Interictal Epileptiform Discharges Research Articles

Automated sleep staging on reduced channels in children with epilepsy

ObjectivesThis study aimed to validate a sleep staging algorithm using in-hospital video-electroencephalogram (EEG) in children without epilepsy, with well-controlled epilepsy (WCE), and with drug-resistant epilepsy (DRE).MethodsOvernight video-EEG, along with electrooculogram (EOG) and chin electromyogram (EMG), was recorded in children between 4 and 18 years of age. Classical sleep staging was performed manually as a ground truth. An end-to-end hierarchical recurrent neural network for sequence-to-sequence automatic sleep staging (SeqSleepNet) was used to perform automated sleep staging using three channels: C4-A1, EOG, and chin EMG.ResultsIn 176 children sleep stages were manually scored: 47 children without epilepsy, 74 with WCE, and 55 with DRE. The 5-class sleep staging accuracy of the automatic sleep staging algorithm was 84.7% for the children without epilepsy, 83.5% for those with WCE, and 80.8% for those with DRE (Kappa of 0.79, 0.77, and 0.73 respectively). Performance per sleep stage was assessed with an F1 score of 0.91 for wake, 0.50 for N1, 0.83 for N2, 0.84 for N3, and 0.86 for rapid eye movement (REM) sleep.ConclusionWe concluded that the tested algorithm has a high accuracy in children without epilepsy and with WCE. Performance in children with DRE was acceptable, but significantly lower, which could be explained by a tendency of more time spent in N1, and by abundant interictal epileptiform discharges and intellectual disability leading to less recognizable sleep stages. REM sleep time, however, significantly affected in children with DRE, can be detected reliably by the algorithm.Clinical trial registration: ClinicalTrials.gov, identifier NCT04584385.

Mapping interictal discharges using intracranial EEG-fMRI to predict postsurgical outcomes.

Various subjective and objective methods have been proposed to identify which interictal epileptiform discharge (IED)-related EEG-fMRI results are more likely to delineate seizure generating tissue in patients with drug-resistant focal epilepsy for the purposes of surgical planning. In this intracranial EEG-fMRI study, we evaluated the utility of these methods to localize clinically relevant regions pre-operatively and compared the extent of resection of these areas to post-operative outcome. Seventy patients admitted for intracranial video-EEG monitoring were recruited for a simultaneous intracranial EEG-fMRI study. For all analyses of blood oxygen level-dependent responses associated with IEDs, an experienced epileptologist identified the most Clinically Relevant brain activation cluster using available clinical information. The Maximum cluster (the cluster with the highest z-score) was also identified for all analyses and assigned to one of three confidence levels (low, medium, or high) based on the difference of the peak z-scores between the Maximum and Second Maximum cluster (the cluster with the second highest peak z-value). The distance was measured and compared between the peak voxel of the aforementioned clusters and the electrode contacts where the interictal discharge and seizure onset were recorded. In patients who subsequently underwent epilepsy surgery, the spatial concordance between the aforementioned clusters and the area of resection was determined and compared to post-operative outcome. We evaluated 106 different IEDs in 70 patients. Both subjective (identification of the Clinically Relevant cluster) and objective (Maximum cluster much more significant than the second maximum cluster) methods of culling non-localizing EEG-fMRI activation maps increased the spatial concordance between these clusters and the corresponding IED or seizure onset zone contacts. However, only the objective methods of identifying medium and high confidence maps resulted in a significant association between resection of the peak voxel of the Maximum cluster and post-operative outcome. Resection of this area was associated with good post-operative outcomes but was not sufficient for seizure freedom. On the other hand, we found that failure to resect the medium and high confidence Maximum clusters was associated with a poor post-surgical outcome (negative predictive value = 1.0, sensitivity = 1.0). Objective methods to identify higher confidence EEG-fMRI results are needed to localize areas necessary for good post-operative outcomes. However, resection of the peak voxel within higher confidence Maximum clusters is not sufficient for good outcomes. Conversely, failure to resect the peak voxel in these clusters is associated with a poor post-surgical outcome.

