The electroencephalogram of idiopathic generalized epilepsy

EEG in focal and generalized epilepsies: Pearls and perils

Correctly diagnosing and classifying seizures and epilepsies is vital to ensure a tailored approach to patients with epilepsy. The ILAE seizure classification consists of two main groups: focal and generalized. Establishing if a seizure is focal or generalized is essential to classify the epilepsy type and the epilepsy syndrome, providing more personalized treatment and counseling about prognosis. EEG is one of the most essential tools for this classification process and further localization of the epileptogenic focus. However, some EEG findings are misleading and may postpone the correct diagnosis and proper treatment. Knowing the most common EEG pitfalls in focal and generalized epilepsies is valuable for clinical practice, avoiding misinterpretations. Some atypical features can be challenging in focal epilepsies, such as secondary bilateral synchrony, focal epileptiform activity induced by hyperventilation and photic stimulation, and non-focal slowing. On the other hand, more than 60 % of persons with idiopathic generalized epilepsies have at least one type of atypical abnormality. In this manuscript, we describe and illustrate some of the most common EEG findings that can make even experienced epileptologists question not only where the epileptogenic focus is but also if the patient has focal or generalized epilepsy. This review summarizes the perils and provide some pearls to assist EEG readers.

Importance of Genetic Testing in Children With Generalized Epilepsy

INTRODUCTION

Epilepsy is a neurological disorder characterized by the predisposition for recurrent unprovoked seizures. It can broadly be classified as focal, generalized, unclassified, and unknown in its onset. Focal epilepsy originates in and involves networks localized to one region of the brain. Generalized epilepsy engages broader, more diffuse networks. The etiology of epilepsy can be structural, genetic, infectious, metabolic, immune, or unknown. Many generalized epilepsies have presumed genetic etiologies. The aim of this study is to compare the role of genetic testing to brain MRI as diagnostic tools for identifying the underlying causes of idiopathic (genetic) generalized epilepsy (IGE).

METHODS

 We evaluated the diagnostic yield of these two categories in children diagnosed with IGE. Data collection was completed using ICD10 codes filtered by TriNetX to select 982 individual electronic medical records (EMRs) of children in the Penn State Children's Hospital who received a diagnosis of IGE. The diagnosis was confirmed after reviewing the clinical history and electroencephalogram (EEG) data for each patient.

RESULTS

From this dataset, neuroimaging and genetic testing results were gathered. A retrospective chart review was done on 982 children with epilepsy, of which 143 (14.5%) met the criteria for IGE. Only 18 patients underwent genetic testing. Abnormalities that could be a potential cause for epilepsy were seen in 72.2% (13/18) of patients with IGE and abnormal genetic testing, compared to 30% (37/123) for patients who had a brain MRI with genetic testing.

CONCLUSION

This study suggests that genetic testing may be more useful than neuroimaging for identifying an etiological diagnosis of pediatric patients with IGE.

Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges

Idiopathic generalized epilepsy (IGE) is characterized by cryptogenic etiology and the striatum and cerebellum are recognized as modulators of epileptic network. We collected simultaneous electroencephalogram and functional magnetic resonance imaging data from 145 patients with IGE, 34 of whom recorded interictal epileptic discharges (IEDs) during scanning. In states without IEDs, hierarchical connectivity was performed to search core cortical regions which might be potentially modulated by striatum and cerebellum. Node-node and edge-edge moderation models were constructed to depict direct and indirect moderation effects in states with and without IEDs. Patients showed increased hierarchical connectivity with sensorimotor cortices (SMC) and decreased connectivity with regions in the default mode network (DMN). In the state without IEDs, striatum, cerebellum, and thalamus were linked to weaken the interactions of regions in the salience network (SN) with DMN and SMC. In periods with IEDs, overall increased moderation effects on the interaction between regions in SN and DMN, and between regions in DMN and SMC were observed. The thalamus and striatum were implicated in weakening interactions between regions in SN and SMC. The striatum and cerebellum moderated the cortical interaction among DMN, SN, and SMC in alliance with the thalamus, contributing to the dysfunction in states with and without IEDs in IGE. The current work revealed state-specific modulation effects of striatum and cerebellum on thalamocortical circuits and uncovered the potential core cortical targets which might contribute to develop new clinical neuromodulation techniques.

Hyperventilation and Seizures: Not a New Sense: A Literature Review

Hyperventilation and seizures have a long association in the clinical literature and were known to have a relationship long before the electroencephalogram (EEG) was used to record changes in brain activity. As the use of EEG recording progressed, hyperventilation was the first activation method used to assist with diagnosis of epilepsy. Along with slowing of brain activity, hyperventilation can activate epileptiform spiking activity in patients with epilepsy. Currently, hyperventilation is used in standard practice to assist with the diagnosis of epilepsy during EEG recording. Hyperventilation activates epileptiform spiking activity more often than seizures but can trigger clinical seizures in up to 50% of patients with generalized epilepsy. It is more likely to trigger events in children with absence seizures than adults, and it acts as a trigger in patients with focal epilepsy far less often. However, while some clinicians suggest that its diagnostic value is limited, especially in adults with focal epilepsies, others suggest that it is simple, safe, and an important diagnostic tool, even in these patients. This review presents the history of hyperventilation and seizures, its use in the clinical practice, and possible mechanisms involved.

Comparison of Automated Spike Detection Software in Detecting Epileptiform Abnormalities on Scalp-EEG of Genetic Generalized Epilepsy Patients

PURPOSE

Despite availability of commercial EEG software for automated epileptiform detection, validation on real-world EEG datasets is lacking. Performance evaluation of two software packages on a large EEG dataset of patients with genetic generalized epilepsy was performed.

METHODS

Three epileptologists labelled IEDs manually of EEGs from three centres. All Interictal epileptiform discharge (IED) markings predicted by two commercial software (Encevis 1.11 and Persyst 14) were reviewed individually to assess for suspicious missed markings and were integrated into the reference standard if overlooked during manual annotation during a second phase. Sensitivity, precision, specificity, and F1-score were used to assess the performance of the software packages against the adjusted reference standard.

RESULTS

One hundred and twenty-five routine scalp EEG recordings from different subjects were included (total recording time, 310.7 hours). The total epileptiform discharge reference count was 5,907 (including spikes and fragments). Encevis demonstrated a mean sensitivity for detection of IEDs of 0.46 (SD 0.32), mean precision of 0.37 (SD 0.31), and mean F1-score of 0.43 (SD 0.23). Using the default medium setting, the sensitivity of Persyst was 0.67 (SD 0.31), with a precision of 0.49 (SD 0.33) and F1-score of 0.51 (SD 0.25). Mean specificity representing non-IED window identification and classification was 0.973 (SD 0.08) for Encevis and 0.968 (SD 0.07) for Persyst.

CONCLUSIONS

Automated software shows a high degree of specificity for detection of nonepileptiform background. Sensitivity and precision for IED detection is lower, but may be acceptable for initial screening in the clinical and research setting. Clinical caution and continuous expert human oversight are recommended with all EEG recordings before a diagnostic interpretation is provided based on the output of the software.

Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography

Predicting seizure recurrence risk is critical to the diagnosis and management of epilepsy. Routine electroencephalography (EEG) is a cornerstone of the estimation of seizure recurrence risk. However, EEG interpretation relies on the visual identification of interictal epileptiform discharges (IEDs) by neurologists, with limited sensitivity. Automated processing of EEG could increase its diagnostic yield and accessibility. The main objective was to develop a prediction model based on automated EEG processing to predict one-year seizure recurrence in patients undergoing routine EEG. We retrospectively selected a consecutive cohort of 517 patients undergoing routine EEG at our institution (training set) and a separate, temporally shifted cohort of 261 patients (testing set). We developed an automated processing pipeline to extract linear and non-linear features from the EEGs. We trained machine learning algorithms on multichannel EEG segments to predict one-year seizure recurrence. We evaluated the impact of IEDs and clinical confounders on performances and validated the performances on the testing set. The receiver operating characteristic area-under-the-curve for seizure recurrence after EEG in the testing set was 0.63 (95% CI 0.55-0.71). Predictions were still significantly above chance in EEGs with no IEDs. Our findings suggest that there are changes other than IEDs in the EEG signal embodying seizure propensity.

Changes in awake and sleep electroencephalography characteristics after 1-year treatment for childhood and juvenile absence epilepsy

PURPOSE

To compare electroencephalography (EEG) features of newly diagnosed drug-naive childhood absence epilepsy (CAE) and juvenile absence epilepsy (JAE) patients and analyze their response to anti-seizure medications (ASMs).

METHOD

EEG characteristics between CAE and JAE patients and responders and non-responders to ASM at baseline and 12 months were compared, and the changes from baseline were analysed.

RESULTS

A total of 62 patients (32 CAE and 30 JAE) were included. Discharges in baseline awake and sleep EEGs and interictal and polyspike discharges in baseline sleep EEGs were more frequent in JAE patients. Although the median discharge densities (discharge containing seconds per minute) were similar in baseline awake and sleep EEGs between the groups, the median was higher in the JAE group at 12 months and decreased significantly in both groups at 12 months compared to the baseline values. Responses to initial ASMs were 94% and 77% in the CAE and JAE groups, respectively. In initial sleep EEGs of non-responders with JAE, focal onset generalized spike and slow wave discharges (GSWDs) were more frequent, and the median ictal and interictal discharge densities were higher.

CONCLUSION

JAE patients had more frequent disorganized discharges at baseline in both awake and sleep EEGs and interictal and polyspike discharges in sleep EEGs than those of CAE patients. Improvement in EEG was more pronounced in CAE patients than in JAE patients. Focal-onset GSWDs and higher ictal and interictal discharge densities on baseline EEG were associated with a poor response to initial ASMs in JAE patients.

Association of symptoms of psychiatric disease and electroencephalographic patterns in idiopathic generalized epilepsy

OBJECTIVE

Idiopathic generalized epilepsies (IGE) are genetic epilepsies with alterations of thalamo-frontocortical circuits that play a major role in seizure generation and propagation. Psychiatric diseases and drug resistance are strongly associated, but it remains unknown if they are symptoms of the same pathophysiological process. Hypothesizing that the same network alterations are associated with the frequency of epileptic discharges (ED) and psychiatric symptoms, we here tested the association of self-reported psychiatric symptoms and IGE severity estimated by electroencephalographic (EEG) biomarkers.

METHODS

Idiopathic generalized epilepsies patients were asked to fill out four validated psychiatric screening tools assessing symptoms of personality disorders (Standard Assessment of Personality- Abbreviated Scale), depression (Major Depression Inventory), impulsiveness (Barratt Impulsiveness Scale), and anxiety (brief Epilepsy Anxiety Survey Instrument). Blinded to results and clinical data on the patients, we analyzed the patients' EEGs, assessed, and quantified ED. The number and duration of ED divided by the duration of the EEG served as a proxy for the severity of IGE that was correlated with the results of the psychiatric screening.

RESULTS

Paired data from 64 patients were available for analysis. The duration of EDs per minute EEG was inversely associated with the time since the last seizure. The number of patients with generalized polyspike trains (n = 2), generalized paroxysmal fast activity (n = 3), and prolonged epileptiform discharges (n = 10) were too low for statistically meaningful analyses. Self-reported symptoms of depression, personality disorder, and impulsivity were not associated with EDs. In contrast, the duration of EDs per minute EEG was associated with self-reported symptoms of anxiety in univariate analyses, not significant, however, following adjustment for time since the last seizure in regression models.

SIGNIFICANCE

Self-reported symptoms of psychiatric diseases were not strongly associated with EDs as the best available quantifiable biomarker of IGE severity. As expected, the duration of EDs per minute and anxiety was inversely associated with time since the last seizure. Our data argue against a direct link between the frequency of EDs - as an objective proxy of IGE severity - and psychiatric symptoms.

Typical absence seizures in children: Review with focus on EEG predictors of treatment response and outcome

Typical absence seizures (TAS) occur in idiopathic generalized epilepsy (IGE) syndromes and are a common presentation to paediatric neurologists. Considerable overlap in clinical features of IGE syndromes comprising TAS often complicates prognostication. Clinical and EEG diagnostic features in TAS are well known. However, knowledge of prognostic features for each syndrome, whether clinical or EEG-related, is less clear. Perpetuated impressions in clinical practice regarding the role of EEG when used for prognostication in TAS are known. Assumed prognostic features, particularly those relating to EEG have been rarely studied systematically. Despite rapid expansion in epilepsy genetics, the complex and presumed polygenic inheritance of IGE, means that clinical and EEG features are likely to remain the main guide to management and prognostication of TAS for the foreseeable future. We comprehensively reviewed available literature and hereby summarize current knowledge of clinical and EEG characteristics (ictal and interictal) in children with TAS. The literature focuses predominantly on ictal EEG. Where studied, interictal findings reported relate to focal discharges, polyspike discharges, and occipital intermittent rhythmic delta activity, with generalized interictal discharges not thoroughly studied. Furthermore, reported prognostic implications of EEG findings are often conflicting. Limitations of available literature include inconsistent clinical syndrome and EEG finding definitions, and variable EEG analysis methods, particularly lack of raw EEG data analysis. These conflicting findings coupled with varying study methodologies cause lack of clear information or evidence on features which may influence treatment response, outcome, or natural history of TAS.

Usefulness and yield of routine electroencephalogram: a retrospective study

BACKGROUND

The electroencephalogram (EEG) is a common diagnostic tool used to investigate patients for various indications including seizure disorders.

AIMS

To investigate factors that predict the presence of epileptiform abnormalities on EEG and review the common indications for ordering an EEG.

METHODS

We retrospectively reviewed all routine adult EEG performed in a hospital over a 6-month period. Data collated included patient demographics, clinical indication for EEG, setting in which EEG was performed, activation procedures utilised, history of epilepsy, and whether the patient was on antiepileptic medication. Our primary objective was to evaluate the factors that were predictive of an EEG with epileptiform abnormalities.

RESULTS

Two hundred and thirty-nine routine EEG were included with indications, including first seizure (25.9%), known epilepsy (25.1%), cognitive change (15.9%), syncope (15.0%), movement disorder (6.7%), psychogenic non-epileptic events (5.4%), unresponsiveness/intensive care unit (4.6%) and psychiatric presentation (1.3%). Most (48.1%) EEG were normal; 8.9% of the EEG demonstrated epileptiform abnormalities. Using multivariate logistic regression, three variables proved significant in predicting an EEG with epileptiform abnormalities. Any seizure as an indication (first seizure or seizure in known epileptic), increasing patient age, and EEG conducted in an inpatient setting and within 48 h of seizure event were all statistically more likely to yield epileptiform abnormalities on EEG.

CONCLUSIONS

Our findings suggest that careful selection of patients based on appropriate indications for EEG referral would likely improve the yield of an EEG. Depending on the indication, a normal EEG result can be of similar usefulness to an abnormal EEG demonstrating epileptiform abnormalities.

