An approach to detect and predict epileptic seizures with high accuracy using convolutional neural networks and single-lead-ECG signal

One of the epileptic patients' challenges is to detect the time of seizures and the possibility of predicting. This research aims to provide an algorithm based on deep learning to detect and predict the time of seizure from one to two minutes before its occurrence. The proposed Convolutional Neural Network (CNN) can detect and predict the occurrence of focal epilepsy seizures through single-lead-ECG signal processing instead of using EEG signals. The structure of the proposed CNN for seizure detection and prediction is the same. Considering the requirements of a wearable system, after a few light pre-processing steps, the ECG signal can be used as input to the neural network without any manual feature extraction step. The desired neural network learns purposeful features according to the labelled ECG signals and then performs the classification of these signals. Training of 39-layer CNN for seizure detection and prediction has been done separately. The proposed method can detect seizures with an accuracy of 98.84% and predict them with an accuracy of 94.29%. With this approach, the ECG signal can be a promising indicator for the construction of portable systems for monitoring the status of epileptic patients.

Corrigendum: Case report: Abruptio placentae and epileptic seizure after occurrence of perinatal hyperglycaemia in woman with gestational diabetes mellitus and hypertriglyceridemia-induced acute pancreatitis

[This corrects the article DOI: 10.3389/fendo.2023.1220957.].

A novel finite spectral entropy: Gated term memory unit recursive network integrated with Ladybug Beetle Optimization algorithm for epileptic seizure detection

Professional medical experts use a visual electroencephalography (EEG) signal for epileptic seizure detection, although this method is time-consuming and highly subject to bias. The majority of previous epileptic detection techniques have poor efficiency, detection performance and also which are unsuited to handle large datasets. In order to solve the aforementioned issues and to assist medical professionals with an advanced technology, a computerized epileptic seizure detection system is essential. Therefore, the proposed work intends to design an automated detection tool for predicting an epileptic seizure from EEG signals. For this purpose, a novel non-linear feature analysis and deep learning algorithms are deployed in this work. Initially, the signal decomposition, filtering and artifacts removal operations are carried out with the use of finite Haar wavelet transformation technique. After that, the finite spectral entropy (FSE) based feature extraction model has been used to extract the time, frequency, and time-frequency features from the normalized signal. Consequently, the novel gated term memory unit recursive network (GTRN) model is employed to predict the given EEG signal as whether healthy or seizure affected including the class with high accuracy. During this process, the recently developed Ladybug Beetle Optimization (LBO) algorithm is used to compute the logistic sigmoid function based on the solution. The purpose of using this algorithm is to simplify the process of classification with increased seizure prediction accuracy and performance. Moreover, the standard and popular benchmark EEG datasets are used to validate and test the results of the proposed FSE-GTRN-LBO mechanism. By leveraging the finite Haar wavelet transformation and FSE-based feature extraction, we can efficiently process EEG signals. The utilization of the GTRN model enables accurate classification of healthy and seizure-affected EEG data. To optimize the classification process further, we integrate the LBO algorithm, streamlining the computation of the logistic sigmoid function. Through comprehensive validation on standard EEG datasets, our proposed FSE-GTRN-LBO mechanism achieves outstanding seizure prediction accuracy and performance, surpassing existing state-of-the-art techniques.

Case Report: Abruptio placentae and epileptic seizure after occurrence of perinatal hyperglycaemia in woman with gestational diabetes mellitus and hypertriglyceridemia-induced acute pancreatitis

Hypertriglyceridemia-induced acute pancreatitis seldom occurs in the second trimester of pregnancy with gestational diabetes mellitus. For these patients, the existing knowledge on concomitant hyperglycemia is not sufficient. We report a case of abruptio placentae and epileptic seizure following perinatal hyperglycaemia in woman with gestational diabetes mellitus and hypertriglyceridemia-induced acute pancreatitis. The occurrence of abruptio placentae and epileptic seizure may be associated with concomitant hyperglycemia, and the epileptic seizure was terminated after she underwent treatment with insulin. We should pay more attention to the adverse effects of perinatal hyperglycemia and continue to give appropriate insulin treatment even if patients have passed the acute phase of hypertriglyceridemia-induced acute pancreatitis.

Remarkable anecdotes illustrating the nature and effect of seizure-precipitating factors in Border Collies with idiopathic epilepsy

Epilepsy is one of the most common chronic neurological syndromes in dogs and has serious implications for the quality of life of both the dogs and owners. Seizure-precipitating factors (SPFs) (also termed "triggers" or "provocative factors") have been studied and reported in both humans and dogs with idiopathic epilepsy. In dogs stress, hormones, sleep deprivation, and the weather have been reported as SPFs. The Border Collie (BC) is a breed of dog that is predisposed to idiopathic epilepsy, and the outcome is often poor. BC is described as a very sensitive dog with a strong focus on their owners, and this may have an influence on their and their owners' stress level. In this article, we described six unrelated BCs with idiopathic epilepsy in which several remarkable SPFs were identified, and avoiding them improved the outcome of these dogs. The possible SPFs were different for each dog. The SPFs were, among others, the other dog in the family, the lack of intellectual challenge, the presence of an autistic child, a busy street, the relation with the owner, and throwing a ball at the beach. These cases illustrate that recognizing the SPF(s) and taking measures with regard to management can lead to a reduction in epileptic seizure frequency or even achieving seizure freedom.

Automatic Detection and Classification of Epileptic Seizures from EEG Data: Finding Optimal Acquisition Settings and Testing Interpretable Machine Learning Approach

Deep learning (DL) is emerging as a successful technique for automatic detection and differentiation of spontaneous seizures that may otherwise be missed or misclassified. Herein, we propose a system architecture based on top-performing DL models for binary and multigroup classifications with the non-overlapping window technique, which we tested on the TUSZ dataset. The system accurately detects seizure episodes (87.7% Sn, 91.16% Sp) and carefully distinguishes eight seizure types (95-100% Acc). An increase in EEG sampling rate from 50 to 250 Hz boosted model performance: the precision of seizure detection rose by 5%, and seizure differentiation by 7%. A low sampling rate is a reasonable solution for training reliable models with EEG data. Decreasing the number of EEG electrodes from 21 to 8 did not affect seizure detection but worsened seizure differentiation significantly: 98.24 ± 0.17 vs. 85.14 ± 3.14% recall. In detecting epileptic episodes, all electrodes provided equally informative input, but in seizure differentiation, their informative value varied. We improved model explainability with interpretable ML. Activation maximization highlighted the presence of EEG patterns specific to eight seizure types. Cortical projection of epileptic sources depicted differences between generalized and focal seizures. Interpretable ML techniques confirmed that our system recognizes biologically meaningful features as indicators of epileptic activity in EEG.

Stereo-Electroencephalography-Recorded Interictal Epileptiform Discharges: Activation Pattern and Its Relationship With Surgical Outcome

Background Patients with drug-resistant epilepsy commonly undergo stereo-electroencephalography (SEEG) intracranial monitoring for surgical evaluation. Our current practice of defining the epileptogenic zone relies heavily on recognizing the seizure onset zone (SOZ), but the clinical significance of interictal epileptiform discharges (IEDs) is not well established. Methodology We retrospectively identified adult patients who underwent SEEG between January 2019 and May 2022. To study IED activation patterns, we classified IEDs as leading spikes (involved within the SOZ) and distant spikes (outside the SOZ). We calculated each patient's total number of brain subregions generating distant spikes. We correlated them with epilepsy type, duration, and surgical outcome (Engel I: good outcome and Engel II-IV: poor outcome). Results A total of 22 patients were identified during the study period, and 16 underwent surgical intervention (ablation or resection) with one-year post-surgery follow-up. The most common IED morphology was a single spike or sharp followed by periodic spikes or sharps. We found that 87% (n = 19/22) of leading spikes were activated during the first 24 hours of SEEG monitoring, whereas no activation pattern was observed for distant spikes. We found that a higher number of subregions generating distant spikes were associated with poor surgical outcomes (p = 0.002). However, we did not find any significant association between the number of subregions generating distant spikes with epilepsy duration (p = 0.67), temporal or extratemporal-onset epilepsy (p = 0.58), or the presence of an MRI lesion (p = 0.62). Conclusions IEDs involved within the SOZ were found to be activated during the first 24 hours of SEEG monitoring, which could aid in recognizing the pathological spikes and targeted mapping of the irritative zone. We also observed that a higher number of brain subregions generating IEDs outside the SOZ were associated with poor surgical outcomes, but this observation needs to be further studied with larger sample size prospective studies.

