Tae-Hoon Eom

Pathogenic variants in SCN1A are associated with a broad and overlapping spectrum of epilepsies, ranging from febrile seizures and genetic epilepsy with febrile seizures plus (GEFS+) to severe developmental and epileptic encephalopathies (DEEs), most notably Dravet syndrome. SCN1A encodes the voltage-gated sodium channel α-subunit Nav1.1, which has a critical role in inhibitory interneurons. In classical loss-of-function-associated Dravet syndrome, reduced Nav1.1 function contributes to impaired inhibitory neuronal excitability and network hyperexcitability. However, SCN1A-related disorders are mechanistically heterogeneous, with gain-of-function or mixed-function pathogenic variants being associated with clinically distinct phenotypes, including early-onset DEE and familial hemiplegic migraine type 3 (FHM3). This narrative review integrates functional variant classification with genotype–function–phenotype relationships, clinical diagnosis, and phenotype-specific treatment considerations. Particular emphasis is placed on early molecular testing, careful variant interpretation, and the distinction between chronic sodium-channel-blocker avoidance in classical loss-of-function-associated Dravet syndrome and potential mechanism-informed treatment strategies for selected gain-of-function phenotypes. We also summarize emerging SCN1A-targeted approaches, including antisense oligonucleotide therapy, gene activation, and interneuron-targeted gene replacement. A clearer understanding of variant-specific mechanisms and longitudinal clinical features may improve diagnostic precision, individualized management, and the development of disease-modifying therapies for SCN1A-related epilepsies.

Electroencephalography (EEG) source localization has evolved from a technical solution to an inverse problem and into a fundamental framework for investigating large-scale brain networks. By reconstructing cortical activity from scalp-recorded signals, source-space EEG improves anatomical interpretability and reduces confounding effects of volume conduction compared with sensor-level analyses. These advances have enabled more reliable estimation of functional and effective connectivity, graph-theoretical characterization of brain networks, and the integration of machine learning for automated analysis and clinical decision support. Nevertheless, the accuracy and reproducibility of source-level analyses remain highly dependent on forward modeling, inverse algorithms, preprocessing strategies, and connectivity estimation methods. Recent methodological developments have further expanded the role of EEG source imaging in computational neuroscience, supporting applications ranging from network-based investigations of brain function to biomarker discovery and disease classification. This review summarizes the computational framework underlying source-level EEG, beginning with the forward and inverse problems and progressing through source reconstruction, connectivity analysis, graph-theoretical network modeling, and emerging machine learning and deep learning techniques. We also highlight current clinical applications and major methodological challenges, including source leakage, model uncertainty, reproducibility, and interpretability, and outline future directions for robust and clinically translatable source-level EEG analysis.

This study aimed to quantitatively assess electrophysiological changes in patients with West syndrome (WS) treated with high-dose prednisolone and vigabatrin, using standardized low-resolution brain electromagnetic tomography (sLORETA). The study included 17 infants newly diagnosed with WS. Electroencephalography (EEG) recordings were obtained before treatment and again at 4 weeks after initiating combination therapy with oral prednisolone (8 mg/kg/day) and vigabatrin (100 mg/kg/day, increased to 150 mg/kg/day if needed). Artifact-free sleep EEG epochs were analyzed using sLORETA to estimate cortical current density across delta, theta, alpha, and beta frequency bands, with statistical comparisons performed using nonparametric voxel-wise permutation testing. At 4 weeks, 11 patients (64.7%) achieved complete cessation of spasms, and hypsarrhythmia resolved in 12 patients (70.6%). sLORETA analysis revealed significant reductions in cortical current density across all frequency bands, most prominently in the delta range. These reductions were most notable in the frontal cortex, particularly in the inferior and middle frontal gyri, with additional involvement of temporal and deep cortical regions, indicating an anterior-dominant, frequency-dependent treatment effect. The suppression of low-frequency activity aligns with attenuation of the pathological slow-wave components characteristic of hypsarrhythmia, indicating that combined high-dose prednisolone and vigabatrin therapy leads to a substantial reduction in cortical hyperexcitability. These findings provide quantitative neurophysiological evidence that treatment modulates dysfunctional cortical networks in WS. Furthermore, sLORETA can be a promising method for objectively monitoring treatment response and increasing the understanding of neurophysiological mechanisms underlying developmental and epileptic encephalopathies.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by deficits in social communication and the presence of restricted, repetitive behaviors. This mini-review provides an overview of the continuum from ASD screening to early diagnosis and intervention. With the global prevalence of ASD steadily increasing, early identification, particularly during critical periods of neuroplasticity, is essential for optimizing long-term outcomes. Screening tools such as the Modified Checklist for Autism in Toddlers facilitate early detection, while multidisciplinary diagnostic evaluations guided by standardized criteria, including the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, confirm the diagnosis and assess comorbid conditions. Evidence-based early interventions that integrate behavioral, developmental, and educational strategies aim to address core symptoms, enhance adaptive functioning, and foster independence. Approaches such as applied behavior analysis, developmental relationship-based therapies, and naturalistic developmental behavioral interventions have demonstrated strong efficacy, especially when introduced during toddlerhood. Family participation is central to the success of these interventions, as it supports skill generalization and reduces caregiver stress. Despite persistent challenges related to screening accuracy and the heterogeneity of ASD, particularly in females and individuals with subtle presentations, ongoing advances in personalized interventions and diagnostic technologies underscore the importance of early, comprehensive care. This review emphasizes the critical role of timely screening, accurate diagnosis, and individualized intervention in improving the quality of life for children with ASD and their families.