The Association of Epileptic Seizures after Acute Ischemic Stroke with Cerebral Cortical Involvement and Electroencephalographic Changes

Background and objectives: while acute ischemic stroke is the leading cause of epilepsy in the elderly population, data about its risk factors have been conflicting. Therefore, the aim of our study is to determine the association of early and late epileptic seizures after acute ischemic stroke with cerebral cortical involvement and electroencephalographic changes. Materials and methods: a prospective cohort study in the Hospital of the Lithuanian University of Health Sciences Kaunas Clinics Department of Neurology was conducted and enrolled 376 acute ischemic stroke patients. Data about the demographical, clinical, radiological, and encephalographic changes was gathered. Patients were followed for 1 year after stroke and assessed for late ES. Results: the incidence of ES was 4.5%, the incidence of early ES was 2.7% and the incidence of late ES was 2.4%. The occurrence of early ES increased the probability of developing late ES. There was no association between acute cerebral cortical damage and the occurrence of ES, including both early and late ES. However, interictal epileptiform discharges were associated with the occurrence of ES, including both early and late ES.

The online educational tool "Roadmap to EEGs" significantly improved trainee performance in recognizing EEG patterns.

We created a framework to assess the competency-based EEG curriculum, outlined by the International League Against Epilepsy (ILAE) through a video-based online educational resource ("Roadmap to EEGs") and assessed its effectiveness and feasibility in improving trainees' knowledge. Ten video-based e-learning modules addressed seven key topics in EEG and epileptology (normal EEG, normal variants, EEG artifacts, interictal epileptiform discharges (IED), focal seizures, idiopathic generalized epilepsy (IGE), and developmental and epileptic encephalopathies (DEE)). We posted the educational videos on YouTube for free access. Pre- and post-tests, each comprising 20 multiple-choice questions, were distributed to institution leadership and advertised on social media platforms to reach a global audience. The tests were administered online to assess the participants' knowledge. Pre- and post-test questions showed different EEG samples to avoid memorization and immediate recall. After completing the post-test, participants were asked to respond to 7 additional questions assessing their confidence levels and recommendations for improvement. A total of 52 complete and matched pre- and post-test responses were collected. The probability of a correct response was 73% before teaching (95% CI: 70%-77%) and 81% after teaching (95% CI: 78%-84%). The odds of a correct response increased significantly by 59% (95% CI: 28%-98%, p < .001). For participants having >4 weeks of EEG training, the probability of a correct response was 76% (95% CI: .72-.79) and 81% after teaching (95% CI: .78-.84). The odds of answering correctly increased by 44% (95% CI: 15%-80%, p = .001). Participants felt completely confident in independently interpreting and identifying EEG findings after completing the teaching modules (17.1% before vs. 37.8% after, p-value < .0001). 86.5% of participants expressed a high likelihood of recommending the module to other trainees. The video-based online educational resource allows participants to acquire foundational knowledge in EEG/epilepsy, and participants to review previously learned EEG/epilepsy information.

Late-Onset Findings During Extended EEG Monitoring Are Rare in Critically Ill Children.

Electrographic seizures (ES) are common in critically ill children undergoing continuous EEG (CEEG) monitoring, and previous studies have aimed to target limited CEEG resources to children at highest risk of ES. However, previous studies have relied on observational data in which the duration of CEEG was clinically determined. Thus, the incidence of late occurring ES is unknown. The authors aimed to assess the incidence of ES for 24 hours after discontinuation of clinically indicated CEEG. This was a single-center prospective study of nonconsecutive children with acute encephalopathy in the pediatric intensive care unit who underwent 24 hours of extended research EEG after the end of clinical CEEG. The authors assessed whether there were new findings that affected clinical management during the extended research EEG, including new-onset ES. Sixty-three subjects underwent extended research EEG. The median duration of the extended research EEG was 24.3 hours (interquartile range 24.0-25.3). Three subjects (5%) had an EEG change during the extended research EEG that resulted in a change in clinical management, including an increase in ES frequency, differential diagnosis of an event, and new interictal epileptiform discharges. No subjects had new-onset ES during the extended research EEG. No subjects experienced new-onset ES during the 24-hour extended research EEG period. This finding supports observational data that patients with late-onset ES are rare and suggests that ES prediction models derived from observational data are likely not substantially underrepresenting the incidence of late-onset ES after discontinuation of clinically indicated CEEG.