Alpha2-Adrenergic Receptors as a Pharmacological Target for Spike-Wave Epilepsy

Spike-wave discharges are the hallmark of idiopathic generalized epilepsy. They are caused by a disorder in the thalamocortical network. Commercially available anti-epileptic drugs have pronounced side effects (i.e., sedation and gastroenterological concerns), which might result from a low selectivity to molecular targets. We suggest a specific subtype of adrenergic receptors (ARs) as a promising anti-epileptic molecular target. In rats with a predisposition to absence epilepsy, alpha2 ARs agonists provoke sedation and enhance spike-wave activity during transitions from awake/sedation. A number of studies together with our own observations bring evidence that the sedative and proepileptic effects require different alpha2 ARs subtypes activation. Here we introduce a new concept on target pharmacotherapy of absence epilepsy via alpha2B ARs which are presented almost exclusively in the thalamus. We discuss HCN and calcium channels as the most relevant cellular targets of alpha2 ARs involved in spike-wave activity generation.

Spike-wave discharges in Sprague-Dawley rats reflect precise intra- and interhemispheric synchronization of somatosensory cortex

Spike-wave discharges (SWDs) are among the most prominent electrical signals recordable from the rat cerebrum. Increased by inbreeding, SWDs have served as an animal model of human genetic absence seizures. Yet, SWDs are ubiquitous in inbred and outbred rats, suggesting they reflect normal brain function. We hypothesized that SWDs represent oscillatory neural ensemble activity underlying sensory encoding. To test this hypothesis, we simultaneously mapped SWDs from wide areas (8 × 8 mm) of both hemispheres in anesthetized rats, using 256-electrode epicortical arrays that covered primary and secondary somatosensory, auditory and visual cortex bilaterally. We also recorded the laminar pattern of SWDs with linear microelectrode arrays. We compared the spatial and temporal organization of SWDs to somatosensory-evoked potentials (SEPs), as well as auditory- and visual-evoked potentials (AEPs and VEPs) to examine similarities and/or differences between sensory-evoked and spontaneous oscillations in the same animals. We discovered that SWDs are confined to the facial representation of primary and secondary somatosensory cortex (SI and SII, respectively), areas that are preferentially engaged during environmental exploration in the rat. Furthermore, these oscillations exhibit highly synchronized bilateral traveling waves in SI and SII, simultaneously forming closely matched spread patterns in both hemispheres. We propose that SWDs could reflect a previously unappreciated capacity for rat somatosensory cortex to perform precise spatial and temporal analysis of rapidly changing sensory input at the level of large neural ensembles synchronized both within and between the cerebral hemispheres.NEW & NOTEWORTHY We simultaneously mapped electrocortical SWDs from both cerebral hemispheres of Sprague-Dawley rats and discovered that they reflect systematic activation of the facial representation of somatosensory cortex. SWDs form mirror spatiotemporal patterns in both hemispheres that are precisely aligned in both space and time. Our data suggest that SWDs may reflect a substrate by which large neural ensembles perform precise spatiotemporal processing of rapidly changing somatosensory input.

Signal in the noise: Altered brain activation among adolescent alcohol users detected via the analysis of intra-individual variability1

RATIONALE

Unlike its average level, the variability in brain activation over time or trials can capture subtle and brief disruptions likely to occur among participants with low-to-moderate levels of substance use or misuse.

OBJECTIVE

The present study used this intra-individual variability measurement approach to detect neural processing differences associated with light-to-moderate use of alcohol among 14-19-year-old adolescents.

METHOD

A total of 128 participants reporting any level of alcohol use during the previous 6 months and 87 participants reporting no use during this period completed intake questionnaires and interviews as well as an assessment of P300 electroencephalographic responses to novel stimuli recorded during two separate tasks.

RESULTS

In addition to differing in recent alcohol use, the groups differed in nicotine and cannabis use, risk-taking behavior and conduct disorder symptoms, and P300 amplitude inter-trial variability (ITV) across both tasks. Across all participants, P300 ITV was positively correlated with a family history of depression but not with a family history of alcohol dependence. There were no group differences in P300 amplitude averaged across trials.

CONCLUSIONS

Recent reports attributing brain volume or brain function differences to an effect of light-to-moderate alcohol use should be viewed with great caution. In the present analysis of brain function differences among substance-using adolescents, the group differences were small, complicated by many factors coinciding with or preceding alcohol use, and not reflected in a stable central tendency.

Using Generalized Polyspike Train to Predict Drug-Resistant Idiopathic Generalized Epilepsy

INTRODUCTION

The authors tested the hypothesis that the EEG feature generalized polyspike train (GPT) is associated with drug-resistant idiopathic generalized epilepsy (IGE).

METHODS

The authors conducted a single-center case-control study of patients with IGE who had outpatient EEGs performed between 2016 and 2020. The authors classified patients as drug-resistant or drug-responsive based on clinical review and in a masked manner reviewed EEG data for the presence and timing of GPT (a burst of generalized rhythmic spikes lasting less than 1 second) and other EEG features. A relationship between GPT and drug resistance was tested before and after controlling for EEG duration. The EEG duration needed to observe GPT was also calculated.

RESULTS

One hundred three patients were included (70% drug-responsive and 30% drug-resistant patients). Generalized polyspike train was more prevalent in drug-resistant IGE (odds ratio, 3.8; 95% confidence interval, 1.3-11.4; P = 0.02). This finding persisted when controlling for EEG duration both with stratification and with survival analysis. A median of 6.5 hours (interquartile range, 0.5-12.7 hours) of EEG recording was required to capture the first occurrence of GPT.

CONCLUSIONS

The findings support the hypothesis that GPT is associated with drug-resistant IGE. Prolonged EEG recording is required to identify this feature. Thus, >24-hour EEG recording early in the evaluation of patients with IGE may facilitate prognostication.

Sleep quality and architecture in Idiopathic generalized epilepsy: A systematic review and meta-analysis

Idiopathic generalized epilepsies are a group of sleep related epilepsy syndromes with sleep deprivation as a strong trigger for seizures and increased spike-wave activity during sleep and transition to sleep. Neuropsychological deficits are common in Idiopathic generalized epilepsy patients. Learning and memory processes are closely linked to sleep. Therefore, this systematic review and meta-analysis investigates the evidence of sleep disturbances in Idiopathic generalized epilepsy patients. A search of the databases EMBASE, Medline and Scopus identified 22 studies comparing polysomnographic parameters and scores of sleep questionnaires between Idiopathic generalized epilepsy patients and healthy controls. Random effect univariate meta-analyses revealed reduced sleep efficiency, total sleep time, proportion of N2 stage and prolonged REM onset latency in Idiopathic generalized epilepsy patients. Self-assessed sleep quality of patients measured by the Pittsburgh sleep quality index was lower in two thirds of reporting studies. Considering the influence on behavioral issues, cognitive performance and quality of life, the revealed alteration in sleep architecture and lower subjective sleep quality emphasizes the importance of screening for sleep disturbances in the medical care of patients with Idiopathic generalized epilepsy.