Background: West syndrome is a developmental epileptic encephalopathy characterized by epileptic spasms, hypsarrhythmia, and neurodevelopmental regression. Despite well-defined clinical criteria, hypsarrhythmia remains challenging to characterize due to its disorganized nature. Recent advancements in quantitative electroencephalography (qEEG) provide a more objective approach to understanding the electrophysiology of this disorder. This study aims to use qEEG and distributed source localization to increase the understanding of hypsarrhythmia in West syndrome. Methods: This study involved 34 participants, 17 diagnosed with West syndrome (West syndrome group) and 17 healthy controls (control group). All participants underwent 30-minute sleep EEG recordings, and data were analyzed using standardized low-resolution brain electromagnetic tomography (sLORETA) to assess the current density distribution across four frequency bands (delta, theta, alpha, and beta). Statistical non-parametric analysis was performed to compare neural activity between the West syndrome and control groups. Results: Significant increases in current density were observed across all frequency bands in the West syndrome group, with the most pronounced difference found in the delta band, followed by theta, alpha, and beta bands. The most prominent changes in the delta band were noted in the right frontal lobe, particularly in the middle frontal gyrus. In the theta band, the most significant differences were observed in the right middle frontal gyrus, while the alpha and beta bands showed notable changes in the left inferior frontal gyrus and the right superior frontal gyrus, respectively. Conclusion: Our study demonstrates a significant increase in current density across all frequency bands, with the most pronounced differences observed in the delta band in patients with West syndrome. These changes exhibit a predominant anterior distribution, particularly within the frontal lobe. The findings provide new insights into the electrophysiology of hypsarrhythmia, highlighting the presence of a low-to-high and anteroposterior gradient in neuronal activity. These results contribute to the growing body of research on West syndrome and emphasizes the value of qEEG in enhancing the interpretation of hypsarrhythmia.

Objective: The long‐term effects of epilepsy surgery (ES) or vagus nerve stimulation (VNS) on antiseizure medication (ASM) usage and status epilepticus (SE) diagnosis in real‐world pediatric drug‐resistant epilepsy (DRE) populations remain unclear. This study aimed to provide a more comprehensive understanding of how VNS and ES affect ASM usage and SE manifestations in pediatric DRE. Methods: We conducted a nationwide, retrospective cohort study using the Korean Health Insurance Review and Assessment Service database from January 1, 2007, to December 31, 2022. Pediatric patients (n = 5407; VNS, n = 217; ES, n = 451). Although the VNS and ES groups had more severe epilepsy at baseline, both interventions significantly reduced ASM usage, albeit with distinct trajectories. ES led to a sharp reduction in ASM usage immediately postoperatively, followed by stabilization, with approximately one‐third of the patients discontinuing ASM by the end of follow‐up. VNS stabilized ASM usage rather than reducing it, with fewer than 10% of patients discontinuing ASM. Both interventions were associated with significant decreases in SE diagnostic rates after the intervention ( p = 0.007 and 0.02, respectively), but no statistically significant difference was found in the overall SE rates among the three groups ( p = 0.18). Significance: These findings demonstrate that VNS and CES positively impact ASM usage, reduce the incidence of SE, and underscore the need for timely intervention to optimize outcomes. Plain Language Summary: We studied children with drug‐resistant epilepsy who were treated with either vagus nerve stimulation (VNS) or brain surgery for epilepsy. We found that brain surgery often led to a large and lasting reduction in seizure medication, whereas VNS helped stabilize medication use. Both treatments were linked to fewer cases of status epilepticus, a severe type of seizure emergency. These findings suggest that VNS and surgery may help reduce medication burden and protect against serious seizures in children with hard‐to‐treat epilepsy.