Investigation of the presence of specific neural antibodies in dogs with epilepsy or dyskinesia using murine and human assays

BACKGROUND

Autoimmune mechanisms represent a novel category for causes of seizures and epilepsies in humans, and LGI1-antibody associated limbic encephalitis occurs in cats.

HYPOTHESIS/OBJECTIVES

To investigate the presence of neural antibodies in dogs with epilepsy or dyskinesia of unknown cause using human and murine assays modified for use in dogs.

ANIMALS

Fifty-eight dogs with epilepsy of unknown cause or suspected dyskinesia and 57 control dogs.

METHODS

Serum and CSF samples were collected prospectively as part of the diagnostic work-up. Clinical data including onset and seizure/episode type were retrieved from the medical records. Screening for neural antibodies was done with cell-based assays transfected with human genes for typical autoimmune encephalitis antigens and tissue-based immunofluorescence assays on mouse hippocampus slices in serum and CSF samples from affected dogs and controls. The commercial human und murine assays were modified with canine-specific secondary antibody. Positive controls were from human samples.

RESULTS

The commercial assays used in this study did not provide unequivocal evidence for presence of neural antibodies in dogs including one dog with histopathologically proven limbic encephalitis. Low titer IgLON5 antibodies were present in serum from one dog from the epilepsy/dyskinesia group and in one dog from the control group.

CONCLUSION AND CLINICAL IMPORTANCE

Specific neural antibodies were not detected using mouse and human target antigens in dogs with epilepsy and dyskinesia of unknown origin. These findings emphasize the need for canine-specific assays and the importance of control groups.

Effective Early Detection of Epileptic Seizures through EEG Signals Using Classification Algorithms Based on t-Distributed Stochastic Neighbor Embedding and K-Means

Epilepsy is a neurological disorder in the activity of brain cells that leads to seizures. An electroencephalogram (EEG) can detect seizures as it contains physiological information of the neural activity of the brain. However, visual examination of EEG by experts is time consuming, and their diagnoses may even contradict each other. Thus, an automated computer-aided diagnosis for EEG diagnostics is necessary. Therefore, this paper proposes an effective approach for the early detection of epilepsy. The proposed approach involves the extraction of important features and classification. First, signal components are decomposed to extract the features via the discrete wavelet transform (DWT) method. Principal component analysis (PCA) and the t-distributed stochastic neighbor embedding (t-SNE) algorithm were applied to reduce the dimensions and focus on the most important features. Subsequently, K-means clustering + PCA and K-means clustering + t-SNE were used to divide the dataset into subgroups to reduce the dimensions and focus on the most important representative features of epilepsy. The features extracted from these steps were fed to extreme gradient boosting, K-nearest neighbors (K-NN), decision tree (DT), random forest (RF) and multilayer perceptron (MLP) classifiers. The experimental results demonstrated that the proposed approach provides superior results to those of existing studies. During the testing phase, the RF classifier with DWT and PCA achieved an accuracy of 97.96%, precision of 99.1%, recall of 94.41% and F1 score of 97.41%. Moreover, the RF classifier with DWT and t-SNE attained an accuracy of 98.09%, precision of 99.1%, recall of 93.9% and F1 score of 96.21%. In comparison, the MLP classifier with PCA + K-means reached an accuracy of 98.98%, precision of 99.16%, recall of 95.69% and F1 score of 97.4%.

Active fault tolerant deep brain stimulator for epilepsy using deep neural network

Millions of people around the world are affected by different kinds of epileptic seizures. A deep brain stimulator is now claimed to be one of the most promising tools to control severe epileptic seizures. The present study proposes Hodgkin-Huxley (HH) model-based Active Fault Tolerant Deep Brain Stimulator (AFTDBS) for brain neurons to suppress epileptic seizures against ion channel conductance variations using a Deep Neural Network (DNN). The AFTDBS contains the following three modules: (i) Detection of epileptic seizures using black box classifiers such as Support Vector Machine (SVM) and K-Nearest Neighbor (KNN), (ii) Prediction of ion channels conductance variations using Long Short-Term Memory (LSTM), and (iii) Development of Reconfigurable Deep Brain Stimulator (RDBS) to control epileptic spikes using Proportional Integral (PI) Controller and Model Predictive Controller (MPC). Initially, the synthetic data were collected from the HH model by varying ion channel conductance. Then, the seizure was classified into four groups namely, normal and epileptic due to variations in sodium ion-channel conductance, potassium ion-channel conductance, and both sodium and potassium ion-channel conductance. In the present work, current controlled deep brain stimulators were designed for epileptic suppression. Finally, the closed-loop performances and stability of the proposed control schemes were analyzed. The simulation results demonstrated the efficacy of the proposed DNN-based AFTDBS.

A case of castration-resistant metastatic prostate cancer who continued treatment with enzalutamide after epileptic seizure

INTRODUCTION

Enzalutamide is an androgen receptor inhibitor and is used in metastatic castration-resistant prostate cancer. Seizure is a rare side effect of enzalutamide. In this case, the patient had an epileptic seizure while on enzalutamide treatment. His treatment management and and use of enzalutamide afterwards is discussed.

CASE REPORT

A 78-year-old male patient who received previous treatments for metastatic castration-resistant prostate cancer was started on enzalutamide due to progression, and had an epileptic seizure while taking enzalutamide was presented. Different pathologies such as the use of other drugs, brain metastasis, bleeding, electrolyte, liver and kidney disorders that can cause epileptic seizures were explored and not found to be the cause in this patient. No neurological pathology was found in the patient after the seizure.

MANAGEMENT AND OUTCOME

Enzalutamide and antiepileptic treatment were initiated simultaneously again in the patient whose treatment was interrupted after the seizure and no pathology was found in the brain magnetic resonance imaging. Under this dual treatment, the patient did not have seizures again.

DISCUSSION

Although observed rarely, enzalutamide-induced epileptic seizure is a known side effect. However, a review of literature did not reveal any report on patients for whom enzalutamide and antiepileptic treatment were initiated and followed up simultaneously after seizures. This case report will contribute to the literature for patients whose treatment options have been exhausted and who may benefit significantly from continued use of enzalutamide despite having a seizure.

Bow Hunter's syndrome with clicking sounds: A rare etiology of transient loss of consciousness with tonic-clonic seizure

We present the case of a young male patient experiencing a transient loss of consciousness and manifesting a seizure when he tilted his head backward. Transcranial Doppler ultrasound (TCD) and carotid artery ultrasound (CAU) examination were normal when the patient's neck was in the neutral position. However, the CAU revealed vertebral artery (VA) transient occlusion during neck rotation or backward movement. Electroencephalogram (EEG) monitoring was performed with multiple neck rotation-induced tests. The patient developed dizziness, which was the same as the prodromal symptoms of the first seizure, and the EEG showed a large number of spinal slow waves and sharp slow waves in the frontal-to-frontal midline area, with an occasional generalization trend. CT angiography revealed occipitalization of the atlas and the lack of contrast agent filling in the local area of the VA when the patient's head was turned contralaterally. Thus, the patient was diagnosed with Bow Hunter's syndrome (BHS) and treated conservatively with neck immobilization. No recurrence occurred at 3 and 6 months of follow-up. Therefore, this case alerts neurologists to suspect BHS on observing seizure manifestations during neck rotation, and CAU may be a recommended dynamic screening method for BHS. This report is accompanied by a discussion of the phenomenon and diagnosis in the context of the existing literature.

