Epilepsy Research

Objective: To determine whether paradoxical relief, feeling unusually better after a seizure compared to before it, is more common after functional/dissociative seizures (FDS) than epileptic seizures (ES), quantify its diagnostic accuracy, and explore its relationship with preictal symptoms. Methods: Consecutive patients admitted to a tertiary epilepsy unit for prolonged inpatient EEG monitoring underwent a structured clinical interview on admission, before final multidisciplinary diagnostic classification. Preictal dissociative and autonomic/somatic symptom burden was assessed using items adapted from established questionnaires. Diagnostic classification incorporated clinical history, seizure semiology, video electroencephalography findings, and collateral information. Patients with dual or indeterminate diagnoses were excluded. Associations with paradoxical relief were examined using logistic regression, followed by an exploratory mediation analysis. Results: Of 176 patients assessed, 66 with FDS and 65 with ES were included. Paradoxical relief was reported by 46/66 patients with FDS (69.7%) and 10/65 with ES (15.4%; unadjusted odds ratio [OR] 12.65, 95% confidence interval [CI] 5.57 to 31.09). As a diagnostic signal for FDS, paradoxical relief had 69.7% sensitivity (95% CI 57.1 to 80.4), 84.6% specificity (95% CI 73.5 to 92.4), a positive likelihood ratio of 4.53 (2.51 to 8.19), and a negative likelihood ratio of 0.36 (0.24 to 0.52). FDS diagnosis remained independently associated with paradoxical relief after adjustment (OR 10.59, 95% CI 3.42 to 38.06). In a parallel mediation analysis, dissociative symptom burden showed a significant indirect effect, accounting for 19.5% of the association between diagnostic group and relief, whereas the indirect effect through somatic/autonomic symptom burden was not significant. Significance: Paradoxical relief is substantially more common after FDS than ES and may provide a simple, clinically useful diagnostic signal. Its absence does not exclude FDS, and the finding requires external validation. The association with dissociative symptoms is exploratory and supports prospective investigation of whether relief reflects transient resolution of a disturbed, disembodied preictal state.

Objective: Cognitive impairment is a common comorbidity among people with epilepsy (PWE) and is associated with disability and reduced quality of life. We characterized the burden of cognitive impairment and identified factors associated with cognitive performance in a large, population-based cohort of PWE living in Northern Peru, a region highly endemic for Taenia solium where neurocysticercosis (NCC) is a common cause of acquired epilepsy. Methods: PWE enrolled in a population-based cohort in Northern Peru between 2007 and 2020 completed the Mini-Mental State Examination (MMSE) at enrollment. Cognitive impairment was defined as an MMSE score <24. Demographic and clinical data, including epilepsy characteristics and NCC status, were collected. Negative binomial regression was used to identify factors associated with the number of MMSE errors. Results: Among 764 participants, the mean MMSE score was 26.4 (SD 4.2), and 16.4% met criteria for cognitive impairment. Memory and attention were the most affected domains. In multivariable analysis, older age and lower educational attainment were independently associated with poorer cognitive performance. Conclusion: In this large, community-based cohort from Northern Peru, approximately 1 in 6 PWE had abnormal global cognition on the MMSE, with memory and attention most affected. These findings underscore the importance of incorporating cognitive evaluation and management into comprehensive epilepsy care, particularly in resource-limited settings where cognitive morbidity may be underrecognized. Given the potential for cognitive difficulties to compound disability and adversely affect quality of life, identifying and addressing cognitive morbidity may be especially important in populations already facing substantial barriers to epilepsy care.

