement of the unilateral cortex and ipsilateral thalamus in SCM and its hyperperfusion state could be helpful in differentiating the consequences of epileptic seizures from other pathologies. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The prevalence of thyrotoxicosis-related seizures.

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Song, Tae-Jin; Kim, Sun-Jung; Kim, Gyu Sik; Choi, Young-Chul; Kim, Won-Joo

2010-09-01

Central nervous system dysfunction, such as hyperexcitation, irritability, and disturbance of consciousness, may occur in patients with thyrotoxicosis. There are also a few case reports of seizures attributed to thyrotoxicosis. The objective of the present study was to determine the prevalence of seizures that appeared to be related to the thyrotoxic state in patients with thyrotoxicosis. We retrospectively determined the prevalence and clinical features of seizures in 3382 patients with hyperthyroidism. Among patients with seizures, we excluded those with other causes of seizures or a history of epilepsy. We did not exclude two patients in whom later work-up showed an abnormal magnetic resonance imaging, as their seizures resolved after they became euthyroid. Among the 3382 patients with hyperthyroidism, there were seven patients (0.2%) with seizures who met our criteria. Primary generalized tonic-clonic seizures occurred in four patients (57%), complex partial seizures with secondary generalized tonic-clonic seizures occurred in two patients (29%), and one patient had a focal seizure (14%). The initial electroencephalography (EEG) was normal in two patients (29%), had generalized slow activity in four patients (57%), and had diffuse generalized beta activity in one patient (14%). On magnetic resonance imaging, one patient had diffuse brain atrophy, and one had an old basal ganglia infarct. After the patients became euthyroid, the EEG was repeated and was normal in all patients. During follow-up periods ranging from 18 to 24 months, none of the patients had seizures. Hyperthyroidism is the precipitating cause of seizures in a small percentage of these patients. In these patients, the prognosis is good if they become euthyroid. The prevalence of thyrotoxicosis-related seizures reported here can be used in conjunction with the prevalence of thyrotoxicosis in the population to estimate the prevalence of thyrotoxicosis-related seizures in populations.

A model based approach in observing the activity of neuronal populations for the prediction of epileptic seizures

International Nuclear Information System (INIS)

Chong, M.S.; Nesic, D.; Kuhlmann, L.; Postoyan, R.; Varsavsky, A.; Cook, M.

2010-01-01

Full text: Epilepsy is a common neurological disease that affects 0.5-1 % of the world's population. In cases where known treatments cannot achieve complete recovery, seizure prediction is essential so that preventive measures can be undertaken to prevent resultant injury. The elcctroencephalogram (EEG) is a widely used diagnostic tool for epilepsy. However, the EEG does not provide a detailed view of the underlying seizure causing neuronal mechanisms. Knowing the dynamics of the neuronal population is useful because tracking the evolution of the neuronal mechanisms will allow us to track the brain's progression from interictal to ictal state. Wendling and colleagues proposed a parameterised mathematical model that represents the activity of interconnected neuronal populations. By modifying the parameters, this model is able to reproduce signals that are very similar to the real EEG depicting commonly observed patterns during interictal and ictal periods. The transition from non-seizure to seizure activity, as seen in the EEG. is hypothesised to be due to the impairment of inhibition. Using Wendling's model, we designed a deterministic nonlinear estimator to recover the average membrane potential of the neuronal populations from a single channel EEG signal. for any fixed and known parameter values. Our nonlinear estimator is analytically proven to asymptotically converge to the true state of the model and illustrated in simulations. We were able to computationally observe the dynamics of the three neuronal populations described in the model: excitatory, fast and slow inhibitory populations. This forms a first step towards the prediction of epileptic seiwres. (author)

Incidence and localizing value of vertigo and dizziness in patients with epilepsy: Video-EEG monitoring study.

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Kim, Dong Wook; Sunwoo, Jun-Sang; Lee, Sang Kun

2016-10-01

Vertigo and dizziness are common neurological complaints that have long been associated with epilepsy. However, studies of patients with epileptic vertigo or dizziness with concurrent EEG monitoring are scarce. We performed the present study to investigate the incidence and localizing value of vertigo and dizziness in patients with epilepsy who had confirmation of EEG changes via video-EEG monitoring. Data of aura and clinical seizure episodes of 831 consecutive patients who underwent video-EEG monitoring were analyzed retrospectively. Out of 831 patients, 40 patients (4.8%) experienced vertigo or dizziness as aura (mean age, 32.8±11.8years), all of whom had partial seizures. Eight had mesial temporal, 20 had lateral temporal, four had frontal, one had parietal, and seven had occipital lobe onset seizures. An intracranial EEG with cortical stimulation study was performed in seven patients, and the area of stimulation-induced vertigo or dizziness coincided with the ictal onset area in only one patient. Our study showed that vertigo or dizziness is a common aura in patients with epilepsy, and that the temporal lobe is the most frequent ictal onset area in these patients. However, it can be suggested that the symptomatogenic area in patients with epileptic vertigo and dizziness may not coincide with the ictal onset area. Copyright © 2016 Elsevier B.V. All rights reserved.

Seizure characteristics of epilepsy in childhood after acute encephalopathy with biphasic seizures and late reduced diffusion.

Science.gov (United States)

Ito, Yuji; Natsume, Jun; Kidokoro, Hiroyuki; Ishihara, Naoko; Azuma, Yoshiteru; Tsuji, Takeshi; Okumura, Akihisa; Kubota, Tetsuo; Ando, Naoki; Saitoh, Shinji; Miura, Kiyokuni; Negoro, Tamiko; Watanabe, Kazuyoshi; Kojima, Seiji

2015-08-01

The aim of this study was to clarify characteristics of post-encephalopathic epilepsy (PEE) in children after acute encephalopathy with biphasic seizures and late reduced diffusion (AESD), paying particular attention to precise diagnosis of seizure types. Among 262 children with acute encephalopathy/encephalitis registered in a database of the Tokai Pediatric Neurology Society between 2005 and 2012, 44 were diagnosed with AESD according to the clinical course and magnetic resonance imaging (MRI) findings and were included in this study. Medical records were reviewed to investigate clinical data, MRI findings, neurologic outcomes, and presence or absence of PEE. Seizure types of PEE were determined by both clinical observation by pediatric neurologists and ictal video-electroencephalography (EEG) recordings. Of the 44 patients after AESD, 10 (23%) had PEE. The period between the onset of encephalopathy and PEE ranged from 2 to 39 months (median 8.5 months). Cognitive impairment was more severe in patients with PEE than in those without. Biphasic seizures and status epilepticus during the acute phase of encephalopathy did not influence the risk of PEE. The most common seizure type of PEE on clinical observation was focal seizures (n = 5), followed by epileptic spasms (n = 4), myoclonic seizures (n = 3), and tonic seizures (n = 2). In six patients with PEE, seizures were induced by sudden unexpected sounds. Seizure types confirmed by ictal video-EEG recordings were epileptic spasms and focal seizures with frontal onset, and all focal seizures were startle seizures induced by sudden acoustic stimulation. Intractable daily seizures remain in six patients with PEE. We demonstrate seizure characteristics of PEE in children after AESD. Epileptic spasms and startle focal seizures are common seizure types. The specific seizure types may be determined by the pattern of diffuse subcortical white matter injury in AESD and age-dependent reorganization of the brain

Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy.

Science.gov (United States)

Ramgopal, Sriram; Thome-Souza, Sigride; Jackson, Michele; Kadish, Navah Ester; Sánchez Fernández, Iván; Klehm, Jacquelyn; Bosl, William; Reinsberger, Claus; Schachter, Steven; Loddenkemper, Tobias

2014-08-01

Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy. Copyright © 2014. Published by Elsevier Inc.

Detection of artifacts from high energy bursts in neonatal EEG.

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Bhattacharyya, Sourya; Biswas, Arunava; Mukherjee, Jayanta; Majumdar, Arun Kumar; Majumdar, Bandana; Mukherjee, Suchandra; Singh, Arun Kumar

2013-11-01

Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the

Deep Recurrent Neural Networks for seizure detection and early seizure detection systems

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Talathi, S. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-06-05

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since seizures, in general, occur infrequently and are unpredictable, automated seizure detection systems are recommended to screen for seizures during long-term electroencephalogram (EEG) recordings. In addition, systems for early seizure detection can lead to the development of new types of intervention systems that are designed to control or shorten the duration of seizure events. In this article, we investigate the utility of recurrent neural networks (RNNs) in designing seizure detection and early seizure detection systems. We propose a deep learning framework via the use of Gated Recurrent Unit (GRU) RNNs for seizure detection. We use publicly available data in order to evaluate our method and demonstrate very promising evaluation results with overall accuracy close to 100 %. We also systematically investigate the application of our method for early seizure warning systems. Our method can detect about 98% of seizure events within the first 5 seconds of the overall epileptic seizure duration.

Tantrums, Emotion Reactions and Their EEG Correlates in Childhood Benign Rolandic Epilepsy vs. Complex Partial Seizures: Exploratory Observations

Directory of Open Access Journals (Sweden)

Michael Potegal

2018-03-01

Full Text Available We explored associations between EEG pathophysiology and emotional/behavioral (E/B problems of children with two types of epilepsy using standard parent questionnaires and two new indicators: tantrums recorded by parents at home and brief, emotion-eliciting situations in the laboratory. Children with Benign Rolandic epilepsy (BRE, N = 6 reportedly had shorter, more angry tantrums from which they recovered quickly. Children with Complex Partial Seizures (CPS, N = 13 had longer, sadder tantrums often followed by bad moods. More generally, BRE correlated with anger and aggression; CPS with sadness and withdrawal. Scores of a composite group of siblings (N = 11 were generally intermediate between the BRE and CPS groups. Across all children, high voltage theta and/or interictal epileptiform discharges (IEDs correlated with negative emotional reactions. Such EEG abnormalities in left hemisphere correlated with greater social fear, right hemisphere EEG abnormalities with greater anger. Right hemisphere localization in CPS was also associated with parent-reported problems at home. If epilepsy alters neural circuitry thereby increasing negative emotions, additional assessment of anti-epileptic drug treatment of epilepsy-related E/B problems would be warranted.

Naloxone fails to prolong seizure length in ECT.

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Rasmussen, K G; Pandurangi, A K

1999-12-01

Electroconvulsive shock (ECS) in animals has been shown to enhance endogenous opiate systems. The anticonvulsant effects of ECS are also partially blocked by the opiate receptor antagonist naloxone, leading some investigators to postulate that the anticonvulsant effects of ECS are mediated by activation of endogenous opiates. If such a phenomenon occurs in humans, then naloxone might prolong seizure length in electroconvulsive therapy (ECT). In the present study, nine patients were given 2.0 mg intravenous (i.v.) naloxone 2 minutes prior to one-half of their ECT treatments. Motor seizure length was measured via the cuff technique. EEG tracings were read by an investigator blind to naloxone status. There was no difference between the two groups in either EEG or nonblindly evaluated motor seizure length. It is concluded that a dose of 2 mg naloxone does not effectively increase seizure length in ECT.

Automated real-time detection of tonic-clonic seizures using a wearable EMG device

DEFF Research Database (Denmark)

Beniczky, Sándor; Conradsen, Isa; Henning, Oliver

2018-01-01

OBJECTIVE: To determine the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) using a wearable surface EMG device. METHODS: We prospectively tested the technical performance and diagnostic accuracy of real-time seizure detection using a wearable surface EMG device....... The seizure detection algorithm and the cutoff values were prespecified. A total of 71 patients, referred to long-term video-EEG monitoring, on suspicion of GTCS, were recruited in 3 centers. Seizure detection was real-time and fully automated. The reference standard was the evaluation of video-EEG recordings...

Clinical and EEG features of ischemic stroke patients with abnormal discharges

Directory of Open Access Journals (Sweden)

Jia-lei YANG

2016-05-01

Full Text Available Objective To investigate the clinical and EEG features of ischemic stroke patients with abnormal discharges.  Methods Clinical data and 24-hour EEG monitoring of 162 ischemic stroke patients were analyzed retrospectively. One-year follow-up was carried out and post-ischemic epilepsy was diagnosed.  Results Among 162 ischemic stroke patients, 24-hour EEG was abnormal in 87 cases (53.70%. According to the correspondence of site of infarcts and abnormal discharges, these 87 cases were classified into 2 groups: matched group (N = 24, 27.59% and unmatched group (N = 63, 72.41%. There was no significant difference between 2 groups in terms of Oxfordshire Community Stroke Project (OCSP and TOAST classification (P = 0.792, 0.111, while there was significant difference between 2 groups on the site of infarcts (P = 0.000. In matched group, the infarcts were mainly located in cortex (N = 23, 95.83%. However, in unmatched group, the infarcts were mainly located in cortex and basal ganglia (N = 27, 42.86%, or in basal ganglia only (N = 24, 38.10%. In matched group, 24-hour EEG showed slowing of background activities, and sharp waves and sharp and slow wave complex which were corresponding to the infarct sites. The abnormal discharges could only be recorded around the infarct unilaterally. In unmatched group, the epileptiform discharges were recorded in both contralateral and ipsilateral ischemic hemispheres, usually with widespread slow waves and asymmetric background. The infarcts were limited, but abnormal discharges were widespread. For example, the infarct was located in deep brain, while scalp abnormal discharges were recorded. Although there was no significant difference in terms of epilepsy incidence between 2 groups (P = 0.908, the types of epilepsy were statistically different between 2 groups (P = 0.000. In matched group, the main type was partial seizure. But in unmatched group, the main types of epilepsy were secondary generalized seizure and

EEG Suppression Associated with Apneic Episodes in a Neonate

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Evonne Low

2012-01-01

Full Text Available We describe the EEG findings from an ex-preterm neonate at term equivalent age who presented with intermittent but prolonged apneic episodes which were presumed to be seizures. A total of 8 apneic episodes were captured (duration 23–376 seconds during EEG monitoring. The baseline EEG activity was appropriate for corrected gestational age and no electrographic seizure activity was recorded. The average baseline heart rate was 168 beats per minute (bpm and the baseline oxygen saturation level was in the mid-nineties. Periods of complete EEG suppression lasting 68 and 179 seconds, respectively, were recorded during 2 of these 8 apneic episodes. Both episodes were accompanied by bradycardia less than 70 bpm and oxygen saturation levels of less than 20%. Short but severe episodes of apnea can cause complete EEG suppression in the neonate.

Treating seizures in Creutzfeldt-Jakob disease.

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Ng, Marcus C; Westover, M Brandon; Cole, Andrew J

2014-01-01

Seizures are known to occur in Creutzfeldt-Jakob disease (CJD). In the setting of a rapidly progressive condition with no effective therapy, determining appropriate treatment for seizures can be difficult if clinical morbidity is not obvious yet the electroencephalogram (EEG) demonstrates a worrisome pattern such as status epilepticus. Herein, we present the case of a 39-year-old man with CJD and electrographic seizures, discuss how this case challenges conventional definitions of seizures, and discuss a rational approach toward treatment. Coincidentally, our case is the first report of CJD in a patient with Stickler syndrome.

Single photon emission computed tomography (SPECT) in seizure disorders in childhood

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Vles, J.S.H.; Demandt, E.; Ceulemans, B.; de Roo, M.; Casaer, P.J.M.

1990-01-01

In 38 children with partial seizures, the EEG, CT and NMR findings were compared to the results obtained with Tc99m HMPAO single photon emission computed tomography (SPECT) in order to determine whether SPECT is a useful adjunct to EEG, CT and NMR in this age group. In 3 out of 7 patients with a normal EEG, SPECT showed focal abnormalities. Nine patients whose EEGs did not show adequate lateralization had an abnormal SPECT which revealed a focus. In 14 out of 21 patients with a normal CT, SPECT showed focal changes in 13 patients and diffuse changes in the other one. In 7 out of 12 patients with a normal NMR, SPECT showed focal abnormalities. Although clinical history and a careful description of the seizures are the most valuable information in partial seizure disorders, SPECT imaging gives valuable additional information, which might target treatment. SPECT was superior to CT and NMR with respect to the depiction of some kind of abnormality. (author)

Versive seizures in occipital lobe epilepsy: lateralizing value and pathophysiology.

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Usui, Naotaka; Mihara, Tadahiro; Baba, Koichi; Matsuda, Kazumi; Tottori, Takayasu; Umeoka, Shuichi; Kondo, Akihiko; Nakamura, Fumihiro; Terada, Kiyohito; Usui, Keiko; Inoue, Yushi

2011-11-01

To clarify the value of versive seizures in lateralizing and localizing the epileptogenic zone in patients with occipital lobe epilepsy, we studied 13 occipital lobe epilepsy patients with at least one versive seizure recorded during preoperative noninvasive video-EEG monitoring, who underwent occipital lobe resection, and were followed postoperatively for more than 2 years with Engel's class I outcome. The videotaped versive seizures were analyzed to compare the direction of version and the side of surgical resection in each patient. Moreover, we examined other motor symptoms (partial somatomotor manifestations such as tonic and/or clonic movements of face and/or limbs, automatisms, and eyelid blinking) associated with version. Forty-nine versive seizures were analyzed. The direction of version was always contralateral to the side of resection except in one patient. Among accompanying motor symptoms, partial somatomotor manifestations were observed in only five patients. In conclusion, versive seizure is a reliable lateralizing sign indicating contralateral epileptogenic zone in occipital lobe epilepsy. Since versive seizures were accompanied by partial somatomotor manifestations in less than half of the patients, it is suggested that the mechanism of version in occipital lobe epilepsy is different from that in frontal lobe epilepsy. Copyright © 2011 Elsevier B.V. All rights reserved.

Elevated Ictal Brain Network Ictogenicity Enables Prediction of Optimal Seizure Control

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Marinho A. Lopes

2018-03-01

Full Text Available Recent studies have shown that mathematical models can be used to analyze brain networks by quantifying how likely they are to generate seizures. In particular, we have introduced the quantity termed brain network ictogenicity (BNI, which was demonstrated to have the capability of differentiating between functional connectivity (FC of healthy individuals and those with epilepsy. Furthermore, BNI has also been used to quantify and predict the outcome of epilepsy surgery based on FC extracted from pre-operative ictal intracranial electroencephalography (iEEG. This modeling framework is based on the assumption that the inferred FC provides an appropriate representation of an ictogenic network, i.e., a brain network responsible for the generation of seizures. However, FC networks have been shown to change their topology depending on the state of the brain. For example, topologies during seizure are different to those pre- and post-seizure. We therefore sought to understand how these changes affect BNI. We studied peri-ictal iEEG recordings from a cohort of 16 epilepsy patients who underwent surgery and found that, on average, ictal FC yield higher BNI relative to pre- and post-ictal FC. However, elevated ictal BNI was not observed in every individual, rather it was typically observed in those who had good post-operative seizure control. We therefore hypothesize that elevated ictal BNI is indicative of an ictogenic network being appropriately represented in the FC. We evidence this by demonstrating superior model predictions for post-operative seizure control in patients with elevated ictal BNI.

Epileptogenic zone localization using magnetoencephalography predicts seizure freedom in epilepsy surgery

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Englot, Dario J.; Nagarajan, Srikantan S.; Imber, Brandon S.; Raygor, Kunal P.; Honma, Susanne M.; Mizuiri, Danielle; Mantle, Mary; Knowlton, Robert C.; Kirsch, Heidi E.; Chang, Edward F.

2015-01-01

Objective The efficacy of epilepsy surgery depends critically upon successful localization of the epileptogenic zone. Magnetoencephalography (MEG) enables non-invasive detection of interictal spike activity in epilepsy, which can then be localized in three dimensions using magnetic source imaging (MSI) techniques. However, the clinical value of MEG in the pre-surgical epilepsy evaluation is not fully understood, as studies to date are limited by either a lack of long-term seizure outcomes or small sample size. Methods We performed a retrospective cohort study of focal epilepsy patients who received MEG for interictal spike mapping followed by surgical resection at our institution. Results We studied 132 surgical patients, with mean post-operative follow-up of 3.6 years (minimum 1 year). Dipole source modelling was successful in 103 (78%) patients, while no interictal spikes were seen in others. Among patients with successful dipole modelling, MEG findings were concordant with and specific to: i) the region of resection in 66% of patients, ii) invasive electrocorticography (ECoG) findings in 67% of individuals, and iii) the MRI abnormality in 74% of cases. MEG showed discordant lateralization in ~5% of cases. After surgery, 70% of all patients achieved seizure-freedom (Engel class I outcome). Whereas 85% of patients with concordant and specific MEG findings became seizure-free, this outcome was achieved by only 37% of individuals with MEG findings that were non-specific or discordant with the region of resection (χ2 = 26.4, p < 0.001). MEG reliability was comparable in patients with or without localized scalp EEG, and overall, localizing MEG findings predicted seizure freedom with an odds ratio of 5.11 (2.23–11.8, 95% CI). Significance MEG is a valuable tool for non-invasive interictal spike mapping in epilepsy surgery, including patients with non-localized findings on long-term EEG monitoring, and localization of the epileptogenic zone using MEG is associated

Phenobarbital for Neonatal Seizures: Response Rate and Predictors of Refractoriness.

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Spagnoli, Carlotta; Seri, Stefano; Pavlidis, Elena; Mazzotta, Silvia; Pelosi, Annalisa; Pisani, Francesco

2016-10-01

Background Phenobarbital is the first-line choice for neonatal seizures treatment, despite a response rate of approximately 45%. Failure to respond to acute anticonvulsants is associated with poor neurodevelopmental outcome, but knowledge on predictors of refractoriness is limited. Objective To quantify response rate to phenobarbital and to establish variables predictive of its lack of efficacy. Methods We retrospectively evaluated newborns with electrographically confirmed neonatal seizures admitted between January 1999 and December 2012 to the neonatal intensive care unit of Parma University Hospital (Italy), excluding neonates with status epilepticus. Response was categorized as complete (cessation of clinical and electrographic seizures after phenobarbital administration), partial (reduction but not cessation of electrographic seizures with the first bolus, response to the second bolus), or absent (no response after the second bolus). Multivariate analysis was used to identify independent predictors of refractoriness. Results Out of 91 newborns receiving phenobarbital, 57 (62.6%) responded completely, 15 (16.5%) partially, and 19 (20.9%) did not respond. Seizure type (p = 0.02), background electroencephalogram (EEG; p ≤ 0.005), and neurologic examination (p  ≤  0.005) correlated with response to phenobarbital. However, EEG (p  ≤  0.02) and seizure type (p  ≤  0.001) were the only independent predictors. Conclusion Our results suggest a prominent role of neurophysiological variables (background EEG and electrographic-only seizure type) in predicting the absence of response to phenobarbital in high-risk newborns. Georg Thieme Verlag KG Stuttgart · New York.

Analyzing Electroencephalogram Signal Using EEG Lab

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Mukesh BHARDWAJ

2009-01-01

Full Text Available The EEG is composed of electrical potentials arising from several sources. Each source (including separate neural clusters, blink artifact or pulse artifact forms a unique topography onto the scalp – ‘scalp map‘. Scalp map may be 2-D or 3-D.These maps are mixed according to the principle of linear superposition. Independent component analysis (ICA attempts to reverse the superposition by separating the EEG into mutually independent scalp maps, or components. MATLAB toolbox and graphic user interface, EEGLAB is used for processing EEG data of any number of channels. Wavelet toolbox has been used for 2-D signal analysis.

Detection of seizures from small samples using nonlinear dynamic system theory.

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Yaylali, I; Koçak, H; Jayakar, P

1996-07-01

The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D2) of EEG time series data. In this paper, D2 of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D2 computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D2 computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies.

Profile of seizures in adult falciparum malaria and the clinical efficacy of phenytoin sodium for control of seizures

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Manoj Ku Mohapatra

2012-10-01

Full Text Available Objective: To study the profile of convulsion in adult severe falciparum malaria and efficacy of phenytoin sodium for its control. Methods: It comprised of two sub studies. Study-1 evaluated the pattern and risk factors of seizure in severe malaria and Study-2 investigated the efficacy of phenytoin sodium to control seizure in an open label trial. Patients of severe malaria were diagnosed as per WHO guideline. Clinical type and duration of convulsion were determined. Biochemical and haematological investigations including EEG and CT scan of brain were performed in all cases. All patients were treated with injection artesunate along with other supportive measures and patients with convulsions were treated with injection phenytoin sodium. Results: Out of 408 patients of severe malaria 118 (28.9% patients had seizure. Generalized tonic clonic seizure, partial seizure with secondary generalization, and status epilepticus was present in 89(75.4%, 25(21.2%, and 4(3.4% cases respectively. CT scan was abnormal in 16 (13.6% cases. EEG was abnormal in 108 (91.5% cases showing generalized seizure activity. Patients with convulsion (n=118 were treated with phenytoin sodium injection and convulsion was controlled within 12 hours [mean (6.2依2.1 hours] of treatment in 107 (90.6% patients. Recurrence of seizure occurred in 2 (1.7% patients and 11 (9.3% patients did not respond. The mortality and sequelae were more among patients with than without convulsion. Conclusions: Seizure is common in adult falciparum malaria and phenytoin is an effective drug for seizure control.

Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System.

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Kiral-Kornek, Isabell; Roy, Subhrajit; Nurse, Ewan; Mashford, Benjamin; Karoly, Philippa; Carroll, Thomas; Payne, Daniel; Saha, Susmita; Baldassano, Steven; O'Brien, Terence; Grayden, David; Cook, Mark; Freestone, Dean; Harrer, Stefan

2018-01-01

Seizure prediction can increase independence and allow preventative treatment for patients with epilepsy. We present a proof-of-concept for a seizure prediction system that is accurate, fully automated, patient-specific, and tunable to an individual's needs. Intracranial electroencephalography (iEEG) data of ten patients obtained from a seizure advisory system were analyzed as part of a pseudoprospective seizure prediction study. First, a deep learning classifier was trained to distinguish between preictal and interictal signals. Second, classifier performance was tested on held-out iEEG data from all patients and benchmarked against the performance of a random predictor. Third, the prediction system was tuned so sensitivity or time in warning could be prioritized by the patient. Finally, a demonstration of the feasibility of deployment of the prediction system onto an ultra-low power neuromorphic chip for autonomous operation on a wearable device is provided. The prediction system achieved mean sensitivity of 69% and mean time in warning of 27%, significantly surpassing an equivalent random predictor for all patients by 42%. This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Source localization of rhythmic ictal EEG activity

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Beniczky, Sándor; Lantz, Göran; Rosenzweig, Ivana

2013-01-01

Although precise identification of the seizure-onset zone is an essential element of presurgical evaluation, source localization of ictal electroencephalography (EEG) signals has received little attention. The aim of our study was to estimate the accuracy of source localization of rhythmic ictal...... EEG activity using a distributed source model....

Management of Reflex Anoxic Seizures

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J Gordon Millichap

2013-10-01

Full Text Available Investigators at the Roald Dahl EEG Unit, Alder Hey Children’s NHS Foundation, Liverpool, UK, review the definition, pathophysiology, clinical presentation, and management of reflex anoxic seizures (RAS in children.