A randomized controlled educational pilot trial of interictal epileptiform discharge identification for neurology residents.

To assess the effectiveness of an educational program leveraging technology-enhanced learning and retrieval practice to teach trainees how to correctly identify interictal epileptiform discharges (IEDs). This was a bi-institutional prospective randomized controlled educational trial involving junior neurology residents. The intervention consisted of three video tutorials focused on the six IFCN criteria for IED identification and rating 500 candidate IEDs with instant feedback either on a web browser (intervention 1) or an iOS app (intervention 2). The control group underwent no educational intervention ("inactive control"). All residents completed a survey and a test at the onset and offset of the study. Performance metrics were calculated for each participant. Twenty-one residents completed the study: control (n = 8); intervention 1 (n = 6); intervention 2 (n = 7). All but two had no prior EEG experience. Intervention 1 residents improved from baseline (mean) in multiple metrics including AUC (.74; .85; p < .05), sensitivity (.53; .75; p < .05), and level of confidence (LOC) in identifying IEDs/committing patients to therapy (1.33; 2.33; p < .05). Intervention 2 residents improved in multiple metrics including AUC (.81; .86; p < .05) and LOC in identifying IEDs (2.00; 3.14; p < .05) and spike-wave discharges (2.00; 3.14; p < .05). Controls had no significant improvements in any measure. This program led to significant subjective and objective improvements in IED identification. Rating candidate IEDs with instant feedback on a web browser (intervention 1) generated greater objective improvement in comparison to rating candidate IEDs on an iOS app (intervention 2). This program can complement trainee education concerning IED identification.

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity.

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework

Interictal Epileptiform Discharges (IED) and High Frequency Oscillations (HFO) in intraoperative electrocorticography (ECoG) may guide the surgeon by delineating the epileptogenic zone. We designed a modular spiking neural network (SNN) in a mixed-signal neuromorphic device to process the ECoG in real-time. We exploit the variability of the inhomogeneous silicon neurons to achieve efficient sparse and decorrelated temporal signal encoding. We interface the full-custom SNN device to the BCI2000 real-time framework and configure the setup to detect HFO and IED co-occurring with HFO (IED-HFO). We validate the setup on pre-recorded data and obtain HFO rates that are concordant with a previously validated offline algorithm (Spearman’s ρ = 0.75, p = 1e-4), achieving the same postsurgical seizure freedom predictions for all patients. In a remote on-line analysis, intraoperative ECoG recorded in Utrecht was compressed and transferred to Zurich for SNN processing and successful IED-HFO detection in real-time. These results further demonstrate how automated remote real-time detection may enable the use of HFO in clinical practice.

Thalamic stereoelectroencephalography for neuromodulation target selection: Proof of concept and review of literature of pulvinar direct electrical stimulation.

In patients with drug-resistant epilepsy (DRE) who are not candidates for resective surgery, various thalamic nuclei, including the anterior, centromedian, and pulvinar nuclei, have been extensively investigated as targets for neuromodulation. However, the therapeutic effects of different targets for thalamic neuromodulation on various types of epilepsy are not well understood. Here, we present a 32-year-old patient with multifocal bilateral temporoparieto-occipital epilepsy and bilateral malformations of cortical development (MCDs) who underwent bilateral stereoelectroencephalographic (SEEG) recordings of the aforementioned three thalamic nuclei bilaterally. The change in the rate of interictal epileptiform discharges (IEDs) from baseline were compared in temporal, central, parietal, and occipital regions after direct electrical stimulation (DES) of each thalamic nucleus. A significant decrease in the rate of IEDs (33% from baseline) in the posterior quadrant regions was noted in the ipsilateral as well as contralateral hemisphere following DES of the pulvinar. A scoping review was also performed to better understand the current standpoint of pulvinar thalamic stimulation in the treatment of DRE. The therapeutic effect of neuromodulation can differ among thalamic nuclei targets and epileptogenic zones (EZs). In patients with multifocal EZs with extensive MCDs, personalized thalamic targeting could be achieved through DES with thalamic SEEG electrodes.

