Search Results (3,259)

Background/Objectives: Post-traumatic epileptogenesis is a frequent and clinically relevant consequence of traumatic brain injury (TBI), often contributing to worsened neurological and functional outcomes. In patients experiencing early post-injury seizures, rehabilitative strategies that support recovery while considering increased epileptogenic risk are needed. This case study explores the potential benefits of combining neurofeedback (NFB) with motor therapy on cognitive and motor recovery. Methods: A patient hospitalized for severe TBI who experienced an acute symptomatic seizure in the early post-injury phase underwent baseline quantitative EEG (qEEG), neuromotor, functional, and neuropsychological assessments. The patient then completed a three-week rehabilitation program (five days/week) including 30 sensorimotor rhythm (SMR) NFB sessions (35 min each) combined with daily one-hour motor therapy. qEEG and clinical assessments were repeated post-intervention and at 6-month follow-up. Results: Post-intervention qEEG showed significant reductions in Delta and Theta power, reflecting decreased cortical slowing and enhanced neural activation. Relative power analysis indicated reduced Theta activity and Alpha normalization, suggesting improved cortical stability. Increases were observed in Beta and High-beta activity, alongside significant reductions in the Theta/Beta ratio, consistent with improved attentional regulation. Neuropsychological outcomes revealed reliable improvements in global cognition, memory, and visuospatial abilities, mostly maintained or enhanced at follow-up. Depressive and anxiety symptoms decreased markedly. Motor and functional assessments demonstrated meaningful improvements in motor performance, coordination, and functional independence. Conclusions: Findings suggest that integrating NFB with motor therapy may support recovery processes and be associated with sustained neuroplastic changes in the early post-injury phase after TBI, a condition associated with elevated risk for post-traumatic epilepsy. Full article

Background/Objectives: Asthma, type 1 diabetes mellitus (T1DM), and epilepsy are prevalent chronic diseases among school-aged children, affecting safety, attendance, and academic performance. This systematic review evaluated school teachers’ knowledge, attitudes, and preparedness regarding these conditions and identified gaps that hinder effective management and inclusion. Methods: Following PRISMA guidelines, PubMed, Cochrane Library, Scopus, and Google Scholar were searched between 20 September and 9 October 2025. Forty-nine quantitative cross-sectional studies assessing teachers’ knowledge, attitudes, or preparedness toward asthma, T1DM, or epilepsy were included. The AXIS tool assessed methodological quality, focusing on clarity of objectives, sample justification, ethical transparency, and instrument validation. Results: Teachers’ knowledge was generally moderate and varied by region. Studies on epilepsy (n = 21) highlighted misconceptions and limited understanding of seizure first aid. Diabetes studies (n = 9) indicated moderate awareness but insufficient preparedness for hypoglycemia and insulin management. Asthma studies (n = 19) revealed inconsistent knowledge, particularly regarding symptom recognition and emergency response. AXIS assessment identified recurring limitations, including unjustified sample sizes, limited instrument validation, and poor reporting of non-responders. Conclusions: These findings emphasize the need to enhance school preparedness through targeted, evidence-based teacher training, clear health policies and emergency protocols, awareness and inclusion initiatives, improved collaboration among teachers, parents, and healthcare providers, and strengthened school health infrastructure. Addressing these areas is critical to ensure safe, inclusive, and supportive learning environments for children with chronic illnesses. Full article

Background/Objectives: Glucose Transporter 1 Deficiency Syndrome (GLUT1-DS) is a neurodevelopmental disorder caused by mutations in the gene encoding glucose transporter 1 (GLUT1), which leads to impaired glucose transport into the brain and is characterized by drug-resistant epilepsy. Limited glucose supply disrupts neuronal and astrocytic energy homeostasis, but how hypometabolism translates into network hyperexcitability remains poorly understood. Here, we used induced pluripotent stem cells (iPSCs)-derived brain organoids to examine how reduced metabolic substrate availability shapes epileptiform dynamics in human neuronal circuits from GLUT1-DS. Methods: Brain organoids were generated from a healthy donor or a GLUT1-DS patient and interfaced with multielectrode arrays (MEA) for recording of neuronal activity. A unified Python (v3.10)-based analytical pipeline was developed to quantify spikes, bursts, and power spectral density (PSD) across frequency bands of neuronal activity. Organoids were challenged with reduced glucose, pentylenetetrazol (PTZ), potassium chloride (KCl), and tetrodotoxin (TTX) to assess metabolic and pharmacological modulation of excitability. Results: GLUT1-DS organoids exhibited elevated baseline hyperexcitability compared to healthy control, characterized by increased spike rates, prolonged bursts, increased spikes per burst, and elevated PSD. Reduced glucose availability further amplified these features selectively in GLUT1-DS. Conclusions: Human brain organoids reproduce the pathological coupling between hypometabolism and hyperexcitability in GLUT1-DS. Our platform provides a mechanistic model and quantification tool for evaluating metabolic and anti-epileptic therapeutic strategies. Full article