A STUDY ON EEG ABNORMALITIES IN CHILDREN WITH MIGRAINE

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Subinay Mandal

2017-04-01

Full Text Available BACKGROUND Migraine is one of the common causes of headache in children. Migraine and epilepsy are both common episodic neurological disorders. The comorbidity of these two conditions is well known. Many researcher have pointed out that neuronal hyperexcitability is the initiating event for occurrence of migraine attack. The aim of the paper was to evaluate the EEG in children with migraine. MATERIALS AND METHODS We retrospectively analysed records of children who attended our paediatric outpatient department with diagnoses as suffering from migraine based on International Headache Society (IHS diagnostic criteria. Apart from detailed clinical history, EEG of every patient was collected and analysed. EEG was performed interictally at least 24 hours after the last episode of headache attack in all the cases. RESULTS 56 children (age range, 4-14 years constituted our study group. 64.3% children had migraine without aura (common type and in 23.2% cases had migraine with aura (classic type other were with migraine variants. Abnormal EEG was reported in 30.3% children. 17% of children with migraine without history of seizure had abnormal EEG. Sixty one percent of patients with aura had abnormal EEG. History of either febrile fits or afebrile fits was present in total 17.1% of cases. The type of paroxysmal discharges we came across was- a Sharp waves, b Spikes and c Spike and slow wave complexes. Abnormal paroxysmal sharp and spike-wave complexes (also called spike-and-slow-wave complexes were the most common EEG abnormality. CONCLUSION EEG abnormality was found in significant number of children with migraine both with and without history of seizure in our study. This indicates neuronal hyperexcitability during episodes of migraine. So, EEG should be considered in patients with clinical diagnoses of migraine to exclude association of any seizure activity.

Dataset of quantitative spectral EEG of different stages of kindling acquisition in rats.

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Jalilifar, Mostafa; Yadollahpour, Ali

2018-02-01

The data represented here are in relation with the manuscript "Quantitative assessments of extracellular EEG to classify specific features of main phases of seizure acquisition based on kindling model in Rat" (Jalilifar et al., 2017) [1] which quantitatively classified different main stages of the kindling process based on their electrophysiological characteristics using EEG signal processing. The data in the graphical form reported the contribution of different sub bands of EEG in different stages of kindling- induced epileptogenesis. Only EEG signals related to stages 1-2 (initial seizure stages (ISSs)), 3 (localized seizure stage (LSS)), and 4-5 (generalized seizure stages (GSSs) were transferred into frequency function by Fast Fourier Transform (FFT) and their power spectrum and power of each sub bands including delta (1-4 Hz), Theta (4-8 Hz), alpha (8-12 Hz), beta (12-28 Hz), gamma (28-40 Hz) were calculated with MATLAB 2013b. Accordingly, all results were obtained quantitatively which can contribute to reduce the errors in the behavioral assessments.

Recording human cortical population spikes non-invasively--An EEG tutorial.

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Waterstraat, Gunnar; Fedele, Tommaso; Burghoff, Martin; Scheer, Hans-Jürgen; Curio, Gabriel

2015-07-30

Non-invasively recorded somatosensory high-frequency oscillations (sHFOs) evoked by electric nerve stimulation are markers of human cortical population spikes. Previously, their analysis was based on massive averaging of EEG responses. Advanced neurotechnology and optimized off-line analysis can enhance the signal-to-noise ratio of sHFOs, eventually enabling single-trial analysis. The rationale for developing dedicated low-noise EEG technology for sHFOs is unfolded. Detailed recording procedures and tailored analysis principles are explained step-by-step. Source codes in Matlab and Python are provided as supplementary material online. Combining synergistic hardware and analysis improvements, evoked sHFOs at around 600 Hz ('σ-bursts') can be studied in single-trials. Additionally, optimized spatial filters increase the signal-to-noise ratio of components at about 1 kHz ('κ-bursts') enabling their detection in non-invasive surface EEG. sHFOs offer a unique possibility to record evoked human cortical population spikes non-invasively. The experimental approaches and algorithms presented here enable also non-specialized EEG laboratories to combine measurements of conventional low-frequency EEG with the analysis of concomitant cortical population spike responses. Copyright © 2014 Elsevier B.V. All rights reserved.

Non-invasive examinations successfully select patients with medial temporal lobe epilepsy for anterior temporal lobectomy

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Morioka, Takato; Nishio, Shunji; Kawamura, Tadao; Fukui, Kimiko; Sasaki, Masayuki; Fukui, Masashi [Kyushu Univ., Fukuoka (Japan). Graduate School of Medical Sciences

2001-06-01

We retrospectively analyzed 8 patients with intractable medial temporal lobe epilepsy (MTLE) who underwent the anterior temporal lobectomy with hippocampectomy (ATL) without invasive examinations such as chronic subdural electrode recording. Five patients had a history of febrile convulsion. While all 8 patients had oral automatism, automatism of ipsilateral limbs with dystonic posture of contralateral limbs was demonstrated in 2 patients. Bilateral temporal paroxysmal activities on interictal EEG was observed in 4 patients and all patients had clear ictal onset zone on unilateral anterior temporal region. MRI demonstrated unilateral hippocampal sclerosis in 5 cases. Interictal FDG-PET depicted hypometabolism of the unilateral temporal lobe in all cases, however, ECD-SPECT failed to reveal the hypoperfusion of the unilateral temporal lobe in a case. Postoperatively, 7 cases became seizure free, and one had rare seizure. Non-invasive examinations, especially ictal EEG and concordant FDG-PET findings, in patients with oral automatism in seizure semiology, successfully select patients with MTLE for ATL. (author)

Non-invasive examinations successfully select patients with medial temporal lobe epilepsy for anterior temporal lobectomy

International Nuclear Information System (INIS)

Morioka, Takato; Nishio, Shunji; Kawamura, Tadao; Fukui, Kimiko; Sasaki, Masayuki; Fukui, Masashi

2001-01-01

We retrospectively analyzed 8 patients with intractable medial temporal lobe epilepsy (MTLE) who underwent the anterior temporal lobectomy with hippocampectomy (ATL) without invasive examinations such as chronic subdural electrode recording. Five patients had a history of febrile convulsion. While all 8 patients had oral automatism, automatism of ipsilateral limbs with dystonic posture of contralateral limbs was demonstrated in 2 patients. Bilateral temporal paroxysmal activities on interictal EEG was observed in 4 patients and all patients had clear ictal onset zone on unilateral anterior temporal region. MRI demonstrated unilateral hippocampal sclerosis in 5 cases. Interictal FDG-PET depicted hypometabolism of the unilateral temporal lobe in all cases, however, ECD-SPECT failed to reveal the hypoperfusion of the unilateral temporal lobe in a case. Postoperatively, 7 cases became seizure free, and one had rare seizure. Non-invasive examinations, especially ictal EEG and concordant FDG-PET findings, in patients with oral automatism in seizure semiology, successfully select patients with MTLE for ATL. (author)

Acute CT perfusion changes in seizure patients presenting to the emergency department with stroke-like symptoms: correlation with clinical and electroencephalography findings

International Nuclear Information System (INIS)

Payabvash, S.; Oswood, M.C.; Truwit, C.L.; McKinney, A.M.

2015-01-01

Aim: To determine acute computed tomography perfusion (CTP) changes in seizure patients presenting with stroke-like symptoms and to correlate those changes with clinical presentation and electroencephalography (EEG). Materials and methods: The medical records of all patients who presented to the emergency department with acute stroke-like symptoms and underwent CTP (n=1085) over a 5.5-year period were reviewed. Patients were included who had primary seizure as the final diagnosis, and underwent CTP within 3 hours of symptom onset. A subset of patients had a follow-up EEG within 7 days. The perfusion changes and EEG findings were compared between different clinical presentations. Results: Eighteen of 1085 patients (1.7%) who underwent CTP following an acute stroke-like presentation were included. The abnormality on CTP was usually focal, unilateral hyperperfusion — increased relative cerebral blood flow (rCBF) and volume (rCBV) (n=14/18), which most often affected the temporal lobe. Those patients who presented with a motor or speech deficit (n=12) had a higher temporal lobe rCBV, and rCBF, and lower relative mean transit time (rMTT) compared to those with non-focal neurological deficit at presentation. Early EEG was available in 13 patients; a sharp-spike epileptiform EEG discharge pattern (n=5) was associated with higher temporal lobe ipsilateral rCBF and rCBV, and lower rMTT on admission CTP examination. Conclusion: Seizure patients who present with a unilateral motor or speech deficit most commonly have contralateral hyperperfusion in the corresponding eloquent brain regions on the acute-stage CTP examination. In such patients, epileptiform discharges on the early follow-up EEG are associated with ipsilateral hyperperfusion on the admission CTP. -- Highlights: •Seizure patients with stroke-mimic symptoms show contralateral hyperperfusion on acute phase CTP (<3 hours of onset). •Seizure patients with unilateral paralysis/aphasia showed asymmetric perfusion

Standardized computer-based organized reporting of EEG SCORE - Second version

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Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE....... In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE...

Characteristic phasic evolution of convulsive seizure in PCDH19-related epilepsy.

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Ikeda, Hiroko; Imai, Katsumi; Ikeda, Hitoshi; Shigematsu, Hideo; Takahashi, Yukitoshi; Inoue, Yushi; Higurashi, Norimichi; Hirose, Shinichi

2016-03-01

PCDH19-related epilepsy is a genetic disorder that was first described in 1971, then referred to as "epilepsy and mental retardation limited to females". PCDH19 has recently been identified as the responsible gene, but a detailed characterization of the seizure manifestation based on video-EEG recording is still limited. The purpose of this study was to elucidate features of the seizure semiology in children with PCDH19-related epilepsy. To do this, ictal video-EEG recordings of 26 convulsive seizures in three girls with PCDH19-related epilepsy were analysed. All seizures occurred in clusters, mainly during sleep accompanied by fever. The motor manifestations consisted of six sequential phases: "jerk", "reactive", "mild tonic", "fluttering", "mild clonic", and "postictal". Some phases were brief or lacking in some seizures, whereas others were long or pronounced. In the reactive phase, the patients looked fearful or startled with sudden jerks and turned over reactively. The tonic and clonic components were less intense compared with those of typical tonic-clonic seizures in other types of epilepsy. The fluttering phase was characterised initially by asymmetric, less rhythmic, and less synchronous tremulous movement and was then followed by the subtle clonic phase. Subtle oral automatism was observed in the postictal phase. The reactive, mild tonic, fluttering and mild clonic phases were most characteristic of seizures of PCDH19-related epilepsy. Ictal EEG started bilaterally and was symmetric in some patients but asymmetric in others. It showed asymmetric rhythmic discharges in some seizures at later phases. The electroclinical pattern of the phasic evolution of convulsive seizure suggests a focal onset seizure with secondary generalisation. Based on our findings, we propose that the six unique sequential phases in convulsive seizures suggest the diagnosis of PCDH19-related epilepsy when occurring in clusters with or without high fever in girls. [Published with

Generalized periodic EEG activity in two cases of neurosyphilis

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Anghinah Renato

2006-01-01

Full Text Available Neurosyphilis is a recognized cause of epileptic seizures and cognitive impairment, but is not usually associated with the finding of generalized periodic activity in the EEG. We report two similar cases characterized by progressive cognitive impairment followed by partial complex seizures, in whom the EEG showed generalized periodic activity. Both cerebrospinal fluid and the response to penicillin therapy confirmed the diagnoses of neurosyphilis in the two cases. The finding of EEG generalized periodic activity in patients with cognitive or behavioral disorders is usually associated with Creutzfeldt-Jakob disease, although there are other conditions, some of them potentially reversible, which may also present this EEG abnormality. Neurosyphilis has tended not to be included among them, and our present findings support the importance of first ruling out neurosyphilis in those patients with cognitive or behavioral disorders associated with generalized periodic epileptiform discharges.

Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

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Ying, Xiaoguo; Lin, Han; Hui, Guohua

2015-01-01

Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

Seizure following the Use of the COX-2 Inhibitor Etoricoxib

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Valentina Arnao

2017-01-01

Full Text Available We describe a case of epileptic seizures occurring after the use of a COX-2 inhibitor. A 61-year-old man was admitted to our department because of a generalized tonic-clonic seizure. EEG showed generalized slowdown of the activity. Neuroimaging and blood samples studies did not evidence alterations, but a careful pharmacological history revealed that the patient had taken the COX-2 inhibitor etoricoxib to treat lumbago few days before the onset of clinical symptoms. No seizures were reported after etoricoxib discontinuation and an EEG resulted to be normal two months after this. Conclusion. Knowing the pharmacological history of a patient is important for understanding the clinical presentation and selecting appropriate treatment. This is, to the best of our knowledge, the first reported case of generalized seizures associated with the use of COX-2 inhibitors.

EEG, PET, SPET and MRI in intractable childhood epilepsies: possible surgical correlations.

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Fois, A; Farnetani, M A; Balestri, P; Buoni, S; Di Cosmo, G; Vattimo, A; Guazzelli, M; Guzzardi, R; Salvadori, P A

1995-12-01

Magnetic resonance imaging (MRI), single photon emission tomography (SPET), and positron emission tomography (PET) using [18F]fluorodeoxyglucose were used in combination with scalp and scalp-video EEGs in a group of 30 pediatric patients with drug resistant epilepsy (DRE) in order to identify patients who could benefit from neurosurgical approach. Seizures were classified according to the consensus criteria of The International League Against Epilepsy. In three patients infantile spasms (IS) were diagnosed; 13 subjects were affected by different types of generalized seizures, associated with complex partial seizures (CPS) in three. In the other 14 patients partial seizures, either simple (SPS) or complex, were present. A localized abnormality was demonstrated in one patient with IS and in three patients with generalized seizures. Of the group of 14 subjects with CPS, MRI and CT were normal in 7, but SPET or PET indicated focal hypoperfusion or hypometabolism concordant with the localization of the EEG abnormalities. In 5 of the other 7 patients anatomical and functional imaging and EEG findings were concordant for a localized abnormality. It can be concluded that functional imaging combined with scalp EEGs appears to be superior to the use of only CT and MRI for selecting children with epilepsy in whom a surgical approach can be considered, in particular when CPS resistant to therapy are present.

Traditional and non-traditional treatments for autism spectrum disorder with seizures: an on-line survey.

Science.gov (United States)

Frye, Richard E; Sreenivasula, Swapna; Adams, James B

2011-05-18

Despite the high prevalence of seizure, epilepsy and abnormal electroencephalograms in individuals with autism spectrum disorder (ASD), there is little information regarding the relative effectiveness of treatments for seizures in the ASD population. In order to determine the effectiveness of traditional and non-traditional treatments for improving seizures and influencing other clinical factor relevant to ASD, we developed a comprehensive on-line seizure survey. Announcements (by email and websites) by ASD support groups asked parents of children with ASD to complete the on-line surveys. Survey responders choose one of two surveys to complete: a survey about treatments for individuals with ASD and clinical or subclinical seizures or abnormal electroencephalograms, or a control survey for individuals with ASD without clinical or subclinical seizures or abnormal electroencephalograms. Survey responders rated the perceived effect of traditional antiepileptic drug (AED), non-AED seizure treatments and non-traditional ASD treatments on seizures and other clinical factors (sleep, communication, behavior, attention and mood), and listed up to three treatment side effects. Responses were obtained concerning 733 children with seizures and 290 controls. In general, AEDs were perceived to improve seizures but worsened other clinical factors for children with clinical seizure. Valproic acid, lamotrigine, levetiracetam and ethosuximide were perceived to improve seizures the most and worsen other clinical factors the least out of all AEDs in children with clinical seizures. Traditional non-AED seizure and non-traditional treatments, as a group, were perceived to improve other clinical factors and seizures but the perceived improvement in seizures was significantly less than that reported for AEDs. Certain traditional non-AED treatments, particularly the ketogenic diet, were perceived to improve both seizures and other clinical factors.For ASD individuals with reported

Spatio-temporal coupling of EEG signals in epilepsy

Science.gov (United States)

Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

2011-05-01

Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

Pre-operative evaluation of medically intractable partial seizures using [sup 123]I-Iomazenil SPECT. Comparison with Video/EEG-monitoring and post-operative results. Praeoperative Bewertung pharmakoresistenter fokaler Epilepsien mit der [sup 123]J-Iomazenil-SPECT. Vergleich mit dem Video/EEG-Monitoring und postoperativen Ergebnissen

Energy Technology Data Exchange (ETDEWEB)

Venz, S [Strahlenklinik und Poliklinik und Neurologische Klinik und Poliklinik, Universitaetsklinikum Rudolf Virchow, FU Berlin (Germany); Cordes, M [Strahlenklinik und Poliklinik und Neurologische Klinik und Poliklinik, Universitaetsklinikum Rudolf Virchow, FU Berlin (Germany); Straub, H B [Strahlenklinik und Poliklinik und Neurologische Klinik und Poliklinik, Universitaetsklinikum Rudolf Virchow, FU Berlin (Germany); Hierholzer, J [Strahlenklinik und Poliklinik und Neurologische Klinik und Poliklinik, Universitaetsklinikum Rudolf Virchow, FU Berlin (Germany); Schroeder, R [Strahlenklinik und Poliklinik und Neurologische Klinik und Poliklinik, Universitaetsklinikum Rudolf Virchow, FU Berlin (Germany); Richter, W [Strahlenklinik und Poliklinik und Neurologische Klinik und Poliklinik, Universitaetsklinikum Rudolf Virchow, FU Berlin (Germany); Schmitz, B [Strahlenklinik und Poliklinik und Neurologische Klinik und Poliklinik, Universitaetsklinikum Rudolf Virchow, FU Ber

1994-10-01

SPECT with the benzodiazepine receptor antagonist [sup 123]I-Iomazenil was performed in 33 patients with intractable partial seizures for pre-operative evaluation. The results combined with MRI and [sup 99m]Tc-HMPAO-SPECT findings were compared with the video-assisted EEG monitoring (gold standard'') which localised the focus in 25 patients. 11 patients underwent surgical resection of the epileptogenic area and became seizure-free for a period up to 13 months. The lomazenil SPECT had a significantly higher sensitivity compared to [sup 99m]Tc-HMPAO in the visualization of an epileptogenic area and should be regularly used in the diagnostic of medically intractable partial seizures. (orig.)

Classification Preictal and Interictal Stages via Integrating Interchannel and Time-Domain Analysis of EEG Features.

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Lin, Lung-Chang; Chen, Sharon Chia-Ju; Chiang, Ching-Tai; Wu, Hui-Chuan; Yang, Rei-Cheng; Ouyang, Chen-Sen

2017-03-01

The life quality of patients with refractory epilepsy is extremely affected by abrupt and unpredictable seizures. A reliable method for predicting seizures is important in the management of refractory epilepsy. A critical factor in seizure prediction involves the classification of the preictal and interictal stages. This study aimed to develop an efficient, automatic, quantitative, and individualized approach for preictal/interictal stage identification. Five epileptic children, who had experienced at least 2 episodes of seizures during a 24-hour video EEG recording, were included. Artifact-free preictal and interictal EEG epochs were acquired, respectively, and characterized with 216 global feature descriptors. The best subset of 5 discriminative descriptors was identified. The best subsets showed differences among the patients. Statistical analysis revealed most of the 5 descriptors in each subset were significantly different between the preictal and interictal stages for each patient. The proposed approach yielded weighted averages of 97.50% correctness, 96.92% sensitivity, 97.78% specificity, and 95.45% precision on classifying test epochs. Although the case number was limited, this study successfully integrated a new EEG analytical method to classify preictal and interictal EEG segments and might be used further in predicting the occurrence of seizures.

[Subacute encephalopathy with epileptic seizures in an alcoholic patient].

Science.gov (United States)

Kozian, R; Otto, F G

2000-09-01

We introduce a case of a 66 year-old male with chronic alcoholism who suffered from confusion, Wernicke-aphasia and epileptic seizures. Several EEG revealed periodic lateralized epileptiform discharges. The patient's case resembles the symptoms of a subacute encephalopathy with epileptic seizures which can occur in alcoholics.

Seizures and paroxysmal events: symptoms pointing to the diagnosis of pyridoxine-dependent epilepsy and pyridoxine phosphate oxidase deficiency

NARCIS (Netherlands)

Schmitt, B.; Baumgartner, M.; Mills, P.B.; Clayton, P.T.; Jakobs, C.; Keller, E.; Wohlrab, G.

2010-01-01

Aim: We report on seizures, paroxysmal events, and electroencephalogram (EEG) findings in four female infants with pyridoxine-dependent epilepsy (PDE) and in one female with pyridoxine phosphate oxidase deficiency (PNPO). Method: Videos and EEGs were analysed and compared with videos of seizures and

Classification of epileptic seizures using wavelet packet log energy and norm entropies with recurrent Elman neural network classifier.

Science.gov (United States)

Raghu, S; Sriraam, N; Kumar, G Pradeep

2017-02-01

Electroencephalogram shortly termed as EEG is considered as the fundamental segment for the assessment of the neural activities in the brain. In cognitive neuroscience domain, EEG-based assessment method is found to be superior due to its non-invasive ability to detect deep brain structure while exhibiting superior spatial resolutions. Especially for studying the neurodynamic behavior of epileptic seizures, EEG recordings reflect the neuronal activity of the brain and thus provide required clinical diagnostic information for the neurologist. This specific proposed study makes use of wavelet packet based log and norm entropies with a recurrent Elman neural network (REN) for the automated detection of epileptic seizures. Three conditions, normal, pre-ictal and epileptic EEG recordings were considered for the proposed study. An adaptive Weiner filter was initially applied to remove the power line noise of 50 Hz from raw EEG recordings. Raw EEGs were segmented into 1 s patterns to ensure stationarity of the signal. Then wavelet packet using Haar wavelet with a five level decomposition was introduced and two entropies, log and norm were estimated and were applied to REN classifier to perform binary classification. The non-linear Wilcoxon statistical test was applied to observe the variation in the features under these conditions. The effect of log energy entropy (without wavelets) was also studied. It was found from the simulation results that the wavelet packet log entropy with REN classifier yielded a classification accuracy of 99.70 % for normal-pre-ictal, 99.70 % for normal-epileptic and 99.85 % for pre-ictal-epileptic.

Clinical utility of early amplitude integrated EEG in monitoring term newborns at risk of neurological injury

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Paulina A. Toso

2014-04-01

Full Text Available OBJECTIVE: to test the clinical utility of an early amplitude-integrated electroencephalography (aEEG to predict short-term neurological outcome in term newborns at risk of neurology injury. METHODS: this was a prospective, descriptive study. The inclusion criteria were neonatal encephalopathy, neurologic disturbances, and severe respiratory distress syndrome. Sensitivity, specificity, positive and negative predictive values, and likelihood ratio (LR were calculated. Clinical and demographic data were analyzed. Neurological outcome was defined as the sum of clinical, electroimaging, and neuroimaging findings. RESULTS: ten of the 21 monitored infants (48% presented altered short-term neurologic outcome. The aEEG had 90% sensitivity, 82% specificity, 82% positive predictive value, and 90% negative predictive value. The positive LR was 4.95, and the negative LR was 0.12. In three of 12 (25% encephalopathic infants, the aEEG allowed for a better definition of the severity of their condition. Seizures were detected in eight infants (38%, all subclinical at baseline, and none had a normal aEEG background pattern. The status of three infants (43% evolved and required two or more drugs for treatment. CONCLUSIONS: in infants with encephalopathy or other severe illness, aEEG disturbances occur frequently. aEEG provided a better classification of the severity of encephalopathy, detected early subclinical seizures, and allowed for monitoring of the response to treatment. aEEG was a useful tool at the neonatal intensive care unit for predicting poor short-term neurological outcomes for all sick newborn.

Clinical and psychosocial characteristics of children with nonepileptic seizures

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Chinta Sri

2008-01-01

Full Text Available Objective: The aim of this study is to present a comprehensive profile of clinical and psychosocial characteristics of children with psychogenic nonepileptic seizures and to assess the short-term outcome of these patients. Materials and Methods: The subjects were consecutive cases of children with a diagnosis of nonepileptic seizures (N=17, mean age = 10.7 years, S.D. = 1.26 and two groups of control groups matched on age and sex: true seizure group and healthy controls. All the children were recruited from the out-patient services of the Department of Pediatrics of a tertiary care teaching hospital in North India. Detailed history taking and clinical examination was done in the case of every child. A standard 18 channel EEG was done in all the children and a video EEG was done in 12 cases of children with nonepileptic seizures. The Childhood Psychopathology Measurement Schedule (CPMS and Life Events Scale for Indian Children (LESIC were used to measure the children′s emotional and behavioral functioning at home, and the number of life events and the stress associated with these events in the preceding year and the year before that. Short-term outcome was examined three to six months after the diagnosis of nonepileptic seizures was made. Results: Unresponsiveness without marked motor manifestations was the most common "ictal" characteristic of the nonepileptic seizures. Pelvic thrusting, upper and lower limb movements, head movements, and vocalization were observed in less than one-third of the patients. Increased psychosocial stress and significantly higher number of life events in the preceding year were found to characterize children with nonepileptic seizures, as compared to the two control groups. The nonepileptic seizures and true seizures groups had a higher proportion of children with psychopathology scores in the clinically significant maladjustment range, as compared to those in the healthy control group. A majority of the patients

Electroconvulsive Therapy In Neuropsychiatry : Relevance Of Seizure Parameters

Directory of Open Access Journals (Sweden)

Gangadhar BN

2000-01-01

Full Text Available Electroconvulsive therapy (ECT is used to induce therapeutic seizures in various clinical conditions. It is specifically useful in depression, catatonia, patients with high suicidal risk, and those intolerant to drugs. Its beneficial effects surpass its side effects. Memory impairment is benign and transient. Its mechanism of action is unknown, though numerous neurotransmitters and neuroreceptors have been implicated. The standards of ECT practice are well established but still evolving in some particularly in unilateral ECT. Assessment of threshold by formula method may deliver higher stimulus dose compared with titration method. Cerebral seizure during ECT procedure is necessary. Motor (cuff method and EEG seizure monitoring are mandatory. Recent studies have shown some EEG parameters (amplitude, fractal dimension, symmetry, and post ictal suppression to be associated with therapeutic outcome. Besides seizure monitoring, measuring other physiological parameters such as heart rate (HR and blood pressure (BP may be useful indicators of therapeutic response. Use of ECT in neurological conditions as well as its application in psychiatric illnesses associated with neurological disorders has also been reviewed briefly.

Time reversibility of intracranial human EEG recordings in mesial temporal lobe epilepsy

Science.gov (United States)

van der Heyden, M. J.; Diks, C.; Pijn, J. P. M.; Velis, D. N.

1996-02-01

Intracranial electroencephalograms from patients suffering from mesial temporal lobe epilepsy were tested for time reversibility. If the recorded time series is irreversible, the input of the recording system cannot be a realisation of a linear Gaussian random process. We confirmed experimentally that the measurement equipment did not introduce irreversibility in the recorded output when the input was a realisation of a linear Gaussian random process. In general, the non-seizure recordings are reversible, whereas the seizure recordings are irreversible. These results suggest that time reversibility is a useful property for the characterisation of human intracranial EEG recordings in mesial temporal lobe epilepsy.

Automatic detection of rhythmic and periodic patterns in critical care EEG based on American Clinical Neurophysiology Society (ACNS) standardized terminology.

