scholarly journals CLINICAL AND EEG PREDICTORS OF INCREASED FREQUENCY OF GENERALIZED SEIZURES IN GESTATIONAL AND POSTGRAVIDARUM PERIOD

2013 ◽  
Vol 12 (5) ◽  
pp. 24-30
Author(s):  
O. V. Grebenyuk ◽  
M. V. Svetlik ◽  
V. M. Alifiriva ◽  
I. D. Yevtushenko ◽  
Yu. A. Bochkov ◽  
...  
Keyword(s):  
Idiopathic Generalized Epilepsy ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Generalized Seizures ◽  
Generalized Epilepsy

We investigated the predictors of increased seizures’ frequency among women with various forms of idiopathic generalized epilepsies (IGE) in the gestational and postgravid period. We observed 41 patients with Idiopathic generalized epilepsy (IGE) before, during and after pregnancy. During the period of observation EEG was recorded in the states of relaxed and active awakeness and sleeping. Patients, who have stopped to take anticonvulsants before pregnancy, have had increased frequency of seizures, more than1 ina year, with interictal epileptiform discharges in a state of relaxed and active awakeness. Increased seizures after pregnancy was observed in patients with interictal epileptiform discharges during sleep. The results can be used during the preparation of pregravid women with IGE. 

Focal interictal epileptiform discharges in idiopathic generalized epilepsy

2016 ◽  
Vol 37 (7) ◽  
pp. 1071-1077 ◽  
Author(s):  
Eman H. Esmail ◽  
Amani M. Nawito ◽  
Dalia M. Labib ◽  
Mye A. Basheer
Keyword(s):  
Idiopathic Generalized Epilepsy ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Generalized Epilepsy

scholarly journals Automated Inter-Ictal Epileptiform Discharge Detection from Routine EEG

2021 ◽  
Author(s):  
Duong Nhu ◽  
Mubeen Janmohamed ◽  
Lubna Shakhatreh ◽  
Ofer Gonen ◽  
Patrick Kwan ◽  
...  
Keyword(s):  
Royal Melbourne Hospital ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Model Variant ◽  
Eeg Recordings ◽  
Generalized Epilepsy ◽  
Electroencephalogram Eeg ◽  
Health Hospital ◽  
Epilepsy Monitoring

Epilepsy is the most common neurological disorder. The diagnosis commonly requires manual visual electroencephalogram (EEG) analysis which is time-consuming. Deep learning has shown promising performance in detecting interictal epileptiform discharges (IED) and may improve the quality of epilepsy monitoring. However, most of the datasets in the literature are small (n≤100) and collected from single clinical centre, limiting the generalization across different devices and settings. To better automate IED detection, we cross-evaluated a Resnet architecture on 2 sets of routine EEG recordings from patients with idiopathic generalized epilepsy collected at the Alfred Health Hospital and Royal Melbourne Hospital (RMH). We split these EEG recordings into 2s windows with or without IED and evaluated different model variants in terms of how well they classified these windows. The results from our experiment showed that the architecture generalized well across different datasets with an AUC score of 0.894 (95% CI, 0.881–0.907) when trained on Alfred’s dataset and tested on RMH’s dataset, and 0.857 (95% CI, 0.847–0.867) vice versa. In addition, we compared our best model variant with Persyst and observed that the model was comparable.

scholarly journals Interictal Activity Is Associated With Slower Binocular Rivalry in Idiopathic Generalized Epilepsy

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiaonan Wu ◽  
Wei Ding ◽  
Xing Ye ◽  
Qiang Wei ◽  
Xinyi Lv ◽  
...  
Keyword(s):  
Standard Error ◽  
Cognitive Assessment ◽  
Characteristic Curve ◽  
Montreal Cognitive Assessment ◽  
Alternation Rate ◽  
Assessment Score ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Perceptual Alternation ◽  
Generalized Epilepsy