Altered Structural Brain Networks in Refractory and Nonrefractory Idiopathic Generalized Epilepsy

Introduction: Idiopathic generalized epilepsy (IGE) is a collection of generalized nonlesional epileptic network disorders. Around 20-40% of patients with IGE are refractory to antiseizure medication, and mechanisms underlying refractoriness are poorly understood. Here, we characterize structural brain network alterations and determine whether network alterations differ between patients with refractory and nonrefractory IGE. Methods: Thirty-three patients with IGE (10 nonrefractory and 23 refractory) and 39 age- and sex-matched healthy controls were studied. Network nodes were segmented from T1-weighted images, while connections between these nodes (edges) were reconstructed from diffusion magnetic resonance imaging (MRI). Diffusion networks of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and streamline count (Count) were studied. Differences between all patients, refractory, nonrefractory, and control groups were computed using network-based statistics. Nodal volume differences between groups were computed using Cohen's d effect size calculation. Results: Patients had significantly decreased bihemispheric FA and Count networks and increased MD and RD networks compared with controls. Alterations in network architecture, with respect to controls, differed depending on treatment outcome, including predominant FA network alterations in refractory IGE and increased nodal volume in nonrefractory IGE. Diffusion MRI networks were not influenced by nodal volume. Discussion: Although a nonlesional disorder, patients with IGE have bihemispheric structural network alterations that may differ between patients with refractory and nonrefractory IGE. Given that distinct nodal volume and FA network alterations were observed between treatment outcome groups, a multifaceted network analysis may be useful for identifying imaging biomarkers of refractory IGE.

Distributed source localization of epileptiform discharges in juvenile myoclonic epilepsy: Standardized low-resolution brain electromagnetic tomography (sLORETA) Study

Juvenile myoclonic epilepsy (JME) is a common generalized epilepsy syndrome considered the prototype of idiopathic generalized epilepsy. To date, generalized and focal seizures have been the fundamental concepts for classifying seizure types. In several studies, focal features of JME have been reported predominantly in the frontal lobe. However, results in previous studies are inconsistent. Therefore, we investigated the origin of epileptiform discharges in JME. We performed electroencephalography source localization using a distributed model with standardized low-resolution brain electromagnetic tomography. In 20 patients with JME, standardized low-resolution brain electromagnetic tomography images corresponding to the midpoint of the ascending phase and the negative peak of epileptiform discharges were obtained from a total of 362 electroencephalography epochs (181 epochs at each timepoint). At the ascending phase, the maximal current source density was located in the frontal lobe (58.6%), followed by the parietal (26.5%) and occipital lobes (8.8%). At the negative peak, the maximal current source density was located in the frontal lobe (69.1%), followed by the parietal (11.6%) and occipital lobes (9.4%). In the ascending phase, 41.4% of discharges were located outside the frontal lobe, and 30.9% were in the negative peak. Frontal predominance of epileptiform discharges was observed; however, source localization extending to various cortical regions also was identified. This widespread pattern was more prominent in the ascending phase (P = .038). The study results showed that JME includes widespread cortical regions over the frontal lobe. The current concept of generalized epilepsy and pathophysiology in JME needs further validation.

Omitting Hyperventilation in Electroencephalogram during the COVID-19 Pandemic May Reduce Interictal Epileptiform Discharges in Patients with Juvenile Myoclonic Epilepsy

BACKGROUND

To prevent the spread of coronavirus disease 2019 (COVID-19), hyperventilation (HV) activation has been avoided in electroencephalograms (EEGs) since April 2020. The influence of omitting HV in EEG on epilepsy diagnosis remains uncertain for patients with epilepsies other than child absence epilepsy. We hypothesized that EEGs with HV would show more interictal epileptiform discharges (IEDs) than EEGs without HV in patients with juvenile myoclonic epilepsy (JME).

METHODS

We reviewed the EEGs of seizure-free patients with JME who underwent EEG, both with and without HV, from January 2019 to October 2021, in our institution, and compared IEDs between EEG with and without HV.

RESULTS

This study analyzed 23 JME patients. The IED-positive rate was significantly higher in EEG with HV (65.2%) than in EEG without HV (34.8%, p = 0.016). The mean ± standard deviation number of IEDs per minute was significantly larger during HV (1.61 ± 2.25 × 10^-1) than during non-activation of both first EEG (0.57 ± 0.93 × 10^-1, p = 0.039) and second EEG (0.39 ± 0.76 × 10^-1, p = 0.009).

CONCLUSIONS

In JME patients, performing HV during EEG may increase IEDs and appears to facilitate the accurate diagnosis of epilepsy.

Hospital-Based Prevalence, Electroencephalogram (EEG), and Neuroimaging Correlation in Seizures Among Children in Odisha, India

Background: Febrile seizures are very common in pediatric practice. We need to differentiate between febrile seizures and other seizures due to central nervous system (CNS) infection by various means of investigation. Though approximately 30% of patients with febrile seizure have later epilepsy and the risk is around 20% even if electroencephalogram (EEG), and neuro-imagings are normal. But data regarding this is laking in developing countries like India.

Aim: The primary objective of this study is to determine the hospital-based prevalence among various types and etiologies of seizures in children admitted to the pediatric department in a teaching hospital of a developing country, India. Besides, the different types of seizures were correlated with the EEG and neuroimaging findings along with the acute onset of seizures among children.

Methods: In this prospective observational study, children from two months to 15 years of age admitted to the Pediatrics Department, KIMS, Bhubaneswar in India between September 2017 and September 2019 were taken. The patients having seizures were included in the study based on the inclusion criteria. Neurological and systemic examinations of the children were recorded and the neuroimaging reports were analyzed.

Results: A total of 19,553 patients aged two months to 15 years were admitted during the study period. Of that, 1,192 cases were diagnosed with febrile and unprovoked seizures. It was observed that the hospital-based prevalence of seizures among children in Odisha was 6%. Besides, it is found that generalized seizure disorder was the most common among the children. It was found that abnormal EEG, magnetic resonance imaging (MRI), and computed tomography (CT) brain in 60% (202/340), 49% (113/230), and 47% (136/288) of cases, respectively. MRI is a better modality of investigation in partial seizure cases 22 (64%) to detect CNS abnormality. Also, MRI of the brain is better in evaluating CNS abnormality in complex febrile cases 4 (31%) than CT brain (0%).

Conclusion: The study concluded that EEG must be the standard modality of test for patients' diagnosis of seizure in children with seizures. CT/MRI scan can give a better supplement to the results but MRI findings are more accurate in cases of complex febrile seizures.

Minimum standards for inpatient long-term video-EEG monitoring: A clinical practice guideline of the international league against epilepsy and international federation of clinical neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events (see Table S1). For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and establish its clinical utility.

Minimum standards for inpatient long-term video-electroencephalographic monitoring: A clinical practice guideline of the International League Against Epilepsy and International Federation of Clinical Neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events. For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and to establish its clinical utility.

High rates of early remission pattern in adult-onset compared with earlier-onset idiopathic generalized epilepsy: A long-term follow-up study

OBJECTIVE

To investigate electroclinical characteristics and prognostic patterns of adult-onset vs. younger-onset idiopathic generalized epilepsy (IGE) patients during long-term follow-up.

METHODS

In this single-center retrospective cohort comparative study, adult-onset IGE was defined as onset after 20 years of age. Patients with a follow-up duration between 10 and 30 years from epilepsy diagnosis were enrolled. Maximum follow-up duration was limited to 30 years to ensure a better comparison of prognostic data between adult-onset and younger-onset patients. The Benjamini-Hochberg false discovery rate (FDR) method was applied to obtain FDR-adjusted p-values.

RESULTS

A total of 177 IGE patients were recruited and 27 adult-onset IGE patients were identified (15.3%). Follow-up duration was similar between younger- and adult-onset IGE patients and 74% of subjects performed at least one 24-hour EEG recording. Of adult-onset IGE patients, 8/27 were diagnosed with juvenile myoclonic epilepsy, while 19/27 were diagnosed with generalized tonic-clonic seizures (GTCS) only. EEG photosensitivity and absence seizures were significantly less frequent among adult-onset IGE patients as compared with younger subjects. When considering prognostic patterns, an early remission pattern was significantly higher among adult-onset IGE patients as compared with younger-onset IGE patients (55.6% vs. 24%, adjusted p value = 0.007). Antiseizure medication withdrawal was attempted in 3/27 adult-onset patients, and all had GTCS relapses.