Scalp high-frequency oscillations (HFOs) are promising noninvasive biomarkers of epileptogenicity, but their phenotypic diversity and clinical relevance in absence epilepsy (AE) remain unclear. This study aimed to classify scalp HFOs in AE using k-means clustering based on multiple morphological characteristics, and to evaluate their distribution across electroencephalogram (EEG) epochs and seizure control statuses. We analyzed scalp EEG recordings from 14 children and adolescents with AE. After excluding outliers, 163 scalp HFOs were characterized by average frequency, duration, amplitude, and number of cycles. Amplitude and cycle count were log-transformed prior to clustering, and k-means clustering was applied to identify distinct HFO phenotypes. Three clusters were identified: Cluster 1 (short duration, low amplitude), Cluster 2 (low frequency), and Cluster 3 (long duration, high cycle count). Cluster 2 and Cluster 3 were significant predictors of ictal HFOs in active AE, with odds ratios (ORs) of 0.33 (95% confidence interval [CI]: 0.14–0.74) and 5.00 (CI: 2.02–17.73), respectively. Cluster 2 also predicted interictal HFOs in active AE (OR [95% CI] = 2.71 [1.23–5.67]). These findings support the utility of scalp HFO phenotypes as EEG-based biomarkers for seizure detection and disease monitoring, potentially guiding treatment strategies in pediatric AE. Full article

Sleep disturbances are prevalent among children receiving pediatric palliative care (PPC) and have a substantial negative impact on the quality of life of both patients and their families. This scoping review aims to examine further key factors contributing to sleep disturbances in PPC by analyzing available clinical studies, focusing on child-related aspects such as pain, repositioning, and epilepsy, as well as environmental factors such as light, noise, and the care setting. In addition, we discuss the critical role of interdisciplinary collaboration in improving sleep outcomes for this population and provide clinical implications. Future research should prioritize developing evidence-based interventions to optimize sleep and enhance the well-being of children with PPC needs and their caregivers. Full article

Background/Objectives: Drug-resistant epilepsy (DRE) is a significant health problem leading to cognitive impairment and reduced quality of life. This study aimed to investigate the incidence and etiology of DRE in children in Estonia. Methods: A retrospective, population-based study of childhood DRE was conducted in Estonia from 1 January 2013, to 31 December 2017. All cases were identified through the only two pediatric neurology departments in the country, both located at tertiary care hospitals (Tartu University Hospital and Tallinn Children’s Hospital), ensuring complete nationwide coverage. Epidemiological, magnetic resonance imaging (MRI), and genetic data (chromosomal microarray, single-gene tests, gene panels, and exome/genome sequencing) were collected. Results: The incidence rate of childhood epilepsy was 84.1 per 100,000. DRE developed in 10% of children with new-onset epilepsy, corresponding to an incidence rate of 8.5 per 100,000. Etiologically relevant MRI abnormalities were identified in 43% of patients with DRE, most commonly congenital brain malformations (19%). Pathogenic single-gene sequence variants were detected in 25 of 110 patients (23%), copy number variants in four patients (4%), and chromosomal aberrations in one patient (1%). Novel candidate disease genes of uncertain pathogenicity were identified in four patients (4%). The most frequent etiology of DRE was structural (29%), followed by genetic (19%), with combined etiologies (13%) also contributing significantly. Conclusions: Our study is the first epidemiological study of DRE in children in Estonia and the Baltic region. The relatively low incidence observed may reflect the comprehensive national ascertainment and centralized management of pediatric epilepsy in tertiary care centers. Full article