Science.gov (United States)

Fürbass, F; Hartmann, M M; Halford, J J; Koren, J; Herta, J; Gruber, A; Baumgartner, C; Kluge, T

2015-09-01

Continuous EEG from critical care patients needs to be evaluated time efficiently to maximize the treatment effect. A computational method will be presented that detects rhythmic and periodic patterns according to the critical care EEG terminology (CCET) of the American Clinical Neurophysiology Society (ACNS). The aim is to show that these detected patterns support EEG experts in writing neurophysiological reports. First of all, three case reports exemplify the evaluation procedure using graphically presented detections. Second, 187 hours of EEG from 10 critical care patients were used in a comparative trial study. For each patient the result of a review session using the EEG and the visualized pattern detections was compared to the original neurophysiology report. In three out of five patients with reported seizures, all seizures were reported correctly. In two patients, several subtle clinical seizures with unclear EEG correlation were missed. Lateralized periodic patterns (LPD) were correctly found in 2/2 patients and EEG slowing was correctly found in 7/9 patients. In 8/10 patients, additional EEG features were found including LPDs, EEG slowing, and seizures. The use of automatic pattern detection will assist in review of EEG and increase efficiency. The implementation of bedside surveillance devices using our detection algorithm appears to be feasible and remains to be confirmed in further multicenter studies. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Seizure pattern-specific epileptic epoch detection in patients with intellectual disability

NARCIS (Netherlands)

Wang, L.; Arends, J.B.A.M.; Long, X.; Cluitmans, P.J.M.; van Dijk, J.P.

Electroencephalogram (EEG) features are crucial for the seizure detection performance. Traditional algorithms are designed for a population with normal brain development. However, for patients with an intellectual disability the seizure detection performance is still largely unknown. In addition,

Using Dictionary Pair Learning for Seizure Detection.

Science.gov (United States)

Ma, Xin; Yu, Nana; Zhou, Weidong

2018-02-13

Automatic seizure detection is extremely important in the monitoring and diagnosis of epilepsy. The paper presents a novel method based on dictionary pair learning (DPL) for seizure detection in the long-term intracranial electroencephalogram (EEG) recordings. First, for the EEG data, wavelet filtering and differential filtering are applied, and the kernel function is performed to make the signal linearly separable. In DPL, the synthesis dictionary and analysis dictionary are learned jointly from original training samples with alternating minimization method, and sparse coefficients are obtained by using of linear projection instead of costly [Formula: see text]-norm or [Formula: see text]-norm optimization. At last, the reconstructed residuals associated with seizure and nonseizure sub-dictionary pairs are calculated as the decision values, and the postprocessing is performed for improving the recognition rate and reducing the false detection rate of the system. A total of 530[Formula: see text]h from 20 patients with 81 seizures were used to evaluate the system. Our proposed method has achieved an average segment-based sensitivity of 93.39%, specificity of 98.51%, and event-based sensitivity of 96.36% with false detection rate of 0.236/h.

Prolonged exposure therapy for the treatment of patients diagnosed with psychogenic non-epileptic seizures (PNES) and post-traumatic stress disorder (PTSD).

Science.gov (United States)

Myers, Lorna; Vaidya-Mathur, Urmi; Lancman, Marcelo

2017-01-01

Although there is general consensus that psychogenic non-epileptic seizures (PNES) are treated with psychotherapy, the effectiveness of most psychotherapeutic modalities remains understudied. In this treatment series of 16 patients dually diagnosed with PNES and post-traumatic stress disorder (PTSD), we evaluated the effect of prolonged exposure therapy (PE) on reduction of PNES. Secondary measures included Beck Depression Inventory (BDI-II) and Post-Traumatic Disorder Diagnostic Scale (PDS). Subjects diagnosed with video EEG-confirmed PNES and PTSD confirmed through neuropsychological testing and clinical interview were treated with traditional PE psychotherapy with certain modifications for the PNES. Treatment was conducted over the course of 12-15 weekly sessions. Seizure frequency was noted in each session by examining the patients' seizure logs, and mood and PTSD symptomatology was assessed at baseline and on the final session. Eighteen subjects enrolled, and 16 (88.8%) completed the course of treatment. Thirteen of the 16 (81.25%) therapy completers reported no seizures by their final PE session, and the other three reported a decline in seizure frequency (Z=-3.233, p=0.001). Mean scores on scales of depression (M=-13.56, SD=12.27; t (15)=-4.420, pPTSD symptoms (M=-17.1875, SD=13.01; t (15)=-5.281, pPTSD reduced the number of PNES and improved mood and post traumatic symptomatology. Follow-up revealed that gains made in seizure control on the last day of treatment were maintained over time. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Long-term EEG in children.

Science.gov (United States)

Montavont, A; Kaminska, A; Soufflet, C; Taussig, D

2015-03-01

Long-term video-EEG corresponds to a recording ranging from 1 to 24 h or even longer. It is indicated in the following situations: diagnosis of epileptic syndromes or unclassified epilepsy, pre-surgical evaluation for drug-resistant epilepsy, follow-up of epilepsy or in cases of paroxysmal symptoms whose etiology remains uncertain. There are some specificities related to paediatric care: a dedicated pediatric unit; continuous monitoring covering at least a full 24-hour period, especially in the context of pre-surgical evaluation; the requirement of presence by the parents, technician or nurse; and stronger attachment of electrodes (cup electrodes), the number of which is adapted to the age of the child. The chosen duration of the monitoring also depends on the frequency of seizures or paroxysmal events. The polygraphy must be adapted to the type and topography of movements. It is essential to have at least an electrocardiography (ECG) channel, respiratory sensor and electromyography (EMG) on both deltoids. There is no age limit for performing long-term video-EEG even in newborns and infants; nevertheless because of scalp fragility, strict surveillance of the baby's skin condition is required. In the specific context of pre-surgical evaluation, long-term video-EEG must record all types of seizures observed in the child. This monitoring is essential in order to develop hypotheses regarding the seizure onset zone, based on electroclinical correlations, which should be adapted to the child's age and the psychomotor development. Copyright © 2015. Published by Elsevier SAS.

Enhancement of Neocortical-Medial Temporal EEG Correlations during Non-REM Sleep

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Nikolai Axmacher

2008-01-01

Full Text Available Interregional interactions of oscillatory activity are crucial for the integrated processing of multiple brain regions. However, while the EEG in virtually all brain structures passes through substantial modifications during sleep, it is still an open question whether interactions between neocortical and medial temporal EEG oscillations also depend on the state of alertness. Several previous studies in animals and humans suggest that hippocampal-neocortical interactions crucially depend on the state of alertness (i.e., waking state or sleep. Here, we analyzed scalp and intracranial EEG recordings during sleep and waking state in epilepsy patients undergoing presurgical evaluation. We found that the amplitudes of oscillations within the medial temporal lobe and the neocortex were more closely correlated during sleep, in particular during non-REM sleep, than during waking state. Possibly, the encoding of novel sensory inputs, which mainly occurs during waking state, requires that medial temporal dynamics are rather independent from neocortical dynamics, while the consolidation of memories during sleep may demand closer interactions between MTL and neocortex.

Seizures and electroencephalography findings in 61 patients with fetal alcohol spectrum disorders.

Science.gov (United States)

Boronat, S; Vicente, M; Lainez, E; Sánchez-Montañez, A; Vázquez, E; Mangado, L; Martínez-Ribot, L; Del Campo, M

2017-01-01

Fetal alcohol spectrum disorders (FASD) cause neurodevelopmental abnormalities. However, publications about epilepsy and electroencephalographic features are scarce. In this study, we prospectively performed electroencephalography (EEG) and brain magnetic resonance (MR) imaging in 61 patients with diagnosis of FASD. One patient had multiple febrile seizures with normal EEGs. Fourteen children showed EEG anomalies, including slow background activity and interictal epileptiform discharges, focal and/or generalized, and 3 of them had epilepsy. In one patient, seizures were first detected during the EEG recording and one case had an encephalopathy with electrical status epilepticus during slow sleep (ESES). Focal interictal discharges in our patients did not imply the presence of underlying visible focal brain lesions in the neuroimaging studies, such as cortical dysplasia or polymicrogyria. However, they had nonspecific brain MR abnormalities, including corpus callosum hypoplasia, vermis hypoplasia or cavum septum pellucidum. The latter was significantly more frequent in the group with EEG abnormal findings (p < 0.01). Copyright © 2016 Elsevier Masson SAS. All rights reserved.

The impact of signal normalization on seizure detection using line length features.

Science.gov (United States)

Logesparan, Lojini; Rodriguez-Villegas, Esther; Casson, Alexander J

2015-10-01

Accurate automated seizure detection remains a desirable but elusive target for many neural monitoring systems. While much attention has been given to the different feature extractions that can be used to highlight seizure activity in the EEG, very little formal attention has been given to the normalization that these features are routinely paired with. This normalization is essential in patient-independent algorithms to correct for broad-level differences in the EEG amplitude between people, and in patient-dependent algorithms to correct for amplitude variations over time. It is crucial, however, that the normalization used does not have a detrimental effect on the seizure detection process. This paper presents the first formal investigation into the impact of signal normalization techniques on seizure discrimination performance when using the line length feature to emphasize seizure activity. Comparing five normalization methods, based upon the mean, median, standard deviation, signal peak and signal range, we demonstrate differences in seizure detection accuracy (assessed as the area under a sensitivity-specificity ROC curve) of up to 52 %. This is despite the same analysis feature being used in all cases. Further, changes in performance of up to 22 % are present depending on whether the normalization is applied to the raw EEG itself or directly to the line length feature. Our results highlight the median decaying memory as the best current approach for providing normalization when using line length features, and they quantify the under-appreciated challenge of providing signal normalization that does not impair seizure detection algorithm performance.

Combined process automation for large-scale EEG analysis.

Science.gov (United States)

Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E

2012-01-01

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Automated differentiation between epileptic and non-epileptic convulsive seizures

DEFF Research Database (Denmark)

Beniczky, Sándor; Conradsen, Isa; Moldovan, Mihai

2015-01-01

Our objective was the clinical validation of an automated algorithm based on surface electromyography (EMG) for differentiation between convulsive epileptic and psychogenic nonepileptic seizures (PNESs). Forty-four consecutive episodes with convulsive events were automatically analyzed with the a......%) and 18 PNESs (95%). The overall diagnostic accuracy was 95%. This algorithm is useful for distinguishing between epileptic and psychogenic convulsive seizures....

Epilepsy in patients with psychogenic non-epileptic seizures Epilepsia em pacientes com crises não epilépticas psicogênicas

Directory of Open Access Journals (Sweden)

Renato Luiz Marchetti

2010-04-01

Full Text Available The aim of this study was to evaluate the frequency of epilepsy in patients who presented psychogenic non-epileptic seizures (PNES. The evaluation was carried out during intensive VEEG monitoring in a diagnostic center for epilepsy in a university hospital. The difficulties involved in reaching this diagnosis are discussed. Ninety-eight patients underwent intensive and prolonged video-electroencephalographic (VEEG monitoring; out of these, a total of 28 patients presented PNES during monitoring. Epilepsy was defined as present when the patient presented epileptic seizures during VEEG monitoring or when, although not presenting epileptic seizures during monitoring, the patient presented unequivocal interictal epileptiform discharges. The frequency of epilepsy in patients with PNES was 50% (14 patients. Our findings suggest that the frequency of epilepsy in patients with PNES is much higher than that of previous studies, and point out the need, at least in some cases, for prolonging the evaluation of patients with PNES who have clinical histories indicating epilepsy.O objetivo deste estudo foi avaliar a frequência de epilepsia em pacientes que apresentaram crises não epilépticas psicogênicas (CNEP. Isto foi realizado durante monitoração intensiva por video-EEG num centro diagnóstico de epilepsia em um hospital universitário. As dificuldades envolvidas para se chegar a este diagnóstico são discutidas. Noventa e oito pacientes foram submetidos a monitoração intensiva por video-EEG; 28 destes pacientes apresentaram CNEP durante a monitoração. Epilepsia foi considerada presente quando o paciente apresentou crises epilépticas durante a avaliação pelo video-EEG ou quando, apesar da não ocorrência de crises epilépticas durante a avaliação, descargas epilépticas interictais inequívocas estavam presentes. A frequência de epilepsia em pacientes com CNEP foi 50% (14 pacientes. Nossos achados sugerem que a frequência de epilepsia em

Measurement and modification of the EEG and related behavior

Science.gov (United States)

Sterman, M. B.

1991-01-01

Electrophysiological changes in the sensorimotor pathways were found to accompany the effect of rhythmic EEG patterns in the sensorimotor cortex. Additionally, several striking behavioral changes were seen, including in particular an enhancement of sleep and an elevation of seizure threshold to epileptogenic agents. This raised the possibility that human seizure disorders might be influenced therapeutically by similar training. Our objective in human EEG feedback training became not only the facilitation of normal rhythmic patterns, but also the suppression of abnormal activity, thus requiring complex contingencies directed to the normalization of the sensorimotor EEG. To achieve this, a multicomponent frequency analysis was developed to extract and separate normal and abnormal elements of the EEG signal. Each of these elements was transduced to a specific component of a visual display system, and these were combined through logic circuits to present the subject with a symbolic display. Variable criteria provided for the gradual shaping of EEG elements towards the desired normal pattern. Some 50-70% of patients with poorly controlled seizure disorders experienced therapeutic benefits from this approach in our laboratory, and subsequently in many others. A more recent application of this approach to the modification of human brain function in our lab has been directed to the dichotomous problems of task overload and underload in the contemporary aviation environment. At least 70% of all aviation accidents have been attributed to the impact of these kinds of problems on crew performance. The use of EEG in this context has required many technical innovations and the application of the latest advances in EEG signal analysis. Our first goal has been the identification of relevant EEG characteristics. Additionally, we have developed a portable recording and analysis system for application in this context. Findings from laboratory and in-flight studies suggest that we

Aminophylline increases seizure length during electroconvulsive therapy.

Science.gov (United States)

Stern, L; Dannon, P N; Hirschmann, S; Schriber, S; Amytal, D; Dolberg, O T; Grunhaus, L

1999-12-01

Electroconvulsive therapy (ECT) is considered to be one of the most effective treatments for patients with major depression and persistent psychosis. Seizure characteristics probably determine the therapeutic effect of ECT; as a consequence, short seizures are accepted as one of the factors of poor outcome. During most ECT courses seizure threshold increases and seizure duration decreases. Methylxanthine preparations, caffeine, and theophylline have been used to prolong seizure duration. The use of aminophylline, more readily available than caffeine, has not been well documented. The objective of this study was to test the effects of aminophylline on seizure length. Fourteen drug-free patients with diagnoses of affective disorder or psychotic episode receiving ECT participated in this study. Seizure length was assessed clinically and per EEG. Statistical comparisons were done using paired t tests. A significant increase (p < 0.04) in seizure length was achieved and maintained on three subsequent treatments with aminophylline. No adverse events were noted from the addition of aminophylline.

Brain imaging during seizure: ictal brain SPECT

International Nuclear Information System (INIS)

Kottamasu, Sambasiva Rao

1997-01-01

The role of single photon computed tomography (SPECT) in presurgical localization of medically intractable complex partial epilepsy (CPE) in children is reviewed. 99m Technetium neurolite, a newer lipophylic agent with a high first pass brain extraction and little or no redistribution is injected during a seizure, while the child is monitored with a video recording and continuous EEG and SPECT imaging is performed in the next 1-3 hours with the images representing regional cerebral profusion at the time of injection. On SPECT studies performed with radiopharmaceutical injected during a seizure, ictal focus is generally hypervascular. Other findings on ictal brain SPECT include hypoperfusion of adjacent cerebral cortex and white matter, hyperperfusion of contralateral motor cortex, hyperperfusion of ipsilateral basal ganglia and thalamus, brain stem and contralateral cerebellum. Ictal brain SPECT is non-invasive, cost effective and highly sensitive for localization of epileptic focus in patients with intractable CPE. (author)

Aspartame exacerbates EEG spike-wave discharge in children with generalized absence epilepsy: a double-blind controlled study.

Science.gov (United States)

Camfield, P R; Camfield, C S; Dooley, J M; Gordon, K; Jollymore, S; Weaver, D F

1992-05-01

There are anecdotal reports of increased seizures in humans after ingestion of aspartame. We studied 10 children with newly diagnosed but untreated generalized absence seizures. Ambulatory cassette recording of EEG allowed quantification of numbers and length of spike-wave discharges in a double-blind study on two consecutive days. On one day the children received 40 mg/kg aspartame and on the other day, a sucrose-sweetened drink. Baseline EEG was the same before aspartame and sucrose. Following aspartame compared with sucrose, the number of spike-wave discharges per hour and mean length of spike-wave discharges increased but not to a statistically significant degree. However, the total duration of spike-wave discharge per hour was significantly increased after aspartame (p = 0.028), with a 40% +/- 17% (SEM) increase in the number of seconds per hour of EEG recording that the children spent in spike-wave discharge. Aspartame appears to exacerbate the amount of EEG spike wave in children with absence seizures. Further studies are needed to establish if this effect occurs at lower doses and in other seizure types.

Temporal lobe dual pathology in malignant migrating partial seizures in infancy.

Science.gov (United States)

Coppola, Giangennaro; Operto, Francesca Felicia; Auricchio, Gianfranca; D'Amico, Alessandra; Fortunato, Delia; Pascotto, Antonio

2007-06-01

A child had the characteristic clinical and EEG pattern of migrating partial seizures in infancy with left temporal lobe atrophy, hippocampal sclerosis and cortical-subcortical blurring. Seizures were drug-resistant, with recurring episodes of status epilepticus. The child developed microcephaly with arrest of psychomotor development. Focal brain lesions, in the context of migrating partial seizures, have not been previously reported.[Published with video sequences].

Frontal lobe epilepsy may present as myoclonic seizures.

Science.gov (United States)

Cho, Yong Won; Yi, Sang Doe; Motamedi, Gholam K

2010-04-01

We describe a patient with seizures arising from right anterior-inferior frontal lobe presenting as myoclonic epilepsy. A 19-year-old man had experienced frequent paroxysmal bilateral myoclonic jerks involving his upper arms, shoulders, neck, and upper trunk since the age of 10. His baseline EEG showed intermittent right frontal spikes, and his ictal EEG showed rhythmic sharp theta discharges in the same area. MRI revealed cortical dysplasia in the right inferior frontal gyrus, and ictal-interictal SPECT analysis by SPM showed increased signal abnormality in this region. Diffusion tensor imaging (DTI) showed defects in fasciculi in the same area. These findings suggest that frontal lobe epilepsy should be considered in some patients with myoclonic seizures. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Predictive modeling of EEG time series for evaluating surgery targets in epilepsy patients.

Science.gov (United States)

Steimer, Andreas; Müller, Michael; Schindler, Kaspar

2017-05-01

During the last 20 years, predictive modeling in epilepsy research has largely been concerned with the prediction of seizure events, whereas the inference of effective brain targets for resective surgery has received surprisingly little attention. In this exploratory pilot study, we describe a distributional clustering framework for the modeling of multivariate time series and use it to predict the effects of brain surgery in epilepsy patients. By analyzing the intracranial EEG, we demonstrate how patients who became seizure free after surgery are clearly distinguished from those who did not. More specifically, for 5 out of 7 patients who obtained seizure freedom (= Engel class I) our method predicts the specific collection of brain areas that got actually resected during surgery to yield a markedly lower posterior probability for the seizure related clusters, when compared to the resection of random or empty collections. Conversely, for 4 out of 5 Engel class III/IV patients who still suffer from postsurgical seizures, performance of the actually resected collection is not significantly better than performances displayed by random or empty collections. As the number of possible collections ranges into billions and more, this is a substantial contribution to a problem that today is still solved by visual EEG inspection. Apart from epilepsy research, our clustering methodology is also of general interest for the analysis of multivariate time series and as a generative model for temporally evolving functional networks in the neurosciences and beyond. Hum Brain Mapp 38:2509-2531, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Oxaliplatin-Induced Tonic-Clonic Seizures

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Ahmad K. Rahal

2015-01-01

Full Text Available Oxaliplatin is a common chemotherapy drug used for colon and gastric cancers. Common side effects are peripheral neuropathy, hematological toxicity, and allergic reactions. A rare side effect is seizures which are usually associated with posterior reversible leukoencephalopathy syndrome (PRES. A 50-year-old male patient presented with severe abdominal pain. CT scan of the abdomen showed acute appendicitis. Appendectomy was done and pathology showed mixed adenoneuroendocrine carcinoma. Adjuvant chemotherapy was started with Folinic acid, Fluorouracil, and Oxaliplatin (FOLFOX. During the third cycle of FOLFOX, the patient developed tonic-clonic seizures. Laboratory workup was within normal limits. EEG and MRI of the brain showed no acute abnormality. The patient was rechallenged with FOLFOX but he had tonic-clonic seizures for the second time. His chemotherapy regimen was switched to Folinic acid, Fluorouracil, and Irinotecan (FOLFIRI. After 5 cycles of FOLFIRI, the patient did not develop any seizures, making Oxaliplatin the most likely culprit for his seizures. Oxaliplatin-induced seizures rarely occur in the absence of PRES. One case report has been described in the literature. We present a rare case of tonic-clonic seizures in a patient receiving Oxaliplatin in the absence of PRES.

Multi-modal Intelligent Seizure Acquisition (MISA) system - A new approach towards seizure detection based on full body motion measures

DEFF Research Database (Denmark)

Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid...... hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three...... test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG...

Mapping brain activity on the verge of a photically induced generalized tonic-clonic seizure

DEFF Research Database (Denmark)

Moeller, Friederike; Siebner, Hartwig R; Wolff, Stephan

2009-01-01

In a photosensitive patient intermittent photic stimulation (IPS) accidentally provoked a generalized tonic-clonic seizure during simultaneous recordings of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Before seizure onset, IPS consistently induced generalized...

EEG spectral analysis and its clinical significance for patients with non-occupationalchronic mercury poisoning

Directory of Open Access Journals (Sweden)

Bin-bin SUN

2015-03-01

Full Text Available Objective To evaluate the features of EEG spectrum and its clinical significance for patients with non-occupational chronic mercury poisoning.  Methods Eighteen patients with chronic mercury poisoning were collected continuously as poisoning group at Affiliated Hospital of Academy of Military Medical Sciences from March 2012 to September 2013. At the same time, 12 age- and sex-matched healthy people were selected as control group. All patients underwent video EEG, and EEGLAB in Matlab 2013 software was used to analyze their EEG data. Relevant spectrum data of the 2 groups were compared and analyzed.  Results The frequency-energy curves of 12 normal subjects were similar to sine curve, with obvious energy peak at α band. The frequency-energy curves of 18 patients showed as follows: 5 cases had the peak at slow δ wave, and the energy curve decreased since δ band appeared, with α band peak disappearing. The curve of 10 cases had 2 peaks respectively at α and δ band, and δ peak was higher than α peak. The spectrum in other 3 cases was normal. The quantitative analysis of EEG revealed the proportion of δ band for the total energy. The proportion of δ band for total energy of the poisoning group in right middle temporal (P = 0.018 and left posterior temporal (P = 0.039 channel was significantly higher than that of the normal group, while the proportion of δ band in middle frontal (P = 0.003, right frontal (P = 0.016 and right anterior temporal (P = 0.024, left middle temporal (P = 0.036 and right posterior temporal (P = 0.031 was lower than that of the normal group. Conclusions EEG examination plays an important role in assessing the severity of brain injury for patients with non-occupational chronic mercury poisoning. Spectrum analysis is an intuitive and simple method, and can provide some help for clinical diagnosis and treatment. DOI: 10.3969/j.issn.1672-6731.2015.02.013

EPILAB: a software package for studies on the prediction of epileptic seizures.

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Teixeira, C A; Direito, B; Feldwisch-Drentrup, H; Valderrama, M; Costa, R P; Alvarado-Rojas, C; Nikolopoulos, S; Le Van Quyen, M; Timmer, J; Schelter, B; Dourado, A

2011-09-15

A Matlab®-based software package, EPILAB, was developed for supporting researchers in performing studies on the prediction of epileptic seizures. It provides an intuitive and convenient graphical user interface. Fundamental concepts that are crucial for epileptic seizure prediction studies were implemented. This includes, for example, the development and statistical validation of prediction methodologies in long-term continuous recordings. Seizure prediction is usually based on electroencephalography (EEG) and electrocardiography (ECG) signals. EPILAB is able to process both EEG and ECG data stored in different formats. More than 35 time and frequency domain measures (features) can be extracted based on univariate and multivariate data analysis. These features can be post-processed and used for prediction purposes. The predictions may be conducted based on optimized thresholds or by applying classifications methods such as artificial neural networks, cellular neuronal networks, and support vector machines. EPILAB proved to be an efficient tool for seizure prediction, and aims to be a way to communicate, evaluate, and compare results and data among the seizure prediction community. Copyright © 2011 Elsevier B.V. All rights reserved.

Correlation between EEG abnormalities and symptoms of autism spectrum disorder (ASD).

Science.gov (United States)

Yasuhara, Akihiro

2010-11-01

Children with ASD often suffer from epilepsy and paroxysmal EEG abnormality. Purposes of this study are the confirmation of incidence of epileptic seizures and EEG abnormalities in children with autism using a high performance digital EEG, to examine the nature of EEG abnormalities such as locus or modality, and to determine if the development of children with ASD, who have experienced developmental delay, improves when their epilepsy has been treated and maintained under control. A total of 1014 autistic children that have been treated and followed-up for more than 3 years at Yasuhara Children's Clinic in Osaka, Japan, were included in this study. Each participant's EEG had been recorded approximately every 6 months under sleep conditions. Epilepsy was diagnosed in 37% (375/1014) of the study participants. Almost all patients diagnosed with epilepsy presented with symptomatic epilepsy. The data showed that the participants with lower IQ had a higher incidence of epileptic seizures. Epileptic EEG discharges occurred in 85.8% (870/1014) of the patients. There was also a very high incidence of spike discharges in participants whose intellectual quotient was very low or low. Epileptic seizure waves most frequently developed from the frontal lobe (65.6%), including the front pole (Fp1 and Fp2), frontal part (F3, F4, F7 and F8) and central part (C3, Cz and C4). The occurrence rate of spike discharges in other locations, including temporal lobe (T3, T4, T5, T6), parietal lobe (P3, Pz, P4), occipital lobe (O1, O2) and multifocal spikes was less than 10%. These results support the notion that there is a relationship between ASD and dysfunction of the mirror neuron system. The management of seizure waves in children diagnosed with ASD may result in improves function and reduction of autistic symptoms. Copyright © 2010 Elsevier B.V. All rights reserved.

Rewarming affects EEG background in term newborns with hypoxic-ischemic encephalopathy undergoing therapeutic hypothermia.

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Birca, Ala; Lortie, Anne; Birca, Veronica; Decarie, Jean-Claude; Veilleux, Annie; Gallagher, Anne; Dehaes, Mathieu; Lodygensky, Gregory A; Carmant, Lionel

2016-04-01

To investigate how rewarming impacts the evolution of EEG background in neonates with hypoxic-ischemic encephalopathy (HIE) undergoing therapeutic hypothermia (TH). We recruited a retrospective cohort of 15 consecutive newborns with moderate (9) and severe (6) HIE monitored with a continuous EEG during TH and at least 12h after its end. EEG background was analyzed using conventional visual and quantitative EEG analysis methods including EEG discontinuity, absolute and relative spectral magnitudes. One patient with seizures on rewarming was excluded from analyses. Visual and quantitative analyses demonstrated significant changes in EEG background from pre- to post-rewarming, characterized by an increased EEG discontinuity, more pronounced in newborns with severe compared to moderate HIE. Neonates with moderate HIE also had an increase in the relative magnitude of slower delta and a decrease in higher frequency theta and alpha waves with rewarming. Rewarming affects EEG background in HIE newborns undergoing TH, which may represent a transient adaptive response or reflect an evolving brain injury. EEG background impairment induced by rewarming may represent a biomarker of evolving encephalopathy in HIE newborns undergoing TH and underscores the importance of continuously monitoring the brain health in critically ill neonates. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Nonseizure SUDEP: Sudden unexpected death in epilepsy without preceding epileptic seizures.