Clptm1, a new target in suppressing epileptic seizure by regulating GABAA R-mediated inhibitory synaptic transmission in a PTZ-induced epilepsy model

Disruption of gamma-amino butyric acid type A receptors (GABAA Rs) synaptic clustering and a decrease in the number of GABAA Rs in the plasma membrane are thought to contribute to alteration of the balance between excitatory and inhibitory neurotransmission, which promotes seizure induction and propagation. The multipass transmembrane protein cleft lip and palate transmembrane protein 1 (Clptm1) controls the forward trafficking of GABAA R, thus decaying miniature inhibitory postsynaptic current (mIPSC) of inhibitory synapses. In this study, using a pentylenetetrazol (PTZ)-induced epilepsy rat model, we found that Clptm1 regulates epileptic seizures by modulating GABAA R-mediated inhibitory synaptic transmission. First, we showed that Clptm1 expression was elevated in the PTZ-induced epileptic rats. Subsequently, we found that downregulation of Clptm1 expression protected against PTZ-induced seizures, which was attributed to an increase in the number of GABAA Rγ2s in the plasma membrane and the amplitude of mIPSC. Taken together, our findings identify a new anti-seizure target that provides a theoretical basis for the development of novel strategies for the prevention and treatment of epilepsy.

Corrigendum: Phenotypic characterization of idiopathic epilepsy and epilepsy of unknown cause in Irish Setters

[This corrects the article DOI: 10.3389/fvets.2022.1066094.].

[Bilateral central femoral dislocation after seizure. Antiprotrusive ring and dual mobility cup as a therapeutic option. Apropos of a case]

INTRODUCTION

seizures can trigger fractures and dislocations. Injuries depend on the severity, duration and type of seizure. We present a case report of a male patient who presented with a bilateral central dislocation fracture of the hip following an episode of seizure. A case rarely described in the literature with complex and unusual management.

CASE REPORT

a 77-year-old man with a history of moderate cognitive impairment suffered a bilateral central dislocation of the hip in the context of a generalized epileptic seizure. Clinically on arrival at the emergency department, the patient presented shortening of the right lower extremity compared to the contralateral, external rotation and joint locking on log roll test in both extremities. An imaging study and clinical optimization were performed prior to surgery. It was performed in two stages. First the left hip on the 8th day of admission, and the right hip on the 15th. In both surgeries the same procedure was performed, with implantation of an antiprotrusive ring and a double mobility cup prosthesis with an uncemented femoral stem. In the immediate postoperative period, the patient did not present any complications associated with the surgery. At 24-month follow-up, the patient performed full weight bearing with a Harris hip score (HHS) of 77 on the right hip and 79 on the left; 12 points on the WOMAC scale. No postoperative complications have occurred so far.

CONCLUSIONS

these injuries are uncommon in our daily practice, where multiple options are available to address them. In our patient, the use of arthroplasty and antiprotrusive rings offers advantages over fracture synthesis techniques, such as early mobilization with moderate functional results and few postoperative complications.

Prognostic impact of epileptic seizures in multiple sclerosis varies according to time of occurrence and etiology

BACKGROUND AND PURPOSE

Epileptic seizures occur more often in patients with multiple sclerosis (MS) than in the general population. Their association with the prognosis of MS remains unclear. This study was undertaken to evaluate whether epileptic seizures may be a prognostic marker of MS disability, according to when the seizure occurs and its cause.

METHODS

Data were extracted from a population-based registry of MS in Lorraine, France. Kaplan-Meier curves and log-rank tests were used to compare the probability of different levels of irreversible handicap during the course of MS in patients who experience epileptic seizures or do not, according to the chronology and the cause of the first epileptic seizure.

RESULTS

Among 6238 patients, 134 had experienced at least one epileptic seizure (2.1%), and 82 (1.2%) had seizures secondary to MS. Patients with epileptic seizure as a first symptom of MS (14 patients) had the same disease progression as other relapsing-remitting MS patients. Patients who developed epileptic seizures during the course of MS (68 patients) had a higher probability of reaching Expanded Disability Status Scale = 3.0 (p = 0.006), 6.0 (p = 0.003), and 7.0 (p = 0.004) than patients without an epileptic background. Patients with a history of epileptic seizures unrelated to MS also had a worse prognosis than patients without an epileptic background.

CONCLUSIONS

Epileptic seizures might be viewed as a "classic MS relapse" in terms of prognosis if occurring early in MS, or as a marker of MS severity if developing during the disease. Epileptic diseases other than MS may worsen the course of MS.

RNN and BiLSTM Fusion for Accurate Automatic Epileptic Seizure Diagnosis Using EEG Signals

Epilepsy is a common neurological condition. The effects of epilepsy are not restricted to seizures alone. They comprise a wide spectrum of problems that might impair and reduce quality of life. Even with medication, 30% of epilepsy patients still have recurring seizures. An epileptic seizure is caused by significant neuronal electrical activity, which affects brain activity. EEG shows these changes as high-amplitude spiky and sluggish waves. Recognizing seizures on an electroencephalogram (EEG) manually by a professional neurologist is a time-consuming and labor-intensive process, hence an efficient automated approach is necessary for the identification of epileptic seizure. One technique to increase the speed and accuracy with which a diagnosis of epileptic seizures could be made is by utilizing computer-aided diagnosis systems that are built on deep neural networks, or DNN. This study introduces a fusion of recurrent neural networks (RNNs) and bi-directional long short-term memories (BiLSTMs) for automatic epileptic seizure identification via EEG signal processing in order to tackle the aforementioned informational challenges. An electroencephalogram's (EEG) raw data were first normalized after undergoing pre-processing. A RNN model was fed the normalized EEG sequence data and trained to accurately extract features from the data. Afterwards, the features were passed to the BiLSTM layers for processing so that further temporal information could be retrieved. In addition, the proposed RNN-BiLSTM model was tested in an experimental setting using the freely accessible UCI epileptic seizure dataset. Experimental findings of the suggested model have achieved avg values of 98.90%, 98.50%, 98. 20%, and 98.60%, respectively, for accuracy, sensitivity, precision, and specificity. To further verify the new model's efficacy, it is compared to other models, such as the RNN-LSTM and the RNN-GRU learning models, and is shown to have improved the same metrics by 1.8%, 1.69%, 1.95%, and 2.2% on using 5-fold. Additionally, the proposed method was compared to state-of-the-art approaches and proved to be a more accurate categorization of such techniques.

Intercorrelation of physiological seizure parameters and hormonal changes in electroconvulsive therapy

OBJECTIVE

Physiological parameters that predict electroconvulsive therapy (ECT) effectiveness may reflect propagation of the induced epileptic seizure. As an indication of seizure propagation to the diencephalon, we here examined the correlation between prolactin increase after ECT and clinical seizure evaluation parameters, focusing on peak heart rate. As a proxy for peripheral endocrine stress response, we examined the correlation to postictal cortisol increase.

METHODS

Participants were consecutively recruited from clinical ECT patients (n = 131, age 18-85 years). The first ECT session in a series was examined. For each participant, blood serum concentrations of prolactin and cortisol were measured immediately before and within 30 min after the seizure. Physiological parameters were extracted from clinical records: peak heart rate (HR) during seizure, electroencephalography (EEG) seizure duration, and motor seizure duration. Correlations were calculated using non-parametric tests.