Malformations of cortical development (MCD) are a group of neurodevelopmental disorders caused by abnormalities in cerebral cortex development, leading to conditions such as intellectual disability and refractory epilepsy. The prenatal phenotypes of MCD are complex and non-specific, complicating accurate diagnosis and prognosis assessment. Genetic testing, particularly chromosomal microarray analysis (CMA) and whole-exome sequencing (WES), has become an important tool for prenatal diagnosis. This review synthesizes current research on prenatal MCD, focusing on the integration of imaging and genetic diagnostic strategies based on the biological foundation of cortical development and the classification system of MCD. Prenatal MCD phenotypes show significant developmental stage clustering, with proliferation-phase abnormalities (62.9%) being the most common and microcephaly as the core phenotype. Genetic studies have revealed a high degree of genetic heterogeneity in MCD, with etiologies encompassing chromosomal abnormalities and a wide range of single-gene mutations. These mutations are clustered by phenotype: microcephaly is associated with neuronal proliferation/DNA repair genes; macrocephaly is driven by genes in the PI3K-AKT-mTOR and RAS-MAPK signaling pathways; and gyral and sulcal abnormalities are closely linked to microtubule-associated genes and migration pathways. De novo mutations account for the majority of pathogenic genetic alterations identified in MCD (50.6%); up to 75.1% of pathogenic mutations cannot be detected by routine prenatal screening. Based on this, the review emphasizes that for fetuses with suspected MCD, NGS, with WES at its core, plays an increasingly important role in achieving early and accurate prenatal diagnosis. Future research should prioritize the advancement of integrated diagnostic methods and large-scale cohort studies to further elucidate genotype–phenotype associations. Full article

Background/Objectives: Speech and language delay (SLD) is one of the most prevalent developmental conditions in childhood, with post-pandemic data indicating a notable increase in identified cases. Within this group, expressive language disorder (ELD) frequently appears alongside neurodevelopmental disorders such as autism spectrum disorder (ASD), epilepsy, and intellectual disability. Although awareness of ELD has grown, the role of genetic testing in its evaluation remains unclear, as such testing is not routinely pursued for isolated expressive language concerns. This gap highlights the need to better define the diagnostic value of genetic analysis and to examine the interval between an ELD diagnosis and the return of genetic testing results. Methods: This study investigated genetic contributions to ELD using the National Brain Gene Registry (BGR), a multisite database of rare neurodevelopmental disorders. Participants with ICD-10 code F80.1 were identified through electronic health records; demographic data, comorbidities, genetic variants, inheritance patterns, age at diagnosis, and timing of interventions were analyzed. Results: Of 687 BGR participants, 32 (4.7%) had documented ELD. The cohort, aged 3–19 years, presented with common comorbidities like developmental delays, ASD, epilepsy, and hypotonia. Across 42 genes, 49 unique variants were identified: 26 pathogenic or likely pathogenic, 22 variants of uncertain significance, and one benign variant. Seventeen variants were de novo, and 10 participants carried multiple variants. Most children (80%) received an expressive language diagnosis prior to genetic testing, with reports returned an average of 1.5 years following the diagnosis. Conclusions: Overall, children with ELD commonly carry genetic variants and neurodevelopmental comorbidities, yet genetic testing is typically pursued well after diagnosis and does not currently alter early management. These findings underscore the need for clearer, evidence-based guidelines to define when genetic testing adds diagnostic or prognostic value in the evaluation of ELD. Full article

Background/Objectives: Edwardsiella tarda is a rare Gram-negative pathogen that uncommonly infects humans. Neonatal infections are extremely rare but often severe, with a high incidence of central nervous system (CNS) complications. Case presentation: We report a term neonate born via spontaneous vaginal delivery who developed systemic signs of infection within 18 h of life. Blood and cerebrospinal fluid (CSF) cultures grew Edwardsiella tarda. CSF analysis revealed severe meningoencephalitis. Maternal stool culture was also positive for E. tarda, suggesting vertical transmission. Despite initial systemic antibiotic therapy with ampicillin, gentamicin, and ceftriaxone, neuroimaging revealed progressive multifocal brain abscesses. The infant underwent a series of neurosurgical procedures, including bilateral drainage of abscesses, Rickham reservoir placement and ventriculoperitoneal shunting. A revised antibiotic regimen, including systemic meropenem and trimethoprim-sulfamethoxazole plus intrathecal gentamicin, was administered. At six months, the infant showed mild motor delay with lower limb hypertonia and was under close neurosurgical and developmental follow-up. Methods: We conducted a literature review of 12 published neonatal E. tarda infections, including our case. Results: Most infected infants presented within 72 h of life and exhibited CNS involvement. Mortality was 25%, and 44% of survivors experienced long-term neurologic sequelae. Conclusions: Edwardsiella tarda infection in neonates is rare but potentially devastating. Early suspicion, culture confirmation, aggressive antibiotic therapy, and multidisciplinary care, including neurosurgical management, are essential for improving outcomes. Full article