Multisensory flicker modulates widespread brain networks and reduces interictal epileptiform discharges

Modulating brain oscillations has strong therapeutic potential. Interventions that both non-invasively modulate deep brain structures and are practical for chronic daily home use are desirable for a variety of therapeutic applications. Repetitive audio-visual stimulation, or sensory flicker, is an accessible approach that modulates hippocampus in mice, but its effects in humans are poorly defined. We therefore quantified the neurophysiological effects of flicker with high spatiotemporal resolution in patients with focal epilepsy who underwent intracranial seizure monitoring. In this interventional trial (NCT04188834) with a cross-over design, subjects underwent different frequencies of flicker stimulation in the same recording session with the effect of sensory flicker exposure on local field potential (LFP) power and interictal epileptiform discharges (IEDs) as primary and secondary outcomes, respectively. Flicker focally modulated local field potentials in expected canonical sensory cortices but also in the medial temporal lobe and prefrontal cortex, likely via resonance of stimulated long-range circuits. Moreover, flicker decreased interictal epileptiform discharges, a pathological biomarker of epilepsy and degenerative diseases, most strongly in regions where potentials were flicker-modulated, especially the visual cortex and medial temporal lobe. This trial met the scientific goal and is now closed. Our findings reveal how multi-sensory stimulation may modulate cortical structures to mitigate pathological activity in humans.

VEpiNet: A multimodal interictal epileptiform discharge detection method based on video and electroencephalogram data

To enhance deep learning-based automated interictal epileptiform discharge (IED) detection, this study proposes a multimodal method, vEpiNet, that leverages video and electroencephalogram (EEG) data. Datasets comprise 24 931 IED (from 484 patients) and 166 094 non-IED 4-second video-EEG segments. The video data is processed by the proposed patient detection method, with frame difference and Simple Keypoints (SKPS) capturing patients’ movements. EEG data is processed with EfficientNetV2. The video and EEG features are fused via a multilayer perceptron. We developed a comparative model, termed nEpiNet, to test the effectiveness of the video feature in vEpiNet. The 10-fold cross-validation was used for testing. The 10-fold cross-validation showed high areas under the receiver operating characteristic curve (AUROC) in both models, with a slightly superior AUROC (0.9902) in vEpiNet compared to nEpiNet (0.9878). Moreover, to test the model performance in real-world scenarios, we set a prospective test dataset, containing 215 h of raw video-EEG data from 50 patients. The result shows that the vEpiNet achieves an area under the precision–recall curve (AUPRC) of 0.8623, surpassing nEpiNet’s 0.8316. Incorporating video data raises precision from 70% (95% CI, 69.8%–70.2%) to 76.6% (95% CI, 74.9%–78.2%) at 80% sensitivity and reduces false positives by nearly a third, with vEpiNet processing one-hour video-EEG data in 5.7 min on average. Our findings indicate that video data can significantly improve the performance and precision of IED detection, especially in prospective real clinic testing. It suggests that vEpiNet is a clinically viable and effective tool for IED analysis in real-world applications.