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Lhatoo, Samden D; Nei, Maromi; Raghavan, Manoj; Sperling, Michael; Zonjy, Bilal; Lacuey, Nuria; Devinsky, Orrin

2016-07-01

To describe the phenomenology of monitored sudden unexpected death in epilepsy (SUDEP) occurring in the interictal period where death occurs without a seizure preceding it. We report a case series of monitored definite and probable SUDEP where no electroclinical evidence of underlying seizures was found preceding death. Three patients (two definite and one probable) had SUDEP. They had a typical high SUDEP risk profile with longstanding intractable epilepsy and frequent generalized tonic-clonic seizures (GTCS). All patients had varying patterns of respiratory and bradyarrhythmic cardiac dysfunction with profound electroencephalography (EEG) suppression. In two patients, patterns of cardiorespiratory failure were similar to those seen in some patients in the Mortality in Epilepsy Monitoring Units Study (MORTEMUS). SUDEP almost always occur postictally, after GTCS and less commonly after a partial seizure. Monitored SUDEP or near-SUDEP cases without a seizure have not yet been reported in literature. When nonmonitored SUDEP occurs in an ambulatory setting without an overt seizure, the absence of EEG information prevents the exclusion of a subtle seizure. These cases confirm the existence of nonseizure SUDEP; such deaths may not be prevented by seizure detection-based devices. SUDEP risk in patients with epilepsy may constitute a spectrum of susceptibility wherein some are relatively immune, death occurs in others with frequent GTCS with one episode of seizure ultimately proving fatal, while in others still, death may occur even in the absence of a seizure. We emphasize the heterogeneity of SUDEP phenomena. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Seizure Prediction and its Applications

Science.gov (United States)

Iasemidis, Leon D.

2011-01-01

Epilepsy is characterized by intermittent, paroxysmal, hypersynchronous electrical activity, that may remain localized and/or spread and severely disrupt the brain’s normal multi-task and multi-processing function. Epileptic seizures are the hallmarks of such activity and had been considered unpredictable. It is only recently that research on the dynamics of seizure generation by analysis of the brain’s electrographic activity (EEG) has shed ample light on the predictability of seizures, and illuminated the way to automatic, prospective, long-term prediction of seizures. The ability to issue warnings in real time of impending seizures (e.g., tens of minutes prior to seizure occurrence in the case of focal epilepsy), may lead to novel diagnostic tools and treatments for epilepsy. Applications may range from a simple warning to the patient, in order to avert seizure-associated injuries, to intervention by automatic timely administration of an appropriate stimulus, for example of a chemical nature like an anti-epileptic drug (AED), electromagnetic nature like vagus nerve stimulation (VNS), deep brain stimulation (DBS), transcranial direct current (TDC) or transcranial magnetic stimulation (TMS), and/or of another nature (e.g., ultrasonic, cryogenic, biofeedback operant conditioning). It is thus expected that seizure prediction could readily become an integral part of the treatment of epilepsy through neuromodulation, especially in the new generation of closed-loop seizure control systems. PMID:21939848

Forced eye closure-induced reflex seizure and non-ketotic hyperglycemia

International Nuclear Information System (INIS)

Tiras, Raziye; Mutlu, Aytul; Ozben, Serkan; Aydemir Tuba; Ozerab, Feriha

2009-01-01

We report an uncommon case of 53-year-old female patient with partial seizure induced by forced voluntary eye closure due to non-ketotic hyperglycemia. The initial laboratory tests showed an elevated blood glucose level of 550 mg/dL but no evidence of ketosis. Brain magnetic resonance imaging was normal. When the blood glucose levels decreased slowly to about 150 mg/dL in five days, the seizures ended completely. No anticonvulsants were used. Since seizures are generally refractory to antiepileptic medication, control of blood glucose is essential. (author)

Diagnostic value of amplitude-integrated electroencephalogram for epileptic seizures in pediatric intensive care unit%振幅整合脑电图在儿童重症监护室癫痫发作中的诊断价值

Institute of Scientific and Technical Information of China (English)

王新华; 沈金梅; 姚佩丽; 周渊峰; 高萱; 马健; 陆国平; 周水珍; 王艺

2016-01-01

Objective To assess the value of amplitude-integrated electroencephalogram(aEEG) in diagnose of epileptic seizure and status epilepticus in pediatric intensive care unit (PICU).Methods Thirty-five children admitted to Children's Hospital of Fudan University from January to December 2014 with severe neurologia situation in PICU were investigated,and bedside video-EEG(VEEG) findings were recorded for more than 4 hours.VEEG signals were transformed into aEEG signals by Galileo NT PMS software:one-channel aEEG (C3-C4),mutichannel aEEG (F3-F4;C3-C4;P3-P4;T3-T4) plus original EEG.Electrical seizure activity on VEEG was signed out with respect to its occurrence,duration and localization of seizure onset;while aEEG seizure was recorded only during its occurrence.The relationship between aEEG and VEEG was analyzed by Spearman analysis.Results A total of 61 traces in 35 cases were suitable for analysis.(1) gender:24 male and 11 female;years of age:12 cases of 2 months-1 year old,13 cases ＞ 1-6 years old,10 cases ＞ 6-12 years old;etiological factors:15 cases associated with severe viral encephalitis,6 cases associated with epilepsy,6 cases associated with intracranial hemorrhage,5 cases associated with hypoxic-ischemic encephalopathy (HIE),3 cases with other factors.(2) The results were divided into 2 groups:status epilepticus (SE) group and epileptic seizures group.There were 37 traces in SE group,19 traces of them were convulsive SE,and severe viral encephalitis and epilepsy were the most common causes.The other 18 traces were non-convulsive SE,the most common causes were severe viral encephalitis,HIE and intracranial hemorrhage.There were 24 traces in non-SE group,and 118 frequencies of epileptic seizures were monitored.(3)The diagnostic value of aEEG for SE and epileptic seizures:37 traces with status epilepticus on VEEG were all diagnosed as SE on aEEG.For non-SE electrical seizures,the sensitivity of aEEG for detection of electrical seizures was as follows:79.66�

Comparative analysis of MR imaging, Ictal SPECT and EEG in temporal lobe epilepsy: a prospective IAEA multi-center study

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Zaknun, John J. [University Hospital of Innsbruck, Department of Nuclear Medicine, Innsbruck (Austria); International Atomic Energy Agency (IAEA), Nuclear Medicine Section, Division of Human Health, Vienna (Austria); IAEA, Nuclear Medicine Section, Division of Human Health, Wagramer Strasse 5, P.O. Box 100, Wien (Austria); Bal, Chandrasekhar [All India Institute of Medical Sciences, Department of Nuclear Medicine, New Delhi (India); Maes, Alex [Katholieke Universiteit Leuven, Leuven (Belgium); AZ Groeninge, Department of Nuclear Medicine, Kortrijk (Belgium); Tepmongkol, Supatporn [Chulalongkorn University, Nuclear Medicine Division, Department of Radiology, Bangkok (Thailand); Vazquez, Silvia [Instituto de Investigaciones Neurologicas, FLENI, Department of Radiology, Buenos Aires (Argentina); Dupont, Patrick [Katholieke Universiteit Leuven, Leuven (Belgium); Dondi, Maurizio [Ospedale Maggiore, Department of Nuclear Medicine, Bologna (Italy); International Atomic Energy Agency (IAEA), Nuclear Medicine Section, Division of Human Health, Vienna (Austria)

2008-01-15

MR imaging, ictal single-photon emission CT (SPECT) and ictal EEG play important roles in the presurgical localization of epileptic foci. This multi-center study was established to investigate whether the complementary role of perfusion SPECT, MRI and EEG for presurgical localization of temporal lobe epilepsy could be confirmed in a prospective setting involving centers from India, Thailand, Italy and Argentina. We studied 74 patients who underwent interictal and ictal EEG, interictal and ictal SPECT and MRI before surgery of the temporal lobe. In all but three patients, histology was reported. The clinical outcome was assessed using Engel's classification. Sensitivity values of all imaging modalities were calculated, and the add-on value of SPECT was assessed. Outcome (Engel's classification) in 74 patients was class I, 89%; class II, 7%; class III, 3%; and IV, 1%. Regarding the localization of seizure origin, sensitivity was 84% for ictal SPECT, 70% for ictal EEG, 86% for MRI, 55% for interictal SPECT and 40% for interictal EEG. Add-on value of ictal SPECT was shown by its ability to correctly localize 17/22 (77%) of the seizure foci missed by ictal EEG and 8/10 (80%) of the seizure foci not detected by MRI. This prospective multi-center trial, involving centers from different parts of the world, confirms that ictal perfusion SPECT is an effective diagnostic modality for correctly identifying seizure origin in temporal lobe epilepsy, providing complementary information to ictal EEG and MRI. (orig.)

Comparative analysis of MR imaging, Ictal SPECT and EEG in temporal lobe epilepsy: a prospective IAEA multi-center study

International Nuclear Information System (INIS)

Zaknun, John J.; Bal, Chandrasekhar; Maes, Alex; Tepmongkol, Supatporn; Vazquez, Silvia; Dupont, Patrick; Dondi, Maurizio

2008-01-01

MR imaging, ictal single-photon emission CT (SPECT) and ictal EEG play important roles in the presurgical localization of epileptic foci. This multi-center study was established to investigate whether the complementary role of perfusion SPECT, MRI and EEG for presurgical localization of temporal lobe epilepsy could be confirmed in a prospective setting involving centers from India, Thailand, Italy and Argentina. We studied 74 patients who underwent interictal and ictal EEG, interictal and ictal SPECT and MRI before surgery of the temporal lobe. In all but three patients, histology was reported. The clinical outcome was assessed using Engel's classification. Sensitivity values of all imaging modalities were calculated, and the add-on value of SPECT was assessed. Outcome (Engel's classification) in 74 patients was class I, 89%; class II, 7%; class III, 3%; and IV, 1%. Regarding the localization of seizure origin, sensitivity was 84% for ictal SPECT, 70% for ictal EEG, 86% for MRI, 55% for interictal SPECT and 40% for interictal EEG. Add-on value of ictal SPECT was shown by its ability to correctly localize 17/22 (77%) of the seizure foci missed by ictal EEG and 8/10 (80%) of the seizure foci not detected by MRI. This prospective multi-center trial, involving centers from different parts of the world, confirms that ictal perfusion SPECT is an effective diagnostic modality for correctly identifying seizure origin in temporal lobe epilepsy, providing complementary information to ictal EEG and MRI. (orig.)

Comparing bilateral to unilateral electroconvulsive therapy in a randomized study with EEG monitoring.

Science.gov (United States)

Horne, R L; Pettinati, H M; Sugerman, A A; Varga, E

1985-11-01

In a double-blind study, 48 DSM-III depressed patients were randomly assigned to either the bilateral or nondominant unilateral electroconvulsive therapy (ECT) group. Seizure length was monitored by electroencephalography (EEG). When seizures were less than 25 s, ECT was immediately readministered. When length of seizure and pretreatment depression scores were controlled between the two groups, there were no differences in treatment effectiveness, as measured by the Hamilton Rating Scale for Depression and the Beck Depression Inventory, or in the number of treatments required. This was true after five ECT treatments as well as after completing all ECT treatments. Thus, when ECT is monitored via EEG to assure the presence of an adequate seizure, bilateral and nondominant unilateral placement yield equivalent responses. If ECT had not been readministered immediately following a missed seizure, unilateral patients would have had significantly more missed seizures. Significant difficulties in both short- and long-term memory were found 24 hours after the fifth ECT in bilateral but not in nondominant unilateral patients. No apparent memory loss could be documented in nondominant unilateral ECT.

Random ensemble learning for EEG classification.

Science.gov (United States)

Hosseini, Mohammad-Parsa; Pompili, Dario; Elisevich, Kost; Soltanian-Zadeh, Hamid

2018-01-01

Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rapid detection of seizure onset. A new method of feature selection and classification for rapid and precise seizure detection is discussed wherein informative components of electroencephalogram (EEG)-derived data are extracted and an automatic method is presented using infinite independent component analysis (I-ICA) to select independent features. The feature space is divided into subspaces via random selection and multichannel support vector machines (SVMs) are used to classify these subspaces. The result of each classifier is then combined by majority voting to establish the final output. In addition, a random subspace ensemble using a combination of SVM, multilayer perceptron (MLP) neural network and an extended k-nearest neighbors (k-NN), called extended nearest neighbor (ENN), is developed for the EEG and electrocorticography (ECoG) big data problem. To evaluate the solution, a benchmark ECoG of eight patients with temporal and extratemporal epilepsy was implemented in a distributed computing framework as a multitier cloud-computing architecture. Using leave-one-out cross-validation, the accuracy, sensitivity, specificity, and both false positive and false negative ratios of the proposed method were found to be 0.97, 0.98, 0.96, 0.04, and 0.02, respectively. Application of the solution to cases under investigation with ECoG has also been effected to demonstrate its utility. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatiotemporal source analysis in scalp EEG vs. intracerebral EEG and SPECT: a case study in a 2-year-old child.

Science.gov (United States)

Aarabi, A; Grebe, R; Berquin, P; Bourel Ponchel, E; Jalin, C; Fohlen, M; Bulteau, C; Delalande, O; Gondry, C; Héberlé, C; Moullart, V; Wallois, F

2012-06-01

This case study aims to demonstrate that spatiotemporal spike discrimination and source analysis are effective to monitor the development of sources of epileptic activity in time and space. Therefore, they can provide clinically useful information allowing a better understanding of the pathophysiology of individual seizures with time- and space-resolved characteristics of successive epileptic states, including interictal, preictal, postictal, and ictal states. High spatial resolution scalp EEGs (HR-EEG) were acquired from a 2-year-old girl with refractory central epilepsy and single-focus seizures as confirmed by intracerebral EEG recordings and ictal single-photon emission computed tomography (SPECT). Evaluation of HR-EEG consists of the following three global steps: (1) creation of the initial head model, (2) automatic spike and seizure detection, and finally (3) source localization. During the source localization phase, epileptic states are determined to allow state-based spike detection and localization of underlying sources for each spike. In a final cluster analysis, localization results are integrated to determine the possible sources of epileptic activity. The results were compared with the cerebral locations identified by intracerebral EEG recordings and SPECT. The results obtained with this approach were concordant with those of MRI, SPECT and distribution of intracerebral potentials. Dipole cluster centres found for spikes in interictal, preictal, ictal and postictal states were situated an average of 6.3mm from the intracerebral contacts with the highest voltage. Both amplitude and shape of spikes change between states. Dispersion of the dipoles was higher in the preictal state than in the postictal state. Two clusters of spikes were identified. The centres of these clusters changed position periodically during the various epileptic states. High-resolution surface EEG evaluated by an advanced algorithmic approach can be used to investigate the

Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm

Directory of Open Access Journals (Sweden)

E. Parvinnia

2014-01-01

Full Text Available Electroencephalogram (EEG signals are often used to diagnose diseases such as seizure, alzheimer, and schizophrenia. One main problem with the recorded EEG samples is that they are not equally reliable due to the artifacts at the time of recording. EEG signal classification algorithms should have a mechanism to handle this issue. It seems that using adaptive classifiers can be useful for the biological signals such as EEG. In this paper, a general adaptive method named weighted distance nearest neighbor (WDNN is applied for EEG signal classification to tackle this problem. This classification algorithm assigns a weight to each training sample to control its influence in classifying test samples. The weights of training samples are used to find the nearest neighbor of an input query pattern. To assess the performance of this scheme, EEG signals of thirteen schizophrenic patients and eighteen normal subjects are analyzed for the classification of these two groups. Several features including, fractal dimension, band power and autoregressive (AR model are extracted from EEG signals. The classification results are evaluated using Leave one (subject out cross validation for reliable estimation. The results indicate that combination of WDNN and selected features can significantly outperform the basic nearest-neighbor and the other methods proposed in the past for the classification of these two groups. Therefore, this method can be a complementary tool for specialists to distinguish schizophrenia disorder.

Epileptic seizures in Neuro-Behcet disease: why some patients develop seizure and others not?

Science.gov (United States)

Kutlu, Gulnihal; Semercioglu, Sencer; Ucler, Serap; Erdal, Abidin; Inan, Levent E

2015-03-01

Behcet disease (BD) is a chronic relapsing inflammatory disorder. Neuro BD (NBD) is seen in approximately 5% of all patients. The aim of this study is to investigate the frequency, type and prognosis of epileptic seizures in different forms of NBD. All files of 42 patients with NBD were evaluated between 2006 and 2012, retrospectively. The demographic data, the presentation of NBD, clinical findings including seizures, EEG and neuroimaging findings were reviewed. The mean age of patients was 35.02±8.43 years. Thirty (71.4%) patients were male; the remaining 12 of them were female. Twenty-four patients had brainstem lesions; 16 patients had cerebral venous thrombosis. Spinal cord involvement was seen in two patients. Seven patients had epileptic seizures (six partial onset seizures with or without secondary generalization). Six of them had cerebral sinus thrombosis (CVT). Four patients had a seizure as the first symptom of the thrombosis. One patient had late onset seizure due to chronic venous infarct. The other patient with seizure had brainstem involvement. The remaining was diagnosed as epilepsy before the determination of NBD. CVT seen in BD seems to be the main risk factor for epileptic seizures in patients with NBD. The prognosis is usually good especially in patients with CVT. Epileptic seizures in patients with brainstem involvement may be an indicator for poor prognosis. Superior sagittal thrombosis or cortical infarct would be predictor of seizures occurrence because of the high ratio in patients with seizures. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Seizure outcomes in non-resective epilepsy surgery: An update

Science.gov (United States)

Englot, Dario J.; Birk, Harjus; Chang, Edward F.

2016-01-01

In approximately 30% of patients with epilepsy, seizures are refractory to medical therapy, leading to significant morbidity and increased mortality. Substantial evidence has demonstrated the benefit of surgical resection in patients with drug-resistant focal epilepsy, and in the present journal, we recently reviewed seizure outcomes in resective epilepsy surgery. However, not all patients are candidates for or amenable to open surgical resection for epilepsy. Fortunately, several non-resective surgical options are now available at various epilepsy centers, including novel therapies which have been pioneered in recent years. Ablative procedures such as stereotactic laser ablation and stereotactic radiosurgery offer minimally invasive alternatives to open surgery with relatively favorable seizure outcomes, particularly in patients with mesial temporal lobe epilepsy. For certain individuals who are not candidates for ablation or resection, palliative neuromodulation procedures such as vagus nerve stimulation, deep brain stimulation, or responsive neurostimulation may result in a significant decrease in seizure frequency and improved quality of life. Finally, disconnection procedures such as multiple subpial transections and corpus callosotomy continue to play a role in select patients with an eloquent epileptogenic zone or intractable atonic seizures, respectively. Overall, open surgical resection remains the gold standard treatment for drug-resistant epilepsy, although it is significantly under-utilized. While non-resective epilepsy procedures have not replaced the need for resection, there is hope that these additional surgical options will increase the number of patients who receive treatment for this devastating disorder - particularly individuals who are not candidates for or who have failed resection. PMID:27206422

An embedded EEG analyzing system based on muC/os-II.

Science.gov (United States)

Liu, Boqiang; Zhang, Yanyan; Liu, Zhongguo; Yin, Cong

2007-01-01

An EEG analyzing system based on Advanced RISC Machines (ARM) and muC/os-II real time operating system is discussed in this paper. The detailed system design including the producing of event signals and the synchronization between event signals and EEG signals is described. The details of data acquisition, data preprocessing, data transmitting through USB and system configurations are also contained in the system design. In this paper the design of high capability amplifier and the software of embedded subsystem are discussed. Also the design of realizing multi-task system in muC/os-II, the definition of communicating protocols between PC and the equipment and the detail configurations of USB are given out. The final test shows that the filter behaviors of this equipment are feasible.

EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome.

Science.gov (United States)

Hassan, Mahmoud; Shamas, Mohamad; Khalil, Mohamad; El Falou, Wassim; Wendling, Fabrice

2015-01-01

The brain is a large-scale complex network often referred to as the "connectome". Exploring the dynamic behavior of the connectome is a challenging issue as both excellent time and space resolution is required. In this context Magneto/Electroencephalography (M/EEG) are effective neuroimaging techniques allowing for analysis of the dynamics of functional brain networks at scalp level and/or at reconstructed sources. However, a tool that can cover all the processing steps of identifying brain networks from M/EEG data is still missing. In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources. It includes i) Basic steps in preprocessing M/EEG signals, ii) the solution of the inverse problem to localize / reconstruct the cortical sources, iii) the computation of functional connectivity among signals collected at surface electrodes or/and time courses of reconstructed sources and iv) the computation of the network measures based on graph theory analysis. EEGNET is the unique tool that combines the M/EEG functional connectivity analysis and the computation of network measures derived from the graph theory. The first version of EEGNET is easy to use, flexible and user friendly. EEGNET is an open source tool and can be freely downloaded from this webpage: https://sites.google.com/site/eegnetworks/.

Continuous EEG-fMRI in Pre-Surgical Evaluation of a Patient with Symptomatic Seizures: Bold Activation Linked to Interictal Epileptic Discharges Caused by Cavernoma.

Science.gov (United States)

Avesani, M; Formaggio, E; Milanese, F; Baraldo, A; Gasparini, A; Cerini, R; Bongiovanni, L G; Pozzi Mucelli, R; Fiaschi, A; Manganotti, P

2008-04-07

We used continuous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) to identify the linkage between the "epileptogenic" and the "irritative" area in a patient with symptomatic epilepsy (cavernoma, previously diagnosed and surgically treated), i.e. a patient with a well known "epileptogenic area", and to increase the possibility of a non invasive pre-surgical evaluation of drug-resistant epilepsies. A compatible MRI system was used (EEG with 29 scalp electrodes and two electrodes for ECG and EMG) and signals were recorded with a 1.5 Tesla MRI scanner. After the recording session and MRI artifact removal, EEG data were analyzed offline and used as paradigms in fMRI study. Activation (EEG sequences with interictal slow-spiked-wave activity) and rest (sequences of normal EEG) conditions were compared to identify the potential resulting focal increase in BOLD signal and to consider if this is spatially linked to the interictal focus used as a paradigm and to the lesion. We noted an increase in the BOLD signal in the left neocortical temporal region, laterally and posteriorly to the poro-encephalic cavity (residual of cavernoma previously removed), that is around the "epileptogenic area". In our study "epileptogenic" and "irritative" areas were connected with each other. Combined EEG-fMRI may become routine in clinical practice for a better identification of an irritative and lesional focus in patients with symptomatic drug-resistant epilepsy.

Regional blood perfusion in childhood partial seizure using N-isopropyl-p-[I-123]iodoamphetamine and single photon emission CT

International Nuclear Information System (INIS)

Michihiro, Narumi; Kurosawa, Yumiko; Hibio, Shuichi; Ishihara, Hiroaki; Ariizumi, Motomizu

1989-01-01

Single photon emission CT (SPECT) with N-isopropyl-p-[I-123]iodoamphetamine was performed in 20 pediatric patients with partial seizure to examine regional blood perfusion. In detecting location of abnormality, SPECT and EEG were concordant in 13 patients (65%) and discordant in 4 patients (20%). In 7 patients undergoing SPECT one to 4 years after seizure onset, decreased blood perfusion corresponded to focal abnormality on EEG. In other 9 patiets in whom SPECT was performed within one year, however, location of abnormality on SPECT did not necessarily concur with that on EEG. These findings suggest that brain lesions are not focal but extensive at the early stage of partial seizure and that they are becoming focal with the mature of the central nervous system. (Namekawa, K)

Recognition of psychogenic non-epileptic seizures: a curable neurophobia?

LENUS (Irish Health Repository)

O'Sullivan, S S

2013-02-01

Diagnosing psychogenic non-epileptic seizures (PNES) remains challenging. The majority of \\'PNES status\\' cases are likely to be seen in the emergency department or similar non-specialised units, where patients are initially assessed and managed by physicians of varying expertise in neurology.

Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram.

Science.gov (United States)

Truong, Nhan Duy; Nguyen, Anh Duy; Kuhlmann, Levin; Bonyadi, Mohammad Reza; Yang, Jiawei; Ippolito, Samuel; Kavehei, Omid

2018-05-07

Seizure prediction has attracted growing attention as one of the most challenging predictive data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic seizures. Many outstanding studies have reported great results in providing sensible indirect (warning systems) or direct (interactive neural stimulation) control over refractory seizures, some of which achieved high performance. However, to achieve high sensitivity and a low false prediction rate, many of these studies relied on handcraft feature extraction and/or tailored feature extraction, which is performed for each patient independently. This approach, however, is not generalizable, and requires significant modifications for each new patient within a new dataset. In this article, we apply convolutional neural networks to different intracranial and scalp electroencephalogram (EEG) datasets and propose a generalized retrospective and patient-specific seizure prediction method. We use the short-time Fourier transform on 30-s EEG windows to extract information in both the frequency domain and the time domain. The algorithm automatically generates optimized features for each patient to best classify preictal and interictal segments. The method can be applied to any other patient from any dataset without the need for manual feature extraction. The proposed approach achieves sensitivity of 81.4%, 81.2%, and 75% and a false prediction rate of 0.06/h, 0.16/h, and 0.21/h on the Freiburg Hospital intracranial EEG dataset, the Boston Children's Hospital-MIT scalp EEG dataset, and the American Epilepsy Society Seizure Prediction Challenge dataset, respectively. Our prediction method is also statistically better than an unspecific random predictor for most of the patients in all three datasets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Acute CT perfusion changes in seizure patients presenting to the emergency department with stroke-like symptoms: correlation with clinical and electroencephalography findings.

Science.gov (United States)

Payabvash, S; Oswood, M C; Truwit, C L; McKinney, A M

2015-10-01

To determine acute computed tomography perfusion (CTP) changes in seizure patients presenting with stroke-like symptoms and to correlate those changes with clinical presentation and electroencephalography (EEG). The medical records of all patients who presented to the emergency department with acute stroke-like symptoms and underwent CTP (n=1085) over a 5.5-year period were reviewed. Patients were included who had primary seizure as the final diagnosis, and underwent CTP within 3 hours of symptom onset. A subset of patients had a follow-up EEG within 7 days. The perfusion changes and EEG findings were compared between different clinical presentations. Eighteen of 1085 patients (1.7%) who underwent CTP following an acute stroke-like presentation were included. The abnormality on CTP was usually focal, unilateral hyperperfusion - increased relative cerebral blood flow (rCBF) and volume (rCBV) (n=14/18), which most often affected the temporal lobe. Those patients who presented with a motor or speech deficit (n=12) had a higher temporal lobe rCBV, and rCBF, and lower relative mean transit time (rMTT) compared to those with non-focal neurological deficit at presentation. Early EEG was available in 13 patients; a sharp-spike epileptiform EEG discharge pattern (n=5) was associated with higher temporal lobe ipsilateral rCBF and rCBV, and lower rMTT on admission CTP examination. Seizure patients who present with a unilateral motor or speech deficit most commonly have contralateral hyperperfusion in the corresponding eloquent brain regions on the acute-stage CTP examination. In such patients, epileptiform discharges on the early follow-up EEG are associated with ipsilateral hyperperfusion on the admission CTP. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Epileptogenic developmental venous anomaly: insights from simultaneous EEG/fMRI.