Background: Temporal lobe epilepsy surgery (TLS) is an effective treatment for drug-resistant focal epilepsy but is often associated with cognitive decline. A key unresolved question is how to distinguish average from severe memory loss and how these levels differentially affect everyday life. We addressed this question applying patient-derived norms of memory decline and conducting qualitative inter-views with patients experiencing expected or unexpectedly severe memory loss. Methods: Regression-based normative change criteria for postoperative verbal memory loss were derived from a single-center cohort of 806 patients. Two matched groups of four patients each were selected from the severe memory de-cline (SMD; below the 5th percentile) and average memory decline (AMD; 20th - 75th percentile) ranges. In-depth, semi-structured narrative interviews were analyzed using qualitative content analysis with a combined deductive-inductive ap-proach. Results: AMD narratives emphasized recovery, with surgery integrated into a con-tinuing sense of self. In contrast, SMD descriptions focused on persistent symp-toms, continued treatment, and illness despite meaningful seizure reduction. Pa-tients with SMD also reported limited information, insufficient psychological preparation or postoperative cognitive rehabilitation. Conclusions: Whereas AMD was generally manageable and successfully integrat-ed into everyday life, SMD disrupted identity, autonomy, and expected life trajecto-ries. Current surgical pathways appear to address these cognitive sequelae insufficiently. Improved expectation management, together with structured preoperative counseling and postoperative rehabilitation, may facilitate adaption to memory de-cline and improve long-term functioning and quality of life after surgery.

Background Psychiatric comorbidities commonly have a negative impact on epilepsy outcomes. However, they are continuously ignored in routine epilepsy care, with focus directed more towards seizure control. There is paucity of data on the burden of psychiatric morbidity among those living with epilepsy in Kenya. This study sought to determine the prevalence and associated factors of psychiatric morbidity among patients living with epilepsy at a tertiary referral hospital in Western Kenya. Methods This was a descriptive cross-sectional study. Consecutive sampling was used to recruit participants, with a sample size of 278. Data were collected using a structured pretested sociodemographic and clinical characteristics questionnaire, and the Mini International Neuropsychiatric Interview (MINI), and analyzed using STATA version 16. Pearson Chi-square test/Fishers Exact test and logistic regression were used to assess relationships at bivariate and multivariate levels respectively. Results The prevalence of psychiatric morbidity was 52.2%. Major depressive disorder was the most prevalent (36%), followed by anxiety disorders (26.2%), psychotic disorders (16.9%), and suicidality (15.1%). Casual/self-employment (aOR=2.590, p=0.020), seizure-related physical trauma (aOR=4.032, p=0.004), antiepileptic polytherapy (aOR=4.280, p=0.001), frequent seizures (aOR=3.801, p<0.001), and comorbid medical conditions (aOR=5.478, p=0.047) were independent predictors of psychiatric morbidity. Having attained a tertiary level of education was protective against psychiatric morbidity (aOR=0.221, p=0.036). Conclusion More than half of the patients living with epilepsy had at least one psychiatric comorbidity. Routine psychiatric screening and integration of mental health services in epilepsy care is essential to improve clinical outcomes.

Abstract: Objective: Post-traumatic epilepsy (PTE) is a common sequela of traumatic brain injury (TBI). Research indicates that individuals with PTE tend to experience greater cognitive difficulties compared to those with TBI alone. However, it is plausible that a distinct cognitive profile exists that distinguishes between TBI cases with and without PTE. We aimed to identify longitudinal changes in cognitive measures among TBI patients to better assess the changes associated with developing PTE. Setting: Outpatient. Participants: Prospective subjects who had suffered TBI within 6 months post-injury (TBI-6M, n=32), retrospective subjects with pre-existing PTE diagnoses (PTE, n=20), and healthy control subjects (HC, n=41). Design: We examined cognitive performance for TBI patients within 6 months post-injury, then again within 12 months (TBI-12M, n=26), and within 18-months (TBI-18M, n=25), and compared this with cognitive performance among HC and PTE. Main Measures: Cognitive tests administered yielded 15 test components for analysis. We utilized linear mixed effects modeling to examine cohort-level differences cognitive function. Results: 11/15 tests showed a significant performance deficit in the PTE subjects compared to HC. TBI-6M was not significantly different from the PTE subjects; with time, 9/15 tests showed some degree of recovery in TBI subjects. Tests for information processing speed/working memory and executive function showed strong recovery (TBI-6M vs. TBI-18M, SDMT written: p<0.0001, SDMT oral and COWAT: p<0.001). Tests for visual attention/working memory also showed a smaller but significant recovery (TBI-18M vs. PTE, p<0.05). By contrast, tests for verbal memory [HVLT-R Delayed Recall] showed chronic impairment in TBI (TBI-18M vs HC, p<0.0001). TBI subjects generally trend towards recovery in cognitive performance post-TBI. Conclusions: Information processing speed/working memory are strong indicators for TBI recovery, while auditory learning/memory shows chronic impairment. The stagnation of recovery in cognitive domains typically characterized by robust recovery may correlate with an elevated risk of developing PTE.

