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Familial focal epilepsy with variable foci (FFEVF) is a genetic epilepsy disorder in which affected family members experience different focal seizures. Focal cortical dysplasia (FCD) is a frequent cause of drug-resistant epilepsy in the pediatric population. Patients with focal epilepsy are less frequently referred for presurgical evaluation when FCD is not identified on MRI or when they have genetic epilepsy. The authors describe the successful surgical management of 3 drug-resistant FFEVF patients who initially had either negative or inconclusive MRI studies. All 3 patients carried the same germline pathogenic variant in NPRL3, a GATOR1 complex gene. In patient 1, an ill-defined signal abnormality on MRI raised the suspicion for FCD and suggested that similar occult lesions might underlie the epilepsy of her relatives, whose scan results were initially reported as negative. Each patient was thus referred for comprehensive presurgical evaluation. Through the use of advanced neuroimaging, epileptogenic zones were identified in all 3 patients, allowing for targeted resection. At the last follow-up, all had remained seizure free for more than 5 years. When a genetic alteration is associated with FCD, such patients warrant imaging reexamination and exhaustive presurgical evaluation with advanced neuroimaging, as eventual lesion detection and subsequent resection can lead to long-term seizure freedom. https://thejns.org/doi/10.3171/CASE26127.

Geomagnetic activity (GMA), particularly during auroras, has emerged as an intriguing area of research due to its potential health impact. Prior studies indicate that fluctuations in geomagnetic fields can affect diverse physiological and psychological outcomes. The aim of this article is to comprehensively review the impact of GMA on neurological health with an emphasis on implications for patients potentially undergoing a neurosurgical procedure or neurologic/psychiatric assessment. A comprehensive literature review was therefore performed, examining peer-reviewed articles sourced from PubMed and Google Scholar. The focus was on evaluating potential correlations between geomagnetic disturbances (GMDs) and a range of health outcomes, particularly in relation to neurosurgical, neurological and neuropsychiatric contexts. Reported associations included: increased seizure frequency in patients with epilepsy, sleep disturbances affecting recovery, and cognitive impairments that may complicate patient consent processes. Additionally, heightened stress and anxiety levels during geomagnetic storms could pose challenges for patient management in surgical settings. This review underlines that such disturbances can potentially result in significant postoperative complications, particularly in the elderly, necessitating enhanced monitoring and tailored care strategies. Understanding the diverse effects of GMA on health is essential for optimizing patient outcomes, particularly in surgical procedures. This review highlights the need for further research to elucidate underlying GMA-triggered molecular mechanisms and establish evidence-based guidelines that consider geomagnetic conditions in neurological/neuropsychiatric evaluations, surgical planning and postoperative care, especially for vulnerable populations. An enhanced awareness among neurosurgeons, psychiatrist, neurologist and healthcare providers is essential to mitigate potential adverse effects of GMA on patient health and optimize recovery. Geomagnetic storms derive from temporary disturbances of the earth's magnetosphere that are driven by solar interactions and often are associated with visually spectacular exhibitions of colorful light in the Earth's atmosphere–termed the “Northern and Southern Lights” (auroras). These storms and their associated auroras are principally observed in high‐latitude regions (around the Arctic and Antarctic circles). However, recently they are being routinely witnessed across northern Europe, North America, and parts of the Southern Hemisphere, including New Zealand, South Africa and South America. Our review article evaluates the available scientific literature–with a focus on neurological perspectives, the need for further research to elucidate underlying mechanisms and to establish evidence‐based guidelines that consider geomagnetic conditions in neurological/neuropsychiatric evaluations, surgical planning and postoperative care, particularly for vulnerable populations like the elderly. Previous studies have indicated a link between geomagnetic activity and various health outcomes, including an increase in seizure activity and mood disorders. However, comprehensive literature evaluations addressing the impacts on neurological and neurosurgical patients are lacking. This review provides a critical examination of the implications of geomagnetic activity on neurological health and surgical outcomes, emphasizing the need for awareness among healthcare providers to optimize patient management.