Science.gov (United States)

Scheidegger, Olivier; Wiest, Roland; Jann, Kay; König, Thomas; Meyer, Klaus; Hauf, Martinus

2013-04-01

Developmental venous anomalies (DVAs) are associated with epileptic seizures; however, the role of DVA in the epileptogenesis is still not established. Simultaneous interictal electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) recordings provide supplementary information to electroclinical data about the epileptic generators, and thus aid in the differentiation of clinically equivocal epilepsy syndromes. The main objective of our study was to characterize the epileptic network in a patient with DVA and epilepsy by simultaneous EEG/fMRI recordings. A 17-year-old woman with recently emerging generalized tonic-clonic seizures, and atypical generalized discharges, was investigated using simultaneous EEG/fMRI at the university hospital. Previous high-resolution MRI showed no structural abnormalities, except a DVA in the right frontal operculum. Interictal EEG recordings showed atypical generalized discharges, corresponding to positive focal blood oxygen level dependent (BOLD) correlates in the right frontal operculum, a region drained by the DVA. Additionally, widespread cortical bilateral negative BOLD correlates in the frontal and parietal lobes were delineated, resembling a generalized epileptic network. The EEG/fMRI recordings support a right frontal lobe epilepsy, originating in the vicinity of the DVA, propagating rapidly to both frontal and parietal lobes, as expressed on the scalp EEG by secondary bilateral synchrony. The DVA may be causative of focal epilepsies in cases where no concomitant epileptogenic lesions can be detected. Advanced imaging techniques, such as simultaneous EEG/fMRI, may thus aid in the differentiation of clinically equivocal epilepsy syndromes.

Psychogenic non-epileptic seizures and psychoanalytical treatment: results

Directory of Open Access Journals (Sweden)

Niraldo de Oliveira Santos

2014-12-01

Full Text Available Background: the occurrence of psychogenic non-epileptic seizures (PNES is estimated to be between 2 to 33 cases in every 100,000 inhabitants. The number of patients with PNES reaches 19% of those treated as epileptics. Patients with PNES are treated as if they had intractable epilepsy, with unsatisfactory results even after medication treatment is used to its maximum. The aim of this study is to present the effects of individual psychoanalytical treatment in patients with PNES, assessing its impact in the evolution of the clinical picture and its association with sex, time of disease, social, psychological and professional harm, as well as going through with treatment. Methods: The case base was composed of 37 patients with PNES. The diagnosis was reached with video-EEG monitoring. Psychoanalytical treatment was carried out through 12 months of weekly sessions timed for around 50-minutes each, in a total of 48 individual sessions. Results: This study found a high rate of success in the treatment of PNES patients. 29.7% (n=11 of patients had cessation or cure of symptoms and 51.4% (n=19 had a decrease in the number of episodes. There is an association between cessation or decrease in the number of episodes and sex (p<0.01, religion (p<0.01 and concluding treatment (p<0.01. Conclusion: Individual psychoanalytical treatment applied to patients with PNES is considered effective and can be an essential form of assistance for the reduction or cessation of episodes.

A Case of Habitual Neck Compression Induced Electroencephalogram Abnormalities: Differentiating from Epileptic Seizures Using a Tc-99m HMPAO SPECT

Energy Technology Data Exchange (ETDEWEB)

Choi, Hongyoon; Seo, Minseok; Lee, Hoyoung; Kim, Youngsoo; Yun, Changho; Kim, Sangeun; Park, Sungho [Seoul National Univ. Bundang Hospital, Seongnam (Korea, Republic of)

2014-06-15

Self-induced hypoxia has been reported particularly in adolescents, and it can result in neurological injury. Here, we present a case of electroencephalogram (EEG) abnormalities induced by habitual neck compression differentiated from epileptic seizures by Tc-99m HMPAO SPECT. A 19-year-old male was admitted for evaluation of recurrent generalized tonic-clonic seizures. No interictal EEG abnormality was detected; however, abnormal slow delta waves were found immediately after habitual right neck compression. To differentiate EEG abnormalities due to a hemodynamic deficit induced by habitual neck compression from an epileptic seizure, Tc-99m HMPAO SPECT was performed immediately after right carotid artery compression. Abnormal delta waves were triggered, and cerebral hypoperfusion in the right internal carotid artery territory was detected on Tc-99m HMPAO SPECT. The slow delta wave detected on the EEG resulted from the cerebral hypoperfusion because of the habitual neck compression.

A Case of Habitual Neck Compression Induced Electroencephalogram Abnormalities: Differentiating from Epileptic Seizures Using a Tc-99m HMPAO SPECT

International Nuclear Information System (INIS)

Choi, Hongyoon; Seo, Minseok; Lee, Hoyoung; Kim, Youngsoo; Yun, Changho; Kim, Sangeun; Park, Sungho

2014-01-01

Self-induced hypoxia has been reported particularly in adolescents, and it can result in neurological injury. Here, we present a case of electroencephalogram (EEG) abnormalities induced by habitual neck compression differentiated from epileptic seizures by Tc-99m HMPAO SPECT. A 19-year-old male was admitted for evaluation of recurrent generalized tonic-clonic seizures. No interictal EEG abnormality was detected; however, abnormal slow delta waves were found immediately after habitual right neck compression. To differentiate EEG abnormalities due to a hemodynamic deficit induced by habitual neck compression from an epileptic seizure, Tc-99m HMPAO SPECT was performed immediately after right carotid artery compression. Abnormal delta waves were triggered, and cerebral hypoperfusion in the right internal carotid artery territory was detected on Tc-99m HMPAO SPECT. The slow delta wave detected on the EEG resulted from the cerebral hypoperfusion because of the habitual neck compression

Factors Predictive of Seizure Outcome in New-Onset Temporal Lobe Epilepsy

Directory of Open Access Journals (Sweden)

J Gordon Millichap

2007-01-01

Full Text Available A community-based cohort of 77 children with new-onset temporal lobe epilepsy (TLE were followed prospectively and reviewed at 7 and 14 years after seizure onset, and clinical, EEG, and neuroimaging findings and seizure outcome are reported from the Royal Children's Hospital and University of Melbourne, Australia, and Starship Children's Hospital, Auckland, New Zealand.

An overview of an amplitude integrated EEG

Directory of Open Access Journals (Sweden)

Setyo Handryastuti

2007-05-01

for neurodevelopmental problem in conditions such as hypoxic-ischemic encephalopathy (HIE, prematurity, neonatal seizures, central nervous system infection, metabolic disorders, intraventricular or intracranial bleeding and brain malformation. This article gives an overview about aEEG and its role in newborn.

Do video games evoke specific types of epileptic seizures?

Science.gov (United States)

Piccioli, Marta; Vigevano, Federico; Buttinelli, Carla; Kasteleijn-Nolst Trenité, Dorothée G A

2005-11-01

We determined whether epileptic clinical manifestations evoked by playing video games (VG) differ from those evoked by intermittent photic stimulation (IPS) or striped patterns (P). We exposed nine children who had TV- and VG-evoked seizures in daily life to 12 VG after standardized photic stimulation and pattern stimulation. Their EEGs were recorded continuously, analyzed, and then correlated with a video of their behavior. Similar types of clinical signs were seen during VG, P, and IPS, but the signs we observed were more subtle during the VG. Eight patients showed a clear lateralization. A new observation was the lowering of the eyelids to a state of half-closed. Our study suggests that the type of visual stimulus provoking a photoparoxysmal response or seizure is not particularly relevant. The children belonged to different epilepsy groups, and our findings add to the discussion on the boundaries of the epilepsy types.

Focal frontal epileptiform discharges in a patient with eyelid myoclonia and absence seizures

Directory of Open Access Journals (Sweden)

Satoru Takahashi

2015-01-01

Full Text Available Eyelid myoclonia with absences is classified as a unique type of generalized seizure. Its pathogenesis is proposed to involve the functional abnormalities in cortical–subcortical networks. Here, we describe the case of a 7-year-old boy who had eyelid myoclonia with absences, along with focal motor seizures. Video-EEG monitoring demonstrated eyelid myoclonia associated with 4- to 5-Hz generalized polyspike–waves preceded by focal frontal discharges. Interictal EEG showed focal epileptiform discharges over the frontal regions. Our case suggests an important role of the frontal lobe in the generation of eyelid myoclonia with absences.

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy

DEFF Research Database (Denmark)

Zibrandtsen, I. C.; Kidmose, P.; Christensen, C. B.

2017-01-01

-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal...... and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance. Conclusions Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe...... seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. Significance Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis....

Non-EEG based ambulatory seizure detection designed for home use : What is available and how will it influence epilepsy care?

NARCIS (Netherlands)

van Andel, Judith; Thijs, Roland D.; de Weerd, Al; Arends, Johan; Leijten, Frans

OBJECTIVE: This study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and disadvantages of seizure detection in epilepsy care. METHODS: PubMed and EMBASE were searched up to November 2014, using variations and synonyms of

Diagnosis and interpretation of EEG on non-convulsive status epilepticus

Directory of Open Access Journals (Sweden)

Xiao-gang KANG

2015-11-01

Full Text Available It is difficult to diagnose non-convulsive status epilepticus (NCSE clinically because of the complicated etiology and various clinical and electroencephalographic features of NCSE without a universally accepted definition. Although the diagnosis of NCSE relies largely on electroencephalogram (EEG findings, the determination of NCSE on EEG is inevitably subjective, and the EEG changes of most patients is lack of specificity. As the diagnosis of NCSE is related to clinical and electroencephalographic manifestations, diagnostic criteria for NCSE should take into account both clinical and electroencephalographic features, and their response to antiepileptic drugs (AEDs. DOI: 10.3969/j.issn.1672-6731.2015.11.005

Epilepsy surgery in children and non-invasive evaluation

International Nuclear Information System (INIS)

Hashizume, Kiyotaka; Sawamura, Atsushi; Yoshida, Katsunari; Tsuda, Hiroshige; Tanaka, Tatsuya; Tanaka, Shigeya

2001-01-01

The technique of EEG recording using subdural and depth electrodes has became established, and such invasive EEG is available for epilepsy surgery. However, a non-invasive procedure is required for evaluation of surgical indication for epilepsy patients, particular for children. We analyzed the relationship between the results of presurgical evaluation and seizure outcome, and investigated the role of invasive EEG in epilepsy surgery for children. Over the past decade, 22 children under 16 years of age have been admitted to our hospital for evaluation of surgical indication. High-resolution MR imaging, MR spectroscopy, video-EEG monitoring, and ictal and interictal SPECT were used for presurgical evaluation. Organic lesions were found on MR images from 19 patients. Invasive EEG was recorded in only one patient with occipital epilepsy, who had no lesion. Surgical indication was determined in 17 children, and 6 temporal lobe and 11 extratemporal lobe resections were performed under intraoperative electrocorticogram monitoring. The surgical outcome was excellent in 14 patients who had Engel's class I or II. Surgical complications occurred in two children who had visual field defects. The results showed that a good surgical outcome could be obtained using an intraoperative electrocorticogram, without presurgical invasive EEG, for localization-related epilepsy in children. The role of invasive EEG should be reevaluated in such children. (author)

Epilepsy surgery in children and non-invasive evaluation

Energy Technology Data Exchange (ETDEWEB)

Hashizume, Kiyotaka; Sawamura, Atsushi; Yoshida, Katsunari; Tsuda, Hiroshige; Tanaka, Tatsuya [Asahikawa Medical Coll., Hokkaido (Japan); Tanaka, Shigeya

2001-04-01

The technique of EEG recording using subdural and depth electrodes has became established, and such invasive EEG is available for epilepsy surgery. However, a non-invasive procedure is required for evaluation of surgical indication for epilepsy patients, particular for children. We analyzed the relationship between the results of presurgical evaluation and seizure outcome, and investigated the role of invasive EEG in epilepsy surgery for children. Over the past decade, 22 children under 16 years of age have been admitted to our hospital for evaluation of surgical indication. High-resolution MR imaging, MR spectroscopy, video-EEG monitoring, and ictal and interictal SPECT were used for presurgical evaluation. Organic lesions were found on MR images from 19 patients. Invasive EEG was recorded in only one patient with occipital epilepsy, who had no lesion. Surgical indication was determined in 17 children, and 6 temporal lobe and 11 extratemporal lobe resections were performed under intraoperative electrocorticogram monitoring. The surgical outcome was excellent in 14 patients who had Engel's class I or II. Surgical complications occurred in two children who had visual field defects. The results showed that a good surgical outcome could be obtained using an intraoperative electrocorticogram, without presurgical invasive EEG, for localization-related epilepsy in children. The role of invasive EEG should be reevaluated in such children. (author)

Exploring the time-frequency content of high frequency oscillations for automated identification of seizure onset zone in epilepsy.

Science.gov (United States)

Liu, Su; Sha, Zhiyi; Sencer, Altay; Aydoseli, Aydin; Bebek, Nerse; Abosch, Aviva; Henry, Thomas; Gurses, Candan; Ince, Nuri Firat

2016-04-01

High frequency oscillations (HFOs) in intracranial electroencephalography (iEEG) recordings are considered as promising clinical biomarkers of epileptogenic regions in the brain. The aim of this study is to improve and automatize the detection of HFOs by exploring the time-frequency content of iEEG and to investigate the seizure onset zone (SOZ) detection accuracy during the sleep, awake and pre-ictal states in patients with epilepsy, for the purpose of assisting the localization of SOZ in clinical practice. Ten-minute iEEG segments were defined during different states in eight patients with refractory epilepsy. A three-stage algorithm was implemented to detect HFOs in these segments. First, an amplitude based initial detection threshold was used to generate a large pool of HFO candidates. Then distinguishing features were extracted from the time and time-frequency domain of the raw iEEG and used with a Gaussian mixture model clustering to isolate HFO events from other activities. The spatial distribution of HFO clusters was correlated with the seizure onset channels identified by neurologists in seven patient with good surgical outcome. The overlapping rates of localized channels and seizure onset locations were high in all states. The best result was obtained using the iEEG data during sleep, achieving a sensitivity of 81%, and a specificity of 96%. The channels with maximum number of HFOs identified epileptogenic areas where the seizures occurred more frequently. The current study was conducted using iEEG data collected in realistic clinical conditions without channel pre-exclusion. HFOs were investigated with novel features extracted from the entire frequency band, and were correlated with SOZ in different states. The results indicate that automatic HFO detection with unsupervised clustering methods exploring the time-frequency content of raw iEEG can be efficiently used to identify the epileptogenic zone with an accurate and efficient manner.

Correlation between temporal pole MRI abnormalities and surface ictal EEG patterns in patients with unilateral mesial temporal lobe epilepsy.

Science.gov (United States)

Caboclo, Luís Otávio S F; Garzon, Eliana; Oliveira, Pedro A L; Carrete, Henrique; Centeno, Ricardo S; Bianchin, Marino M; Yacubian, Elza Márcia T; Sakamoto, Américo C

2007-01-01

The objective of this retrospective study is to analyze ictal patterns observed during continuous Video-EEG monitoring in patients with temporal lobe epilepsy (TLE) due to unilateral hippocampal sclerosis (HS), and to correlate these EEG patterns to temporal pole abnormalities observed on magnetic resonance imaging exams. We analyzed 147 seizures from 35 patients with TLE and unilateral HS. Ictal patterns were classified and correlated to signal abnormalities and volumetric measures of the temporal poles. Volume differences over 10% were considered abnormal. The most frequent type of ictal pattern was rhythmic theta activity (RTA), encountered in 65.5% of the seizures. Rhythmic beta activity (RBA) was observed in 11% of the seizures, localized attenuation in 8%, interruption of epileptiform discharges in 6%, repetitive discharges in 5.5%, and rhythmic delta activity (RDA) in 4%. Sixty-six percent of the patients presented signal abnormalities in the temporal pole that were always ipsilateral to the HS. Sixty percent presented significant asymmetry of the temporal poles consisting of reduced volume that was also always ipsilateral to HS. Although patients with RTA as the predominant ictal pattern tended to present asymmetry of temporal poles (p=0.305), the ictal EEG pattern did not correlate with temporal pole asymmetry or signal abnormalities. RTA is the most frequent initial ictal pattern in patients with TLE due to unilateral HS. Temporal pole signal changes and volumetric reduction were commonly found in this group of patients, both abnormalities appearing always ipsilateral to the HS. However, neither temporal pole volume reduction nor signal abnormalities correlated with the predominant ictal pattern, suggesting that the temporal poles are not crucially involved in the process of epileptogenesis.

HMPAO-SPECT during epileptic seizures: Early and late images

International Nuclear Information System (INIS)

Overbeck, B.; Gruenwald, F.; Bockisch, A.; Biersack, H.J.; Reinke, U.; Gratz, K.F.

1990-01-01

For presurgical evaluation of epilepsy a 44-year old patient with complex-partial seizures underwent HMPAO-SPECT. The morphology of the seizures, the MRI-scan, psychometry and ictal as well as interictal EEGs showed a left temporal origin of the seizures. Early images were obtained 20 min and late images 24 h following injection. On both scans a marked hyperperfusion was observed in the left temporal area. A crossed cerebellar diaschisis was also seen on both SPECTs. It could be shown that during ictal examinations there is no bloodflow-dependent wash-out from brain tissue. (orig.) [de

EEG-confirmed epileptic activity in a cat with VGKC-complex/LGI1 antibody-associated limbic encephalitis.

Science.gov (United States)

Pakozdy, Akos; Glantschnigg, Ursula; Leschnik, Michael; Hechinger, Harald; Moloney, Teresa; Lang, Bethan; Halasz, Peter; Vincent, Angela

2014-03-01

A 5-year-old, female client-owned cat presented with acute onset of focal epileptic seizures with orofacial twitching and behavioural changes. Magnetic resonance imaging showed bilateral temporal lobe hyperintensities and the EEG was consistent with ictal epileptic seizure activity. After antiepileptic and additional corticosteroid treatment, the cat recovered and by 10 months of follow-up was seizure-free without any problem. Retrospectively, antibodies to LGI1, a component of the voltage-gated potassium channel-complex, were identified. Feline focal seizures with orofacial involvement have been increasingly recognised in client-owned cats, and autoimmune limbic encephalitis was recently suggested as a possible aetiology. This is the first report of EEG, MRI and long-term follow-up of this condition in cats which is similar to human limbic encephalitis.

Video electroencephalography monitoring differentiates between epileptic and non-epileptic seizures

DEFF Research Database (Denmark)

Nørmark, Mette Borch; Erdal, Jesper; Kjær, Troels Wesenberg

2011-01-01

Epilepsy is often misdiagnosed and approximately one in every four patients diagnosed with refractory epilepsy does not have epilepsy, but instead non-epileptic seizures. Video electroencephalography monitoring (VEM) is the gold standard for differentiation between epileptic and non...

EEG criteria predictive of complicated evolution in idiopathic rolandic epilepsy.

Science.gov (United States)

Massa, R; de Saint-Martin, A; Carcangiu, R; Rudolf, G; Seegmuller, C; Kleitz, C; Metz-Lutz, M N; Hirsch, E; Marescaux, C

2001-09-25

Although so-called "benign" epilepsy with centrotemporal spikes (BECTS) always has an excellent prognosis with regard to seizure remission, behavioral problems and cognitive dysfunctions may sometimes develop in its course. To search for clinical or EEG markers allowing early detection of patients prone to such complications, the authors conducted a prospective study in a cohort of unselected patients with BECTS. In 35 children with BECTS, academic, familial, neurologic, neuropsychological, and wake and sleep EEG evaluations were repeated every 6 to 12 months from the beginning of the seizure disorder up to complete recovery. In 25 of 35 patients (72%), behavioral and intellectual functioning remained unimpaired. In 10 of 35 patients (28%), educational performance and familial maladjustment occurred. These sociofamilial problems were correlated with impulsivity, learning difficulties, attention disorders, and minor (7/35 cases, 20%) or serious (3/35 cases, 8%) auditory-verbal or visual-spatial deficits. Worsening phases started 2 to 36 months after onset and persisted for 9 to 39 months. Occurrence of atypical evolutions was significantly correlated with five qualitative and one quantitative interictal EEG pattern: intermittent slow-wave focus, multiple asynchronous spike-wave foci, long spike-wave clusters, generalized 3-c/s "absence-like" spike-wave discharges, conjunction of interictal paroxysms with negative or positive myoclonia, and abundance of interictal abnormalities during wakefulness and sleep. Clinical deterioration was not linked with seizure characteristics or treatment. Different combinations of at least three of six distinctive interictal EEG patterns and their long-lasting (> or =6-month) persistence seem to be the hallmarks of patients with BECTS at risk for neuropsychological impairments.

Recurrent seizures during acute acquired toxoplasmosis in an immunocompetent traveller returning from Africa.

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Beltrame, Anna; Venturini, Sergio; Crichiutti, Giovanni; Meroni, Valeria; Buonfrate, Dora; Bassetti, Matteo

2016-04-01

We report an unusual case of acute acquired toxoplasmosis (AAT) presenting as lymphadenopathy and recurrent seizures in an immunocompetent 15-year-old boy. The patient reported an 18-day vacation to Africa (Ethiopia), 39 days prior to the first seizure. Electroencephalogram (EEG) showed sporadic single-spike or sharp-wave paroxysms and the magnetic resonance imaging (RMI) of the brain was negative. The serology for T. gondii was compatible with an acute infection defined as positive for both toxoplasma-specific IgG and IgM and a low avidity (6 %), confirmed by a reference laboratory. The patient reported other two episodes of seizures, occurring 7 days apart. He was treated with pyrimethamine plus sulfadiazine and leucovorin for 4 weeks, with an improvement of lymphadenitis and normalization of EEG. After 5 months, new seizures were reported and a diagnosis of epilepsy was done. Toxoplasma polymerase chain reaction (PCR) of cerebrospinal fluid (CSF) and blood were negative. A treatment with valproic acid was started, obtaining control of the neurological disease. Awareness of this neurologic manifestation by clinicians is required, also in immunocompetent patients. The relationship between toxoplasmosis and recurrent seizure needs to be investigated by new studies.

Low-frequency stimulation in anterior nucleus of thalamus alleviates kainate-induced chronic epilepsy and modulates the hippocampal EEG rhythm.

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Wang, Yi; Liang, Jiao; Xu, Cenglin; Wang, Ying; Kuang, Yifang; Xu, Zhenghao; Guo, Yi; Wang, Shuang; Gao, Feng; Chen, Zhong

2016-02-01

High-frequency stimulation (HFS) of the anterior nucleus of thalamus (ANT) is a new and alternative option for the treatment of intractable epilepsy. However, the responder rate is relatively low. The present study was designed to determine the effect of low-frequency stimulation (LFS) in ANT on chronic spontaneous recurrent seizures and related pathological pattern in intra-hippocampal kainate mouse model. We found that LFS (1 Hz, 100 μs, 300 μA), but not HFS (100 Hz, 100 μs, 30 μA), in bilateral ANT significantly decreased the frequency of spontaneous recurrent seizures, either non-convulsive focal seizures or tonic-clonic generalized seizures. The anti-epileptic effect persisted for one week after LFS cessation, which manifested as a long-term inhibition of the frequency of seizures with short (20-60 s) and intermediate duration (60-120 s). Meanwhile, LFS decreased the frequency of high-frequency oscillations (HFOs) and interictal spikes, two indicators of seizure severity, whereas HFS increased the HFO frequency. Furthermore, LFS decreased the power of the delta band and increased the power of the gamma band of hippocampal background EEG. In addition, LFS, but not HFS, improved the performance of chronic epileptic mice in objection-location task, novel objection recognition and freezing test. These results provide the first evidence that LFS in ANT alleviates kainate-induced chronic epilepsy and cognitive impairment, which may be related to the modulation of the hippocampal EEG rhythm. This may be of great therapeutic significance for clinical treatment of epilepsy with deep brain stimulation. Copyright © 2015 Elsevier Inc. All rights reserved.

Prevalence of non-febrile seizures in children with idiopathic autism spectrum disorder and their unaffected siblings: a retrospective cohort study.

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McCue, Lena M; Flick, Louise H; Twyman, Kimberly A; Xian, Hong; Conturo, Thomas E

2016-11-28

Autism spectrum disorder (ASD) is a heterogeneous disorder characterized not only by deficits in communication and social interactions but also a high rate of co-occurring disorders, including metabolic abnormalities, gastrointestinal and sleep disorders, and seizures. Seizures, when present, interfere with cognitive development and are associated with a higher mortality rate in the ASD population. To determine the relative prevalence of non-febrile seizures in children with idiopathic ASD from multiplex and simplex families compared with the unaffected siblings in a cohort of 610 children with idiopathic ASD and their 160 unaffected siblings, participating in the Autism Genetic Resource Exchange project, the secondary analysis was performed comparing the life-time prevalence of non-febrile seizures. Statistical models to account for non-independence of observations, inherent with the data from multiplex families, were used in assessing potential confounding effects of age, gender, and history of febrile seizures on odds of having non-febrile seizures. The life-time prevalence of non-febrile seizures was 8.2% among children with ASD and 2.5% among their unaffected siblings. In a logistic regression analysis that adjusted for familial clustering, children with ASD had 5.27 (95%CI: 1.51-18.35) times higher odds of having non-febrile seizures compared to their unaffected siblings. In this comparison, age, presence of gastrointestinal dysfunction, and history of febrile seizures were significantly associated with the prevalence of non-febrile seizures. Children with idiopathic ASD are significantly more likely to have non-febrile seizures than their unaffected siblings, suggesting that non-febrile seizures may be ASD-specific. Further studies are needed to determine modifiable risk factors for non-febrile seizures in ASD.

Fibromyalgia and seizures.

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Tatum, William O; Langston, Michael E; Acton, Emily K

2016-06-01

The purpose of this case-matched study was to determine how frequently fibromyalgia is associated with different paroxysmal neurological disorders and explore the utility of fibromyalgia as a predictor for the diagnosis of psychogenic non-epileptic seizures. The billing diagnosis codes of 1,730 new, non-selected patient encounters were reviewed over a three-year period for an epileptologist in a neurology clinic to identify all patients with historical diagnoses of fibromyalgia. The frequency with which epileptic seizures, psychogenic non-epileptic seizures, and physiological non-epileptic events were comorbid with fibromyalgia was assessed. Age and gender case-matched controls were used for a between-group comparison. Wilcoxon tests were used to analyse interval data, and Chi-square was used to analyse categorical data (pFibromyalgia was retrospectively identified in 95/1,730 (5.5%) patients in this cohort. Females represented 95% of the fibromyalgia sample (age: 53 years; 95% CI: 57, 51). Forty-three percent of those with fibromyalgia had a non-paroxysmal, neurological primary clinical diagnosis, most commonly chronic pain. Paroxysmal events were present in 57% of fibromyalgia patients and 54% of case-matched controls. Among patients with fibromyalgia and paroxysmal disorders, 11% had epileptic seizures, 74% had psychogenic non-epileptic seizures, and 15% had physiological non-epileptic events, compared to case-matched controls with 37% epileptic seizures, 51% psychogenic non-epileptic events, and 12% physiological non-epileptic events (p = 0.009). Fibromyalgia was shown to be a predictor for the diagnosis of psychogenic non-epileptic seizures in patients with undifferentiated paroxysmal spells. However, our results suggest that the specificity and sensitivity of fibromyalgia as a marker for psychogenic non-epileptic seizures in a mixed general neurological population of patients is less than previously described.