Background: On-call clinicians frequently report the anecdotal impression of 'theme shifts' during which specific acute neurological diagnoses appear to cluster. Whether such clustering reflects a statistically true and reproducible phenomenon has not been systematically investigated; the present paper examines seasonality and temporal clustering within six different acute neurological conditions. Methods: In this retrospective, single-center cohort study, we identified all patients admitted to a tertiary neurological department between July 2016 and June 2026 with acute unilateral vestibulopathy, cerebral artery dissection, generalized epileptic seizures, primary intracerebral hemorrhage, peripheral facial nerve palsy, or transient global amnesia (TGA) (n = 2,140). Monthly and seasonal distributions were assessed using chi-squared goodness-of-fit and cosinor analysis. Short-term temporal clustering was tested by Monte Carlo permutation across time windows from 24 hours to 90 days, and endogenous cluster dynamics were characterized using Hawkes self-exciting point process modeling. Results: Admissions for generalized epileptic seizures showed a statistically significant deviation from a uniform monthly distribution with a winter distribution (p<0.001 and q = 0.002), and a significant temporal clustering across time windows from 72 hours to 90 days (all q < 0.05). Peripheral facial nerve palsy presented significant clustering at the 90-day window (q = 0.029) and TGA at 60-day time window (q = 0.041) without seasonality; the diagnostic groups of acute unilateral vestibulopathy, cerebral artery dissection and primary intracerebral hemorrhage showed neither seasonality nor clustering after correction for multiple comparison. No diagnostic group showed clustering within a 24-hour window, statistically significant self-excitation in Hawkes process modelling, or a significant linear trend in monthly case counts over the study period. Conclusion: The anecdotal impression of diagnostic 'theme shifts' among on-call neurologists appears to have a measurable basis, although clustering is confined to specific conditions and rather on a time scale of weeks to months. Generalized epileptic seizures were the only diagnostic group that uniquely combined seasonality with temporal clustering, suggesting a shared trigger, while facial palsy and TGA showed episodic, yet non-seasonal clustering.

Abstract Objective To validate a neonatal seizure detection algorithm that is based on extracted clinical features of the aEEG and CSA on a cohort of cooled neonatal patients with HIE. Methods A seizure detection algorithm was designed using aEEG margin features, CSA features, trained on a public dataset of 79 neonatal EEGs with three supervised machine learning classifiers. It was subsequently tested on an inhouse cohort of 23 neonates with asphyxia whose EEGs were collected during hypothermia therapy. Results The trained Random Forest Classifier, Support Vector Machines and Artificial Neural Network classifiers had an AUC of 0.76, 0.77, and 0.77 and an average accuracy of 0.85, 0.86, and 0.85 respectively. Finally, the average AUC across the 10 seizure patients included was 0.85. Conclusion A neonatal seizure detection algorithm that uses a combination of aEEG and CSA clinical features can capture seizures in HIE patients. Performance across seizure patients is not correlated with seizure duration.