RESULTS

Serum prolactin increased after ECT and correlated with peak HR, EEG seizure duration, and motor seizure duration. Peak HR during seizure also correlated positively with both EEG seizure duration and motor seizure duration. Correlations were unaffected by age, sex, baseline prolactin levels, antipsychotics, or beta-blocking agents. Serum cortisol increased after ECT but did not correlate with the seizure evaluation parameters, nor with prolactin concentrations.

CONCLUSIONS

Our findings of a positive correlation between peak HR and prolactin that was independent from the peripheral endocrine stress response might be in line with the idea that tachycardia during ECT seizures reflects seizure propagation to the diencephalon. This supports the practice of monitoring cardiovascular response for ECT seizure evaluation.

[A case of Creutzfeldt-Jakob disease presenting with nonconvulsive status epilepticus in the early stages]

A 64-year-old Japanese woman presented with 1 week of recurrent convulsive seizures. At the time of admission, she was in a coma and did not present with convulsions. Intravenous diazepam administration improved her consciousness, although severe psychomotor excitement developed. Brain MRI demonstrated diffusion restriction in the cerebral cortex of the right hemisphere. Electroencephalography (EEG) showed periodic discharges centered around the parietal regions with right-sided dominance. Nonconvulsive status epilepticus (NCSE) was suspected, and the patient was actively treated with anti-epileptic drugs. She developed akinetic mutism and generalized myoclonus 1 month after admission. Follow-up EEG studies disclosed periodic synchronous discharges. Abnormal prion protein in the cerebral fluid was detected using a real-time quaking-induced conversion assay. The clinical diagnosis in the present case was sporadic Creutzfeldt-Jakob disease (CJD). Seizures as an initial symptom in patients with CJD are relatively rare. Our case suggests that CJD should be considered as a differential diagnosis when a patient presents with refractory NCSE.

Glymphatic system function in patients with newly diagnosed focal epilepsy

INTRODUCTION

The aim of this study was to analyze the glymphatic system function and its relationship with clinical characteristics, global diffusion tensor imaging (DTI) parameters, and global structural connectivity in treatment-naïve patients with newly diagnosed focal epilepsy.

METHODS

This retrospective single-center study investigated patients with focal epilepsy and healthy controls. All participants underwent routine brain magnetic resonance imaging and DTI. DTI analysis along the perivascular space (DTI-ALPS) was used to evaluate glymphatic system function. We also calculated the measures of global DTI parameters, including whole-brain fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), and performed a graph theoretical network analysis to measure global structural connectivity.

RESULTS

A total of 109 patients with focal epilepsy and 88 healthy controls were analyzed. There were no significant differences in the DTI-ALPS index (1.67 vs. 1.68, p = 0.861) between the groups. However, statistically significant associations were found between the DTI-ALPS index and age (r = -0.242, p = 0.01), FA (r = 0.257, p = 0.007), MD (r = -0.469, p < 0.001), AD (r = -0.303, p = 0.001), RD (r = -0.434, p < 0.001), and the assortative coefficient (r = 0.230, p = 0.016) in patients with focal epilepsy.

CONCLUSION

The main finding of this study is that DTI-ALPS index is significantly correlated with global DTI parameters and structural connectivity measures of the brain in patients with focal epilepsy. In addition, DTI-ALPS index decreases with age in these patients. We conclude that the DTI-ALPS index can be used to investigate glymphatic system function in patients with focal epilepsy.

Management of Epileptic Seizures in Disorders of Consciousness: An International Survey

Epileptic seizures/post-traumatic epilepsy (ES/PTE) are frequent in persons with brain injuries, particularly for patients with more severe injuries including ones that result in disorders of consciousness (DoC). Surprisingly, there are currently no best practice guidelines for assessment or management of ES in persons with DoC. This study aimed to identify clinician attitudes toward epilepsy prophylaxis, diagnosis and treatment in patients with DoC as well as current practice in regards to the use of amantadine in these individuals. A cross-sectional online survey was sent to members of the International Brain Injury Association (IBIA). Fifty physician responses were included in the final analysis. Withdrawal of antiepileptic drug/anti-seizure medications (AED/ASM) therapy was guided by the absence of evidence of clinical seizure whether or not the AED/ASM was given prophylactically or for actual seizure/epilepsy treatment. Standard EEG was the most frequent diagnostic method utilized. The majority of respondents ordered an EEG if there were concerns regarding lack of neurological progress. AED/ASM prescription was reported to be triggered by the first clinically evident seizure with levetiracetam being the AED/ASM of choice. Amantadine was frequently prescribed although less so in patients with epilepsy and/or EEG based epileptic abnormalities. A minority of respondents reported an association between amantadine and seizure. Longitudinal studies on epilepsy management, epilepsy impact on neurologic prognosis, as well as potential drug effects on seizure risk in persons with DoC appear warranted with the goal of pushing guideline development forward and improving clinical assessment and management of seizures in this unique, albeit challenging, population.

Determination of the Initial Abnormal Discharge Site in Temporal Lobe Epilepsy Through Combined EEG and Neuroimaging. What Is Next?

Objective: The objective of this study was to determine the relationship between atrophy of the hippocampus and severity of epilepsy in patients with temporal lobe epilepsy (TLE) as the first step to evaluate the possibility of surgery for epilepsy and analyze why patients cannot undergo epilepsy surgery.

Methods: Volumetric MRI of the hippocampus was performed in 51 consecutive patients (29 men; mean age 40) with TLE. TLE diagnosis, lateralization, and severity (mild, moderate, severe) of seizures were based on a comprehensive evaluation that included neurologic examination and EEG in all patients. Patients with evidence of a lesion other than hippocampal sclerosis were not included in the study. We assessed the relationship between hippocampal volumes and electrophysiological evidence of seizure severity.

Results: According to the affected side based on the EEG, a statistically significant difference (p < 0.001) in volume and a positive correlation between epilepsy and hippocampal atrophy were found.

Conclusion: Our results confirm that volume loss to the hippocampus in patients with TLE correlates with the severity of epilepsy based on the EEG. Therefore, surgical treatment is considered early when hippocampal atrophy is evident in patients with refractory TLE. However, in Latin American countries, it is a challenge to get a patient to undergo epilepsy surgery. Therefore, we try to analyze the sad situation in our hospital.

Phenotypic characterization of idiopathic epilepsy and epilepsy of unknown cause in Irish Setters

Canine epileptic seizures are common neurological symptom presenting to veterinary practice. Idiopathic epilepsy (IE) with a suspected genetic background has been reported in several dog breeds. Although it has been reported in the Irish Setter (IS), the phenotypic characteristics have not yet been described. The aim of this study was to characterize the phenotype of IE in this breed and to trace its mode of inheritance. Owners of IS were requested to fill in a questionnaire via the Dutch Irish Setter Club concerning the epileptic seizures in their dogs. The data was assessed retrospectively using descriptive statistics. Forty-eight privately owned IS dogs fulfilling tier I criteria for IE according to the International Veterinary Epilepsy Task Force of both sexes were included in the study. The mean age of seizure onset was 41 months. Five of the dogs included in the study had an onset of seizures >6 years of age. These dogs were classified with epilepsy of unknown cause (EUC). Primary generalized tonic-clonic seizures were the most common type of seizure and were seen in almost all dogs. Cluster seizures were reported in 54% of the studied population. Most owners reported pre- (56%) and post-ictal (97%) signs in their dogs. A pedigree analysis of one subpopulation was performed and traced the lineage of 13 affected IS. A segregation analysis of this population rejected a simple autosomal recessive inheritance pattern. The present study supports the occurrence of IE and EUC in the IS. The results provide clinical insight into epileptic seizures in this breed and may be a starting point for further, including genetic, analysis.