CONCLUSION

Our study contributes to better defining the electroclinical characteristics and long-term follow-up of adult-onset IGE patients. A favorable long-term seizure outcome was found in adult-onset IGE patients, as evidenced by the high rates of early remission pattern when compared with younger onset patients.

Brainwaves beyond diagnosis: Wider applications of electroencephalography in idiopathic generalized epilepsy

Electroencephalography (EEG) has long been used as a versatile and noninvasive diagnostic tool in epilepsy. With the advent of digital EEG, more advanced applications of EEG have emerged. Compared with technologically advanced practice in focal epilepsies, the utilization of EEG in idiopathic generalized epilepsy (IGE) has been lagging, often restricted to a simple diagnostic tool. In this narrative review, we provide an overview of broader applications of EEG beyond this narrow scope, discussing how the current clinical and research applications of EEG may potentially be extended to IGE. The current literature, although limited, suggests that EEG can be used in syndromic classification, guiding antiseizure medication therapy, predicting prognosis, unraveling biorhythms, and investigating functional brain connectivity of IGE. We emphasize the need for longer recordings, particularly 24-h ambulatory EEG, to capture discharges reflecting circadian and sleep-wake cycle-associated variations for wider EEG applications in IGE. Finally, we highlight the challenges and limitations of the current body of literature and suggest future directions to encourage and enhance more extensive applications of this potent tool.

The spectrum of epilepsy in children with 15q13.3 microdeletion syndrome

PURPOSE

To further define the epilepsy phenotype in a cohort of children with 15q13.3 microdeletion syndrome.

METHODS

We retrospectively reviewed the phenotypic spectrum of all children aged < 18 years with epilepsy and 15q13.3 microdeletion syndrome.

RESULTS

Thirteen children were included, 69% were female. The median age of children in the cohort was 12 years (age range: 3 years-15 years). Median age at seizure onset was 4 years. Eleven children (85%) had intellectual disability. Nine of 13 children (69%) had a history of typical absence seizures with median age of onset at 5 years (2 had absence status epilepticus). Thirty-one percent (4/13) had focal with impaired awareness non-motor onset seizures. ILAE recognized absence epilepsy syndromes were diagnosed in 6/13 (46%). The remainder were classified as having genetic generalized epilepsies with overlap clinical features, combined or focal epilepsies. Electroencephalogram in the cohort showed generalized (85%) and focal epileptiform discharges (62%) and posterior dominant rhythm slowing (33%). One child had electrical status epilepticus of sleep. Neuroimaging was performed in 5 children (38%) and revealed abnormal findings in 3. Seizures were drug resistant in a third of the cohort. Valproate resulted in seizure freedom in 5 (42%). Oxcarbazepine caused clinical worsening in one child with combined seizure types. Two children tried cannabidiol and one tried the ketogenic diet; neither was effective.

CONCLUSIONS

The epilepsy phenotype in children with 15q13.3 microdeletion syndrome is defined by childhood onset absence seizures, and may have atypical features such as, early onset absences, persistence into adolescence, status epilepticus, intellectual disability and treatment resistance. Focal seizures and focal EEG findings may be observed and should be treated cautiously, given the possibility of combined seizure types. Valproate appeared effective, although other treatments must be explored further.

Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy

Epilepsy diagnosis can be costly, time-consuming, and not uncommonly inaccurate. The reference standard diagnostic monitoring is continuous video-electroencephalography (EEG) monitoring, ideally capturing all events or concordant interictal discharges. Automating EEG data review would save time and resources, thus enabling more people to receive reference standard monitoring and also potentially heralding a more quantitative approach to therapeutic outcomes. There is substantial research into the automated detection of seizures and epileptic activity from EEG. However, automated detection software is not widely used in the clinic, and despite numerous published algorithms, few methods have regulatory approval for detecting epileptic activity from EEG. This study reports on a deep learning algorithm for computer-assisted EEG review. Deep convolutional neural networks were trained to detect epileptic discharges using a preexisting dataset of over 6000 labelled events in a cohort of 103 patients with idiopathic generalized epilepsy (IGE). Patients underwent 24-hour ambulatory outpatient EEG, and all data were curated and confirmed independently by two epilepsy specialists (Seneviratne et al., 2016). The resulting automated detection algorithm was then used to review diagnostic scalp EEG for seven patients (four with IGE and three with events mimicking seizures) to validate performance in a clinical setting. The automated detection algorithm showed state-of-the-art performance for detecting epileptic activity from clinical EEG, with mean sensitivity of >95% and corresponding mean false positive rate of 1 detection per minute. Importantly, diagnostic case studies showed that the automated detection algorithm reduced human review time by 80%-99%, without compromising event detection or diagnostic accuracy. The presented results demonstrate that computer-assisted review can increase the speed and accuracy of EEG assessment and has the potential to greatly improve therapeutic outcomes. This article is part of the Special Issue "NEWroscience 2018".

Spectrum of Electroencephalography Findings in Newly Diagnosed Epilepsy

Background Epilepsy is a neurological disorder that presents with recurrent seizures associated with erratic brain activity which can be measured through EEG in addition to other neurological investigations. However, EEG may show abnormal patterns and waveforms while the patient is having a seizure which is crucial for making an accurate diagnosis. Objective This study aims to evaluate the spectrum of EEG findings in newly diagnosed epileptic patients as part of a neurological investigation. Material and methods This cross-sectional study was carried out at the Department of Paediatric Neurology, the Children's Hospital, and the Institute of Child Health, Lahore for six months. A sample of 122 patients was enrolled in this study with an age range of >1 month and <18 years, with a diagnosis of epilepsy based upon ≥2 unprovoked seizures that occurred ≥ 24 hours apart. After obtaining informed consent from the patients, a one-time EEG was carried out and details were noted such as type and frequency of the discharge, site of maximum amplitude, paroxysm morphology, and onset and offset (focal/generalized) of the discharges. The data was analyzed using SPSS v.25 (IBM SPSS Statistics for Windows, Armonk, NY). Results The mean age of children enrolled in this study was 5.58 ± 3.46 years. There were 70 (57.4%) males and 52 (42.6%) females. The mean age at the onset of seizures was 4.85 ± 3.16 years. Out of 122 children, focal onset aware epilepsy type was noted in 8 cases, focal onset impaired awareness was noted in 19 cases and generalized onset motor type of epilepsy was noted in 95 cases. Furthermore, EEG findings were normal in 41 (33.61%) patients; however, 81 (66.39%) EEG findings of the patients place them in the abnormal range. On EEG, paroxysm morphology was typical in 78 (96.3%) patients while atypical in 3 (3.7%) patients. Discharge spectrum was generalized in 46 (56.8%) patients, localized in 19 (23.5%) patients, bilateral independent in 1 (1.2%) patient and multifocal in 15 (18.5%) patients. Discharge pattern was periodic in seven (8.6%) cases, rhythmic delta activity was noted in 4 (4.9%) cases, spike and wave pattern was noted in 68 (84.0%) cases and sharp and wave pattern was observed in 36 (44.4%) patients. Conclusion Our study concluded that EEG findings were abnormal in 81 (66.39%) patients. Thus to make the recommendations locally and nationally, we observed that EEG can highlight the abnormal pattern and discharges in newly diagnosed individuals with epilepsy. Our findings could be instrumental to identify the type of EEG discharges in a timely fashion while making diagnoses and treatment plan protocols accordingly. This study finding recommends the early application of EEG after the presentation of epileptic symptoms by the patient. We further recommend that further similar studies be conducted in multiple tertiary care settings to reach a firm and valuable conclusion.