Background To build a clinically translatable neonatal seizure detection algorithm using amplitude-integrated electroencephalography (aEEG) and compressed spectral array (CSA). Methods Using a public dataset of annotated neonatal EEGs, features of the aEEG and CSA were extracted from the left and right centroparietal electrodes. These features were then used to train and test three machine learning classifiers, Random Forest (RF), Support Vector Machines (SVM), and Artificial Neural Networks (ANN). Results The trained RF, SVM, and ANN classifiers had areas under the curve (AUC) of 0.80, 0.69, and 0.79 for capturing seizure time periods and an average accuracy of 0.91, 0.90, and 0.92 respectively for capturing seizure and non-seizure time periods. Median accuracy scores were higher among patients without hypoxic-ischemic encephalopathy (HIE; median = 1 for all three classifiers) than HIE patients (median = 0.92, 0.93, 0.93). Conclusion A clinically interpretable aEEG-CSA algorithm is feasible for neonatal seizure detection by extracting standard EEG features and coupling these features with a supervised ML classifier.

Objective To estimate the prevalence of epilepsy-associated malformations of cortical development (MCDs) in Eastern Denmark, and to validate whether epilepsy prevalence in the same population is consistent with national estimates. Methods A retrospective cohort study of people registered with ICD-10 code DG40* and/or DZ033A from 1998 up to 1 July 2023 was conducted. The study population was defined as all living residents in Eastern Denmark with at least one recorded hospital-patient contact within the year preceding 1 July 2023. Magnetic resonance imaging (MRI) availability was required to assess presence of any MCD. MRI radiology reports were manually reviewed or evaluated using a language model to identify MCDs, including encephalocele, focal cortical dysplasia (FCD), hemimegalencephaly, heterotopia, hypothalamic hamartoma, lissencephaly, polymicrogyria and schizencephaly. Prevalence estimates were calculated for each MCD subtype and for epilepsy overall, and compared with the available literature. Results On 1 July 2023, 28,739 people met inclusion criteria, and 14,434 had an available brain MRI, including radiological description of possible MCDs. The prevalence per 100,000 population was 1044.6 (95\% CI 1032.6 to 1056.6) for epilepsy and 32.1 (95\% CI 30.1 to 34.3) for any MCD associated with seizures. Reported MCD prevalence in the literature, when existent, was derived from pediatric age-ranged selected cohorts, except for FCD. No prevalence estimates for hemimegalencephaly and heterotopia were identified. Signifiance We presented the first population-based estimates of seizure-associated MCD prevalence in a large all-age cohort. Direct comparison with prior literature was prevented due to differences in study design and population structure, but epilepsy prevalence was consistent with previously reported national estimates.

Background and Objectives: In persons with epilepsy, seizure risk is tightly linked to the health of sleep and circadian rhythms. Rest-activity rhythms (RARs), derived from continuously worn activity monitors, can provide objective assessments of diurnal patterns of activity. Compared with healthy controls, adults with epilepsy have been shown to display weak and unstable RARs. In this study, we aimed to directly measure RARs in patients with infantile epileptic spasms syndrome (IESS), a potentially devastating developmental and epileptic encephalopathy. As a comparator, we similarly examined identically measured RARs from a cohort of healthy infants. Methods: For this cross-sectional case-control comparison, we obtained multiday actograms in a sample of infants with IESS using ankle-worn Actiwatch-2 devices deployed during overnight follow-up EEG evaluations designed to assess initial treatment efficacy. Control actograms (similarly obtained via Actiwatch-2 devices) from the Rise & SHINE study (Sleep Health in Infancy and Early Childhood) were downloaded from the National Sleep Research Resource. We computed a series of parametric and non-parametric measures to depict the maturation of RARs over this developmental window and compared RARs from each IESS subject against up to 4 age-matched controls. Results: In 891 actigraphy recordings obtained from 333 SHINE subjects, age-dependent increases in body length and weight were associated with progressive increases in RAR height (amplitude/mesor/M10), regularity (interdaily stability), entropy and fractal complexity, together with progressive declines in RAR fragmentation (intradaily variability). Compared with age-matched controls, multiday actograms from IESS subjects (n = 11, 9 males) displayed marked reductions in RAR height (amplitude/mesor/M10) and interdaily stability, together with reductions in entropy and fractal complexity. Conclusions: During infancy, rest-activity rhythms display a stereotyped maturation in height, complexity and day to day consistency, revealing a developmental "growth curve" of RAR maturation. Severe RAR disruptions in infants with IESS may relate to the encephalopathy imposed by the underlying genetic/metabolic condition, structural lesion, and/or the psychomotor retardation imparted by antiseizure medications. Actigraphy recordings may offer a scalable, noninvasive approach to objectively and longitudinally assess circadian health in patients with IESS.