[Depression in patients with epilepsy: experience in a private hospital in Argentina]

INTRODUCTION

Depression is the most frequent psychiatric disorder in patients with epilepsy, with an estimated prevalence between 35% and 60%, associated with poorer control of epileptic seizures. Despite the high prevalence of depression, many patients are not diagnosed, presenting a worse clinical course and quality of life. There are no prevalence studies in our population. The main objective was to determinate the prevalence of depression in epilepsy and its relationship with seizure control.

MATERIALS AND METHODS

It is a prospective, descriptive and cross-sectional study of a cohort of patients who underwent the Depression Inventory in Patients with Neurological Disorders for Epilepsy (NDDI-E) and the data from the medical records were analyzed.

RESULTS

A total of 121 patients were inluded, and the prevalence of depression was 43% (n:52), of whom 77% were women (p = 0.01). A 63% of patients with depression was diagnosed in this study. Most of them with good seizure control (70%) did not present depression, while the majority of those with poor (57%) and regular (63%) seizure control presented depression (p < 0.001).

DISCUSSION

Comorbidity between depression and epilepsy is highly prevalent, negatively influencing the control of epileptic seizures. Most patients are underdiagnosed. Screening for major depression in patients with epilepsy is necessary, contributing to the clinical improvement.

A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction

OBJECTIVE

Scarcity of good quality electroencephalography (EEG) data is one of the roadblocks for accurate seizure prediction. This work proposes a deep convolutional generative adversarial network (DCGAN) to generate synthetic EEG data. Another objective of our study is to use transfer-learning (TL) for evaluating the performance of four well-known deep-learning (DL) models to predict epileptic seizure.

METHODS

We proposed an algorithm that generate synthetic data using DCGAN trained on real EEG data in a patient-specific manner. We validate quality of generated data using one-class SVM and a new proposal namely convolutional epileptic seizure predictor (CESP). We evaluate performance of VGG16, VGG19, ResNet50, and Inceptionv3 trained on augmented data using TL with average time of 10 min between true prediction and seizure onset samples.

RESULTS

The CESP model achieves sensitivity of 78.11% and 88.21%, and false prediction rate of 0.27/h and 0.14/h for training on synthesized and testing on real Epilepsyecosystem and CHB-MIT datasets, respectively. Using TL and augmented data, Inceptionv3 achieved highest accuracy with sensitivity of 90.03% and 0.03 FPR/h. With the proposed data augmentation method prediction results of CESP model and Inceptionv3 increased by 4-5% as compared to state-of-the-art augmentation techniques.

CONCLUSION

The performance of CESP shows that synthetic data acquired association between features and labels very well and by using the augmented data CESP predicted better than chance level for both datasets.

SIGNIFICANCE

The proposed DCGAN can be used to generate synthetic data to increase the prediction performance and to overcome good quality data scarcity issue.

Comparative structural analysis of human Nav1.1 and Nav1.5 reveals mutational hotspots for sodium channelopathies

Among the nine subtypes of human voltage-gated sodium (Na_v) channels, the brain and cardiac isoforms, Na_v1.1 and Na_v1.5, each carry more than 400 missense mutations respectively associated with epilepsy and cardiac disorders. High-resolution structures are required for structure-function relationship dissection of the disease variants. We report the cryo-EM structures of the full-length human Na_v1.1-β4 complex at 3.3 Å resolution here and the Na_v1.5-E1784K variant in the accompanying paper. Up to 341 and 261 disease-related missense mutations in Na_v1.1 and Na_v1.5, respectively, are resolved. Comparative structural analysis reveals several clusters of disease mutations that are common to both Na_v1.1 and Na_v1.5. Among these, the majority of mutations on the extracellular loops above the pore domain and the supporting segments for the selectivity filter may impair structural integrity, while those on the pore domain and the voltage-sensing domains mostly interfere with electromechanical coupling and fast inactivation. Our systematic structural delineation of these mutations provides important insight into their pathogenic mechanism, which will facilitate the development of precise therapeutic interventions against various sodium channelopathies.

Prognostic Features of Sporadic Creutzfeldt-Jakob Disease: An Analysis of Taiwan's Nationwide Surveillance

OBJECTIVES

To study the prognostic features of Creutzfeldt-Jakob disease (CJD) and shed light on its future therapy.

DESIGN

Retrospective cohort study of a longitudinal national cohort of the Taiwan Centers for Disease Control.

SETTING AND PARTICIPANTS

All patients with suspected CJD are reported to the CJD surveillance unit of the Taiwan Centers for Disease Control. An expert committee discussed the reported cases and designated a consensus-based diagnosis. From 1996 to 2020, a total of 809 cases were referred to the CJD surveillance unit for confirmation; of these, 441 cases (women, n = 230) were determined to be sporadic CJD.

METHODS

We investigated the clinical manifestations and laboratory findings for 400 patients diagnosed with definite or probable sporadic CJD. We used Kaplan-Meier analyses and Cox proportional hazards model to identify prognostic factors.

RESULTS

The mean age of onset was 67 ± 9.9 years. The mean survival duration was 13.3 ± 14.2 (median 10) months. The leading clinical symptoms were myoclonus (73%) and akinetic mutism (54%). For PRNP polymorphism, 99% of patients (195/197) showed a methionine homozygous genotype at codon 129 (M129M). The sensitivity of periodic sharp wave complexes (PSWCs) on electroencephalograms (EEGs) was 59.7%. The sensitivity of cerebrospinal fluid 14-3-3 protein and total tau protein (>1200 pg/mL) were 69.7% and 75.6%, respectively. Younger patients lived longer than those aged ≥65 years [hazard ratio (HR) 0.466, P < .001]. Women had a better survival probability in the first 3 years than their male counterparts (HR 0.712, P = .005). PSWCs had a persistent negative effect on survival (HR 0.788, P < .05). Although uncommon, epileptic seizures were the only clinical prognostic factor for survival time (HR 0.768, P < .05). PSWCs can be used as an EEG biomarker for prognosis. Epileptic seizures, though not common, are the only clinical prognostic factor for a short survival.

CONCLUSIONS AND IMPLICATIONS

We found that a lower age of onset and female gender favor the survival of patients with sCJD. PSWCs are EEG biomarkers unfavorable for survival, and so are epileptic seizures.

Non-Ruptured Temporal Lobe Dermoid Cyst Concomitant with Focal Cortical Dysplasia Causing Temporal Lobe Epilepsy-A Case Report and Literature Review

Background: Intracranial dermoid cyst is a rare, benign, nonneoplastic tumor-like lesion that could cause seizures, headache, and hydrocephalus. We hypothesized that the temporal lobe dermoid cyst in combination with other factors were causing the epileptic seizure. Methods: We encountered a 17-year-old girl with anti-seizure medication-resistant epilepsy secondary to dermoid cyst located in the temporal region depicted on magnetic resonance imaging (MRI). She showed neither symptoms of meningitis nor rupture of the cyst according to serial MRI. We hypothesized that temporal lobe dermoid cyst in combination with other factors, such as focal cortical dysplasia (FCD), etc., was causing epileptic seizures in this case. She underwent dermoid cyst removal surgery with resection of the tip of the antero-inferior temporal lobe. Results: Histopathological study showed multiple small intramedullary dermoid cysts in the left antero-inferior temporal lobe in addition to MRI lesions and FCD. Conclusion: A patient with medically intractable epilepsy secondary to left temporal lobe dermoid cyst showed multiple intramedullary dermoid cysts and focal cortical dysplasia that might have interacted to create epileptogenicity. To our knowledge, this is the first case report of dermoid cyst concomitant with FCD.