To systematically review evidence on the effects of temperature manipulation on transcranial magnetic stimulation (TMS)-derived measures of cortical excitability in healthy individuals and temperature-sensitive neurological conditions. Following PRISMA guidelines, we searched PubMed, Cochrane Library, EMBASE, and MEDLINE through November-December 2025. Studies reporting quantitative TMS-EMG or TMS-EEG outcomes after experimentally induced, non-noxious temperature changes were included. Parallel searches examined healthy populations and six temperature-sensitive neurological conditions. Twenty-one studies in healthy individuals (n = 360, mean age 30.9 ± 5.7 years) and one study in multiple sclerosis (MS) met inclusion criteria. Temperature manipulations included whole-body (core changes -2.4 °C to +1.5 °C) and focal interventions (-22 °C to +18 °C). Most studies reported no significant effects on motor evoked potential (MEP) amplitude (73.3%), latency (71.4%), cortical silent period (85.7%), or paired-pulse measures (100%). Effect directions were inconsistent in studies reporting significant findings. The single MS study demonstrated heat-induced impairment, with increased motor threshold and decreased MEP amplitude, not observed in controls. Experimental TMS studies largely show null effects of temperature on cortical excitability in healthy individuals, contrasting with epidemiological evidence of temperature-related neurological vulnerability. This discrepancy likely reflects modest brain temperature changes, peripheral confounds, and limited ecological validity of current paradigms. There is a critical need for climate-relevant experimental designs incorporating sustained thermal exposure and direct cortical readouts (e.g., TMS-EEG) in temperature-sensitive populations to elucidate mechanisms of thermal vulnerability.

Neurodevelopmental disorders (NDDs), including Autism Spectrum Disorder (ASD), Fragile X syndrome (FXS), and Rett Syndrome (RTT), share impairments in cognitive and behavioral functioning and may involve an altered excitatory/inhibitory balance modulated by the endocannabinoid system. This systematic review evaluated the safety and efficacy of cannabinoid-based products (CBPs) in these pediatric NDDs. We conducted a systematic review according to Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) 2020, including randomized and nonrandomized studies of patients under 18 years treated with cannabidiol (CBD), cannabidivarin (CBDV), tetrahydrocannabinol (THC), or their combinations. Outcomes were adverse events (AEs) and treatment discontinuation, seizure reduction, and behavioral and cognitive changes. Study quality and certainty of evidence were assessed using design-specific risk-of-bias tools and the GRADE approach. Seventeen studies (two randomized controlled trials, observational studies, and case series) met the inclusion criteria. Across diagnoses, CBPs were generally associated with mild-to-moderate AEs and low discontinuation rates. Descriptive pooled proportions suggested behavioral improvements in ASD and FXS and seizure reduction in RTT, with exploratory analyses indicating differential effects of CBD versus CBD + THC on behavioral and cognitive outcomes in ASD. CBPs may offer potential benefits for selected behavioral symptoms and comorbid epilepsy in pediatric NDDs, but current evidence is insufficient to support routine clinical use. High-quality randomized controlled trials with standardized outcome measures and long-term follow-up are needed to clarify efficacy, safety, and syndrome-specific effects.

Deep learning is increasingly explored to support decision-making in epilepsy surgery, yet evidence for implementation across the epilepsy surgery pathway remains limited. We conducted a scoping review of 145 studies published between January 2018 and May 2025 to map deep learning enabled decision support systems across surgical stages and clinical tasks, characterize datasets by modality, size, geographic provenance and accessibility, and synthesize modeling practices, external validation and workflow integration. The literature is heavily concentrated in the pre-operative stage, with no included intra-operative studies and relatively few post-operative applications. Most studies rely on small, single-center and non-public datasets and use supervised CNN-based models. External validation and workflow-integrated evaluation are uncommon, and only a minority of systems report semi-integrated clinical workflows. These findings highlight key gaps in generalizability, workflow readiness and equity, and inform priorities for multi-center data resources, rigorous cross-site evaluation and clinically meaningful endpoints to enable safe, scalable adoption.

BackgroundEpilepsy is a common pediatric diagnosis, and recent national and international efforts aim to improve care for neurologic conditions. This study examined initial clinical differences between English- and Spanish-speaking pediatric epilepsy patients.MethodsWe used single-center retrospective analysis of pediatric English- and Spanish-speaking patients with epilepsy. Demographic information was recorded. Initial encounters and subsequent care for the first 6 months were reviewed. Wilcoxon rank sum tests, Fisher exact tests, and multivariable logistic regression were used.ResultsA total of 118 English-speaking and 112 Spanish-speaking patients met the inclusion criteria. Epilepsy classification, presenting seizure type, initial encounter location, medications prescribed, and subjective seizure improvement rates did not differ between language cohorts. Differences between language cohorts were seen in communication rates and medication trials. Some differences were found depending on race within Spanish-speaking populations.ConclusionDespite many similarities in care, institutional processes-specifically our triage differences for English- and Spanish-speaking patients-may explain differences in contact rates and medications trials with similar rates of seizure improvement. The intersection of race within Spanish-speaking patients with epilepsy should be explored further.