Many patients with epilepsy have inadequate seizure control using current anti-seizure medications (ASMs), illustrating the need for new treatments. Genetic epilepsy syndromes like pathogenic variants in voltage gated sodium channel SCN2A and SCN8A are often poorly controlled by current medications, highlighting the need for better models. Voltage gated sodium channel pathogenic variants that induce epilepsy are often gain-of-function, producing hyperexcitability. We established a fast and precise zebrafish seizure assay using mRNA overexpression of SCN2A and SCN8A variants, which allows rapid screening of both variants and ASMs. These short-term genetic seizure models are assayed in 3 days postfertilization (dpf) larvae. Pathogenic variants of SCN2A and SCN8A produced sporadic seizure behavior. We tested human SCN2A R1882Q, SCN2A R853Q and SCN8A R1872Q pathogenic variants that were identified in epilepsy syndrome patients. These models were used to evaluate the efficacy of 3 ASMs: Topiramate, GS967 and PF-04856264. All 3 epilepsy-associated variants increased seizure activity, and the ASMs significantly decreased this seizure activity. This mRNA overexpression assay successfully evaluates seizure activity induced by variants in voltage gated sodium channel genes and examines ASM efficacy in patient specific pathogenic variants.

Objective Temporal lobe encephaloceles (ENC) are underdiagnosed causes of drug-resistant temporal lobe epilepsy (TLE), frequently associated with idiopathic intracranial hypertension (IIH). Emerging evidence suggests glymphatic system dysfunction in both IIH and TLE. We investigated glymphatic markers in TLE associated with ENC compared with seizure-free postoperative TLE controls of different aetiology. Methods Surgical specimens from 13 patients with TLE-ENC and 12 TLE-control patients were analyzed. Histological glymphatic markers included aquaporin-4 (AQP4), glial fibrillary acidic protein (GFAP), podoplanin (PDPN), perivascular space (PVS) enlargement, and vessel density. High resolution MRI was used to assess a global PVS score. Results Compared with TLE-controls, TLE-ENC specimens showed increased white matter AQP4 expression and AQP4/GFAP ratio, whereas the AQP4/GFAP ratio was reduced in grey matter. PDPN expression was significantly elevated in both grey and white matter in TLE-ENC cases. MRI demonstrated greater supratentorial PVS enlargement in in ENC patients. Radiological features suggestive of IIH were identified in 46.1% of TLE-ENC patients. Compared with controls, TLE-ENC patients had shorter disease duration and lacked association with previous febrile seizures. Surgical treatment achieved seizure freedom in 70% of ENC patients at a median follow-up of 32 months. Interpretation This study provides the first characterization of glymphatic alterations in TLE-ENC-related epilepsy. Dysregulation of AQP4 and PDPN together with increased PVS burden suggests a distinct glymphatic dysfunction pattern in TLE-ENC, supporting a potential pathophysiological link among ENC formation, IIH, and epileptogenesis mediated by altered cerebrospinal fluid dynamics.