Non traumatic fractures of the lumbar spine and seizures: case report

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Moscote-Salazar Luis Rafael

2015-12-01

Full Text Available Injury-induced seizures may appear clinically asymptomatic and can be easily monitored by the absence of trauma and post-ictal impairment of consciousness. Patients with epilepsy have a higher risk of compression fractures, leading to serious musculoskeletal injuries, this type of non-traumatic compression fractures of the spine secondary to seizures are rare lesions, and is produced by the severe contraction of the paraspinal muscles that can achieve the thoracic spine fracture. Seizures induced lesions may appear clinically asymptomatic and can be easily monitored by the absence of trauma and post-ictal impairment of consciousness. We present a case report.

Spherical Harmonics Reveal Standing EEG Waves and Long-Range Neural Synchronization during Non-REM Sleep.

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Sivakumar, Siddharth S; Namath, Amalia G; Galán, Roberto F

2016-01-01

Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10-20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10-16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in

AR2, a novel automatic muscle artifact reduction software method for ictal EEG interpretation: Validation and comparison of performance with commercially available software [version 2; referees: 2 approved

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Shennan Aibel Weiss

2017-04-01

Full Text Available Objective: To develop a novel software method (AR2 for reducing muscle contamination of ictal scalp electroencephalogram (EEG, and validate this method on the basis of its performance in comparison to a commercially available software method (AR1 to accurately depict seizure-onset location. Methods: A blinded investigation used 23 EEG recordings of seizures from 8 patients. Each recording was uninterpretable with digital filtering because of muscle artifact and processed using AR1 and AR2 and reviewed by 26 EEG specialists. EEG readers assessed seizure-onset time, lateralization, and region, and specified confidence for each determination. The two methods were validated on the basis of the number of readers able to render assignments, confidence, the intra-class correlation (ICC, and agreement with other clinical findings. Results: Among the 23 seizures, two-thirds of the readers were able to delineate seizure-onset time in 10 of 23 using AR1, and 15 of 23 using AR2 (p<0.01. Fewer readers could lateralize seizure-onset (p<0.05. The confidence measures of the assignments were low (probable-unlikely, but increased using AR2 (p<0.05. The ICC for identifying the time of seizure-onset was 0.15 (95% confidence interval (CI, 0.11-0.18 using AR1 and 0.26 (95% CI 0.21-0.30 using AR2.  The EEG interpretations were often consistent with behavioral, neurophysiological, and neuro-radiological findings, with left sided assignments correct in 95.9% (CI 85.7-98.9%, n=4 of cases using AR2, and 91.9% (77.0-97.5% (n=4 of cases using AR1. Conclusions: EEG artifact reduction methods for localizing seizure-onset does not result in high rates of interpretability, reader confidence, and inter-reader agreement. However, the assignments by groups of readers are often congruent with other clinical data. Utilization of the AR2 software method may improve the validity of ictal EEG artifact reduction.

Clinical utility of early amplitude integrated EEG in monitoring term newborns at risk of neurological injury

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Paulina A. Toso

2014-03-01

Conclusions: in infants with encephalopathy or other severe illness, aEEG disturbances occur frequently. aEEG provided a better classification of the severity of encephalopathy, detectedearly subclinical seizures, and allowed for monitoring of the response to treatment. aEEG was a useful tool at the neonatal intensive care unit for predicting poor short-term neurologicaloutcomes for all sick newborn.

Why are seizures rare in rapid eye movement sleep? Review of the frequency of seizures in different sleep stages.

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Ng, Marcus; Pavlova, Milena

2013-01-01

Since the formal characterization of sleep stages, there have been reports that seizures may preferentially occur in certain phases of sleep. Through ascending cholinergic connections from the brainstem, rapid eye movement (REM) sleep is physiologically characterized by low voltage fast activity on the electroencephalogram, REMs, and muscle atonia. Multiple independent studies confirm that, in REM sleep, there is a strikingly low proportion of seizures (~1% or less). We review a total of 42 distinct conventional and intracranial studies in the literature which comprised a net of 1458 patients. Indexed to duration, we found that REM sleep was the most protective stage of sleep against focal seizures, generalized seizures, focal interictal discharges, and two particular epilepsy syndromes. REM sleep had an additional protective effect compared to wakefulness with an average 7.83 times fewer focal seizures, 3.25 times fewer generalized seizures, and 1.11 times fewer focal interictal discharges. In further studies REM sleep has also demonstrated utility in localizing epileptogenic foci with potential translation into postsurgical seizure freedom. Based on emerging connectivity data in sleep, we hypothesize that the influence of REM sleep on seizures is due to a desynchronized EEG pattern which reflects important connectivity differences unique to this sleep stage.

Differential antagonism of tetramethylenedisulfotetramine-induced seizures by agents acting at NMDA and GABAA receptors

International Nuclear Information System (INIS)

Shakarjian, Michael P.; Velíšková, Jana; Stanton, Patric K.; Velíšek, Libor

2012-01-01

Tetramethylenedisulfotetramine (TMDT) is a highly lethal neuroactive rodenticide responsible for many accidental and intentional poisonings in mainland China. Ease of synthesis, water solubility, potency, and difficulty to treat make TMDT a potential weapon for terrorist activity. We characterized TMDT-induced convulsions and mortality in male C57BL/6 mice. TMDT (ip) produced a continuum of twitches, clonic, and tonic–clonic seizures decreasing in onset latency and increasing in severity with increasing dose; 0.4 mg/kg was 100% lethal. The NMDA antagonist, ketamine (35 mg/kg) injected ip immediately after the first TMDT-induced seizure, did not change number of tonic–clonic seizures or lethality, but increased the number of clonic seizures. Doubling the ketamine dose decreased tonic–clonic seizures and eliminated lethality through a 60 min observation period. Treating mice with another NMDA antagonist, MK-801, 0.5 or 1 mg/kg ip, showed similar effects as low and high doses of ketamine, respectively, and prevented lethality, converting status epilepticus EEG activity to isolated interictal discharges. Treatment with these agents 15 min prior to TMDT administration did not increase their effectiveness. Post-treatment with the GABA A receptor allosteric enhancer diazepam (5 mg/kg) greatly reduced seizure manifestations and prevented lethality 60 min post-TMDT, but ictal events were evident in EEG recordings and, hours post-treatment, mice experienced status epilepticus and died. Thus, TMDT is a highly potent and lethal convulsant for which single-dose benzodiazepine treatment is inadequate in managing electrographic seizures or lethality. Repeated benzodiazepine dosing or combined application of benzodiazepines and NMDA receptor antagonists is more likely to be effective in treating TMDT poisoning. -- Highlights: ► TMDT produces convulsions and lethality at low doses in mice. ► Diazepam pre- or post-treatments inhibit TMDT-induced convulsions and death. �

An Improved Sparse Representation over Learned Dictionary Method for Seizure Detection.

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Li, Junhui; Zhou, Weidong; Yuan, Shasha; Zhang, Yanli; Li, Chengcheng; Wu, Qi

2016-02-01

Automatic seizure detection has played an important role in the monitoring, diagnosis and treatment of epilepsy. In this paper, a patient specific method is proposed for seizure detection in the long-term intracranial electroencephalogram (EEG) recordings. This seizure detection method is based on sparse representation with online dictionary learning and elastic net constraint. The online learned dictionary could sparsely represent the testing samples more accurately, and the elastic net constraint which combines the 11-norm and 12-norm not only makes the coefficients sparse but also avoids over-fitting problem. First, the EEG signals are preprocessed using wavelet filtering and differential filtering, and the kernel function is applied to make the samples closer to linearly separable. Then the dictionaries of seizure and nonseizure are respectively learned from original ictal and interictal training samples with online dictionary optimization algorithm to compose the training dictionary. After that, the test samples are sparsely coded over the learned dictionary and the residuals associated with ictal and interictal sub-dictionary are calculated, respectively. Eventually, the test samples are classified as two distinct categories, seizure or nonseizure, by comparing the reconstructed residuals. The average segment-based sensitivity of 95.45%, specificity of 99.08%, and event-based sensitivity of 94.44% with false detection rate of 0.23/h and average latency of -5.14 s have been achieved with our proposed method.

Diagnostic accuracy of the Salzburg EEG criteria for non-convulsive status epilepticus

DEFF Research Database (Denmark)

Leitinger, Markus; Trinka, Eugen; Gardella, Elena

2016-01-01

Background Several EEG criteria have been proposed for diagnosis of non-convulsive status epilepticus (NCSE), but none have been clinically validated. We aimed to assess the diagnostic accuracy of the EEG criteria proposed by a panel of experts at the fourth London–Innsbruck Colloquium on Status...... Epilepticus in Salzburg, 2013 (henceforth called the Salzburg criteria). Methods We did a retrospective, diagnostic accuracy study using EEG recordings from patients admitted for neurological symptoms or signs to three centres in two countries (Danish Epilepsy Centre, Dianalund, Denmark; Aarhus University...

Are we missing non-motor seizures in Parkinson's disease? Two case reports.

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Son, Andre Y; Cucca, Alberto; Agarwal, Shashank; Liu, Anli; Di Rocco, Alessandro; Biagioni, Milton C

2017-01-01

Parkinson's disease (PD) is predominantly recognized for its motor symptoms, but patients struggle from a morbid and heterogeneous collection of non-motor symptoms (NMS-PD) that can affect their quality of life even more. NMS-PD is a rather generalized term and the heterogeneity and non-specific nature of many symptoms poses a clinical challenge when a PD patient presents with non-motor complaints that may not be NMS-PD. We report two patients with idiopathic PD who presented with acute episodes of cognitive changes. Structural brain images, cardiovascular and laboratory assessment were unremarkable. Both patients experienced a considerable delay before receiving an epilepsy-evaluation, at which point electroencephalogram abnormalities supported the diagnosis of focal non-motor seizures with alteration of awareness. Antiepileptic therapy was implemented and was effective in both cases. Diagnosing non-motor seizures can be challenging. However, PD patients pose an even greater challenge given their eclectic non-motor clinical manifestations and other disease-related complications that could confound and mislead adequate clinical interpretation. Our two cases provide examples of non-motor seizures that may mimic non-motor symptoms of PD. Treating physicians should always consider other possible causes of non-motor symptoms that may coexist in PD patients. Epilepsy work-up should be contemplated in the differential of acute changes in cognition, behavior, or alertness.

Occipital lobe seizures related to marked elevation of hemoglobin A1C: report of two cases.

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Hung, Wan-Ling; Hsieh, Peiyuan F; Lee, Yi-Chung; Chang, Ming-Hong

2010-07-01

Occipital lobe seizures caused by nonketotic hyperglycemia (NKH) have been reported in only a few cases and are not fully characterized. We report two cases of NKH-related occipital lobe seizures with high hemoglobin A1C (HbA1C), epileptiform electroencephalograph (EEG) and MRI abnormalities. Both patients had moderate hyperglycemia (310-372 mg/dl) and mildly elevated serum osmolarity (295-304 mOsm/kg) but markedly elevated HbA1C (13.8-14.4%). One patient had a clinico-EEG seizure originating from the right occipital region during sleep. The other patient had an interictal epileptiform discharge consisting of unilateral occipital beta activity in sleep. None of the previously reported cases fulfilled the criteria of a nonketotic hyperglycemic hyperosmolar (NKHH) state, or showed any interictal beta paroxysms, spikes, sharp waves, or spike/sharp-slow wave complexes. We suggest that prolonged exposure to uncontrolled hyperglycemia, as indicated by HbA1C, rather than an acute NKHH state is crucial in the development of this peculiar seizure. We also suggest clinicians look for the presence of interictal focal beta paroxysms in addition to the usual epileptiform discharges while reading the EEG of these patients. 2010 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Traditional and non-traditional treatments for autism spectrum disorder with seizures: an on-line survey

OpenAIRE

Frye, Richard E; Sreenivasula, Swapna; Adams, James B

2011-01-01

Abstract Background Despite the high prevalence of seizure, epilepsy and abnormal electroencephalograms in individuals with autism spectrum disorder (ASD), there is little information regarding the relative effectiveness of treatments for seizures in the ASD population. In order to determine the effectiveness of traditional and non-traditional treatments for improving seizures and influencing other clinical factor relevant to ASD, we developed a comprehensive on-line seizure survey. Methods A...

A Functional-genetic Scheme for Seizure Forecasting in Canine Epilepsy.

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Bou Assi, E; Nguyen, D K; Rihana, S; Sawan, M

2017-09-13

The objective of this work is the development of an accurate seizure forecasting algorithm that considers brain's functional connectivity for electrode selection. We start by proposing Kmeans-directed transfer function, an adaptive functional connectivity method intended for seizure onset zone localization in bilateral intracranial EEG recordings. Electrodes identified as seizure activity sources and sinks are then used to implement a seizure-forecasting algorithm on long-term continuous recordings in dogs with naturallyoccurring epilepsy. A precision-recall genetic algorithm is proposed for feature selection in line with a probabilistic support vector machine classifier. Epileptic activity generators were focal in all dogs confirming the diagnosis of focal epilepsy in these animals while sinks spanned both hemispheres in 2 of 3 dogs. Seizure forecasting results show performance improvement compared to previous studies, achieving average sensitivity of 84.82% and time in warning of 0.1. Achieved performances highlight the feasibility of seizure forecasting in canine epilepsy. The ability to improve seizure forecasting provides promise for the development of EEGtriggered closed-loop seizure intervention systems for ambulatory implantation in patients with refractory epilepsy.

Masturbation mimicking seizure in an infant.

Science.gov (United States)

Deda, G; Caksen, H; Suskan, E; Gümüs, D

2001-08-01

A 3.5-month-old boy was referred to our hospital with the diagnosis of infantile spasm. His developmental milestones and physical examination were normal. During the follow-up we recorded about six to nine attacks a day and the duration of attacks was changed between 15 seconds-1.5 minutes. During the episodic attacks he was flushed and had tonic posturing associated with crossing of thighs, without loss of consciousness and his eye movements were normal. Routine and long-term electroencephalogram (EEG) were normal during attack. The patient was diagnosed as masturbation according to the clinical and EEG findings. In conclusion, we would like to stress that masturbation should also be considered in infants who were admitted with complaint of seizure, and aside from EEG monitoring a detailed history and careful observation are very important factors in differential diagnosis of these two different conditions.

Clinical utility of early amplitude integrated EEG in monitoring term newborns at risk of neurological injury

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Paulina A. Toso

2014-03-01

Full Text Available Objective: to test the clinical utility of an early amplitude-integrated electroencephalography (aEEG to predict short-term neurological outcome in term newborns at risk of neurology injury. Methods: this was a prospective, descriptive study. The inclusion criteria were neonatal encephalopathy, neurologic disturbances, and severe respiratory distress syndrome. Sensitivity, specificity, positive and negative predictive values, and likelihood ratio (LR were calculated. Clinical and demographic data were analyzed. Neurological outcome was defined as the sum of clinical, electroimaging, and neuroimaging findings. Results: ten of the 21 monitored infants (48% presented altered short-term neurologic outcome. The aEEG had 90% sensitivity, 82% specificity, 82% positive predictive value, and 90% negative predictive value. The positive LR was 4.95, and the negative LR was 0.12. In three of 12 (25% encephalopathic infants, the aEEG allowed for a better definition of the severity of their condition. Seizures were detected in eight infants (38%, all subclinical at baseline, and none had a normal aEEG background pattern. The status of three infants (43% evolved and required two or more drugs for treatment. Conclusions: in infants with encephalopathy or other severe illness, aEEG disturbances occur frequently. aEEG provided a better classification of the severity of encephalopathy, detected early subclinical seizures, and allowed for monitoring of the response to treatment. aEEG was a useful tool at the neonatal intensive care unit for predicting poor short-term neurological outcomes for all sick newborn. Resumo: Objetivo: testar a utilidade clínica do aEEG precoce em recém-nascidos a termo com risco de lesão neurológica, para prever resultados neurológicos de curto prazo. Métodos: estudo prospectivo e descritivo. Os critérios de inclusão foram encefalopatia neonatal, distúrbios neurológicos e bebês com SARA grave. Sensibilidade, especificidade

Huperzine A prophylaxis against pentylenetetrazole-induced seizures in rats is associated with increased cortical inhibition.

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Gersner, R; Ekstein, D; Dhamne, S C; Schachter, S C; Rotenberg, A

2015-11-01

Huperzine A (HupA) is a naturally occurring compound found in the firmoss Huperzia serrata. While HupA is a potent acetylcholinesterase inhibitor, its full pharmacologic profile is incompletely described. Since previous works suggested a capacity for HupA to prophylax against seizures, we tested the HupA antiepileptic potential in pentylenetetrazole (PTZ) rat epilepsy model and explored its mechanism of action by spectral EEG analysis and by paired-pulse transcranial magnetic stimulation (ppTMS), a measure of GABA-mediated intracortical inhibition. We tested whether HupA suppresses seizures in the rat PTZ acute seizure model, and quantified latency to first myoclonus and to generalized tonic-clonic seizure, and spike frequency on EEG. Additionally, we measured power in the EEG gamma frequency band which is associated with GABAergic cortical interneuron activation. Then, as a step toward further examining the HupA antiepileptic mechanism of action, we tested long-interval intracortical inhibition (LICI) using ppTMS coupled with electromyography to assess whether HupA augments GABA-mediated paired-pulse inhibition of the motor evoked potential. We also tested whether the HupA effect on paired-pulse inhibition was central or peripheral by comparison of outcomes following administration of HupA or the peripheral acetylcholinesterase inhibitor pyridostigmine. We also tested whether the HupA effect was dependent on central muscarinic or GABAA receptors by co-administration of HupA and atropine or PTZ, respectively. In tests of antiepileptic potential, HupA suppressed seizures and epileptic spikes on EEG. Spectral EEG analysis also revealed enhanced gamma frequency band power with HupA treatment. By ppTMS we found that HupA increases intracortical inhibition and blocks PTZ-induced cortical excitation. Atropine co-administration with HupA did not alter HupA-induced intracortical inhibition suggesting independent of muscarinic acetylcholine receptors mechanism in this model

Robust Deep Network with Maximum Correntropy Criterion for Seizure Detection

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Yu Qi

2014-01-01

Full Text Available Effective seizure detection from long-term EEG is highly important for seizure diagnosis. Existing methods usually design the feature and classifier individually, while little work has been done for the simultaneous optimization of the two parts. This work proposes a deep network to jointly learn a feature and a classifier so that they could help each other to make the whole system optimal. To deal with the challenge of the impulsive noises and outliers caused by EMG artifacts in EEG signals, we formulate a robust stacked autoencoder (R-SAE as a part of the network to learn an effective feature. In R-SAE, the maximum correntropy criterion (MCC is proposed to reduce the effect of noise/outliers. Unlike the mean square error (MSE, the output of the new kernel MCC increases more slowly than that of MSE when the input goes away from the center. Thus, the effect of those noises/outliers positioned far away from the center can be suppressed. The proposed method is evaluated on six patients of 33.6 hours of scalp EEG data. Our method achieves a sensitivity of 100% and a specificity of 99%, which is promising for clinical applications.

Seizure control of Gamma Knife radiosurgery for non-hemorrhagic arteriovenous malformations

International Nuclear Information System (INIS)

Lim, Y.J.; Lee, C.Y.; Koh, J.S.; Kim, T.S.; Kim, G.K.; Rhee, B.A.

2006-01-01

Although radiosurgery has been found to be a safe and effective alternative treatment, seizure outcome of arteriovenous malformation (AVM) radiosurgery has not been documented in detail. We report the effect of Gamma Knife radiosurgery (GKRS) on seizures associated with AVMs and discuss the various factors that influence the prognosis. Between 1992 and 2001 246 patients were treated with GKRS for AVMs at Kyung-Hee medical center. Forty five (17.0 %) patients have non-hemorrhagic AVMs and presenting symptom was seizure. Two patients of all were excluded from this study due to loss of follow-up after radiosurgery. In this study retrospective analysis of clinical characteristics, radiological findings, radiosurgical seizure outcome were performed. There were 32 male and 11 female with age ranging from 10 to 74 years (mean 35 years). Type of seizure included: general tonic clonic (n = 28); focal motor or sensory (n = 7): partial complex (n = 8). The location of AVM was temporal (n = 18); frontal (n = 9): deep seated (n =7): parietal (n = 5); occipital (n = 4). Follow-up period was from 8 months to 12 years (mean 46 months). Mean volume was 6.2 cc (2.7-20), mean marginal and maximal dosage was 19.5 (17-26) and 36.6 Gy (13-50). During follow-up after radiosurgical treatment, 23 (53.5 %) of 43 patients were seizure-free. 10 (23.3 %) had significant improvement, were unchanged in 8 (18.6 %) and aggravated in 2 (4.6 %) patients. In 33 patients, follow-up angiography or MRI was performed. Complete obliteration was achieved in 16 (49.0 %) patients, partial obliteration in 13 (39.0 %). Four were unchanged (12.0 %). Of 33 patients with follow-up performed, 26 were followed for over 2 years. Eleven (84.6 %) of 13 patients with complete obliteration were seizure-free (p < 0.005). Four (36.3 %) of 13 with partial obliteration and unchanged remained seizure-free. Fifteen patients had experienced intractable seizure before radiosurgery. After radiosurgery, seizures disappeared in 8

"Just like EKGs!" Should EEGs undergo a confirmatory interpretation by a clinical neurophysiologist?

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Benbadis, Selim R

2013-01-01

The misdiagnosis of epilepsy is common and has serious consequences. A major contributor to the misdiagnosis of epilepsy is the tendency to overread normal EEGs as abnormal. In fact, the wrong diagnosis of seizures is sometimes based solely on the "abnormal" EEG. Reasons for the common overinterpretation of normal EEGs are mostly related to the lack of standards or mandatory training in EEG, and the erroneous assumption that all neurologists are trained to read EEGs. The most common overread pattern consists of benign, nonspecific, sharply contoured temporal transients. In particular, there is a common misconception that "phase reversals" are indicative of abnormality. Potential solutions include defining and ensuring EEG competency of neurologists who read EEGs, and perhaps providing a confirmatory reading by an electroencephalographer, as is done for EKGs.

Local cerebral metabolism during partial seizures

International Nuclear Information System (INIS)

Engel, J. Jr.; Kuhl, D.E.; Phelps, M.E.; Rausch, R.; Nuwer, M.

1983-01-01

Interictal and ictal fluorodeoxyglucose scans were obtained with positron CT from four patients with spontaneous recurrent partial seizures, one with epilepsia partialis continua, and one with a single partial seizure induced by electrical stimulation of the hippocampus. Ictal metabolic patterns were different for each patient studied. Focal and generalized increased and decreased metabolism were observed. Ictal hypermetabolism may exceed six times the interictal rate and could represent activation of excitatory or inhibitory synapses in the epileptogenic region and its projection fields. Hypometabolism seen on ictal scans most likely reflects postictal depression and may indicate projection fields of inhibited neurons. No quantitative relationship between alterations in metabolism and EEG or behavioral measurements of ictal events could be demonstrated

Local cerebral metabolism during partial seizures

Energy Technology Data Exchange (ETDEWEB)

Engel, J. Jr.; Kuhl, D.E.; Phelps, M.E.; Rausch, R.; Nuwer, M.

1983-04-01

Interictal and ictal fluorodeoxyglucose scans were obtained with positron CT from four patients with spontaneous recurrent partial seizures, one with epilepsia partialis continua, and one with a single partial seizure induced by electrical stimulation of the hippocampus. Ictal metabolic patterns were different for each patient studied. Focal and generalized increased and decreased metabolism were observed. Ictal hypermetabolism may exceed six times the interictal rate and could represent activation of excitatory or inhibitory synapses in the epileptogenic region and its projection fields. Hypometabolism seen on ictal scans most likely reflects postictal depression and may indicate projection fields of inhibited neurons. No quantitative relationship between alterations in metabolism and EEG or behavioral measurements of ictal events could be demonstrated.

Rhythmic EEG patterns in extremely preterm infants : Classification and association with brain injury and outcome

NARCIS (Netherlands)

Weeke, Lauren C; van Ooijen, Inge M; Groenendaal, Floris; van Huffelen, Alexander C.; van Haastert, Ingrid C; van Stam, Carolien; Benders, Manon J; Toet, Mona C; Hellström-Westas, Lena; de Vries, Linda S

2017-01-01

OBJECTIVE: Classify rhythmic EEG patterns in extremely preterm infants and relate these to brain injury and outcome. METHODS: Retrospective analysis of 77 infants born <28 weeks gestational age (GA) who had a 2-channel EEG during the first 72 h after birth. Patterns detected by the BrainZ seizure

Neuropeptide Y inhibits hippocampal seizures and wet dog shakes

DEFF Research Database (Denmark)

Woldbye, D P; Madsen, T M; Larsen, P J

1996-01-01

effects in the dentate gyrus and subiculum, but also in areas to which epileptiform EEG activity spreads before reverberating. In addition, NPY strongly reduced seizure-related 'wet dog shakes' (WDS). This is consistent with previous studies showing that the dentate gyrus is essential for the generation...

Role of I-123-iomazenil SPEDT imaging in drug resistant epilepsy with complex partial seizures

Energy Technology Data Exchange (ETDEWEB)

Sjoeholm, H.; Rosen, I.; Elmqvist, D. [Univ. Hospital, Dept. of Clinical Neurophysiology, Lund (Sweden)

1995-07-01

Fifteen patients with therapy resistant partial complex seizures with no structural lesions were examined interictally with 123-I-IOMAXENIL SPECT for measurement of benzodiazepine receptor distribution and with 99m-Tc-HMPAO SPEDT for measurement of cerebral blood flow distribution. Regional abnormalities were correlated with the seizure onset patterns in EEG later recorded with implanted subdural strips. SPECT scans were made immediately after and at 1 and 2 h after intravenous injection of 123-I-Iomaxenil. During that time there was a continuous change from an immediate flow-related distribution toward a more specific receptor distribution. The decay of radioactivity of I-123 in the brain was linear over time. Two patients on benzodiazepine treatment showed much faster elimination and showed no focal abnormalities. Eight patients with clear-cut unifocal seizure onset showed concordant focal benzodiazepine defects. These patients showed a progressive focus/homotopic non-focus enhancement over time much larger than the HMPAO scans in the same patients. Also the estimated focal area of abnormality was more restricted in the Iomazenil scans than in HMPAO scans. Five patients had more complex seizure onset patterns. In these patients a mismatch between the locations of abnormalities in Iomaxenil and HMPAO scans were often found but benzodiazepine receptor abnormalities were more circumscribed also in these patients. The results suggest that 123-I-Iomazenil SPECT is more useful than 99mTc-HMPAO SPECT when applied interictally in patients with partial complex epilepsy, since in addition to demonstrate the hemispheric laterality of the epileptogenic zone, 123-I-Iomazenil appears to indicate its anatomical location with higher confidence, which could be of practical value for positioning of intracranial EEG electrodes. (au) 36 refs.