Epilepsy in British Shorthair cats in Sweden

OBJECTIVES

The primary objective of this study was to investigate the prevalence of epileptic seizures and of presumed idiopathic epilepsy (PIE, describing epilepsy of unknown origin) in a cohort of British Shorthair (BSH) cats in Sweden. The secondary objective was to describe epileptic seizure characteristics and outcome for cats with PIE.

METHODS

Owners of BSH cats born between 2006 and 2016 and registered with SVERAK (the Swedish Cat Clubs' National Association) were invited to reply to a questionnaire about their cat's general health. Owners who indicated that their cat had experienced epileptic seizures were invited to participate in an in-depth telephone interview about the epileptic seizures. The clinical characteristics of epileptic seizures in BSH cats were determined from the results of the interview.

RESULTS

In this population comprising 1645 BSH cats (representing 28% of registered BSHs), the prevalence of epileptic seizures was 0.9% and for PIE it was 0.7%. BSH cats with PIE presented with infrequent but consistent epileptic seizures. Twenty-seven percent of BSH cats with epileptic seizures had cluster seizures but none presented with status epilepticus. None of the BSH cats was treated with antiepileptic drugs, and none of the owners reported epileptic seizure remission in their cat.

CONCLUSIONS AND RELEVANCE

The prevalence of PIE in this population of BSH cats was 0.7%. The prevalence of epileptic seizures was 0.9%. In general, PIE in the BSH cat displayed a relatively benign phenotype where progression of epileptic seizures was uncommon.

Spontaneous regression of a symptomatic developmental venous anomaly with capillary stain

BACKGROUND

Developmental venous anomalies are considered benign lesions; however, they can become symptomatic. A capillary stain, which is an atypical angiographical feature of developmental venous anomalies, is reported to be relevant to symptomatic developmental venous anomalies.

CASE DESCRIPTION

A 20-year-old man with no pertinent medical history had an epileptic seizure. Magnetic resonance imaging showed severe focal oedema and gadolinium contrast enhancement in the right precentral gyrus and inferior frontal gyrus adjacent to the Sylvian fissure, indicating venous congestion; these presentations had not been observed on magnetic resonance imaging 8 months before. Digital subtraction angiography revealed a developmental venous anomaly with capillary stain. After conservative treatment, the brain oedema resolved spontaneously and contrast enhancement of the lesion reduced significantly.

CONCLUSION

We report a rare case of a symptomatic developmental venous anomaly with unique radiological characteristics and its natural and clinical evolution. Despite the presence of a capillary stain, our patient exhibited temporary exacerbations and spontaneous regression, suggesting that the capillary stain was associated with a reversible condition. This is the first report to detail the spatiotemporal changes of a developmental venous anomaly with capillary stain through imaging, suggesting that regular follow-up imaging is warranted in the management of patients with developmental venous anomalies.

Chinese Herbal Medicine for Treating Epilepsy

Chinese herbal medicine has a long history of use for treating epilepsy. Because of the side effects of Western antiepileptic therapy and the quest for more accessible treatment, complementary and alternative medicines have become popular. Traditional Chinese medical diet therapy appears to be safe and effective. We searched PubMed and the Cochrane Library through November 2020 for the use of traditional Chinese medicine in clinical settings, including plants, fungi, and animals. Combinations of keywords included “epilepsy,” “seizure,” “antiepileptic,” “anticonvulsive,” “Chinese herbal medicine,” “Chinese herb,” and each of the Latin names, English names, and scientific names of herbs. We also summarized the sources and functions of these herbs in Chinese medicine. Different herbs can be combined to increase antiepileptic effects through various mechanisms, including anti-inflammation, antioxidation, GABAergic effect enhancement, modulation of NMDA channels and sodium channel, and neuroprotection. Despite reports of their anticonvulsive effects, adequate experimental evidence and randomized controlled clinical trials are required to confirm their antiepileptic effects.

The Utility of Delta-9-Tetrahydrocannibinol Therapy in a Multiple Sclerosis Patient with a Neoplastic Brain Lesion

Multiple sclerosis (MS) can sometimes cause uncommon pseudotumoural lesions that produce atypical symptoms, such as motor epileptic seizures which are often pharmacoresistant. In these cases, accurate diagnosis is essential for correct therapy, even if unconventional. We present the case of a brain tumour in a 40-year-old relapsing-remitting MS patient who presented with pharmacoresistant seizures which eventually responded to nabiximols. After various therapeutic approaches, delta-9-tetrahydrocannabinol therapy was introduced with good results. Spasticity improved, pain decreased and we observed a reduction in the number of daily seizures. It is possible that delta-9-tetrahydrocannabinol can enhance the efficacy of anti-epilepsy therapy.

LEARNING POINTS

The patient experienced fewer daily focal motor crises after the administration of nabiximols in the morning.The correct combination of symptomatic drugs can optimize a specific multiple sclerosis (MS) therapy even if the real cause of symptoms is a primary brain tumour and not MS.The addition of nabiximols to the therapeutic program allowed anti-epilepsy drug doses to be reduced and improved the patient's cognitive impairment.

Epileptic Seizure after Use of Moxifloxacin in Man with Legionella longbeachae Pneumonia

Legionellosis caused by Legionella longbeachae is diagnosed mainly by PCR. We report a case of L. longbeachae infection in mainland China, which was diagnosed by metagenomic next-generation sequencing, in a man who developed an epileptic seizure after using moxifloxacin. Metagenomic next-generation sequencing may be a useful tool to detect Legionella spp.

The Effect of Anti-seizure Medications on the Propagation of Epileptic Activity: A Review

The propagation of epileptiform events is a highly interesting phenomenon from the pathophysiological point of view, as it involves several mechanisms of recruitment of neural networks. Extensive in vivo and in vitro research has been performed, suggesting that multiple networks as well as cellular candidate mechanisms govern this process, including the co-existence of wave propagation, coupled oscillator dynamics, and more. The clinical importance of seizure propagation stems mainly from the fact that the epileptic manifestations cannot be attributed solely to the activity in the seizure focus itself, but rather to the propagation of epileptic activity to other brain structures. Propagation, especially when causing secondary generalizations, poses a risk to patients due to recurrent falls, traumatic injuries, and poor neurological outcome. Anti-seizure medications (ASMs) affect propagation in diverse ways and with different potencies. Importantly, for drug-resistant patients, targeting seizure propagation may improve the quality of life even without a major reduction in simple focal events. Motivated by the extensive impact of this phenomenon, we sought to review the literature regarding the propagation of epileptic activity and specifically the effect of commonly used ASMs on it. Based on this body of knowledge, we propose a novel classification of ASMs into three main categories: major, minor, and intermediate efficacy in reducing the propagation of epileptiform activity.

A Recent Investigation on Detection and Classification of Epileptic Seizure Techniques Using EEG Signal

The benefits of early detection and classification of epileptic seizures in analysis, monitoring and diagnosis for the realization and actualization of computer-aided devices and recent internet of medical things (IoMT) devices can never be overemphasized. The success of these applications largely depends on the accuracy of the detection and classification techniques employed. Several methods have been investigated, proposed and developed over the years. This paper investigates various seizure detection algorithms and classifications in the last decade, including conventional techniques and recent deep learning algorithms. It also discusses epileptiform detection as one of the steps towards advanced diagnoses of disorders of consciousness (DOCs) and their understanding. A performance comparison was carried out on the different algorithms investigated, and their advantages and disadvantages were explored. From our survey, much attention has recently been paid to exploring the efficacy of deep learning algorithms in seizure detection and classification, which are employed in other areas such as image processing and classification. Hybrid deep learning has also been explored, with CNN-RNN being the most popular.