When should we obtain a routine EEG while managing people with epilepsy?

More than eight decades after its discovery, routine electroencephalogram (EEG) remains a safe, noninvasive, inexpensive, bedside test of neurological function. Knowing when a routine EEG should be obtained while managing people with epilepsy is a critical aspect of optimal care. Despite advances in neuroimaging techniques that aid diagnosis of structural lesions in the central nervous system, EEG continues to provide critical diagnostic evidence with implications on treatment. A routine EEG performed after a first unprovoked seizure can support a clinical diagnosis of epilepsy and differentiate those without epilepsy, classify an epilepsy syndrome to impart prognosis, and characterize seizures for antiseizure management. Despite a current viral pandemic, EEG services continue, and the value of routine EEG is unchanged.

Electroencephalography findings in childhood epilepsy in a Saudi population: Yield, pattern and determinants of abnormality

OBJECTIVE

The study was designed to evaluate the yield, pattern, and factors that are independently associated with electroencephalography (EEG) abnormalities in childhood epilepsy in a Saudi population.

METHODS

We characterised the features of the first EEG and evaluated the associated factors in children with epilepsy in a Saudi population. The features of interictal epileptiform discharges (interictal epileptiform activity (IEA)) adopted by the International Federation of Societies for Electroencephalography and Clinical Neurophysiology were used in the study.

RESULT

A total of 756 paediatric patients, comprised of 427 men (56.5%) and 329 women (43.5%) with a clinical diagnosis of epilepsy, underwent EEG. Clinically, seizure was generalised in 619 (81.9%) patients and focal in 137 (18.1%). Among the patients, 397 (52.51%) had an abnormal EEG, while EEG was normal in 359 (47.49%) patients. Seizure frequency, gender, family history of epilepsy, and age were independent predictors of the presence of EEG abnormalities.

CONCLUSION

This study revealed a yield of 52% abnormal EEG findings in children with epilepsy. Age, gender, family history, and seizure frequency were independent predictors of the presence of EEG abnormalities in childhood epilepsy.

White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.

Clinico-electrographic characteristics and classification of genetic generalized epilepsy in Oman

PURPOSE

There is a lack of information on the annual incidence of genetic generalized epilepsy (GGE) in the Arab countries, especially Oman. Ascertaining the true burden of illness has crucial implications for health policies and priorities. We aim to study the clinico-electrographic characteristics, classification, and annual incidence of GGE in Oman.

METHOD

Using the cross-sectional data of EEGs obtained from all patients with GGE who presented to Sultan Qaboos University hospital (major referral center for epilepsy in Oman) from January 2007 to June 2014. Analyses were performed using univariate statistics.

RESULTS

Approximately 10,423 patients had EEG studies during the study period of which 376 patients (3.6 %) had EEG abnormalities suggestive of GGE. Forty two percent of the 376 GGE patients were male with ages ranging from 3 to 58 years. We were able to classify 273 patients to one of the GGE syndromes. Forty-three percent of 130 patients had a positive family history of epilepsy in their first or second-degree relatives. The generalized tonic-clonic seizure was the most common seizure type observed in 242 patients (64 %; 95 %CI: 59.2 %-68.9 %). Juvenile myoclonic epilepsy was the most common epilepsy syndrome (41 % of the total GGE patients) encountered in our region. A significant female predominance (9.7 % vs 2.5 %; p = 0.016) was observed in juvenile absence epilepsy. Certain interictal focal EEG abnormalities did not exclude a diagnosis of GGE. An average annual GGE incidence of 2.9 % (95 % CI: 2.6 %-3.2 %) was observed during the study period.

CONCLUSION

This hospital-based study is the first of its kind in the Arabian Gulf region, classifying the different subcategories of GGE. Our results indicate that GGE is a common epilepsy subtype in Oman. A prospective population-based epidemiological study is required to estimate the precise frequency of GGE in Oman.

Rapid eye movement (REM) sleep and seizure control in idiopathic generalized epilepsy

BACKGROUND

Sleep and epilepsy are bedfellows, and they affect each other reciprocally. Despite the well-known relationship between sleep and epilepsy, data about the impact of sleep on seizure control and responsiveness to therapy are scarce.

OBJECTIVE

The aim of this work was to study the impact of sleep architecture in drug-naïve patients with idiopathic generalized epilepsy (IGE) on seizure control and responsiveness to treatment.

METHODS

This is a prospective cohort study conducted on thirty newly diagnosed patients with IGE attending the epilepsy clinic in Alexandria University Hospital in Egypt and thirty healthy controls. All recruited subjects had a baseline overnight polysomnographic study, then patients were given sodium valproate in therapeutic doses and followed up for six months for assessment of seizure control. After follow-up, they were classified into fully controlled and inadequately controlled patients, and a comparison between them was made.

RESULTS

Of the recruited patients, 13 were fully controlled. Rapid eye movement (REM) sleep % was significantly lower among inadequately controlled patients (9.01 ± 6.23) than fully controlled group (19.6 ± 9.01) and controls (18.17 ± 4.85) (p = 0.002), and the REM sleep latency was significantly longer among the inadequately controlled patients (115.7 ± 72.8 min) than fully controlled patients (54.6 ± 77.3 min) and controls (68.75 ± 37.95 min) (p = 011). On univariate regression analysis, the Odd's ratio (OR) for REM sleep percentage was 3.04 (p = 0.001).

CONCLUSION

Rapid eye movement sleep percentage and latency can contribute to seizure control in IGE.

Juvenile myoclonic epilepsy shows increased posterior theta, and reduced sensorimotor beta resting connectivity

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We investigated whole brain source space connectivity in JME using across standard MEG frequency bands.

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Connectivity was increased in posterior theta and alpha bands in JME, and decreased in sensorimotor beta band.

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Our findings highlight altered interactions between posterior networks of arousal and attention and the motor system in JME.

Background

Widespread structural and functional brain network changes have been shown in Juvenile Myoclonic Epilepsy (JME) despite normal clinical neuroimaging. We sought to better define these changes using magnetoencephalography (MEG) and source space connectivity analysis for optimal neurophysiological and anatomical localisation.

Methods

We consecutively recruited 26 patients with JME who underwent resting state MEG recording, along with 26 age-and-sex matched controls. Whole brain connectivity was determined through correlation of Automated Anatomical Labelling (AAL) atlas source space MEG timeseries in conventional frequency bands of interest delta (1−4 Hz), theta (4−8 Hz), alpha (8−13 Hz), beta (13−30 Hz) and gamma (40−60 Hz). We used a Linearly Constrained Minimum Variance (LCMV) beamformer to extract voxel wise time series of ‘virtual sensors’ for the desired frequency bands, followed by connectivity analysis using correlation between frequency- and node-specific power fluctuations, for the voxel maxima in each AAL atlas label, correcting for noise, potentially spurious connections and multiple comparisons.

Results

We found increased connectivity in the theta band in posterior brain regions, surviving statistical correction for multiple comparisons (corrected p < 0.05), and decreased connectivity in the beta band in sensorimotor cortex, between right pre- and post- central gyrus (p < 0.05) in JME compared to controls.

Conclusions

Altered resting-state MEG connectivity in JME comprised increased connectivity in posterior theta – the frequency band associated with long range connections affecting attention and arousal - and decreased beta-band sensorimotor connectivity. These findings likely relate to altered regulation of the sensorimotor network and seizure prone states in JME.