Objective: Pediatric epilepsy patients undergoing stereo-electroencephalography (sEEG) for ictal onset evaluation provide a rare window to study the developing brain. While methodological frameworks for task-based sEEG research are well-established in adults, pediatric-specific guidance remains underdeveloped. Furthermore, many pediatric epilepsy patients have comorbidities that might typically exclude them from participating in research. We examine factors that influence research participation and discuss considerations for conducting sEEG research in children. Methods: Here, we present a retrospective analysis of task-based research participation patterns from an NIH-funded study of speech and language representations (1R01DC018579) in 66 patients (ages 4-24) undergoing sEEG monitoring at Texas Children's Hospital to determine whether specific comorbidities influenced research participation. Results: Eighty-nine percent (n=66) of patients approached for consent agreed to participate in the study. Despite high rates of comorbidities including neurocognitive disorder (66.67%), language delay (31.75%), global developmental delay (23.81%), mood disorders (33.33%), ADHD (46.03%), autism spectrum disorder (14.29%) or other cognitive/intellectual disabilities (36.51%), all participants engaged in at least one task. While the majority of these diagnoses did not appear to influence subject participation, global developmental delay was associated with a significant reduction in time spent on active tasks. Discussion: Despite high prevalence of neuropsychological comorbidities among participants, our evidence suggests that these participants contribute meaningfully to studies investigating important developmental questions. We suggest strategies for tailoring task-based research to accommodate the unique needs of individuals in this population. Such practices are important for ensuring that research studies reflect the true diversity of the population.

Objective: Whether a scheduled antiseizure medication (ASM) continues on schedule across the ICU-to-floor transfer has not been characterized. We quantified ASM administration-gap frequency across this transfer and compared it with gap frequency during matched non-transfer intervals in the same patient and drug. Methods: In this retrospective MIMIC-IV (version 3.1) cohort study, we identified epilepsy and status-epilepticus admissions with an ICU stay followed by floor transfer and a scheduled ASM order active at ICU departure. A gap was defined as an interval exceeding 1.5 times the expected dosing interval between the last ICU dose and first floor dose, or no further dose before discharge, and compared with a matched non-transfer control interval in the same patient and drug (paired McNemar test). A multivariable model evaluated six prespecified clinical predictors; sociodemographic variables were summarized descriptively. Results: Among 2,469 ASM transition-by-drug observations (1,583 admissions, 1,335 patients), an administration gap occurred in 251 (10.2%; 95% CI, 8.7%-11.7%). Gap frequency across the transfer exceeded frequency during matched non-transfer control intervals in the same patient and drug: a paired rate difference of 5.8 percentage points (95% CI, 4.4-7.1; 7.5% vs 1.7%; P = 7.3 x 10^-22) before the transfer and 6.4 percentage points (95% CI, 4.9-7.9; 8.9% vs 2.5%; P = 1.9 x 10^-23) after. Gap rates were similar for intravenous-available (9.9%) and oral-only (11.4%) drugs (rate difference, 1.5 percentage points; 95% CI, -1.6 to 4.5; P = .34). None of six prespecified predictors reached significance after correction. Significance: An antiseizure medication administration gap occurred in approximately 1 of every 10 drug-transition observations at the ICU-to-floor transfer, exceeding matched non-transfer gap rates by 5.8 to 6.4 percentage points. This transfer-associated excess, rather than any single medication or patient characteristic, supports a structured medication-continuity check.

Automated seizure detection devices are increasingly plausible tools for epilepsy trials, but no device is perfect. We used CHOCOLATES, a realistic seizure diary simulator, to examine how device sensitivity and false alarm rate (FAR) affect regression-to-the-mean (RTM) and placebo median percentage change (MPC) in a simulated randomized trial design. For each device condition, 100,000 potential participants were generated; eligibility was assessed during a 2-month baseline, followed by a 3-month test period. With FAR fixed at 0, reducing sensitivity from 100% to 10% increased the fraction of eligible participants exhibiting RTM from 38.2% to 64.8% and increased placebo MPC from 14.7% to 48.1%. With sensitivity fixed at 100% and expected FAR correction, increasing FAR from 0 to 1 alarm/day increased RTM from 38.2% to 53.2% and placebo MPC from 14.7% to 31.3%. Imperfect seizure detection can therefore change the apparent placebo response expected from RTM.