Characteristics of late-onset epilepsy and EEG findings in children with autism spectrum disorders

Directory of Open Access Journals (Sweden)

Haneul Lee

2011-01-01

Full Text Available Purpose: To investigate the clinical characteristics of late-onset epilepsy combined with autism spectrum disorder (ASD, and the relationship between certain types of electroencephalography (EEG abnormalities in ASD and associated neuropsychological problems. Methods: Thirty patients diagnosed with ASD in early childhood and later developed clinical seizures were reviewed retrospectively. First, the clinical characteristics, language and behavioral regression, and EEG findings of these late-onset epilepsy patients with ASD were investigated. The patients were then classified into 2 groups according to the severity of the EEG abnormalities in the background rhythm and paroxysmal discharges. In the severe group, EEG showed persistent asymmetry, slow and disorganized background rhythms, and continuous sharp and slow waves during slow sleep (CSWS. Results: Between the two groups, there was no statistically significant difference in mean age (P=0.259, age of epilepsy diagnosis (P=0.237, associated family history (P=0.074, and positive abnormal magnetic resonance image (MRI findings (P=0.084. The severe EEG group tended to have more neuropsychological problems (P=0.074. The severe group statistically showed more electrographic seizures in EEG (P =0.000. Rett syndrome was correlated with more severe EEG abnormalities (P=0.002. Although formal cognitive function tests were not performed, the parents reported an improvement in neuropsychological function on the follow up checkup according to a parent’s questionnaire. Conclusion: Although some ASD patients with late-onset epilepsy showed severe EEG abnormalities, including CSWS, they generally showed an improvement in EEG and clinical symptoms in the longterm follow up. In addition, severe EEG abnormalities tended to be related to the neuropsychological function.

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI

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Umair J. Chaudhary

2016-01-01

In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum.

Probability of detection of clinical seizures using heart rate changes.

Science.gov (United States)

Osorio, Ivan; Manly, B F J

2015-08-01

Heart rate-based seizure detection is a viable complement or alternative to ECoG/EEG. This study investigates the role of various biological factors on the probability of clinical seizure detection using heart rate. Regression models were applied to 266 clinical seizures recorded from 72 subjects to investigate if factors such as age, gender, years with epilepsy, etiology, seizure site origin, seizure class, and data collection centers, among others, shape the probability of EKG-based seizure detection. Clinical seizure detection probability based on heart rate changes, is significantly (pprobability of detecting clinical seizures (>0.8 in the majority of subjects) using heart rate is highest for complex partial seizures, increases with a patient's years with epilepsy, is lower for females than for males and is unrelated to the side of hemisphere origin. Clinical seizure detection probability using heart rate is multi-factorially dependent and sufficiently high (>0.8) in most cases to be clinically useful. Knowledge of the role that these factors play in shaping said probability will enhance its applicability and usefulness. Heart rate is a reliable and practical signal for extra-cerebral detection of clinical seizures originating from or spreading to central autonomic network structures. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The importance of early immunotherapy in patients with faciobrachial dystonic seizures

DEFF Research Database (Denmark)

Thompson, Julia; Bi, Mian; Murchison, Andrew G

2018-01-01

between those with and without cognitive impairment, and to determine whether cessation of faciobrachial dystonic seizures can prevent cognitive impairment. The 22/103 patients without cognitive impairment typically had normal brain MRI, EEGs and serum sodium levels (P

Differential antagonism of tetramethylenedisulfotetramine-induced seizures by agents acting at NMDA and GABA{sub A} receptors

Energy Technology Data Exchange (ETDEWEB)

Shakarjian, Michael P., E-mail: michael_shakarjian@nymc.edu [Department of Environmental Health Science, School of Health Sciences and Practice, Institute of Public Health, New York Medical College, Valhalla, NY, 10595 (United States); Department of Medicine, Division of Pulmonary and Critical Care Medicine, UMDNJ–Robert Wood Johnson Medical School, Piscataway, NJ 08854 (United States); Velíšková, Jana [Department of Cell Biology and Anatomy, New York Medical College, Valhalla, NY 10595 (United States); Department of Obstetrics and Gynecology, New York Medical College, Valhalla, NY 10595 (United States); Department of Neurology, New York Medical College, Valhalla, NY 10595 (United States); Stanton, Patric K., E-mail: patric_stanton@nymc.edu [Department of Cell Biology and Anatomy, New York Medical College, Valhalla, NY 10595 (United States); Department of Neurology, New York Medical College, Valhalla, NY 10595 (United States); Velíšek, Libor [Department of Cell Biology and Anatomy, New York Medical College, Valhalla, NY 10595 (United States); Department of Neurology, New York Medical College, Valhalla, NY 10595 (United States); Department of Pediatrics, New York Medical College, Valhalla, NY 10595 (United States)

2012-11-15

Tetramethylenedisulfotetramine (TMDT) is a highly lethal neuroactive rodenticide responsible for many accidental and intentional poisonings in mainland China. Ease of synthesis, water solubility, potency, and difficulty to treat make TMDT a potential weapon for terrorist activity. We characterized TMDT-induced convulsions and mortality in male C57BL/6 mice. TMDT (ip) produced a continuum of twitches, clonic, and tonic–clonic seizures decreasing in onset latency and increasing in severity with increasing dose; 0.4 mg/kg was 100% lethal. The NMDA antagonist, ketamine (35 mg/kg) injected ip immediately after the first TMDT-induced seizure, did not change number of tonic–clonic seizures or lethality, but increased the number of clonic seizures. Doubling the ketamine dose decreased tonic–clonic seizures and eliminated lethality through a 60 min observation period. Treating mice with another NMDA antagonist, MK-801, 0.5 or 1 mg/kg ip, showed similar effects as low and high doses of ketamine, respectively, and prevented lethality, converting status epilepticus EEG activity to isolated interictal discharges. Treatment with these agents 15 min prior to TMDT administration did not increase their effectiveness. Post-treatment with the GABA{sub A} receptor allosteric enhancer diazepam (5 mg/kg) greatly reduced seizure manifestations and prevented lethality 60 min post-TMDT, but ictal events were evident in EEG recordings and, hours post-treatment, mice experienced status epilepticus and died. Thus, TMDT is a highly potent and lethal convulsant for which single-dose benzodiazepine treatment is inadequate in managing electrographic seizures or lethality. Repeated benzodiazepine dosing or combined application of benzodiazepines and NMDA receptor antagonists is more likely to be effective in treating TMDT poisoning. -- Highlights: ► TMDT produces convulsions and lethality at low doses in mice. ► Diazepam pre- or post-treatments inhibit TMDT-induced convulsions and death

Drug taper during long-term video-EEG monitoring

DEFF Research Database (Denmark)

Guld, A. T.; Sabers, A.; Kjaer, T. W.

2017-01-01

Objectives: Anti-epileptic drugs (AED) are often tapered to reduce the time needed to record a sufficient number of seizure during long-term video-EEG monitoring (LTM). Fast AED reduction is considered less safe, but few studies have examined this. Our goal is to examine whether the rate of AED r...

MRI-negative focal cortical dysplasias and seizure outcome after epilepsy surgery

International Nuclear Information System (INIS)

Minkin, K; Dimova, P.; Penkov, M.; Nachev, G.; Kostadinova, I.; Zlatareva, D.; Gabrovsky, K.; Naydenov, E.; Romansky, K.; Marinov, M.

2012-01-01

Full text: Introduction: The focal cortical dysplasias (FCD) are a main cause of drug-resistant epilepsies. The MRI appearance of FCD is specific but some FCD remain hidden for the MRI. Aim: The aim of this study was to investigate the success rate of epilepsy surgery in patients with FCD and especially MRI-negative FCD during the first 6 years of the epilepsy surgery program of University Hospital 'St. Ivan Rilski', Sofia. Material and methods: Fourteen patients with drug resistant epilepsy and focal cortical dysplasias were operated on from January 2006 to april 2012. The mean age at surgery was 13 years (7-35 years) and the mean age of epilepsy onset was 7 years (1 year - 19 years). The presurgical work-up have included preoperative MRI (1.5T, GE) and seizures registration with video- EEG in all patients, PET-CT in 4 patients and invasive EEG in 5 patients. Eleven patients have MRI-positive cortical dysplasia and 3 patients were MRI negative. Results: Complete seizure control (Engel class I) was achieved in 9 patients, significant improvement (Engel class II) was observed in 3 patients and two patients remain without improvement (Engel class IV). In the small group of 3 patients with MRI-negative FCD, complete seizure control was achieved in two patients. No significant improvement was observed in one patient with MRI-negative FCD and one patient with MRI-positive FCD. Discussion: FCD type I are frequently invisible for the MRI and the localization of the epileptogenic zone is a difficult problem. Many studies have demonstrated the negative predictive value of MRI-negative FCD regarding seizure control after epilepsy surgery for drug-resistant epilepsy. Conclusions: Patients with drug-resistant epilepsy and MRI-negative FCD are good candidates for epilepsy surgery but need comprehensive presurgical workup including PET-CT and invasive-EEG.

Preterm EEG: a multimodal neurophysiological protocol.

Science.gov (United States)

Stjerna, Susanna; Voipio, Juha; Metsäranta, Marjo; Kaila, Kai; Vanhatalo, Sampsa

2012-02-18

Since its introduction in early 1950s, electroencephalography (EEG) has been widely used in the neonatal intensive care units (NICU) for assessment and monitoring of brain function in preterm and term babies. Most common indications are the diagnosis of epileptic seizures, assessment of brain maturity, and recovery from hypoxic-ischemic events. EEG recording techniques and the understanding of neonatal EEG signals have dramatically improved, but these advances have been slow to penetrate through the clinical traditions. The aim of this presentation is to bring theory and practice of advanced EEG recording available for neonatal units. In the theoretical part, we will present animations to illustrate how a preterm brain gives rise to spontaneous and evoked EEG activities, both of which are unique to this developmental phase, as well as crucial for a proper brain maturation. Recent animal work has shown that the structural brain development is clearly reflected in early EEG activity. Most important structures in this regard are the growing long range connections and the transient cortical structure, subplate. Sensory stimuli in a preterm baby will generate responses that are seen at a single trial level, and they have underpinnings in the subplate-cortex interaction. This brings neonatal EEG readily into a multimodal study, where EEG is not only recording cortical function, but it also tests subplate function via different sensory modalities. Finally, introduction of clinically suitable dense array EEG caps, as well as amplifiers capable of recording low frequencies, have disclosed multitude of brain activities that have as yet been overlooked. In the practical part of this video, we show how a multimodal, dense array EEG study is performed in neonatal intensive care unit from a preterm baby in the incubator. The video demonstrates preparation of the baby and incubator, application of the EEG cap, and performance of the sensory stimulations.

Automatic detection of epileptic seizures on the intra-cranial electroencephalogram of rats using reservoir computing.

Science.gov (United States)

Buteneers, Pieter; Verstraeten, David; van Mierlo, Pieter; Wyckhuys, Tine; Stroobandt, Dirk; Raedt, Robrecht; Hallez, Hans; Schrauwen, Benjamin

2011-11-01

In this paper we propose a technique based on reservoir computing (RC) to mark epileptic seizures on the intra-cranial electroencephalogram (EEG) of rats. RC is a recurrent neural networks training technique which has been shown to possess good generalization properties with limited training. The system is evaluated on data containing two different seizure types: absence seizures from genetic absence epilepsy rats from Strasbourg (GAERS) and tonic-clonic seizures from kainate-induced temporal-lobe epilepsy rats. The dataset consists of 452hours from 23 GAERS and 982hours from 15 kainate-induced temporal-lobe epilepsy rats. During the preprocessing stage, several features are extracted from the EEG. A feature selection algorithm selects the best features, which are then presented as input to the RC-based classification algorithm. To classify the output of this algorithm a two-threshold technique is used. This technique is compared with other state-of-the-art techniques. A balanced error rate (BER) of 3.7% and 3.5% was achieved on the data from GAERS and kainate rats, respectively. This resulted in a sensitivity of 96% and 94% and a specificity of 96% and 99% respectively. The state-of-the-art technique for GAERS achieved a BER of 4%, whereas the best technique to detect tonic-clonic seizures achieved a BER of 16%. Our method outperforms up-to-date techniques and only a few parameters need to be optimized on a limited training set. It is therefore suited as an automatic aid for epilepsy researchers and is able to eliminate the tedious manual review and annotation of EEG. Copyright © 2011 Elsevier B.V. All rights reserved.

Prevalence and predictors of subclinical seizures during scalp video-EEG monitoring in patients with epilepsy.

Science.gov (United States)

Jin, Bo; Wang, Shan; Yang, Linglin; Shen, Chunhong; Ding, Yao; Guo, Yi; Wang, Zhongjin; Zhu, Junming; Wang, Shuang; Ding, Meiping

2017-08-01

This study first aimed to establish the prevalence and predictors of subclinical seizures in patients with epilepsy undergoing video electroencephalographic monitoring, then to evaluate the relationship of sleep/wake and circadian pattern with subclinical seizures. We retrospectively reviewed the charts of 742 consecutive patients admitted to our epilepsy center between July 2012 and October 2014. Demographic, electro-clinical data and neuroimage were collected. A total of 148 subclinical seizures were detected in 39 patients (5.3%) during video electroencephalographic monitoring. The mean duration of subclinical seizures was 47.18 s (range, 5-311). Pharmacoresistant epilepsy, abnormal MRI and the presence of interictal epileptiform discharges were independently associated with subclinical seizures in multivariate logistic regression analysis. Subclinical seizures helped localizing the presumed epileptogenic zone in 24 (61.5%) patients, and suggested multifocal epilepsy in five (12.8%). In addition, subclinical seizures occurred more frequently in sleep and night than wakefulness and daytime, respectively, and they were more likely seen between 21:00-03:00 h, and less likely seen between 09:00-12:00 h. Thirty patients (76.9%) had their first subclinical seizures within the first 24 h of monitoring while only 7.7% of patients had their first subclinical seizures detected within 20 min. Subclinical seizures are not uncommon in patients with epilepsy, particularly in those with pharmacoresistant epilepsy, abnormal MRI or interictal epileptiform discharges. Subclinical seizures occur in specific circadian patterns and in specific sleep/wake distributions. A 20-min VEEG monitoring might not be long enough to allow for their detection.

Epileptic seizures due to multiple cerebral cavernomatosis

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Spasić Mirjana

2007-01-01

Full Text Available Background. Cavernous angiomas are angiographically occult vascular malformations that are present in 0.4−0.9 % of people, and represent around 5% of all cerebrovascular malformations. They can be single or multiple, and sporadic or familial. The presence of multiple lesions is more frequent in familial cavernomatosis. Ten to 30 % are associated with familial clustering. Case report. We presented the case of a 43-year-old man, admitted to the Emergency Department due to unprovoked seizure during the wide awake and everyday activities. Neurological examination was with no focal signs. A 32-channel standard digital EEG was without any significant changes of normal baseline activity. After sleep deprivation EEG showed multifocal, bilateral and asymmetric polyspikes and sharpwaves activity. Hyperventilation induced generalized epileptiform discharges. MRI scan demonstrated multiple small cavernous angiomas. Neuropsychological testing demonstrated a delayed memory impairment. Neurosurgery treatment was not recommended, and the therapy with valproate 1 250 mg/day had an excellent efficacy with no singnificant adverse effects. Conclusion. This patient considered as a rare case with multiple cavernomatosis highlights the importance of neuroradiological examination in adult patients with the first epileptic seizure but with no focal neurological signs. .

The role of the standard EEG in clinical psychiatry.

LENUS (Irish Health Repository)

O'Sullivan, S S

2012-02-03

BACKGROUND: The EEG is a commonly requested test on patients attending psychiatric services, predominantly to investigate for a possible organic brain syndrome causing behavioural changes. AIMS: To assess referrals for EEG from psychiatric services in comparison with those from other sources. We determine which clinical factors were associated with an abnormal EEG in patients referred from psychiatric sources. METHODS: A retrospective review of EEG requests in a 1-year period was performed. Analysis of referral reasons for psychiatric patients was undertaken, and outcome of patients referred from psychiatric services post-EEG was reviewed. RESULTS: One thousand four hundred and seventy EEGs were reviewed, of which 91 (6.2%) were referred from psychiatry. Neurology service referrals had detection rates of abnormal EEGs of 27%, with psychiatric referrals having the lowest abnormality detection rate of 17.6% (p < 0.1). In psychiatric-referred patients the only significant predictors found of an abnormal EEG were a known history of epilepsy (p < 0.001), being on clozapine (p < 0.05), and a possible convulsive seizure (RR = 6.51). Follow-up data of 53 patients did not reveal a significant clinical impact of EEG results on patient management. CONCLUSIONS: Many patients are referred for EEG from psychiatric sources despite a relatively low index of suspicion of an organic brain disorders, based on reasons for referral documented, with an unsurprising low clinical yield.

Seizure outcomes in children with epilepsy after resective brain surgery.

Science.gov (United States)

Nagarajan, Lakshmi; Lee, Michael; Palumbo, Linda; Lee, Sharon; Shah, Snehal; Walsh, Peter; Cannell, Patricia; Ghosh, Soumya

2015-09-01

To assess the role of resective brain surgery in childhood epilepsy. We retrospectively analysed the seizure outcomes in 55 children with epilepsy who had resective brain surgery between 1997 and 2012, at our centre. The children were 1.5-18 years at the time of surgery; their seizure onset was between 0.2 andto 15 years of age. 48 had refractory epilepsy. One child died of tumour progression. Follow-up duration in the survivors ranged from 2 to -16 years (mean: 9).Presurgical evaluation included clinical profiles, non-invasive V-EEG monitoring, neuroimaging with MRIs in all; SPECT and PET in selected patients. 54 had intraoperative ECoG. An Engel Class 1 outcome was seen in 78% of the cohort, with 67% being off all AEDs at the most recent follow-up. Children with tumours constituted the majority (56%), with 87% of this group showing a Class 1 outcome and 84% being off AEDs. Children with cortical dysplasia had a Class 1 outcome in 56%. Resective brain surgery is an efficacious option in some children with epilepsy. We found ECoG useful to tailor the cortical resection and in our opinion ECoG contributed to the good seizure outcomes. Copyright © 2015 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Study on patterns and prevalence of EEG abnormalities in children presenting with behavioural disturbances in psychiatry OPD, Gauhati Medical College and Hospital

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Bobby Hmar

2016-01-01

Full Text Available Background of the study: Children with behavioural abnormalities and developmental disorders are often advised electroencephalography (EEG for evaluation of electrophysiological process of the brain to rule out any organic pathology. Various studies have reported abnormal EEG in these groups of children without history of clinical seizure on routine EEG and sleep EEG. Aim of the study: To study pattern and prevalence of EEG abnormalities in children with behavioural abnormalities without history of clinical seizure. Materials and methods: The study is a retrospective study. Ethical clearance has been obtained from institutional ethical committee for the study. To collect data, socio-demographic and clinical data proforma has been used. Data has been evaluated during the period from June 2011 to June 2014 as per selection criteria from the case history record of children with behavioural abnormalities attending child guidance clinic (CGC. Associations of abnormal EEG with various psychiatric diagnoses has been analysed and chi-square test has been used. p value <0.05 has been taken as test of significance. Result: Total 2011 children attended CGC from 2011 June to 2014 June. One hundred and ninety two children of various psychiatric diagnoses as per the tenth revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10 criteria had fulfilled the selection criteria and 113 children had done EEG. Abnormal EEG was found in 26.54% of children with various psychiatric diagnoses. Association was statistically significant (p<0.05. The EEG abnormalities were found more in male gender than female (p<0.05 and more in younger age group (four to ten years, p<0.05. Conclusion: Children with various psychiatric diagnoses have significant association with abnormal EEG without history of clinical seizure.

Psychogenic Nonepileptic Seizures after Head Injury: A Case Report

Directory of Open Access Journals (Sweden)

Laura Scévola

2009-01-01

another medical illness. The gold standard for PNES diagnosis is video electroencephalogram (Video-EEG. PNESs are defined by modern psychiatry as conversion and dissociative disorders but these disorders may coexist with many others psychiatric disorders, including depression, posttraumatic stress disorder, and personality disorders. It is well known that epileptic seizures are a frequent and well-studied complication of traumatic head injury (THI. However, THI may also generate psychic symptoms including PNES. In this paper we describe a patient who developed PNES after THI in a bus accident and received a diagnosis of refractory epilepsy for 24 years until she underwent Video-EEG.

Subacute encephalopathy with epileptic seizures in alcoholism (SESA): case report.

Science.gov (United States)

Otto, F G; Kozian, R

2001-10-01

The case of a 66-year-old patient is reported in view of the rarity of his condition: a case of subacute encephalopathy with seizures in alcoholics (SESA syndrome), described first in 1981 by Niedermeyer, et al. Wernicke-type aphasia, epileptic seizures (generalized tonic-clonic) and PLEDs EEG pattern dominated the neurological picture, in addition to hepatomegaly and rhabdomyolysis. This condition differs from all other known CNS complications in chronic alcoholism and is withdrawal-independent. It is prognostically favorable as far as the syndrome as such is concerned.

Focal Electrically Administered Seizure Therapy (FEAST): A novel form of ECT illustrates the roles of current directionality, polarity, and electrode configuration in seizure induction

Science.gov (United States)

Spellman, Timothy; Peterchev, Angel V.; Lisanby, Sarah H.

2009-01-01

Electroconvulsive therapy (ECT) is a mainstay in the treatment of severe, medication resistant depression. The antidepressant efficacy and cognitive side effects of ECT are influenced by the position of the electrodes on the head and by the degree to which the electrical stimulus exceeds the threshold for seizure induction. However, surprisingly little is known about the effects of other key electrical parameters such as current directionality, polarity, and electrode configuration. Understanding these relationships may inform the optimization of therapeutic interventions to improve their risk/benefit ratio. To elucidate these relationships, we evaluated a novel form of ECT (focal electrically administered seizure therapy, FEAST) that combines unidirectional stimulation, control of polarity, and an asymmetrical electrode configuration, and contrasted it with conventional ECT in a nonhuman primate model. Rhesus monkeys had their seizure thresholds determined on separate days with ECT conditions that crossed the factors of current directionality (unidirectional or bidirectional), electrode configuration (standard bilateral or FEAST (small anterior and large posterior electrode)), and polarity (assignment of anode and cathode in unidirectional stimulation). Ictal expression and post-ictal suppression were quantified via scalp EEG. Findings were replicated and extended in a second experiment with the same subjects. Seizures were induced in each of 75 trials, including 42 FEAST procedures. Seizure thresholds were lower with unidirectional than with bidirectional stimulation (pFEAST than in bilateral ECS (p=0.0294). Ictal power was greatest in posterior-anode unidirectional FEAST, and post-ictal suppression was strongest in anterior-anode FEAST (p=0.0008 and p=0.0024, respectively). EEG power was higher in the stimulated hemisphere in posterior-anode FEAST (p=0.0246), consistent with the anode being the site of strongest activation. These findings suggest that current

Automatic epileptic seizure detection using scalp EEG and advanced artificial intelligence techniques.

Science.gov (United States)

Fergus, Paul; Hignett, David; Hussain, Abir; Al-Jumeily, Dhiya; Abdel-Aziz, Khaled

2015-01-01

The epilepsies are a heterogeneous group of neurological disorders and syndromes characterised by recurrent, involuntary, paroxysmal seizure activity, which is often associated with a clinicoelectrical correlate on the electroencephalogram. The diagnosis of epilepsy is usually made by a neurologist but can be difficult to be made in the early stages. Supporting paraclinical evidence obtained from magnetic resonance imaging and electroencephalography may enable clinicians to make a diagnosis of epilepsy and investigate treatment earlier. However, electroencephalogram capture and interpretation are time consuming and can be expensive due to the need for trained specialists to perform the interpretation. Automated detection of correlates of seizure activity may be a solution. In this paper, we present a supervised machine learning approach that classifies seizure and nonseizure records using an open dataset containing 342 records. Our results show an improvement on existing studies by as much as 10% in most cases with a sensitivity of 93%, specificity of 94%, and area under the curve of 98% with a 6% global error using a k-class nearest neighbour classifier. We propose that such an approach could have clinical applications in the investigation of patients with suspected seizure disorders.

Interval analysis of interictal EEG: pathology of the alpha rhythm in focal epilepsy

Science.gov (United States)

Pyrzowski, Jan; Siemiński, Mariusz; Sarnowska, Anna; Jedrzejczak, Joanna; Nyka, Walenty M.

2015-11-01

The contemporary use of interictal scalp electroencephalography (EEG) in the context of focal epilepsy workup relies on the visual identification of interictal epileptiform discharges. The high-specificity performance of this marker comes, however, at a cost of only moderate sensitivity. Zero-crossing interval analysis is an alternative to Fourier analysis for the assessment of the rhythmic component of EEG signals. We applied this method to standard EEG recordings of 78 patients divided into 4 subgroups: temporal lobe epilepsy (TLE), frontal lobe epilepsy (FLE), psychogenic nonepileptic seizures (PNES) and nonepileptic patients with headache. Interval-analysis based markers were capable of effectively discriminating patients with epilepsy from those in control subgroups (AUC~0.8) with diagnostic sensitivity potentially exceeding that of visual analysis. The identified putative epilepsy-specific markers were sensitive to the properties of the alpha rhythm and displayed weak or non-significant dependences on the number of antiepileptic drugs (AEDs) taken by the patients. Significant AED-related effects were concentrated in the theta interval range and an associated marker allowed for identification of patients on AED polytherapy (AUC~0.9). Interval analysis may thus, in perspective, increase the diagnostic yield of interictal scalp EEG. Our findings point to the possible existence of alpha rhythm abnormalities in patients with epilepsy.

PHYSIOLOGIC PATTERNS OF SLEEP ON EEG, MASKING OF EPILEPTIFORM ACTIVITY

Directory of Open Access Journals (Sweden)

L. Yu. Glukhova

2013-01-01

Full Text Available Physiologic patterns of sleep on EEG can sometimes be similar to epileptiform activity and even to the EEG pattern of epileptic seizures, but they have no connection to epilepsy and their incorrect interpretation may lead to overdiagnosis of epilepsy. These sleep patterns include vertex transients, K-complexes, hypnagogic hypersynchrony, 14 and 6 Hz positive bursts, wicket-potentials, etc. The main distinctive features of acute physiological phenomena of sleep unlike epileptiform activity are stereotyped, monomorphic morphology of waves, which frequently has rhythmic, arcuate pattern, often with change of lateralization, mainly dominated in the first stages of sleep (N1-N2, with their reduction in the deeper stages and transition to delta sleep (N3. The correct interpretation of physiological sharp-wave phenomena of sleep on EEG requires considerable training and experience of the physician. Our review includes a variety of physiological sleep patterns, which can mimic epileptiform activity on EEG, their criteria of diagnostic with demonstration of own illustrations of EEG.