Montages for Noninvasive EEG Recording

Identifying the localization, distribution, and polarity of waveforms are the prime goals of clinical scalp EEG analysis. Appropriate choices of bipolar and referential montages are keys to emphasizing the diagnostic features of interest, and demand some understanding of the spatiotemporal physical behavior of the underlying neuronal generators. Several examples drawn from canonical epilepsy syndromes are used to illustrate this general message.

Brainstem spreading depolarization and cortical dynamics during fatal seizures in Cacna1a S218L mice

Sudden unexpected death in epilepsy (SUDEP) is a fatal complication of epilepsy in which brainstem spreading depolarization may play a pivotal role, as suggested by animal studies. However, patiotemporal details of spreading depolarization occurring in relation to fatal seizures have not been investigated. In addition, little is known about behavioural and neurophysiological features that may discriminate spontaneous fatal from non-fatal seizures. Transgenic mice carrying the missense mutation S218L in the α1A subunit of Cav2.1 (P/Q-type) Ca2+ channels exhibit enhanced excitatory neurotransmission and increased susceptibility to spreading depolarization. Homozygous Cacna1aS218L mice show spontaneous non-fatal and fatal seizures, occurring throughout life, resulting in reduced life expectancy. To identify characteristics of fatal and non-fatal spontaneous seizures, we compared behavioural and electrophysiological seizure dynamics in freely-behaving homozygous Cacna1aS218L mice. To gain insight on the role of brainstem spreading depolarization in SUDEP, we studied the spatiotemporal distribution of spreading depolarization in the context of seizure-related death. Spontaneous and electrically-induced seizures were investigated by video monitoring and electrophysiological recordings in freely-behaving Cacna1aS218L and wild-type mice. Homozygous Cacna1aS218L mice showed multiple spontaneous tonic-clonic seizures and died from SUDEP in adulthood. Death was preceded by a tonic-clonic seizure terminating with hindlimb clonus, with suppression of cortical neuronal activity during and after the seizure. Induced seizures in freely-behaving homozygous Cacna1aS218L mice were followed by multiple spreading depolarizations and death. In wild-type or heterozygous Cacna1aS218L mice, induced seizures and spreading depolarization were never followed by death. To identify temporal and regional features of seizure-induced spreading depolarization related to fatal outcome, diffusion-weighted MRI was performed in anaesthetized homozygous Cacna1aS218L and wild-type mice. In homozygous Cacna1aS218L mice, appearance of seizure-related spreading depolarization in the brainstem correlated with respiratory arrest that was followed by cardiac arrest and death. Recordings in freely-behaving homozygous Cacna1aS218L mice confirmed brainstem spreading depolarization during spontaneous fatal seizures. These data underscore the value of the homozygous Cacna1aS218L mouse model for identifying discriminative features of fatal compared to non-fatal seizures, and support a key role for cortical neuronal suppression and brainstem spreading depolarization in SUDEP pathophysiology.

EEG changes in patients on antipsychotic therapy: A systematic review

OBJECTIVES

The objective of the study was to characterize the electroencephalogram (EEG) changes associated with different antipsychotic medications based on the evidence from the literature.

METHODS

A systematic search of the databases Medline, PsycINFO, and PubMed was conducted. The Preferred Items Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in the construction of this systematic review. Primary research articles that reported descriptive EEG results, included comparisons of subjects with and without antipsychotic therapy, and excluded patients with epilepsy were included in the analysis. The outcome was the presence of epileptiform discharges or slowing on EEG. We analyzed pooled data, where possible, from studies with a similar intervention and methodology.

RESULTS

Fourteen articles reporting on a total of 665 patients were reviewed. Among the publications, clozapine was the drug most consistently accompanied by EEG slowing and epileptiform discharges, with an odds ratio of 16.9 (95% confidence intervals (CI): 5.4 to 53.2) and 6.2 (95% CI: 3.4 to 11.3), respectively in the analysis of pooled data. Only one study reported a significant increase in epileptiform discharges with phenothiazine antipsychotic therapy as a group, but the impact of individual drugs was not analyzed separately.

CONCLUSIONS

This systematic review suggests that, among antipsychotics, clozapine most frequently induces EEG slowing and epileptiform discharges. There remains limited data with respect to other individual antipsychotic agents and covariates including drug dose, plasma levels, dose adjustments, and treatment duration that influence EEG changes.

Generalized polyspike train: An EEG biomarker of drug-resistant idiopathic generalized epilepsy

OBJECTIVE

To identify clinical and EEG biomarkers of drug resistance in adults with idiopathic generalized epilepsy.

METHODS

We conducted a case-control study consisting of a discovery cohort and a replication cohort independently assessed at 2 different centers. In each center, patients with the idiopathic generalized epilepsy phenotype and generalized spike-wave discharges on EEG were classified as drug-resistant or drug-responsive. EEG changes were classified into predefined patterns and compared between the 2 groups in the discovery cohort. Factors associated with drug resistance in multivariable analysis were tested in the replication cohort.

RESULTS

The discovery cohort included 85 patients (29% drug-resistant and 71% drug-responsive). Their median age at assessment was 32 years and 50.6% were female. Multivariable analysis showed that higher number of seizure types ever experienced (3 vs 1: odds ratio [OR] = 31.1, 95% confidence interval [CI]: 4.5-214, p < 0.001; 3 vs 2: OR = 14.6, 95% CI: 2.3-93.1, p = 0.004) and generalized polyspike train (burst of generalized rhythmic spikes lasting less than 1 second) during sleep were associated with drug resistance (OR = 10.8, 95% CI: 2.4-49.4, p = 0.002). When these factors were tested in the replication cohort of 80 patients (27.5% drug-resistant and 72.5% drug-responsive; 71.3% female; median age 27.5 years), the proportion of patients with generalized polyspike train during sleep was also higher in the drug-resistant group (OR = 4.0, 95% CI: 1.35-11.8, p = 0.012).

CONCLUSION

Generalized polyspike train during sleep may be an EEG biomarker for drug resistance in adults with idiopathic generalized epilepsy.

Can EEG Differentiate Among Syndromes in Genetic Generalized Epilepsy?

PURPOSE

To evaluate EEG differences among syndromes in genetic generalized epilepsy based on quantified data.

METHODS

Twenty-four-hour ambulatory EEGs were recorded in consecutive patients diagnosed with genetic generalized epilepsy. All epileptiform EEG abnormalities were quantified into density scores (total duration of epileptiform discharges per hour). One-way analysis of variance was conducted to find out differences in EEG density scores among the syndromes. Generalized linear mixed models were also fitted to explore the association between the proportion of "pure" generalized spike-wave paroxysms and fragments (without intervening polyspikes/polyspike-waves) and the syndromes.

RESULTS

In total, 6,923 epileptiform discharges were analyzed from 105 abnormal EEGs. In the analysis of variance, six EEG variables were significantly different among syndromes: total spike density (P = 0.001), total polyspike and polyspike-wave density (P = 0.049), generalized spike-wave-only density (P < 0.001), generalized paroxysm density (P < 0.001), generalized paroxysm duration mean (P = 0.018), and generalized paroxysm duration maximum (P = 0.009). The density of epileptiform discharges and the paroxysm durations were the highest in juvenile absence epilepsy followed by juvenile myoclonic epilepsy, childhood absence epilepsy, and generalized epilepsy with tonic-clonic seizures only. Generalized linear mixed models revealed that "pure" generalized spike-wave discharges (without intervening polyspikes/polyspike waves) tended to be more frequent in absence epilepsies, although the difference was not statistically significant (P = 0.21).

CONCLUSIONS

The findings of this study suggest that the density and duration of epileptiform discharges can help differentiate among genetic generalized epilepsy syndromes.