EEG before chimeric antigen receptor T-cell therapy and early after onset of immune effector cell-associated neurotoxicity syndrome

BackgroundImmune effector cell-associated neurotoxicity syndrome (ICANS) is common after chimeric antigen receptor T-cell (CAR-T) therapy. Objective. This study aimed to assess the impact of preinfusion electroencephalography (EEG) abnormalities and EEG findings at ICANS onset for predicting ICANS risk and severity in 56 adult patients with refractory lymphoma undergoing CAR-T therapy. Study design. EEGs were conducted at the time of lymphodepleting chemotherapy and shortly after onset of ICANS. Results. Twenty-eight (50%) patients developed ICANS at a median time of 6 days after CAR-T infusion. Abnormal preinfusion EEG was identified as a risk factor for severe ICANS (50% vs. 17%, P = 0.036). Following ICANS onset, EEG abnormalities were detected in 89% of patients [encephalopathy (n=19, 70%) and/or interictal epileptiform discharges (IEDs) (n=14, 52%)]. Importantly, IEDs seemed to be associated with rapid progression to higher grades of ICANS within 24 hours. Conclusions. If confirmed in a large cohort of patients, these findings could establish the basis for modifying current management guidelines, enabling the identification of patients at risk of neurotoxicity, and providing support for preemptive corticosteroid use in patients with both initial grade 1 ICANS and IEDs at neurotoxicity onset, who are at risk of neurological impairment.

Idiopathic generalized epilepsies in the epilepsy monitoring unit: Systematic quantification of focal EEG and semiological signs

ObjectiveFocal seizure symptoms (FSS) and focal interictal epileptiform discharges (IEDs) are common in patients with idiopathic generalized epilepsies (IGEs), but dedicated studies systematically quantifying them both are lacking. We used automatic IED detection and localization algorithms and correlated these EEG findings with clinical FSS for the first time in IGE patients. Methods32 patients with IGEs undergoing long-term video EEG monitoring were systematically analyzed regarding focal vs. generalized IEDs using automatic IED detection and localization algorithms. Quantitative EEG findings were correlated with FSS. ResultsWe observed FSS in 75% of patients, without significant differences between IGE subgroups. Mostly varying/shifting lateralizations of FSS across successive recorded seizures were seen. We detected a total of 81,949 IEDs, whereof 19,513 IEDs were focal (23.8%). Focal IEDs occurred in all patients (median 13% focal IEDs per patient, range 1.1 – 51.1%). Focal IED lateralization and localization predominance had no significant effect on FSS. ConclusionsAll included patients with IGE showed focal IEDs and three-quarter had focal seizure symptoms irrespective of the specific IGE subgroup. Focal IED localization had no significant effect on lateralization and localization of FSS. SignificanceOur findings may facilitate diagnostic and treatment decisions in patients with suspected IGE and focal signs.

Termination of convulsion seizures by destabilizing and perturbing seizure memory engrams.

Epileptogenesis, arising from alterations in synaptic strength, shares mechanistic and phenotypic parallels with memory formation. However, direct evidence supporting the existence of seizure memory remains scarce. Leveraging a conditioned seizure memory (CSM) paradigm, we found that CSM enabled the environmental cue to trigger seizure repetitively, and activating cue-responding engram cells could generate CSM artificially. Moreover, cue exposure initiated an analogous process of memory reconsolidation driven by mammalian target of rapamycin-brain-derived neurotrophic factor signaling. Pharmacological targeting of the mammalian target of rapamycin pathway within a limited time window reduced seizures in animals and interictal epileptiform discharges in patients with refractory seizures. Our findings reveal a causal link between seizure memory engrams and seizures, which leads us to a deeper understanding of epileptogenesis and points to a promising direction for epilepsy treatment.

ATP1A2-related epileptic encephalopathy and movement disorder: Clinical features of three novel patients.