Infantile Epileptic Spasms Syndrome (IESS) represents a severe form of developmental epileptic encephalopathy in infancy, characterized by clusters of spasms and hypsarrhythmia patterns on electroencephalogram (EEG), which often lead to long-term neurodevelopmental impairments if not diagnosed promptly. The inherent non-stationarity and polymorphic complexity of EEG signals complicate interpretation, resulting in time-consuming and error-prone diagnostics that hinder timely therapeutic interventions. To address these challenges, we propose SinTransNet, an innovative EEG-based deep learning framework that combines multi-band signal decomposition, adaptive sinusoidal convolutions, and Transformer-based attention mechanism. This architecture decomposes EEG into five key frequency bands (δ, θ, α, β, γ) to isolate oscillatory features such as spike-and-wave complexes, employs sinusoidal convolutions for frequency-adaptive feature extraction, and utilizes Transformer attention to capture inter-band correlations and long-range dependencies essential for accurate IESS detection. Evaluated on a proprietary dataset comprising 129 EEG recordings with 1,941 epileptic spasm events, SinTransNet demonstrates superior performance with average accuracy of 85.69%, sensitivity of 80.55%, and specificity of 90.76%. By providing an automated, efficient tool for IESS identification, SinTransNet holds promise for enhancing clinical workflows and supporting early interventions in pediatric neurology.

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Synaptoporin (SPO; synaptophysin II) has classically been described as a presynaptic vesicle protein enriched in the hippocampal mossy fiber pathway, distinguishing it from the ubiquitously expressed synaptophysin I (SYP). However, its distribution and synapse-type specificity in the human brain have not been studied yet. Here, we comprehensively mapped SPO protein expression across multiple human brain regions using immunofluorescence staining of post mortem tissue and biochemical analysis of brain lysates. We identified high SPO protein expression in the hippocampus, cerebral cortex, and dorsal horn of the spinal cord; moderate expression in the cerebellum and amygdala; and low levels in the putamen. The analyzed brainstem regions and the thalamus were devoid of SPO. Notably, SPO was present in distinct components of the human auditory pathway, mirroring rodent patterns. Colocalization analyses revealed largely separate distributions of SPO and SYP, challenging the concept of SYP as 'pan-synaptic' marker. In the cerebral cortex, a region with pronounced SPO expression, SYP-based synapse quantification underestimated total synapse numbers by up to 35%, a result replicated across independent brain tissue sources. SPO puncta were associated with both excitatory and inhibitory synaptic markers, reflecting the highly heterogeneous human synaptome. Collectively, these findings demonstrate that SYP-only assays overlook a substantial subset of synapses and they highlight the combinatorial complexity of vesicle protein expression in the human brain. This work establishes SPO as a critical determinant of synaptic diversity and can serve as reference to identify vulnerable synaptic subtypes in neurodegenerative diseases.

In patients with drug-resistant epilepsy who undergo anterior nucleus of the thalamus (ANT) deep brain stimulation (DBS), efficacy is assessed months after therapy initiation and clinicians have no guidance when choosing stimulation parameters due to the lack of real-time biomarkers. Here, we identified acute and chronic suppression of slow gamma local field potential (LFP) oscillations (SGOs) (20-50 Hz) in the ANT as a novel electrophysiological biomarker correlated with therapeutic response. Participants enrolled in an ongoing prospective ANT-DBS parameter optimization trial (N = 11) were analyzed retrospectively for the effects of stimulation on ANT LFPs. One-minute baseline and stimulation ANT LFPs were captured across follow-up visits using a Medtronic Percept, testing different stimulation settings around the Stimulation of the Anterior Nucleus of the Thalamus in Epilepsy (SANTE) trial clinical setting (145 Hz, 90 μs) in the clinic. Aperiodic component detrended ANT LFP power spectral density responses during stimulation were compared against each baseline responses. Participants kept a seizure diary, where responders were those who achieved greater than a 50% seizure frequency reduction compared to their pre-DBS seizure frequency. In the seven participants exhibiting SGOs, six were responders. Progressive suppression ("gamma fade") of SGOs under chronic stimulation correlated with long-term seizure reduction in five of six responders. Acute stimulation in-clinic with multiple settings suppressed SGOs in four of five responders, challenging fixed-programming paradigms, with only one responder using the clinical gold standard parameters at the last follow-up visit. These findings establish SGO suppression as a potential multiscale biomarker for responder identification, parameter titration, and therapeutic tracking for precise, biomarker-guided intervention.