Electroencephalography abnormalities in generalized epilepsy and their predictors: A multicenter experience

Background:

In spite of the overwhelming significance of knowledge of basic elements of electroencephalography (EEG) in its application to the diagnostic workup and the management of patients with suspected or already established generalized epilepsy (GE), there is a dearth of data on the pattern and utility of clinical variables that can independently determine EEG abnormalities in GE.

Objective:

The study was designed to evaluate the frequency and pattern of EEG abnormality as well as assess the utility of clinical variables in predicting the likelihood of an abnormal EEG in GE.

Methods:

It was a cross-sectional study involving the analysis of EEGs of consecutive patients with clinical diagnosis of idiopathic GE from three centers over a 7-year period. Information on sociodemographic and seizure variables was obtained. The International Federation of Societies for Electroencephalography and Clinical Neurophysiology definition of interictal epileptiform discharges (interictal epileptiform activity [IEA]) was adopted in the study.

Results:

A total of 403 patients comprising 242 (60%) males and 161 (40%) females with clinical diagnosis of GE had EEG. Their age ranged between 2 weeks and 70 years, with a median age of 21 years and an interquartile age of 26 years. Two hundred and thirty-seven (58.8%) and 213 (52.9%) patients had abnormal EEG and IEA, respectively. Before adjustment for confounders, female gender (P = 0.0001), pediatric age group (P = 0.0388), duration of epilepsy of 1–4 years (P = 0.01387), uncontrolled seizure (P = 0.0060), and seizure frequency (P = 0.0001) were significantly associated with the presence of abnormal EEG. However, age, female gender, poor seizure control, and seizure frequencies were the independent predictors of EEG abnormality.

Conclusion:

The study showed that about 58% of patients with GE patients had abnormal EEG. Age, poor seizure control, and high frequency of seizure were independent predictors of the presence of EEG abnormality.

Characteristics of Epileptiform Discharge Duration and Interdischarge Interval in Genetic Generalized Epilepsies

We sought to investigate (1) the characteristics of epileptiform discharge (ED) duration and interdischarge interval (IDI) and (2) the influence of vigilance state on the ED duration and IDI in genetic generalized epilepsy (GGE). In a cohort of patients diagnosed with GGE, 24-h ambulatory EEG recordings were performed prospectively. We then tabulated durations, IDI, and vigilance state in relation to all EDs captured on EEGs. We used K-means cluster analysis and finite mixture modeling to quantify and characterize the groups of ED duration and IDI. To investigate the influence of sleep, we calculated the mean, median, and SEM in each population from all subjects for sleep state and wakefulness separately, followed by the Kruskal–Wallis test to compare the groups. We analyzed 4,679 EDs and corresponding IDI from 23 abnormal 24-h ambulatory EEGs. Our analysis defined two populations of ED durations and IDI: short and long. In all populations, both ED durations and IDI were significantly longer in wakefulness. Our results highlight different characteristics of ED populations in GGE and the influence by the sleep–wake cycle.

Absence Seizures as a Feature of Juvenile Myoclonic Epilepsy in Rhodesian Ridgeback Dogs

Myoclonic epilepsy in Rhodesian Ridgeback (RR) dogs is characterized by myoclonic seizures occurring mainly during relaxation periods, a juvenile age of onset and generalized tonic‐clonic seizures in one‐third of patients. An 8‐month‐old female intact RR was presented for myoclonic seizures and staring episodes that both started at 10 weeks of age. Testing for the DIRAS1 variant indicated a homozygous mutant genotype. Unsedated wireless video‐electroencephalography (EEG) identified frequent, bilaterally synchronous, generalized 4 Hz spike‐and‐wave complexes (SWC) during the staring episodes in addition to the characteristic myoclonic seizures with generalized 4–5 Hz SWC or 4–5 Hz slowing. Photic stimulation did not evoke a photoparoxysmal response. Repeat video‐EEG 2 months after initiation of levetiracetam treatment disclosed a >95% decrease in frequency of myoclonic seizures, and absence seizures were no longer evident. Absence seizures represent another seizure type in juvenile myoclonic epilepsy (JME) in RR dogs, which reinforces its parallels to JME in humans.

Electroencephalography in the Diagnosis of Genetic Generalized Epilepsy Syndromes

Genetic generalized epilepsy (GGE) consists of several syndromes diagnosed and classified on the basis of clinical features and electroencephalographic (EEG) abnormalities. The main EEG feature of GGE is bilateral, synchronous, symmetric, and generalized spike-wave complex. Other classic EEG abnormalities are polyspikes, epileptiform K-complexes and sleep spindles, polyspike-wave discharges, occipital intermittent rhythmic delta activity, eye-closure sensitivity, fixation-off sensitivity, and photoparoxysmal response. However, admixed with typical changes, atypical epileptiform discharges are also commonly seen in GGE. There are circadian variations of generalized epileptiform discharges. Sleep, sleep deprivation, hyperventilation, intermittent photic stimulation, eye closure, and fixation-off are often used as activation techniques to increase the diagnostic yield of EEG recordings. Reflex seizure-related EEG abnormalities can be elicited by the use of triggers such as cognitive tasks and pattern stimulation during the EEG recording in selected patients. Distinct electrographic abnormalities to help classification can be identified among different electroclinical syndromes.

Clinical factors associated with the yield of routine outpatient scalp electroencephalograms: A retrospective analysis from a tertiary hospital

The routine outpatient electroencephalogram (EEG) is most often used in the diagnosis and classification of epilepsy. The diagnostic yield of outpatient EEGs is low and the clinical factors contributing to the EEG outcome have not been well established. In this study, we sought to determine the yield and the factors predicting the EEG outcome. We retrospectively analyzed 1092 routine adult EEGs that were performed in a tertiary referral center over a period of 1year. Patient demographics, sources of referral, and indications for EEG were recorded. The majority of the referrals were from neurologists (54.7%), followed by the emergency department (15.4%). The indications for requesting an EEG included patients with a provisional or established diagnosis of epilepsy (56.3%), first seizure (10.7%), and seizure mimickers (29.1%). The majority (66.7%) of the EEGs were normal, whereas 13.2% demonstrated epileptiform discharges. At the time of recording, epileptic seizures occurred in 0.6% of the cases. With logistic regression analysis, three factors were found to be significantly associated with an abnormal (epileptiform) EEG: no antiepileptic drug therapy, the age of the patient, and indication for EEG (pre-test provisional diagnosis). Patients who are not on antiepileptic drug therapy and with a diagnosis of epilepsy or seizures are more likely to have epileptiform abnormalities in EEGs. Our findings suggest that careful selection of patients is likely to improve the diagnostic yield and cost-effectiveness of routine outpatient EEG.

The Cacna1h mutation in the GAERS model of absence epilepsy enhances T-type Ca2+ currents by altering calnexin-dependent trafficking of Cav3.2 channels

Low-voltage-activated T-type calcium channels are essential contributors to the functioning of thalamocortical neurons by supporting burst-firing mode of action potentials. Enhanced T-type calcium conductance has been reported in the Genetic Absence Epilepsy Rat from Strasbourg (GAERS) and proposed to be causally related to the overall development of absence seizure activity. Here, we show that calnexin, an endoplasmic reticulum integral membrane protein, interacts with the III-IV linker region of the Ca_v3.2 channel to modulate the sorting of the channel to the cell surface. We demonstrate that the GAERS missense mutation located in the Ca_v3.2 III-IV linker alters the Ca_v3.2/calnexin interaction, resulting in an increased surface expression of the channel and a concomitant elevation in calcium influx. Our study reveals a novel mechanism that controls the expression of T-type channels, and provides a molecular explanation for the enhancement of T-type calcium conductance in GAERS.