Variants in the ATP1A2 gene exhibit a wide clinical spectrum, ranging from familial hemiplegic migraine to childhood epilepsies and early infantile developmental epileptic encephalopathy (EIDEE) with movement disorders. This study aims to describe the epileptology of three unpublished cases and summarize epilepsy features of the other 17 published cases with ATP1A2 variants and EIDEE. Medical records of three novel patients with pathogenic ATP1A2 variants were retrospectively reviewed. Additionally, the PUBMED, EMBASE, and Cochrane databases were searched until December 2023 for articles on EIDEE with ATP1A2 variants, without language or publication year restrictions. Three female patients, aged 6 months-10 years, were investigated. Epilepsy onset occurred between 5 days and 2 years, accompanied by severe developmental delay, intellectual disability, drug-resistant epilepsy, severe movement disorder, and recurrent status epilepticus. All individuals had pathogenic variants of the ATP1A2 gene (ATP1A2 c.720_721del (p.Ile240MetfsTer9), ATP1A2c.3022C > T (p.Arg1008Trp), ATP1A2 c.1096G > T (p.Gly366Cys), according to ACMG criteria. Memantine was p) rescribed to three patients, one with a reduction in ictal frequency, one with improvement in gait pattern, coordination, and attention span, and another one in alertness without significant side effects. This study reinforces the association between ATP1A2 variants and a severe phenotype. All patients had de novo variants, focal motor seizures with impaired awareness as the primary type of seizure; of the 11 EEGs recorded, 10 presented a slow background rhythm, 7 multifocal interictal epileptiform discharges (IED), predominantly temporal IEDs, followed by frontal IED, as well as ten ictal recordings, which showed ictal onset from the same regions mentioned above. Treatment with antiseizure medication was generally ineffective, but memantine showed moderate improvement. Prospective studies are needed to enlarge the phenotype and assess the efficacy of NMDA receptor antagonist therapies in reducing seizure frequency and improving quality of life.

Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy

ObjectiveThe aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. MethodsWe developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. ResultsFor these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. ConclusionsThe proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SignificanceThese models are likely to play a key role in the mechanistic interpretation of epileptiform activity.

Iatrogenic Epileptogenicity Caused by CNS Drugs: A Short Case Series and Narrative Review

Multiple medications are known to increase epileptogenicity in patients with and without an underlying seizure disorder. Paradoxically, some of these medications include anti-seizure medications (ASMs) and other medications, such as psychotropics, that act on the central nervous system (CNS). This article aims to discuss 3 clinical cases that highlight the gamut of epileptogenic reactivity secondary to CNS drugs ranging from increased epileptogenicity in the form of interictal epileptiform discharges (IEDs) without seizures, increased epileptogenicity on electroencephalogram (EEG) with associated non-epileptic movement disorders, and frank, de novo seizures. We also analyze the relevant literature on the impact of CNS medications on epileptogenicity.

Analysis of related factors for neuropsychiatric comorbidities in children with epilepsy

ObjectiveTo analyze the risk factors affecting psychiatric behavior and study the psychobehavioral conditions of children with epilepsy.MethodWe randomly selected and enrolled 294 children with epilepsy who visited and were hospitalized in the pediatric clinic of Hebei General Hospital between January 2017 and January 2022, as the study participants. We comprehensively assessed their cognitive functions using the Gesell development schedule or Wechsler Intelligence Scales. The participants were divided into the study group (n = 123) with cognitive impairment and the control group (n = 171) with normal cognitive functions, for analysis.ResultsThere were statistically significant differences between the two groups in disease course, frequency of epilepsy, status epilepticus, and the number of antiseizure medications (ASMs) used (P < 0.05), while there were no statistically significant differences in age, gender, age of onset, form of onset, interictal epileptiform discharge, history of febrile convulsion, and the time from onset to initial visit (P > 0.05). Based on multivariate logistic regression analysis, the course of disease, frequency of onset, status epilepticus and number of ASMs used were identified as high-risk factors for cognitive impairment in children with epilepsy. Similarly, early onset, long course of disease, known etiology, and combination of multiple drugs have a negative impact on behavioral problems, school education, and social adaptability.ConclusionThe course of disease, the frequency of onset, status epilepticus, and the number of ASMs used are high-risk factors for cognitive impairment in children with epilepsy, which can be prevented and controlled early. When selecting ASMs, their advantages and disadvantages should be weighed. Moreover, the availability of alternative treatment options must be considered. With the help of genomic technology, the causes of epilepsy should be identified as early as possible, and precision medicine and gene therapy for children with epilepsy should be actively developed.