Case Studies in Neuroscience: Transcranial Doppler assessment of increased cerebral blood flow during iterative seizures

This case study aimed at monitoring ictal vasodilation in a clinical setting to confirm the experimental data on enhanced cerebral perfusion during epileptic seizures. Clinical observation of a patient presenting relapsing seizures in the intensive care unit. Transcranial Doppler (TCD) was used to monitor both blood velocities and the arterial caliber in the B-flow mode as a proxy of blood flow of the middle cerebral artery (MCA). A 35-yr-old woman experienced partial epileptic seizures lasting for 1 min that recurred every 5 min. Seizures were monitored with continuous EEG and TCD. During the seizure, the MCA caliber increased whereas velocities remained stable, which doubled the MCA blood flow. Immediately after the seizure, the artery caliber returned to its initial value, and the velocities increased by one-third of the initial value. After intensification of antiepileptic treatment, clinical seizures ceased, and TCD findings returned to normal MCA caliber and velocities. Autoimmune encephalitis was identified by brain biopsy and the patient recovered with corticosteroids treatment. This is the first description of ictal vasodilatation assessed by TCD. Our current understanding holds that cerebral blood flow increases during a seizure, but our report demonstrates that arterial dilation preceded the acceleration of velocities. This case study in a clinical setting confirms the impact of seizures on cerebral blood flow. NEW & NOTEWORTHY The case study is a clinical demonstration of ictal vasodilation. By assessing arterial caliber and blood velocities with transcranial Doppler, we dissected the impact of seizures on blood flow of the middle cerebral artery in the following sequence: 1) vasodilation occurred, concomitant to the epileptic activity, whereas the blood velocities remained stable and 2) immediately after the seizure, the velocities increased and the artery caliber returned to its initial value. As per author, there was no protocol, but one patient gave consent to use data from her medical file.

[A case of epileptic seizure that required differentiation from hyper-acute ischemic stroke: usefulness of comparing DWI and FLAIR]

A 60-year-old man developed aphasia and transient right upper limb paresis in the presence of chronic subdural hematoma and was transferred to our hospital at an early stage. Cranial MRI within an hour after onset showed diffusion-weighted image (DWI) hyperintensity in the left parietal, temporal, and insular cortex and the pulvinar, and decreased apparent diffusion coefficient (ADC) in the left parietal cortex and pulvinar, suggesting a differential diagnosis of hyper-acute ischemic stroke. However, the distribution and timing of the MRI abnormalities were considered to be atypical for hyper-acute ischemic stroke. The area with both DWI hyperintensity and decreased ADC included the cerebral cortex adjacent to the hematoma and the ipsilateral pulvinar, and fluid-attenuated inversion recovery (FLAIR) hyperintensity co-existed with DWI hyperintensity within only an hour from onset. Furthermore, FLAIR images showed infiltration of the hematoma content into the subarachnoid space, which might have triggered the attack. These findings collectively led us to diagnose an epileptic seizure. The present case suggests that the distribution and timing of MRI abnormalities are essential to differentiate epileptic seizures from hyper-acute ischemic stroke.

Classification of epileptic seizure using feature selection based on fuzzy membership from EEG signal

BACKGROUND:

Feature selection is a technology that improves the performance result by eliminating overlapping or unrelated features.

OBJECTIVE:

To improve the performance result, this study proposes a new feature selection that uses the distance between the centers.

METHODS:

This study uses the distance between the centers of gravity (DBCG) of the bounded sum of the weighted fuzzy memberships (BSWFMs) supported by a neural network with weighted fuzzy membership (NEWFM).

RESULTS:

Using distance-based feature selection, 22 minimum features with a high performance result are selected, with the shortest DBCG of BSWFMs removed individually from the initial 24 features. The NEWFM used 22 minimum features as inputs to obtain a sensitivity, accuracy, and specificity of 99.3%, 99.5%, and 99.7%, respectively.

CONCLUSIONS:

In this study, only the mean DBCG is used to select the features; in the future, however, it will be necessary to incorporate statistical methods such as the standard deviation, maximum, and normal distribution.

Measuring the Coupling Direction between Neural Oscillations with Weighted Symbolic Transfer Entropy

Neural oscillations reflect rhythmic fluctuations in the synchronization of neuronal populations and play a significant role in neural processing. To further understand the dynamic interactions between different regions in the brain, it is necessary to estimate the coupling direction between neural oscillations. Here, we developed a novel method, termed weighted symbolic transfer entropy (WSTE), that combines symbolic transfer entropy (STE) and weighted probability distribution to measure the directionality between two neuronal populations. The traditional STE ignores the degree of difference between the amplitude values of a time series. In our proposed WSTE method, this information is picked up by utilizing a weighted probability distribution. The simulation analysis shows that the WSTE method can effectively estimate the coupling direction between two neural oscillations. In comparison with STE, the new method is more sensitive to the coupling strength and is more robust against noise. When applied to epileptic electrocorticography data, a significant coupling direction from the anterior nucleus of thalamus (ANT) to the seizure onset zone (SOZ) was detected during seizures. Considering the superiorities of the WSTE method, it is greatly advantageous to measure the coupling direction between neural oscillations and consequently characterize the information flow between different brain regions.

The Anti-Inflammatory Properties of Mesenchymal Stem Cells in Epilepsy: Possible Treatments and Future Perspectives

Mesenchymal stem cells (MSCs) are multipotent adult cells with self-renewing capacities. MSCs display specific properties, such as the ability to repair damaged tissues, resulting in optimal candidates for cell therapy against degenerative diseases. In addition to the reparative functions of MSCs, growing evidence shows that these cells have potent immunomodulatory and anti-inflammatory properties. Therefore, MSCs are potential tools for treating inflammation-related neurological diseases, including epilepsy. In this regard, over the last decades, epilepsy has no longer been considered a purely neuronal pathology, since inflammatory events underlying the genesis of epilepsy have been demonstrated. This review assessed current knowledge on the use of MSCs in the treatment of epilepsy. Mostly, attention will be focused on the anti-inflammatory and immunological skills of MSCs. Understanding the mechanisms by which MSCs might modulate the severity of the disease will contribute to the development of new potential alternatives for both prophylaxis and treatment against epilepsy.

Neurogenic pulmonary edema secondary to epileptic seizure

Neurogenic pulmonary edema (NPE) is a non-cardiogenic pulmonary edema that is caused by an acute central nervous system injury and usually develops rapidly after an injury. Although several episodes of NPE resolve spontaneously, the condition may cause unexpected death among patients with epilepsy.

Electroencephalographic Abnormalites in SARS-CoV-2 Patients

Viral infection with SARS-CoV-2 has a neurological tropism that may induce an encephalopathy. In this context, electroencephalographic exploration (EEG) is indicated as a diagnostic argument correlated with lumbar puncture, biology, and imaging. We performed a retrospective analysis of 42 patients explored by EEG and infected by COVID-19, according to the EEG abnormalities and clinical signs that motivated the examination. Confusion and epileptic seizures were the most common clinical indications, with 64% of the patients displaying these symptoms. The EEG was altered in 85% of the cases of confusion, in 57% of the cases of epileptic symptoms (general or focal seizure or prolonged loss of contact) and 20% of the cases of malaise or brief loss of consciousness. Nine EEG (21%) were in favor of an encephalopathy, two had de novo alterations in persistent consciousness and two had alterations in general states of confusion; one was very agitated and without history of epilepsy and combined eyelids clonia while a second one exhibited unconsciousness with left hemicorpus clonus. Two were being investigated for delayed awakening without sedation for more than 24 h. All of these patients were diagnosed COVID-19, some of them with associated mild to severe respiratory disorders. This work shows the interest of the EEG in exploring COVID-19 patients suffering from neurological or general symptoms looking for cerebral alteration.