Purpose: The early detection and management of dyslexia are crucial for preventing irreversible educational gaps and various negative consequences for affected students. However, diagnosing dyslexia is challenging because it requires a comprehensive assessment. Dyslexia screening tests that utilize fast, automated, computer-based technology can be useful for early identification and management. In this paper, we introduce a tablet computer-based dyslexia screening application that uses an eye-tracking system and verify its reliability.Methods: The study included 200 participants between 8 and 13 years of age from an elementary school, all of whom underwent dyslexia screening tests twice. The screening was conducted using the VisualCamp SeeSo eye-tracking Android Software Development Kit v3.0.0, implemented on Samsung Galaxy Tab S5e tablets. The eye-tracking system measured reading speed by gaze, mean gaze fixation time, gaze fixation frequency, saccadic length, and regression ratio. To assess the reliability of the two sets of measurements, the intraclass correlation coefficient (ICC) was employed.Results: Excellent reliability was found for measurements of gaze fixation frequency (ICC=0.83), gaze fixation mean time (ICC=0.82), and reading speed by gaze (ICC=0.76), and good reliability for measurements of regression ratio (ICC=0.75) and saccadic length (ICC=0.72).Conclusion: This study demonstrated that the tablet computer-based dyslexia screening application reliably measured eye movements in subjects with dyslexia. Furthermore, the application proved to be highly reliable and potentially suitable for use in clinical or school settings, eliminating the need for a laboratory environment and extensive equipment.

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders found in children and adolescents. The American Academy of Pediatrics (AAP) first published a clinical practice guideline on ADHD in 2000, which was revised in 2011 and republished together with an accompanying process-of-care algorithm. More recently, the 2019 clinical practice guideline revision was published. Since the 2011 guideline, the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5), was released. In addition, the Society of Developmental and Behavioral Pediatrics (SDBP) recently released another clinical practice guideline for complex ADHD. Although there are nonessential changes reflected in these updates, a number of changes have still been made; for example, the DSM-5 criteria lowered the diagnostic threshold for ADHD in older teens and adults. Additionally, the criteria were revised to facilitate application to older teens and adults, and a comorbid diagnosis with autism spectrum disorder is now allowed. Meanwhile, the 2019 AAP guideline added the recommendation related to comorbid conditions with ADHD. Lastly, SDBP developed a complex ADHD guideline, covering areas such as comorbid conditions, moderate-to-severe impairment, treatment failure, and diagnostic uncertainty. In addition, other national ADHD guidelines have been published, as have European guidelines for managing ADHD during the coronavirus disease 2019 pandemic. To facilitate ADHD management in a primary care, it is important to provide and review clinical guidelines and recent updates. In this article, we will review and summarize the recent clinical guidelines and their updates.

Electroencephalography (EEG) has been and is still widely used in brain function research. EEG has advantages over other neuroimaging modalities. First, it not only directly images the electrical activity of neurons; it has a higher temporal resolution. Furthermore, current advanced technologies enable accurate mathematical calculations and sophisticated localization from EEG data. Several important factors should be considered for EEG analysis using these advanced technologies. First, raw EEG data contain physiological or nonphysiological artifacts. Therefore, preprocessing methods and algorithms to detect and remove these artifacts have been proposed and developed. In the analysis of preprocessed EEG, forward and inverse problems require solving and several proposed models have been applied. To solve the forward problem, the source information and matrix parameters from which the EEG originates are essential. Therefore, an accurate head model is required. In contrast, the possible combinations of the current sources computed inversely from EEG measured at a limited number of electrodes are infinite, referring to the inverse problem. The inverse problem can be solved by setting limits based on assumptions made of the anatomy and physiology on the generation and propagation of the current sources. Thus, methods such as dipole source models and distributed source models have been proposed. Source localization requires the consideration of many factors such as the preprocessing of raw EEG data, artifact removal, accurate head models and forward problems, and inverse computation problems. This review summarizes the methods and considerations applied to the above EEG source localization process. It also introduces the applications of EEG source localization for epilepsy and other diseases as well as brain function studies and discusses future directions.

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.