Dravet syndrome (DS) is a severe developmental and epileptic encephalopathy whose clinical and research representation requires integration of heterogeneous knowledge spanning seizures, development, behavior, SUDEP/autonomic risk, genetics, comorbidities, electrophysiology, pharmacology, and drug responsiveness. We report the development of a DS-focused ontology created by expert-guided specialization of a previously published epilepsy ontology. Scope expansion was defined through a scientific advisory board, structured review meetings, and iterative ontology curation in OWL. The resulting resource reorganized DS content across nine major domains and expanded the publicly released ontology from the pre-extension baseline to the current BioPortal version. Beyond structural growth, the ontology was assessed through expert-guided curation and downstream task-based reuse, including two published ontology-enabled LLM studies and an ongoing ontology-derived DS knowledge graph and AI assistant platform. These results suggest that disease-focused ontology specialization can provide durable infrastructure for DS data harmonization, knowledge representation, and AI-enabled translational informatics.

The aim of this work is to validate patient-specific EEG baseline establishment using the e-norms method as a screening and retrospective-review tool for seizure detection in pediatric epilepsy. The method was applied to 247 seizure-free EEG recordings (263.92 hours) from 10 patients in the CHB-MIT Scalp EEG Database (ages 3-18). A composite stability metric combining first-derivative dynamics, spectral entropy, variance, and line length was computed per 2-second epoch across 23 channels. Patient-specific detection thresholds were derived from each patient's seizure-free baseline using a weighted statistical procedure. Performance was validated against 72 expert-annotated seizures (2,705 epochs) across 62 seizure files, with durations spanning 6 to 264 seconds (44-fold range). The results show that detection achieved 94.4% event-level sensitivity (68 of 72 seizures; 95% CI 86.6-97.8%) and 81.5% epoch-level sensitivity (2,204 of 2,705 epochs; 95% CI 80.0-82.9%). Eight of ten patients achieved 100% event-level sensitivity with epoch-level sensitivity ranging from 58.7% to 100.0%. Two patients showed partial event-level failures (CHB-15: 17 of 20; CHB-18: 5 of 6), with the four missed events attributable to two characterizable failure modes. Patient-specific thresholds ranged from 4.06 to 4.81 (mean 4.51 +/- 0.25); threshold variation did not correlate reliably with age or sex, confirming that no universal threshold could achieve comparable performance. Detection margins ranged from 0.88 to 1.24 times. Patient-specific e-norms achieves 94.4% event-level sensitivity for pediatric EEG seizure detection without requiring labeled seizure training data, exceeding published human expert inter-rater agreement (50-76%) and recent automated approaches in adult cohorts using behind-the-ear EEG and wearable ECG. Two characterizable failure modes account for the four missed events and inform appropriate clinical use. As a high-sensitivity screening tool complementary to real-time alarm systems, the method is ready for adult validation, prospective deployment, and head-to-head benchmarking.

Fragile X syndrome (FXS) is the leading inherited cause of intellectual disability, and is frequently accompanied by seizures. Early-life treatment with the hormone oxytocin (OXT) improves social behavior and cognitive function in rodent models of autism with intellectual disability, including FXS, but potential OXT treatment effects on seizure susceptibility have not been evaluated. Here we tested, in both sexes, if intranasal OXT (iOXT) or saline (iSAL) during the second postnatal week reduces audiogenic seizures (AGS) in the Fmr1-Knockout (KO) mouse model of FXS. OXT given daily from postnatal day (P) 7 to P13 significantly reduced the incidence and severity of AGS and the latency to seize in adult male Fmr1-KOs. Female KOs exhibited less severe seizures that were unaffected by treatment. Wild type mice did not exhibit AGS independent of treatment. To test if antiepileptic effects of iOXT are age-dependent, a separate cohort received iOXT daily from P30 to P36. Male KOs receiving later treatments exhibited robust seizures that were comparable between OXT- and SAL-treatment groups, suggesting that OXTs enduring antiepileptic effects are confined to early postnatal treatments. Tests of acute OXT effects in adulthood demonstrated an attenuation of male Fmr1-KO AGS at testing 30-60 min and 1 day post-treatment but these effects were not evident 15 days later. These findings reveal marked sex differences in the propensity for audiogenic seizures in Fmr1-KO mice and demonstrate that early-life OXT treatment mitigates seizure susceptibility in males FXS model mice.