Background: Standard ketogenic diets (KD) and fish oil have established efficacy for drug-resistant epilepsy (DRE), but adherence and variability remain challenging. Objective: The objective of this study is to provide the first systematic evaluation of clinical evidence for emerging dietary interventions for epilepsy—specifically those other than standard KD and fish oil—and to rigorously evaluate their effectiveness and certainty of evidence to address the current gap in dietary management literature. Unlike prior reviews focused on standard KD or carbohydrate-modified versions, this study is the first to synthesize evidence for “non-standard” interventions—including olive oil-based KDs, probiotics, and restrictive gluten/glutamate-free diets—which are typically excluded from traditional dietary meta-analyses. Methods: Following PRISMA 2020 guidelines, we searched PubMed, Web of Science, Cochrane, and Google Scholar up to March 2025. Randomized Controlled Trials (RCTs) and Non-Randomized Studies of Interventions (NRSIs) were included, with quality assessed using RoB 2 and ROBINS-I tools. Results: Eight studies (total n = 675) were identified, comprising 2 RCTs and 6 NRSIs. These included olive oil-based KDs (n = 1), probiotic/synbiotic supplementation (n = 2), medium-chain triglyceride (MCT) additions (n = 2), and gluten-free (n = 1) or glutamate-free (n = 1) diets. Evidence quality is generally low, with 75% of studies at high risk of bias. Preliminary responder rates reached 83.1% in uncontrolled olive oil-based KD studies, whereas the only RCT evaluating a low-glutamate diet showed no significant seizure reduction (p = 0.57). Conclusion: Evidence for emerging dietary interventions beyond standard KD is nascent and of low certainty. Interpretation: While preliminary signals exist for olive oil-based KDs and probiotics, current data are insufficient for clinical recommendation; this review identifies these as promising exploratory targets requiring validation through rigorous, blinded RCTs. Full article

This paper presents a modular mathematical model of neuronal activity, designed to simulate the dynamics of main molecular targets of antiepileptic drugs and their pharmacological effects. The model was developed based on several existing synaptic transmission models that capture cellular processes crucial to the pathology of epilepsy. It incorporates the primary molecular mechanisms involved in regulating excitation and inhibition within the neural network. Special attention is given to the dynamics of ion currents (Na⁺, K⁺, Ca²⁺), receptors (AMPA, NMDA, GABA_A, GABA_B and mGlu), and neurotransmitters (glutamate and GABA). Examples of simulations illustrating the inhibitory effects on synaptic transmission are provided. The numerical results are consistent with experimental data reported in the literature. Full article

Religious experiences represent a universal and timeless phenomenon that has accompanied humanity since its origins. In recent decades, neuroscience has explored the relationship between temporal lobe epilepsy (TLE) and hyperreligiosity phenomena, describing sudden convictions, states of ecstasy, and spiritual conversions associated with epileptic seizures. This article offers a narrative review of the literature on the relationship between epilepsy and religion, including its clinical manifestations (ictal, postictal, and interictal) and the main neurobiological models proposed to explain it, such as the limbic marker hypothesis and theory of mind (ToM). The possible role of the uncinate fasciculus as an integrative pathway between temporal and limbic regions is also explored, based on recent neuroimaging studies. Finally, we present an illustrative clinical case of a patient with meningioma and TLE associated with episodes of intense religious conviction, in whom a structural alteration of the right uncinate fasciculus was observed. This case reinforces the relevance of considering both neuronal networks and white matter tracts in the study of religious experiences, while underscoring the need for broader and more systematic studies to confirm these findings. Full article