Planning invasive treatment for medication-resistant epilepsy depends on interpreting intracranial EEG (iEEG) recordings to identify seizure onset patterns and locations. Clinicians currently rely on multimodal data, experience and literature to recommend treatments. Referencing a new patient's seizures against past cases remains subjective because implant strategies, electrode placements, and seizure onset zones vary across individuals and centers. This study introduces a transformer-based framework to rigorize this process by embedding spatial and temporal information in iEEG recordings to categorize seizure networks and relate them to clinical outcomes across a large cohort of drug-resistant epilepsy patients. The ultimate goal is to quantitatively compare new patients' seizure characteristics with thousands of historical cases to guide treatment recommendations.&#xD;Approach: We design a spatiotemporal transformer that uses convolutional tokenization and anatomical positional encoding to extract spatial-temporal features in multi-channel iEEG seizure onset data. The model accommodates variable electrode counts and implant types, including stereotactic EEG and electrocorticography implants. We validated the learned seizure embeddings through unsupervised clustering and a cross-validated multi-class logistic-regression model.&#xD;Main Result: The model was applied to 882 seizures from 102 subjects with drug-resistant epilepsy. Unsupervised clustering reveals 74 cross-subject clusters, and a multi-class regression model with 10-fold cross-validation reveals significant clustering of onset patterns in embedding space (acc. = 0.8159). Seizures occurring closer in time exhibited greater embedding similarity (p < 0.05). Although seizure clusters did not differentiate therapy or surgical outcome, they were significantly associated with the anatomical onset region and seizure classification.&#xD;Significance: We propose a method for representing iEEG recordings of seizures with embeddings that contain spatial and temporal information. These embeddings enable comparison of common patterns in seizure onset. Future work will refine this framework by incorporating multimodal data, including imaging, semiology and patient history to move toward quantitative, evidence-based decision making for patients with drug-resistant epilepsy.

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Traumatic brain injury (TBI) often leads to long-lasting neurological, cognitive, and behavioral impairments. Despite its high global burden, no disease-modifying therapies currently exist to mitigate secondary injury processes that contribute to chronic neurological deficits. Activation of &#x3b1;7 nicotinic acetylcholine receptors (&#x3b1;7-nAChRs), which are expressed on neurons, glia, and immune cells, has been implicated in neuroprotection, modulation of neuronal excitability, and suppression of neuroinflammation. The present study investigated the efficacy of &#x3b1;7-nAChRs using the selective positive allosteric modulator PNU-120596 (PNU) on functional recovery and inflammatory responses. TBI was induced in adult mice using a cortical contusion injury model, which was followed by PNU (1 or 3&#x202f;mg/kg, ip) treatment for six days. Neurological and behavioral outcomes were assessed using composite neuroscore, beam-walk, rotarod, burrowing, and health assessment tests. Serum inflammatory markers were measured using multiplex assays, hippocampal gene expression and glial activation markers by quantitative PCR. PNU treatment significantly improved neurological motor performance and motor coordination following TBI. In addition, PNU attenuated systemic inflammatory responses, reducing circulating levels of pro-inflammatory cytokines, including IFN-&#x3b3;, GM-CSF, and IL-12. In the contralateral hippocampus, the lower dose of PNU normalized injury-induced increases in GFAP, IL-1&#x3b2;, and CXCL10 mRNA expression, indicating reduced astrogliosis and inflammatory signaling, whereas the higher dose was ineffective. Collectively, these findings demonstrate that potentiation of &#x3b1;7-nAChRs promotes dose-limited functional recovery and modulates inflammatory responses following TBI. Targeting &#x3b1;7-nAChR signaling may represent a promising therapeutic strategy to improve neurological outcomes after TBI.