Temporal lobe epilepsy (TLE) is associated with dysregulation of transforming growth factor {beta} (TGF{beta}) signaling, a key contributor to epileptogenesis. SARA (Smad Anchor for Receptor Activation), a central regulator of this pathway, is controlled by the E3 ubiquitin ligase Smurf2 through ubiquitination. However, the role of the SARA-Smurf2 axis in regulating TGF{beta} signaling during TLE has not previously been described, and whether this pathway can be therapeutically targeted remains unknown. Using a pilocarpine-induced status epilepticus (SE) model and astrocytes derived from patients with refractory TLE, we identified dysregulation of the SARA-Smurf2 pathway in both experimental systems. In SE rats, SARA and Glial Fibrillary Acidic Protein (GFAP) levels were significantly increased, whereas Smurf2 induction was insufficient to prevent SARA accumulation. In TLE-derived astrocytes, increased SARA and GFAP immunoreactivity was accompanied by reduced Smurf2 immunoreactivity and altered Smurf2 subcellular distribution. Losartan treatment restored SARA and Smurf2 immunoreactivity toward a control-like pattern in both models and reduced seizure frequency and duration in SE animals. These findings point towards a dysregulation of the SARA-Smurf2 axis as a molecular signature of TLE, support SARA as a potential therapeutic target, providing experimental evidence for the repositioning of Losartan as a potential treatment alternative for drug-resistant epilepsy, warranting further translational and clinical investigation. KEY POINTSO_LIDysregulation of the SARA-Smurf2 axis is a molecular signature of experimental and human temporal lobe epilepsy. C_LIO_LIImpaired Smurf2-dependent regulation of SARA may sustain TGF{beta} signaling, astrocyte reactivity, and epileptogenesis. C_LIO_LILosartan restores the SARA-Smurf2 axis and reduces seizures, supporting a novel therapeutic strategy for TLE. C_LI

Abstract Importance: Drug-resistant focal epilepsy affects approximately 30% of children with epilepsy and carries excess mortality, impaired neurodevelopment, and substantial costs. Epilepsy surgery is underutilized despite proven superiority over medical management. MRI-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive alternative to open resection, but comparative evidence to guide procedure selection is limited. Objective: To estimate lifetime outcomes and costs of epilepsy surgery versus medical management for pediatric drug-resistant focal epilepsy, and to provide etiology-informed guidance for choosing between open resection and MRgLITT. Design: Markov decision analytic model with a lifetime horizon, parameterized from published systematic reviews, meta-analyses, and cohort studies. Setting: United States, healthcare payer perspective. Participants: Hypothetical cohort of 10-year-old children with drug-resistant focal epilepsy and a seizure focus <3 cm3. Interventions: Best medical management, open resective surgery, or MRgLITT. Main Outcomes and Measures: Quality-adjusted life years (QALYs), lifetime direct medical costs, incremental cost-effectiveness ratios, and lifetime survival. Seizure outcomes were classified as seizure freedom or disabling seizures. Cost-effectiveness was assessed at $100,000/QALY. Results: Both surgical strategies were associated with a 4.6-year survival advantage, 3.6 additional lifetime QALYs, and lower costs than medical management. MRgLITT yielded 22.64 QALYs at $120,943; open resection yielded 22.62 QALYs at $121,650; medical management yielded 19.00 QALYs at $127,471. The difference between MRgLITT and open resection was 0.015 QALYs, reflecting near-equivalent effectiveness; in probabilistic sensitivity analysis, MRgLITT was optimal in 50.3% of iterations and open resection in 38.3%, with neither showing clear superiority. Etiology-specific analyses favored MRgLITT for focal cortical dysplasia and mesial temporal sclerosis, and open resection for tumor-related and cavernoma-related epilepsy. Conclusions and Relevance: Both open resection and MRgLITT were associated with substantially better lifetime outcomes and lower costs than medical management, supporting early surgical referral. Overall effectiveness between surgical approaches was clinically similar, with neither demonstrating clear superiority; the model suggests epilepsy etiology, rather than expected effectiveness alone, should guide procedure selection between MRgLITT and open resection.