Study on localization diagnosis with SPECT rCBF image in childhood epilepsy: in comparison with EEG and MRI findings

International Nuclear Information System (INIS)

Wu Meiqian; Tang Jihong; Wu Jinchang; Shi Yizhen

1999-01-01

Objective: To evaluate the diagnostic value of SPECT rCBF imaging in localization of childhood epileptic foci. Methods: rCBF imaging was performed in 74 epileptic patients not in seizure and 10 epileptic patients right in seizure. EEG was performed in 84, MRI in 67 of the subjects mentioned above. All the results of three modalities were compared with each other. Results: The highest positive rate (82.14%) was found in SPECT rCBF imaging, the positive rate in EEG or MRI was 71.43 or 47.76%. The epileptic foci localized by EEG (60 abnormalities) and by MRI (32 abnormalities) were 70.59% or 58.82% in concordance with those by SPECT, respectively. Conclusions: SPECT rCBF imaging is a sensitive and effective method for epileptic foci localization. It may have some advantages over EEG and MRI in detecting and localizing epileptic foci. However, abnormal SPECT areas may cover some abnormalities which do not belong to epileptic category. A combination of these three methods (SPECT, EEG and MRI) will improve the positive rate and accuracy for localizing

Ictal brain SPET during seizures pharmacologically provoked with pentylenetetrazol: a new diagnostic procedure in drug-resistant epileptic patients

International Nuclear Information System (INIS)

Calcagni, Maria Lucia; Giordano, Alessandro; Bruno, Isabella; Di Giuda, Daniela; De Rossi, Giuseppe; Troncone, Luigi; Parbonetti, Giovanni; Colicchio, Gabriella

2002-01-01

Functional brain imaging plays an important role in seizure focus localisation. However, truly ictal single-photon emission tomography (SPET) studies are not routinely performed owing to technical problems associated with the use of tracers and methodological and logistical difficulties. In this study we tried to resolve both of these issues by means of a new procedure: technetium-99m ethyl cysteinate dimer (ECD) brain SPET performed during seizures pharmacologically provoked with pentylenetetrazol, a well-known central and respiratory stimulant. We studied 33 drug-resistant epileptic patients. All patients underwent anamnestic evaluation, neuropsychological and psychodynamic assessment, magnetic resonance imaging, interictal and ictal video-EEG monitoring, and interictal and ictal SPET with 99m Tc-ECD. In order to obtain truly ictal SPET, 65 mg of pentylenetetrazol was injected every 2 minutes and, immediately the seizure began, 740 MBq of 99m Tc-ECD was injected. The scintigraphic findings were considered abnormal if a single area of hyperperfusion was present and corresponded to the site of a single area of hypoperfusion at interictal SPET: the ''hypo-hyperperfusion'' SPET pattern. In 27 of the 33 patients (82%), interictal-ictal SPET showed the hypo-hyperperfusion SPET pattern. Video-EEG showed a single epileptogenic zone in 21/33 patients (64%), and MRI showed anatomical lesions in 19/33 patients (57%). Twenty-two of the 27 patients with hypo-hyperperfusion SPET pattern underwent ablative or palliative surgery and were seizure-free at 3 years of follow-up. No adverse effects were noted during pharmacologically provoked seizure. It is concluded that ictal brain SPET performed during pharmacologically provoked seizure provides truly ictal images because 99m Tc-ECD is injected immediately upon seizure onset. Using this feasible procedure it is possible to localise the focus, to avoid the limitations due to the unpredictability of seizures, to avoid pitfalls due

Complex partial seizures and aphasia as initial manifestations of non-ketotic hyperglycemia: case report Crises parciais complexas e afasia como manifestações iniciais de hiperglicemia não cetótica: relato de caso

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MARCUS SABRY AZAR BATISTA

1998-06-01

Full Text Available We describe a case of non-ketotic hyperglycemia (NKH, heralded by complex partial seizures and aphasia of epileptic origin, besides versive and partial motor seizures. This clinical picture was accompanied by left fronto-temporal spikes in the EEG. The seizures were controlled by carbamazepine only after the control of the diabetes. A month later, carbamazepine was discontinued. The patient remained without seizures, with normal language, using only glybenclamide. Complex partial seizures, opposed to simple partial seizures, are rarely described in association to NKH. Epileptic activity localized over language regions can manifest as aphasia.Descrevemos um caso de hiperglicemia não-cetótica (HNC cujas manifestações iniciais foram crises parciais complexas e afasia de origem epiléptica, além de crises versivas e parcias motoras. Este quadro clínico foi acompanhado por atividade epileptiforme na região fronto-temporal esquerda ao eletrencefalograma. As crises epilépticas foram controladas com carbamazepina (CBZ apenas após o controle do diabetes mellitus. Após um mês, a CBZ foi suspensa, permanecendo a paciente com linguagem normal, sem novas crises epilépticas, em uso apenas de glibenclamida. Crises parciais complexas, ao contrário de crises parciais simples, são raramente descritas como manifestação de HNC. Atividade epileptiforme nas regiões relacionadas a linguagem podem manifestar-se como afasia.

Clonic Seizures in GAERS Rats after Oral Administration of Enrofloxacin

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Bauquier, Sebastien H; Jiang, Jonathan L; Lai, Alan; Cook, Mark J

2016-01-01

The aim of this study was to evaluate the effect of oral enrofloxacin on the epileptic status of Genetic Absence Epilepsy Rats from Strasbourg (GAERS). Five adult female GAERS rats, with implanted extradural electrodes for EEG monitoring, were declared free of clonic seizures after an 8-wk observation period. Enrofloxacin was then added to their drinking water (42.5 mg in 750 mL), and rats were observed for another 3 days. The number of spike-and-wave discharges and mean duration of a single discharge did not differ before and after treatment, but 2 of the 5 rats developed clonic seizures after treatment. Enrofloxacin should be used with caution in GAERS rats because it might induce clonic seizures. PMID:27298247

Classifying epileptic EEG signals with delay permutation entropy and Multi-Scale K-means.

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Zhu, Guohun; Li, Yan; Wen, Peng Paul; Wang, Shuaifang

2015-01-01

Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) MSK-means algorithm to distinguish epileptic EEG signals and identify epileptic zones. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means MSK-means algorithm initializes the coarse-scale centroid of a cluster with a suitable scale factor. In this chapter, the MSK-means algorithm is proved theoretically superior to the K-means algorithm on efficiency. In addition, three classifiers: the K-means, MSK-means MSK-means and support vector machine (SVM), are used to identify seizure and localize epileptogenic zone using delay permutation entropy features. The experimental results demonstrate that identifying seizure with the MSK-means algorithm and delay permutation entropy achieves 4. 7 % higher accuracy than that of K-means, and 0. 7 % higher accuracy than that of the SVM.

Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

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Ge, Jing; Zhang, Guoping

2015-01-01

Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diversity and the evolution of the epileptic seizures make it very difficult in detecting and identifying the undergoing disease. Fortunately, the determinism and nonlinearity in a time series could characterize the state changes. Literature review indicates that the Delay Vector Variance (DVV) could examine the nonlinearity to gain insight into the EEG signals but very limited work has been done to address the quantitative DVV approach. Hence, the outcomes of the quantitative DVV should be evaluated to detect the epileptic seizures. To develop a new epileptic seizure detection method based on quantitative DVV. This new epileptic seizure detection method employed an improved delay vector variance (IDVV) to extract the nonlinearity value as a distinct feature. Then a multi-kernel functions strategy was proposed in the extreme learning machine (ELM) network to provide precise disease detection and prediction. The nonlinearity is more sensitive than the energy and entropy. 87.5% overall accuracy of recognition and 75.0% overall accuracy of forecasting were achieved. The proposed IDVV and multi-kernel ELM based method was feasible and effective for epileptic EEG detection. Hence, the newly proposed method has importance for practical applications.

Epileptic seizures and headache/migraine: a review of types of association and terminology.

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Cianchetti, Carlo; Pruna, Dario; Ledda, Mariagiuseppina

2013-11-01

There are different possible temporal associations between epileptic seizures and headache attacks which have given rise to unclear or controversial terminologies. The classification of the International League Against Epilepsy does not refer to this type of disorder, while the International Classification of Headache Disorders (ICHD-2) defines three kinds of association: (1) migraine-triggered seizure ("migralepsy"), (2) hemicrania epileptica, and (3) post-ictal headache. We performed an extensive review of the literature, not including "post-ictal" and "inter-ictal" headaches. On the basis of well-documented reports, the following clinical entities may be identified: (A) "epileptic headache (EH)" or "ictal epileptic headache (IEH)": in this condition headache (with or without migrainous features) is an epileptic manifestation per se, with onset, and cessation if isolated, coinciding with the scalp or deep EEG pattern of an epileptic seizure. EH maybe followed by other epileptic manifestations (motor/sensory/autonomic); this condition should be differentiated from "pure" or "isolated" EH, in which headache/migraine is the sole epileptic manifestation (requiring differential diagnosis from other headache forms). "Hemicrania epileptica" (if confirmed) is a very rare variant of EH, characterized by ipsilateral location of headache and ictal EEG paroxysms. (B) "Pre-ictal migraine" and "pre-ictal headache": when a headache attack is followed during, or shortly after, by a typical epileptic seizure. The migraine attack may be with or without aura, and its seizure-triggering role ("migraine-triggered seizure") is still a subject of debate. A differentiation from occipital epilepsy is mandatory. The term "migralepsy" has not been used uniformly, and may therefore led to misinterpretation. On the basis of this review we suggest definitions and a terminology which may become the basis of a forthcoming classification of headaches associated with epileptic seizures. Copyright

Benign infantile seizures and paroxysmal dyskinesia caused by an SCN8A mutation

DEFF Research Database (Denmark)

Gardella, Elena; Becker, Felicitas; Møller, Rikke S

2016-01-01

by stretching, motor initiation or by emotional stimuli. In one case, we recorded typical PKD spells by video-EEG-polygraphy, documenting a cortical involvement. INTERPRETATION: Our study establishes SCN8A as a novel gene in which a recurrent mutation causes BFIS/ICCA, expanding the clinical-genetic spectrum...... patient had seizures only at school age. All patients stayed otherwise seizure-free, most without medication. Interictal EEG was normal in all cases but two. Five/16 patients developed additional brief paroxysmal episodes in puberty, either dystonic/dyskinetic or "shivering" attacks, triggered...... identified as the major gene in all three conditions, found to be mutated in 80-90% of familial and 30-35% of sporadic cases. METHODS: We searched for the genetic defect in PRRT2-negative, unrelated families with BFIS or ICCA using whole exome or targeted gene panel sequencing, and performed a detailed...

Seizures in dominantly inherited Alzheimer disease.

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Zarea, Aline; Charbonnier, Camille; Rovelet-Lecrux, Anne; Nicolas, Gaël; Rousseau, Stéphane; Borden, Alaina; Pariente, Jeremie; Le Ber, Isabelle; Pasquier, Florence; Formaglio, Maite; Martinaud, Olivier; Rollin-Sillaire, Adeline; Sarazin, Marie; Croisile, Bernard; Boutoleau-Bretonnière, Claire; Ceccaldi, Mathieu; Gabelle, Audrey; Chamard, Ludivine; Blanc, Frédéric; Sellal, François; Paquet, Claire; Campion, Dominique; Hannequin, Didier; Wallon, David

2016-08-30

To assess seizure frequency in a large French cohort of autosomal dominant early-onset Alzheimer disease (ADEOAD) and to determine possible correlations with causative mutations. A national multicentric study was performed in patients with ADEOAD harboring a pathogenic mutation within PSEN1, PSEN2, APP, or a duplication of APP, and a minimal follow-up of 5 years. Clinical, EEG, and imaging data were systematically recorded. We included 132 patients from 77 families: 94 PSEN1 mutation carriers (MCs), 16 APP duplication carriers, 15 APP MCs, and 7 PSEN2 MCs. Seizure frequency was 47.7% after a mean follow-up of 8.4 years (range 5-25). After 5-year follow-up and using a Cox model analysis, the percentages of patients with seizures were respectively 19.1% (10.8%-26.7%) for PSEN1, 28.6% (0%-55.3%) for PSEN2, 31.2% (4.3%-50.6%) for APP duplications, and no patient for APP mutation. APP duplication carriers showed a significantly increased seizure risk compared to both APP MCs (hazard ratio [HR] = 5.55 [95% confidence interval 1.87-16.44]) and PSEN1 MCs (HR = 4.46 [2.11-9.44]). Among all PSEN1 mutations, those within the domains of protein hydrophilic I, transmembrane II (TM-II), TM-III, TM-IV, and TM-VII were associated with a significant increase in seizure frequency compared to other domains (HR = 4.53 [1.93-10.65], p = 0.0005). Seizures are a common feature of ADEOAD. In this population, risk was significantly higher in the APP duplication group than in all other groups. Within PSEN1, 5 specific domains were associated with a higher seizure risk indicating specific correlations between causative mutation and seizures. © 2016 American Academy of Neurology.

Absence-like and tonic seizures in aspartoacylase/attractin double-mutant mice.

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Gohma, Hiroshi; Kuramoto, Takashi; Matalon, Reuben; Surendran, Sankar; Tyring, Stephen; Kitada, Kazuhiro; Sasa, Masashi; Serikawa, Tadao

2007-04-01

The Spontaneously Epileptic Rat (SER), a double-mutant for tremor and zitter mutations, shows spontaneous occurrences of absence-like and tonic seizures. Several lines of evidence suggest that the combined effect of Aspa and Atrn mutations is the most likely cause of the epileptic phenotype of the SER. To address this issue, we produced a new double-mutant mouse line carrying both homozygous Aspa-knockout and Atrn(mg-3J) mutant alleles. The Aspa/Atrn double-mutant mice exhibited absence-like and tonic seizures that were characterized by the appearance of 5-7 Hz spike-wave-like complexes and low voltage fast waves on EEGs. These results demonstrate directly that the simultaneous loss of the Aspa and Atrn gene functions causes epileptic seizures in the mouse and suggest that both Aspa and Atrn deficiencies might be responsible for epileptic seizures in the SER.

EEG signal classification using PSO trained RBF neural network for epilepsy identification

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Sandeep Kumar Satapathy

Full Text Available The electroencephalogram (EEG is a low amplitude signal generated in the brain, as a result of information flow during the communication of several neurons. Hence, careful analysis of these signals could be useful in understanding many human brain disorder diseases. One such disease topic is epileptic seizure identification, which can be identified via a classification process of the EEG signal after preprocessing with the discrete wavelet transform (DWT. To classify the EEG signal, we used a radial basis function neural network (RBFNN. As shown herein, the network can be trained to optimize the mean square error (MSE by using a modified particle swarm optimization (PSO algorithm. The key idea behind the modification of PSO is to introduce a method to overcome the problem of slow searching in and around the global optimum solution. The effectiveness of this procedure was verified by an experimental analysis on a benchmark dataset which is publicly available. The result of our experimental analysis revealed that the improvement in the algorithm is significant with respect to RBF trained by gradient descent and canonical PSO. Here, two classes of EEG signals were considered: the first being an epileptic and the other being non-epileptic. The proposed method produced a maximum accuracy of 99% as compared to the other techniques. Keywords: Electroencephalography, Radial basis function neural network, Particle swarm optimization, Discrete wavelet transform, Machine learning

Data-Driven Approaches for Computation in Intelligent Biomedical Devices: A Case Study of EEG Monitoring for Chronic Seizure Detection

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Naveen Verma

2011-04-01

Full Text Available Intelligent biomedical devices implies systems that are able to detect specific physiological processes in patients so that particular responses can be generated. This closed-loop capability can have enormous clinical value when we consider the unprecedented modalities that are beginning to emerge for sensing and stimulating patient physiology. Both delivering therapy (e.g., deep-brain stimulation, vagus nerve stimulation, etc. and treating impairments (e.g., neural prosthesis requires computational devices that can make clinically relevant inferences, especially using minimally-intrusive patient signals. The key to such devices is algorithms that are based on data-driven signal modeling as well as hardware structures that are specialized to these. This paper discusses the primary application-domain challenges that must be overcome and analyzes the most promising methods for this that are emerging. We then look at how these methods are being incorporated in ultra-low-energy computational platforms and systems. The case study for this is a seizure-detection SoC that includes instrumentation and computation blocks in support of a system that exploits patient-specific modeling to achieve accurate performance for chronic detection. The SoC samples each EEG channel at a rate of 600 Hz and performs processing to derive signal features on every two second epoch, consuming 9 μJ/epoch/channel. Signal feature extraction reduces the data rate by a factor of over 40×, permitting wireless communication from the patient’s head while reducing the total power on the head by 14×.

Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design.

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Westhall, Erik; Rosén, Ingmar; Rossetti, Andrea O; van Rootselaar, Anne-Fleur; Kjaer, Troels Wesenberg; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Cronberg, Tobias

2014-08-16

Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. The TTM-trial is registered at ClinicalTrials.gov (NCT01020916).

MRI in temporal lobe epilepsy. Correlation between EEG, SPECT and clinical features

International Nuclear Information System (INIS)

Uesugi, Hideji; Onuma, Teiichi; Matsuda, Hiroshi; Ishida, Shiro

1996-01-01

The relationship between MRI, SPECT, EEG and clinical features in temporal lobe epilepsy was investigated. Subjects were 162 patients (84 males, 78 females) whose average age was 38.1±12.1 years. SPECT was carried out in 45 patients. The results were as follows: abnormal MR images were obtained in 36% of the group without epileptic discharge, and in 42% of the group with temporal spikes. There was no correlation between epileptic discharge in EEG and MRI abnormality. The lateralities of epileptic discharge and MRI were in disagreement in 9 of 39 patients (23%), indicating that determining the epileptic focus from scalp EEG was difficult. There was no correlation between the basic activity in EEG and abnormality in MRI. The rate of abnormal SPECT (89%) was higher than that of abnormal MRI (40%). The rate of the group with ictal automatism (52%) was higher than that of the group without ictal automatism (35%). The rate of abnormal MR images was high in the group with encephalitis (73%). The rate was higher in the group with febrile convulsion (62%) than in the group without it (28%). The rate of the abnormal MR images was higher in the group with a seizure frequency of at least several mal/month (48%) than in the group with a seizure frequency of less than several mal/year (29%). (author)

Genital automatisms: Reappraisal of a remarkable but ignored symptom of focal seizures.

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Dede, Hava Özlem; Bebek, Nerses; Gürses, Candan; Baysal-Kıraç, Leyla; Baykan, Betül; Gökyiğit, Ayşen

2018-03-01

Genital automatisms (GAs) are uncommon clinical phenomena of focal seizures. They are defined as repeated fondling, grabbing, or scratching of the genitals. The aim of this study was to determine the lateralizing and localizing value and associated clinical characteristics of GAs. Three hundred thirteen consecutive patients with drug-resistant seizures who were referred to our tertiary center for presurgical evaluation between 2009 and 2016 were investigated. The incidence of specific kinds of behavior, clinical semiology, associated symptoms/signs with corresponding ictal electroencephalography (EEG) findings, and their potential role in seizure localization and lateralization were evaluated. Fifteen (4.8%) of 313 patients had GAs. Genital automatisms were identified in 19 (16.4%) of a total 116 seizures. Genital automatisms were observed to occur more often in men than in women (M/F: 10/5). Nine of fifteen patients (60%) had temporal lobe epilepsy (right/left: 4/5) and three (20%) had frontal lobe epilepsy (right/left: 1/2), whereas the remaining two patients could not be classified. One patient was diagnosed as having Rasmussen encephalitis. Genital automatisms were ipsilateral to epileptic focus in 12 patients and contralateral in only one patient according to ictal-interictal EEG and neuroimaging findings. Epileptic focus could not be lateralized in the last 2 patients. Genital automatisms were associated with unilateral hand automatisms such as postictal nose wiping or manual automatisms in 13 (86.7%) of 15 and contralateral dystonia was seen in 6 patients. All patients had amnesia of the performance of GAs. Genital automatisms are more frequent in seizures originating from the temporal lobe, and they can also be seen in frontal lobe seizures. Genital automatisms seem to have a high lateralizing value to the ipsilateral hemisphere and are mostly concordant with other unilateral hand automatisms. Men exhibit GAs more often than women. Copyright © 2017

PROFILE AND SHORT-TERM OUTCOME IN ADULT PATIENTS WITH NEW-ONSET SEIZURES

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S. Gopi

2018-01-01

Full Text Available BACKGROUND The annual incidence is 85 per 1,00,000 for people aged 65-69 years and 135 per 1,00,000 for those aged over 80 years. Epilepsy in older patients poses several additional problems for the provision of services compared with the rest of the population as diagnostic difficulties and polypharmacy. The aim of the study is to1. Know the various causes of seizures, clinical profile and correlation between neurological imaging and VEEG characteristics. 2. Know the differences between the aetiologies of seizures in young age and elderly >65 years. MATERIALS AND METHODS This was a prospective, hospital-based case control study conducted on 75 patients older than 65 years with new-onset seizures at KGH Neurology OP and IP Services from September 2014 - November 2016 using EEG, MRI or CT brain and relevant laboratory tests. RESULTS 75 patients (46 males, 29 females with a mean age of 73.72 ± 8.72 years were enrolled in the study. Overall, the seizures were classified as generalised onset in 7 (9.4%, focal onset in 52 (70.1% and uncertain onset in 15 (20.5% patients. The aetiology was acute symptomatic in 29 (39.2%, remote symptomatic in 24 (31.7%, progressive symptomatic in 14 (19.1% and unknown in 8 (10.1% patients. CONCLUSION Most of the new-onset seizures in our elderly patients were focal onset as a consequence of vascular brain lesion. The recurrence was high. The major risk factors for recurrent seizures were acute, remote and progressive symptomatic aetiologies, epileptiform discharges and nonspecific abnormalities on EEG. Elderly patients maybe at a higher risk of recurrence following an initial stroke than younger people.

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy.

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Mishra, Vikas; Gautier, Nicole M; Glasscock, Edward

2018-01-29

In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can potentially increase risk of sudden unexpected death in epilepsy (SUDEP). Electroencephalography (EEG) and electrocardiography (ECG) are widely used clinical diagnostic tools to monitor for abnormal brain and cardiac rhythms in patients. Here, a technique to simultaneously record video, EEG, and ECG in mice to measure behavior, brain, and cardiac activities, respectively, is described. The technique described herein utilizes a tethered (i.e., wired) recording configuration in which the implanted electrode on the head of the mouse is hard-wired to the recording equipment. Compared to wireless telemetry recording systems, the tethered arrangement possesses several technical advantages such as a greater possible number of channels for recording EEG or other biopotentials; lower electrode costs; and greater frequency bandwidth (i.e., sampling rate) of recordings. The basics of this technique can also be easily modified to accommodate recording other biosignals, such as electromyography (EMG) or plethysmography for assessment of muscle and respiratory activity, respectively. In addition to describing how to perform the EEG-ECG recordings, we also detail methods to quantify the resulting data for seizures, EEG spectral power, cardiac function, and heart rate variability, which we demonstrate in an example experiment using a mouse with epilepsy due to Kcna1 gene deletion. Video-EEG-ECG monitoring in mouse models of epilepsy or other neurological disease provides a powerful tool to identify dysfunction at the level of the brain, heart, or brain-heart interactions.

USE OF STRUCTURAL MRI IN PATIENTS WITH MEDICALLY REFRACTORY SEIZURES

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Ara G. Kaprelyan

2012-12-01

Full Text Available Introduction: Refractory epilepsy is common in patients with structural brain lesions including acquired disorders and genetic abnormalities. Recently, MRI is a precise diagnostic tool for recognition of different structural causes underlying medically intractable seizures.Objective: To evaluate the usefulness of MRI for detection of brain lesions associated with refractory epilepsy.Material and methods: 49 patients (20M and 29F; aged 48.6±24.7 years with refractory epilepsy were included in the study. They presented with partial (46.0%, secondary (31.0% or primary (23.0% generalized tonic-clonic seizures. Clinical diagnosis was based on the revised criteria of ILAE. Structural neuroimaging (MRI, EEG recording, and neurological examination were performed.Results: MRI detected different structural brain abnormalities totally in 36 (73.5% patients, including cerebral tumors (21p, cerebrovascular accidents (5p, hyppocampal sclerosis (3p, developmental malformations (2p, postencephalitic lesions (2p, arachnoid cysts (2p, and tuberous sclerosis (1p. Neuroimaging revealed normal findings in 13 (27.5% cases. EEG recordings showed focal epileptic activity in 38 (77.6% patients, including 33 cases with and 5 without structural brain abnormalities.Conclusion: This study revealed that structural brain lesions are commonly associated with refractory epilepsy. We suggested that MRI is a useful diagnostic method for assessment of patients with uncontrolled seizures or altered epileptic pattern.

TOWARDS A PERSONALIZED REAL-TIME DIAGNOSIS IN NEONATAL SEIZURE DETECTION

DEFF Research Database (Denmark)

Temko, Andriy; Sarkar, Achintya Kumar; Boylan, Geraldine

2017-01-01

recordings is achievable with on-the-fly incorporation of patient-specific EEG characteristics. In the clinical setting, the employment of the developed system will maintain a seizure detection rate at 70% while halving the number of false detections per hour, from 0.4 FD/h to 0.2 FD/h. This is the first...

[A modified approach to the diagnosis and therapy of epileptic seizures in the third stage of life].

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Gavranović, Muhamed; Delilović, Jasminka; Kurtović, Azra; Alibegović, Sakib; Rajić, Zeljka; Ajanović, Zakira

2003-01-01

Incidence of seizures in the elderly is nowadays greater than the one characteristic for children up to 10 years of age. Epileptic seizures are the third most common serious neurological disorder in this age group, after stroke and dementia. Optimal care for those patients, regarding to the seizures, demands some modification in diagnostic and treatment approach. Aim of this report was to point out problems in diagnostics, treatment and most common mistakes in practice. Fifty one patients were assessed, aged 65-83 years, (30 female and 21 male), with diagnosis of epilepsy and established antiepileptic treatment. All patients were re-examined, and following procedures were utilised: auto and heteroanamnesis (especially data provided by eyewitnesses), clinical examination, biochemical status, complete cardiological examination, EEG registration, serum concentrations of antiepileptic drugs, CT and MRI scan. Out of 51 patients 11 were misdiagnosed (syncope, provoked seizures, TIA). The most common form of seizures were partial seizures with or without secondary generalization (31 cases). Etiologic factors: stroke (25 cases), arteriosclerosis (7 cases), tumours (3 cases), trauma (2 cases), unknown (3 cases) cardiovascular diseases (29 casec) diabetes mellitus (20 cases), respiratory disturbance (12 cases) renal disturbances (8 cases). Only 30 patients had monotherapy from the beginning, with either carbamazepine or valproate. Rest were treated from the beginning with 2 antiepileptic drugs (phenobarbital + carbamazepine or pheytoin + phenobarbital). Adverse effects were recorded in 21 patients. I. It is crucial to distingiush unprovoked and provoked seizures during diagnostic procedures, as well as epileptic and non-epileptic attacks; 2. Principle of monotherapy is conditio sine qua non, and in treatment attention should be paid to co-morbidity, multitherapy, drug interactions, intoxication, diminished detoxication and elimination of drugs, as well as increased

CT scan findings and EEG in systemic lupus erythematodes patients with neuro-psychiatric disorders

Energy Technology Data Exchange (ETDEWEB)

Kan, Rumiko; Hagiwara, Mariko; Katayose, Keiko; Yashima, Yuko; Kumashiro, Hisashi

1988-06-01

In 14 patients with systemic lupus erythematodes presenting with neuro-psychiatric disorders, CT scans were compared with encephalographic (EEG) findings. CT findings were markedly abnormal in 6, slight with a sulcal enlargement in 3, and normal in 5. In the group of markedly abnormal CT findings, focal abnormal low density areas were detected in 2, severe generalized cerebral atrophy in one, and severe atrophy of the right hemisphere in one. EEG findings included focal paroxysmal abnormality of high voltage slow burst at the left frontal dominance and positive spike on the right hemisphere. Epileptic seizure and depressed sensorium seemed to be related to CT abnormality. In 3 patients with epileptic seizures, their symptoms were closely related to CT abnormality. Parkinsonisms and depressed sensorium were also related to CT abnormality. (Namekawa, K).

CT scan findings and EEG in systemic lupus erythematodes patients with neuro-psychiatric disorders

International Nuclear Information System (INIS)

Kan, Rumiko; Hagiwara, Mariko; Katayose, Keiko; Yashima, Yuko; Kumashiro, Hisashi

1988-01-01