Ketogenic diet (KD) is an established treatment option for pediatric drug-resistant epilepsy; however, early indicators of treatment response are limited. This study aimed to explore whether early changes in routine electroencephalographic (EEG) findings, particularly the interictal epileptiform discharge index (IED index), are associated with subsequent clinical response to KD therapy. We conducted a single-center retrospective cohort study including children with drug-resistant epilepsy who initiated a classical ketogenic diet. Standardized natural sleep EEG recordings were obtained at baseline and approximately one month after diet initiation. IED &#x131;ndex was calculated during the first five minutes of non-rapid eye movement sleep, and background activity was visually assessed using a standardized grading scale. Clinical response was defined as a &#x2265;50% reduction in seizure frequency or seizure freedom at six months. EEG changes were compared between responders and non-responders, and receiver operating characteristic analysis was performed to evaluate the association between early EEG changes and clinical outcome. Thirty-four patients were included, of whom 23 (67.6%) were classified as responders at six months. Baseline EEG characteristics did not differ between responders and non-responders. At one month, responders showed a significant reduction in IED index, whereas no significant change was observed in non-responders. A reduction in IED index of approximately 40% was associated with clinical response, demonstrating good discriminative performance. Changes in background EEG activity were observed in both groups and were not associated with seizure outcome. Early reduction in IED index on routine sleep EEG is associated with favorable clinical response to the ketogenic diet. Routine EEG assessment may offer supportive electrophysiological information during early follow-up of KD therapy in pediatric drug-resistant epilepsy.

Past experiences stored in long-term memory (LTM) provide a valuable resource for making predictions that shape perception and guide goal-directed behavior. Contents from the high-capacity LTM system guide contextual selective attention to enhance sensory and higher-order processing of memory-predicted targets, in a process known as LTM-guided attention. While this essential cognitive function is believed to depend on the hippocampus, evidence is still scarce. In this study, we used a neuropsychological approach to test LTM-guided attention in the context of isolated hippocampal pathology and to explore structure-behavior covariance patterns. We tested healthy individuals (n = 20) and individuals suffering from focal epilepsy, with isolated, unilateral left (n = 20) or right (n = 17) hippocampal sclerosis (HS), in a task probing LTM-guided attention. Behavioral data indicated that individuals with left or right HS retained LTM-guided attention. We also assessed structure-behavior covariance using a multivariate structural neuroimaging approach. Hierarchical clustering analysis revealed that, in healthy individuals, LTM-guided attention performance covaried with atlas-derived subfield measures of the left hippocampal body. The volume of the left hippocampal body also covaried with attentional benefit in individuals with right HS. Interestingly, for individuals with left HS, LTM-guided attention covaried with the volume of the left hippocampus and with part of the right hippocampal volume. Together, these findings suggest that LTM-guided attention can be preserved in unilateral HS, with differences in hippocampal volume-behavior covariance depending on the side of hippocampal pathology.

Negative interpretation bias - the tendency to perceive ambiguous stimuli as threatening - is a core cognitive distortion underlying post-traumatic stress disorder (PTSD). The amygdala, a key structure in fear processing, is implicated in PTSD-related hypervigilance and heightened fear perception, yet direct causal evidence linking amygdala function to negative interpretation bias remains limited. Here, we present a unique prospective case of a male patient with refractory epilepsy and comorbid chronic PTSD, who underwent stereoelectroencephalography-guided radiofrequency ablation (SEEG-guided RFA) targeting the right amygdala. Before ablation, the patient exhibited heightened negative interpretation bias, judging ambiguous faces as more fearful compared to control groups of epilepsy patients without PTSD. Intracranial SEEG recordings revealed that this cognitive bias was associated with increased late-phase event-related potential (L-ERP) differentiation between fearful and happy faces in the right amygdala. Immediately following focal right amygdala ablation, negative interpretation bias and PTSD symptom severity were significantly reduced, while seizure frequency remained unchanged. Notably, reductions in L-ERP amplitude after ablation closely tracked decreases in fear perception, highlighting L-ERP as a potential biomarker of negative interpretation bias and therapeutic response. Our findings provide causal evidence from an n-of-1 study that the right amygdala supports maladaptive negative interpretation bias in a patient with PTSD and that right amygdala ablation can contribute to the relief of PTSD symptomatology.

In temporal lobe epilepsy (TLE), recurrent seizures can cause structural and functional disruptions within the temporal lobe and nearby language regions, resulting in neural reorganization. In this study, we leverage task-based functional magnetic resonance imaging (tb-fMRI) to understand how this language reorganization process varies based on the seizure location, the timing of seizure onset, and the chronicity of epileptic activity. 84 drug-resistant TLE patients who completed a tb-fMRI sentence completion task were included in this study. Analysis included group comparison of activation and comparison of the extent of reorganization in the whole brain and standard language regions of interest (ROI) level. We also measured the impact of the age of onset and the duration of epilepsy in the reorganization process. A significantly higher degree of language network reorganization is observed in left (L) TLE than in right (R) TLE at the whole brain level. At the regional level, a higher degree of reorganization is observed in temporal and frontal lobe ROIs in LTLE compared to RTLE, especially in the middle frontal gyrus and posterior temporal gyrus. The effects of age of onset and epilepsy duration were prominent in LTLE subjects at both the whole-brain and ROI levels. Patients with LTLE show greater changes in the middle frontal and posterior temporal regions, particularly in those with an earlier age of onset and longer disease duration. Identifying these patterns may assist in surgical planning and personalizing treatment to protect cognitive function.