Developmental outcome of electroencephalographic findings in SYNGAP1 encephalopathy.

SYNGAP1 haploinsufficiency results in a developmental and epileptic encephalopathy (DEE) causing generalized epilepsies accompanied by a spectrum of neurodevelopmental symptoms. Concerning interictal epileptiform discharges (IEDs) in electroencephalograms (EEG), potential biomarkers have been postulated, including changes in background activity, fixation-off sensitivity (FOS) or eye closure sensitivity (ECS). In this study we clinically evaluate a new cohort of 36 SYNGAP1-DEE individuals. Standardized questionnaires were employed to collect clinical, electroencephalographic and genetic data. We investigated electroencephalographic findings, focusing on the cortical distribution of interictal abnormalities and their changes with age. Among the 36 SYNGAP1-DEE cases 18 presented variants in the SYNGAP1 gene that had never been previously reported. The mean age of diagnosis was 8 years and 8 months, ranging from 2 to 17years, with 55.9% being male. All subjects had global neurodevelopmental/language delay and behavioral abnormalities; 83.3% had moderate to profound intellectual disability (ID), 91.7% displayed autistic traits, 73% experienced sleep disorders and 86.1% suffered from epileptic seizures, mainly eyelid myoclonia with absences (55.3%). A total of 63 VEEGs were revised, observing a worsening of certain EEG findings with increasing age. A disorganized background was observed in all age ranges, yet this was more common among older cases. The main IEDs were bilateral synchronous and asynchronous posterior discharges, accounting for ≥50% in all age ranges. Generalized alterations with maximum amplitude in the anterior region showed as the second most frequent IED (≥15% in all age ranges) and were also more common with increasing age. Finally, diffuse fast activity was much more prevalent in cases with 6years or older. To the best of our knowledge, this is the first study to analyze EEG features across different age groups, revealing an increase in interictal abnormalities over infancy and adolescence. Our findings suggest that SYNGAP1 haploinsufficiency has complex effects in human brain development, some of which might unravel at different developmental stages. Furthermore, they highlight the potential of baseline EEG to identify candidate biomarkers and the importance of natural history studies to develop specialized therapies and clinical trials.

Cavernous malformation located medially and deeply in the brain may be prone to false lateralization in cavernous malformation-associated epilepsy

BackgroundCavernous malformation (CM) is a well-known cause of epilepsy. Although the location of the CM is usually consistent with the side of seizure onset, some reports have described discrepancies between results from scalp electroencephalography (EEG) and CM location. This study investigated the prevalence and features of patients showing false lateralization (FL). Particularly, we tested the hypothesis that patients showing FL were more likely to have CM in medial and deep areas of the brain than in other areas. MethodsPatients diagnosed with CM-associated epilepsy in our institution between March 2009 and March 2023 were included in this retrospective analysis. We investigated the presence or absence of FL of interictal epileptiform discharges (IEDs) or ictal discharges against MRI findings or against the true focus as determined from surgical outcomes. We compared the FL group with the non-false-lateralization group (NFL group) to clarify features of CM-associated epilepsy patients showing FL. ResultsThirty-two epilepsy patients with CM were analyzed. The frequency of FL to MRI was 10.3% for IEDs and 7.7% for ictal discharges, while the frequency of FL to true focus after removal surgery was 10.5% for IEDs and 7.7% for ictal discharges. Regarding the FL of IEDs against MRI findings, the percentage of medial and deep lesions was significantly higher in the FL group (3/3, 100%) than in the NFL group (6/26, 23.1%; p = 0.023). No significant differences in age, sex, seizure type, or size of the CM were seen between groups. ConclusionsCM-associated epilepsy can also present with FL, particularly if the location of the CM is medial and deep. Caution may be needed in determining the area for resection based solely on scalp EEG findings.