Mutual interaction between the nervous and immune systems underpins many pathophysiological processes. Transient Receptor Potential Melastatin 2 (TRPM2) channels are abundantly expressed in both systems, acting as a critical interface of neuroimmune interaction. TRPM2 channels in immune cells participate in innate immunity and immune inflammation by acting as an oxidative stress and metabolic sensor. TRPM2 in neurons functions not only as an oxidative sensor but also a temperature sensor and a pain transducer critical to neuronal death, temperature sensing, thermoregulation, and chronic pain. Cooperation between immune and neuronal TRPM2 influences the outcome of neuroimmune interaction and many diseases such as infection, inflammation, ischemic stroke, pain, and neurodegenerative diseases. Improved understanding of neuronal and immune TRPM2 interaction is essential for therapeutic interventions for the treatment of diseases mediated by TRPM2 channels. Full article

Cardiolipin (CL), a unique dimeric phospholipid predominantly enriched in the inner mitochondrial membrane, is a crucial determinant of mitochondrial structure and function. Its content, fatty acyl composition, and oxidation state are associated with mitochondrial bioenergetics, dynamics, and cellular signaling. Disruptions in CL metabolism are increasingly implicated in the pathogenesis of various central nervous system (CNS) disorders, including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, epilepsy, and traumatic brain injury. This narrative review summarizes recent advances in the analytical techniques employed for CL analysis. The principles and applications of mass spectrometry-based platforms, nuclear magnetic resonance, Fourier-transform infrared spectroscopy, atomic force microscopy-infrared spectroscopy, and fluorescent probes were discussed, with an emphasis on their strengths in revealing the structure, composition, dynamics, and spatial distribution of CL. Furthermore, the evidence of CL abnormalities in various CNS disorders was assessed, often showing decreased CL levels, loss of polyunsaturated species, and increased oxidation associated with mitochondrial dysfunction and neuronal apoptosis. Furthermore, the nutritional interventions for CL modulation were discussed, such as polyunsaturated fatty acids, polyphenols, carotenoids, retinoids, alkaloids, and triterpenoids, which summarize their potential health-beneficial effects in remodeling the CL acyl chain, preventing oxidation, and regulating mitochondrial homeostasis. Overall, this review provided insight into integrating CL analysis and dietary modulation in understanding CL-related pathologies in CNS disorders. Full article

Infantile Epileptic Spasms Syndrome (IESS) is a devastating epileptic encephalopathy of infancy that carries a high risk of lifelong neurodevelopmental disability. Timely diagnosis is critical, as every week of delay in effective treatment is associated with worse cognitive outcomes. Although synchronized electroencephalogram (EEG) and surface electromyography (EMG) recordings capture both the electrophysiological and motor signatures of spasms, accurate automated detection remains challenging due to the non-stationary nature of the signals and the absence of physiologically plausible inter-modal fusion in current deep learning approaches. We introduce IESS-FusionNet, an end-to-end dual-stream framework specifically designed for accurate, real-time IESS detection from simultaneous EEG and EMG. Each modality is processed by a dedicated Unimodal Encoder that hierarchically integrates Continuous Wavelet Transform, Spatio-Temporal Convolution, and Bidirectional Mamba to efficiently extract frequency-specific, spatially structured, local and long-range temporal features within a compact module. A novel Cross Time-Mixing module, built upon the linear recurrent attention of the Receptance Weighted Key Value (RWKV) architecture, subsequently performs efficient, time-decaying, bidirectional cross-modal integration that explicitly respects the causal and physiological properties of cortico-muscular coupling during spasms. Evaluated on an in-house clinical dataset of synchronized EEG-EMG recordings from infants with confirmed IESS, IESS-FusionNet achieves 89.5% accuracy, 90.7% specificity, and 88.3% sensitivity, significantly outperforming recent unimodal and multimodal baselines. Comprehensive ablation studies validate the contribution of each component, while the proposed cross-modal fusion requires approximately 60% fewer parameters than equivalent quadratic cross-attention mechanisms, making it suitable for real-time clinical deployment. IESS-FusionNet delivers an accurate, computationally efficient solution with physiologically inspired cross-modal fusion for the automated detection of infantile epileptic spasms, offering promise for future clinical applications in reducing diagnostic delay. Full article