Intraparenchymal schwannomas are a rare subtype of central nervous system tumor, with descriptions of this pathology within the neurosurgical literature exclusively consisting of case reports and small case series. The present study details an illustrative case of a young patient with this rare tumor type who was recently treated at our institution via craniotomy for resection of her intracranial neoplasm. We then conducted a systematic review of the published patient data on supratentorial intraparenchymal schwannomas, including a meta-analysis aimed at quantifying postoperative seizure-freedom rates in this patient population. The present study included both a surgical case report in addition to a PRISMA-compliant systematic review that involved individual-patient data (IPD) meta-analysis. The systematic review searched PubMed, the Cochrane Library, and Scopus, with 63 articles meeting inclusion criteria. The IPD meta-analysis utilized the nonparametric Kaplan-Meier estimator and a parametric Bayesian Weibull accelerated-failure-time (AFT) model to estimate seizure-freedom time after surgery. Our case report detailed a right frontal craniotomy for tumor resection in a 23-year old female. Gross total resection was achieved and postoperative pathology was ultimately consistent with WHO grade I schwannoma, with the neoplastic tissue staining positive for S-100 and SOX-10, in addition to being negative for OLIG-2 and positive for GFAP. Molecular profiling also detected a CHD7-VGLL3 fusion. Among the 63 articles identified via our systematic review, a total of 82 patients with supratentorial, intraparenchymal schwannomas were identified. Using the parametric AFT model, median seizure-free survival time was calculated as 133.43&#xa0;months (95% CrI&#xa0;=&#xa0;65.89-296.29&#xa0;months; 90% CrI&#xa0;=&#xa0;72.40-260.25&#xa0;months; 50% CrI&#xa0;=&#xa0;103.15-175.89&#xa0;months), while the probability of remaining seizure-free 12, 36, and 60&#xa0;months after surgery being 95.28% (95% CrI&#xa0;=&#xa0;88.52-99.15%), 85.00% (95% CrI&#xa0;=&#xa0;70.95-95.32%), and 74.75% (95% CrI&#xa0;=&#xa0;54.05-90.44%), respectively. The observed postoperative seizure-freedom rate of 83.8% was statistically significantly greater than the 70% lower-bound benchmark established for low-grade epilepsy-associated neuroepithelial tumors (p&#xa0;=&#xa0;0.044). The present study provides quantitative seizure-freedom estimates for patients undergoing surgical resection of epileptogenic intraparenchymal schwannoma, a rare disease entity with fewer than 100 reported cases in the neurosurgical literature. Given the inherent constraints of quantifying treatment outcomes of a rare disease, the ability to obtain such estimates underscores the utility of Bayesian methods for statistical inference under data-limited conditions. Our meta-analysis suggests that most patients can expect at least multiple years of seizure-freedom postoperatively following resection of an epileptogenic intraparenchymal schwannoma.

Sudden unexpected death in epilepsy (SUDEP) and long QT syndrome (LQTS) are severe disorders causing sudden death in the neurological and cardiovascular systems, respectively, and have traditionally been viewed as distinct clinical entities. However, their overlapping clinical phenotypes and partially shared genetic backgrounds suggest that, in a subset of patients, overlapping molecular mechanisms may contribute to neurocardiac vulnerability. This review systematically elucidates and bridges the potential mechanistic intersections between these two conditions at the level of ion channel dysfunction. It focuses on key shared ion channel genes, such as KCNQ1, KCNH2, and SCN5A, and analyzes how their variants may simultaneously induce neuronal hyperexcitability and cardiomyocyte repolarization abnormalities, thereby suggesting a potential risk-modifying framework of "cardio-cerebral ion channelopathies" in specific clinical scenarios. Additionally, this article discusses the significant implications of this shared mechanism for clinical practice, particularly in evaluating the cardiac safety of anti-seizure medications (ASMs), integrating genetic risk stratification, and developing future therapeutic strategies. By synthesizing and integrating existing evidence, this review aims to provide a broader pathophysiological perspective on the intrinsic links between SUDEP and LQTS, offering novel insights for interdisciplinary precision medicine.