Effects of Cerebrolysin on Hippocampal Neuronal Death After Pilocarpine-Induced Seizure

Epilepsy is one of the most common and severe brain diseases. The exact cause of epilepsy is unclear. Epilepsy often occurs following brain damage, such as traumatic brain injury (TBI) and ischemia. Cerebrolysin is a porcine brain peptide that is a unique neurotropic and neuroprotective agent. Cerebrolysin has been reported to increase neuroprotective effects after TBI, ischemia, and other CNS diseases. However, the effects of cerebrolysin on seizures are not known. Therefore, this study aimed to investigate the effects of neuropeptide cerebrolysin on neuronal death in the hippocampus after a seizure. To confirm the effects of cerebrolysin, we used a pilocarpine-induced seizure animal model. Cerebrolysin (2.5 ml/kg, i.p., once per day for 7 days) was immediately injected after a seizure induction. After 1 week, we obtained brain tissues and performed staining to histologically evaluate the potentially protective effects of cerebrolysin on seizure-induced neuronal death in the hippocampus. We found that cerebrolysin decreased hippocampal neuronal death after a seizure. In addition, an increase in brain-derived neurotrophic factor (BDNF) was confirmed through Western blot analysis to further support our hypothesis. Therefore, the present study suggests that the administration of cerebrolysin can be a useful therapeutic tool for preventing neuronal death after a seizure.

Cerebral pleomorphic xanthoastrocytoma mimicking inflammatory granuloma: Two case reports

RATIONALE

Pleomorphic xanthoastrocytoma (PXA) is a rare low-grade glial neoplasm of the central nervous system, which is difficult to distinguish from other neoplastic and non-neoplastic entities. Herein, we report 2 cases of PXA that had been misdiagnosed as an inflammatory granuloma.

PATIENT CONCERNS

The first case was a 22-year-old man who originally presented with a generalized seizure 7 years previously. Magnetic resonance imaging (MRI) revealed a lesion in the right parietal lobe, leading to a diagnosis of inflammatory granuloma. The second case was a 43-year-old man who presented with repeated generalized seizures. MRI revealed a nodular lesion in the left temporal lobe. The magnetic resonance spectrum showed elevated Cho and NAA peaks and a decreased Cr peak. An inflammatory granuloma was suspected.

DIAGNOSIS

After surgical treatment, histopathological examination revealed PXA.

INTERVENTIONS

In the first case, after 10 months of anti-inflammatory treatment, the lesion was significantly reduced in size. During the following 7 years, the patient experienced generalized seizures 3 to 4 times annually. To control intractable epilepsy, the lesion was resected. In the second case, conservative treatment provided no benefit, and then the lesion was resected.

OUTCOMES

In the first case, during a follow-up period of 14 months, the patient was seizure-free with no tumor recurrence. In the second case, after a 6 months of follow-up, the patient remained seizure-free with no tumor recurrence.

LESSONS

The preoperative differential diagnosis of PXA is challenging due to the nonspecific symptoms and imaging manifestations. Considering the potential risk of malignant transformation of PXA, early surgery should be highlighted, and gross total resection is associated with a favorable prognosis.

A Novel Recognition Strategy for Epilepsy EEG Signals Based on Conditional Entropy of Ordinal Patterns

Epilepsy is one of the most ordinary neuropathic illnesses, and electroencephalogram (EEG) is the essential method for recording various brain rhythm activities due to its high temporal resolution. The conditional entropy of ordinal patterns (CEOP) is known to be fast and easy to implement, which can effectively measure the irregularity of the physiological signals. The present work aims to apply the CEOP to analyze the complexity characteristics of the EEG signals and recognize the epilepsy EEG signals. We discuss the parameter selection and the performance analysis of the CEOP based on the neural mass model. The CEOP is applied to the real EEG database of Bonn epilepsy for identification. The results show that the CEOP is an excellent metrics for the analysis and recognition of epileptic EEG signals. The differences of the CEOP in normal and epileptic brain states suggest that the CEOP could be a judgment tool for the diagnosis of the epileptic seizure.

[Psychogenic pseudoseizures as psychoneurological problem]

The complexity of the problem is associated with the lack of reliable differential diagnostic indications for distinguishing epileptic and pseudo-epileptic seizures, as well as with the risk of provoking seizures during psychological sessions in patients with PPS. Therefore, apparently, only one of the Russian-language monographs that were published in recent years and one of the 1999 neurology guidelines pay attention to this problem. We have shown the nosological heterogeneity of patients with PPS, clinical particularities related to it and the need for a differentiated approach to its therapy. PPS is a serious clinical problem that can successfully be solved only by interdisciplinary development.

The risk of epilepsy in children with celiac disease: a population-based cohort study

BACKGROUNDAND PURPOSE

The purpose was to estimate the risk of epilepsy in a cohort of young individuals with celiac disease (CD) compared to that of matched references.

METHODS

The cohort consisted of 213 635 individuals born during 1989-2011 and residing in Friuli-Venezia Giulia (Italy). 1215 individuals affected by CD and 6075 reference individuals matched by sex and age were identified. Epilepsy was defined by means of hospital diagnosis or drug prescriptions. Conditional logistic regression was used to estimate the odds ratios (ORs) of having epilepsy amongst individuals with CD, before CD diagnosis and in the entire period, compared with those of their matched references. Cox regression was used to calculate the hazard ratios for epilepsy diagnosed after CD diagnosis. Different definitions of epilepsy were used for sensitivity analyses.

RESULTS

Thirty-one (2.6%) individuals with CD and 78 (1.3%) reference individuals had epilepsy [adjusted OR 2.03; 95% confidence interval (CI) 1.33-3.10]. The risk of epilepsy was increased prior to CD (adjusted OR 2.29; 95% CI 1.33-3.94), with similar estimates after CD diagnosis (adjusted hazard ratio 1.96; 95% CI 0.95-4.02). The increased risk of epilepsy was not explained by a peak in epilepsy diagnosis just around CD diagnosis. Sex stratification found a significantly higher risk of epilepsy amongst female individuals with CD. Sensitivity analyses confirmed the positive association between CD and epilepsy.

CONCLUSION

Children and youths with CD were at increased risk of epilepsy. Patients with epilepsy without a clear etiology should be screened for CD since an early diagnosis and treatment might improve the response to antiepileptic therapies.

Reactive bite-related tongue lesions in cognitively impaired epilepsy patients: A report of two cases

AIM

Tongue bites frequently occur during seizures in epilepsy patients. We report two cases of cognitively impaired Lennox-Gastaut syndrome patients with reactive lesions on the tongues.

CASE PRESENTATIONS

Case 1 was a 30-year-old man whose chief complaint was mouth pain. Local finding was a small bean-sized pedunculated mass on the tongue, histopathologically diagnosed as inflammatory fibrous hyperplasia. Case 2 was a 45-year-old man whose chief complaint was bleeding from the mouth. His clinical finding was blood loss anemia. Local finding was a 20-mm-diameter pedunculated mass on the tongue, histopathologically diagnosed as pyogenic granuloma.

CONCLUSION

These mass lesions were believed to be reactive, caused by repetitive minor damage involving reparative fibrous tissue response. Therefore, the two cases may have involved reparative responses to mucosal injury incurred by accidental bites during epileptic seizures. Intellectual disability made medical treatment difficult and had allowed the massive lesions to form. It is necessary for cognitively impaired epilepsy patients to undergo regular dental examinations in order to get used to dental checks and to increase the number of intraoral observations in the context of close cooperation between dentists and epilepsy therapists.

Atypical presentation of ventricular tachycardia

Cardiac syncope and epileptic seizure are two very similar presentations and difficult to differentiate without a proper history, physical examination and investigations. In a former study, 10 out of 22 episodes of induced ventricular tachycardia or fibrillation can result in stereotypical tonic-clonic movement with varied electroencephalography changes. We present a case which was diagnosed as ventricular tachycardia from seizure-like attack. It is to emphasise the importance of including ventricular tachycardia among other differential diagnoses of seizure-like activity in a patient with cardiovascular risks.