Objective: Perceptual alternations evoked by binocular rivalry (BR) reflect cortical dynamics strongly dependent on the excitatory–inhibitory balance, suggesting potential utility as a biomarker for epileptogenesis. Therefore, we investigated the characteristics of BR in patients with idiopathic generalized epilepsy (IGE) and potential associations with clinical variables.Methods: Sixty-two healthy controls (HCs) and 94 IGE patients completed BR task. Perceptual alternation rates were compared between HC and IGE groups as well as among the HC group and IGE patients stratified according to the presence or absence of interictal activity on the ambulatory electroencephalogram (EEG), termed the abnormal ambulatory EEG group (AB-AEEG, n = 64) and normal ambulatory EEG group (N-AEEG, n = 30), respectively.Results: The IGE patients demonstrated a slower rate of BR perceptual alternation than HC subjects (t = −4.364, p < 0.001). The alternation rate also differed among the HC, AB-AEEG, and N-AEEG groups (F = 44.962, df = 2, p < 0.001), and post hoc comparisons indicated a significantly slower alternation rate in the AB-AEEG group compared with the N-AEEG and HC groups (0.28 vs. 0.46, and 0.43 Hz). Stepwise linear regression revealed positive correlations between the BR alternation rate and both the ambulatory EEG status (β, 0.173; standard error, 0.022 p < 0.001) and Montreal Cognitive Assessment score (β, 0.013; standard error, 0.004; p = 0.003). Receiver operating characteristic curve analysis of the BR alternation rate distinguished AB-AEEG from N-AEEG subjects with 90.00% sensitivity and 76.90% specificity (area under the curve = 0.881; 95% confidence interval = 0.801– 0.961, cut-off = 0.319). Alternatively, Montreal Cognitive Assessment score did not accurately distinguish AB-AEEG from N-AEEG subjects and the area under the receiver operating characteristic curve combining the BR alternation rate and Montreal Cognitive Assessment score was not markedly larger than that of the BR alternation rate alone (0.894, 95% confidence interval = 0.822–0.966, p < 0.001). K-fold cross-validation was used to evaluate the predictive performance of BR alternation rate, MoCA score, and the combination of both, which yielded average AUC values of 0.870, 0.584 and 0.847, average sensitivity values of 89.36, 92.73, and 91.28%, and average specificity values of 62.25, 13.42, and 61.78%, respectively. The number of interictal epileptiform discharges was significantly correlated with the alternation rate in IGE patients (r = 0.296, p = 0.018). A forward stepwise linear regression model identified the number of interictal epileptiform discharges (β, 0.001; standard error, 0.001; p = 0.025) as an independent factor associated with BR alternation rate in these patients.Conclusion: These results suggest that interictal epileptiform discharges are associated with disruptions in perceptual awareness, and that the BR may be a useful auxiliary behavioral task to diagnosis and dynamically monitor IGE patients with interictal discharge.

The Role of Thalamus Versus Cortex in Epilepsy: Evidence from Human Ictal Centromedian Recordings in Patients Assessed for Deep Brain Stimulation

2017 ◽  
Vol 27 (07) ◽  
pp. 1750010 ◽  
Author(s):  
David Martín-López ◽  
Diego Jiménez-Jiménez ◽  
Lidia Cabañés-Martínez ◽  
Richard P. Selway ◽  
Antonio Valentín ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Seizure Onset ◽  
Epileptiform Discharges ◽  
Generalized Seizures ◽  
Centromedian Nucleus ◽  
Interictal Discharges ◽  
Generalized Epilepsy ◽  
Deep Brain

Background: The onset of generalized seizures is a long debated subject in epilepsy. The relative roles of cortex and thalamus in initiating and maintaining the different seizure types are unclear. Objective: The purpose of the study is to estimate whether the cortex or the centromedian thalamic nucleus is leading in initiating and maintaining seizures in humans. Methods: We report human ictal recordings with simultaneous thalamic and cortical electrodes from three patients without anesthesia being assessed for deep brain stimulation (DBS). Patients 1 and 2 had idiopathic generalized epilepsy whereas patient 3 had frontal lobe epilepsy. Visual inspection was combined with nonlinear correlation analysis. Results: In patient 1, seizure onset was bilateral cortical and the belated onset of leading thalamic discharges was associated with an increase in rhythmicity of discharges, both in thalamus and cortex. In patient 2, we observed bilateral independent interictal discharges restricted to the thalamus. However, ictal onset was diffuse, with discharges larger in the cortex even though they were led by the thalamus. In patient 3, seizure onset was largely restricted to frontal structures, with belated lagging thalamic involvement. Conclusion: In human generalized seizures, the thalamus may become involved early or late in the seizure but, once it becomes involved, it leads the cortex. In contrast, in human frontal seizures the thalamus gets involved late in the seizure and, once it becomes involved, it lags behind the cortex. In addition, the centromedian nucleus of the thalamus is capable of autonomous epileptogenesis as suggested by the presence of independent focal unilateral epileptiform discharges restricted to thalamic structures. The thalamus may also be responsible for maintaining the rhythmicity of ictal discharges.

scholarly journals Automatic Identification of Interictal Epileptiform Discharges in Secondary Generalized Epilepsy

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Won-Du Chang ◽  
Ho-Seung Cha ◽  
Chany Lee ◽  
Hoon-Chul Kang ◽  
Chang-Hwan Im
Keyword(s):  
Automatic Identification ◽  
Sharp Waves ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Detection And Identification ◽  
Characteristic Signal ◽  
Generalized Epilepsy ◽  
Scalp Electroencephalogram ◽  
Patients With Epilepsy ◽  
Epileptogenic Foci

Ictal epileptiform discharges (EDs) are characteristic signal patterns of scalp electroencephalogram (EEG) or intracranial EEG (iEEG) recorded from patients with epilepsy, which assist with the diagnosis and characterization of various types of epilepsy. The EEG signal, however, is often recorded from patients with epilepsy for a long period of time, and thus detection and identification of EDs have been a burden on medical doctors. This paper proposes a new method for automatic identification of two types of EDs, repeated sharp-waves (sharps), and runs of sharp-and-slow-waves (SSWs), which helps to pinpoint epileptogenic foci in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS). In the experiments with iEEG data acquired from a patient with LGS, our proposed method detected EDs with an accuracy of 93.76% and classified three different signal patterns with a mean classification accuracy of 87.69%, which was significantly higher than that of a conventional wavelet-based method. Our study shows that it is possible to successfully detect and discriminate sharps and SSWs from background EEG activity using our proposed method.

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