OBJECTIVE:Surgery is increasingly recognized as an effective treatment for drug-resistant epilepsy in children but remains under-utilized. Evidence on its safety and benefits in infants 6 months or younger is very limited, leaving early surgical decision-making insufficiently supported. METHODS:A matched cohort study included 23 infants with age-dependent epileptic encephalopathy (ADEE) and structural brain abnormalities who underwent epilepsy surgery within 6 months and 115 matched non-surgical controls. Neurodevelopment was assessed using developmental quotient (DQ). Multivariable linear regression and propensity score matching (PSM) were used to examine the association between surgery and neurodevelopmental outcomes, whereas surgical safety and long-term seizure control were also evaluated. RESULTS:Among the 23 surgical infants, the median age at seizure onset was .27 months, and all had congenital brain malformations. Hemimegalencephaly was the most common etiology (n = 13). The mean age at surgery was 3.5 months. Hemispherotomy was the most commonly performed surgical procedure (n = 14). No perioperative death or permanent severe complications were observed. Four (17.4%) infants developed transient unilateral limb weakness and 13.6% had postoperative hydrocephalus. The rate of Engel class Ia was 82.6% at 1 year postoperatively and 78.2% at a mean follow-up of 44.4 months. At last follow-up, 69.6% of the infants had discontinued anti-seizure medications (ASMs). The DQ scores of the control group showed a continuous decline over time, whereas the surgical group showed a more favorable trajectory. Multivariable linear regression analysis revealed that surgery was significantly associated with a higher DQ (β = 30.2, 95% confidence interval [CI]: 19.5-40.9; p < .001). After 1:1 PSM to control confounding variables, the surgical group had significantly higher DQ scores than the control group in all five neurodevelopmental domains (p < .05). SIGNIFICANCE:Epilepsy surgery performed by an experienced team is safe and feasible for very young infants due to congenital brain malformations, without severe perioperative complications. It provides good long-term seizure control, supports ASM withdrawal, and may protect brain development, potentially stabilizing or even improving neurodevelopment in some infants.

BACKGROUND AND OBJECTIVES:More than half of people undergoing epilepsy surgery become seizure-free and may consider withdrawing antiseizure medications (ASMs). Withdrawal practices vary, and the optimal timing remains unclear. We aim to compare seizure relapse risk among individuals initiating ASM withdrawal at different time points after epilepsy surgery. METHODS:We conducted a multicenter observational cohort study of adults who underwent resective epilepsy surgery between 1990 and 2016 at 12 tertiary centers. Participants were seizure-free before medication withdrawal and had at least 1 year of follow-up. Seizure relapse risk was compared among those initiating withdrawal 1, 2, 3, 4, or 5 years postoperatively vs later. We used propensity score matching for each comparison to adjust for treatment selection bias. RESULTS:Of the 964 people included (51% female; median age at surgery 34 years [interquartile range 26-44]), 446 (46%) began ASM withdrawal in the first year after surgery, 255 (26%) in the second, 110 (11%) in the third, 58 (6%) in the fourth, 29 (3%) in the fifth, and 66 (7%) after the fifth year. After matching, those starting withdrawal in the first (hazard ratio [HR] 1.4; p = 0.003) or second (HR 1.18; p < 0.001) year had a higher risk of relapse than those who withdrew later. Starting withdrawal in the third (HR 1.7; p = 0.12), fourth (HR 1.3; p = 0.45), or fifth (HR 0.17; p = 0.82) year after surgery showed no increase in risk compared with later withdrawal. Long-term outcomes, such as seizure freedom and being entirely off ASMs at the final follow-up, were not substantially associated with withdrawal timing. DISCUSSION:Initiating ASM withdrawal within the first 2 postoperative years was linked to a higher initial risk of seizure relapse compared with later withdrawal, although long-term outcomes were similar regardless of withdrawal timing. Waiting more than 2 years did not confer additional benefit in reducing seizure risk. Deciding whether and when to withdraw ASMs is a shared process involving individuals, caregivers, and clinicians, balancing preferences, risk of injury, social factors (e.g., driving, work, and supervision), and clinical judgment. Transparent information on risks and benefits is essential. Our findings offer real-world evidence that may inform future evidence-based withdrawal protocols and follow-up strategies.

Attention is a cornerstone of cognitive function, and understanding its neural mechanisms is of great significance for both cognitive science and clinical applications. A critical aspect of this endeavor involves elucidating how the brain's network architecture shifts between internally- and externally-directed states. However, the distinct organizational principles of neural networks in these states, as well as the pivotal brain regions and connections that mediate such transitions, remain largely unclear. To investigate these network dynamics, this study analyzed stereo-electroencephalography (SEEG) data from 17 patients with refractory epilepsy performing a modified gradual-onset continuous performance task (gradCPT) designed to induce distinct internal and external attention states. High-frequency broadband (HFB, 70-170 Hz) signals were extracted as indicators of neural activity, and neural Granger causality analysis was employed to construct effective connectivity networks between brain regions. For the effective connectivity networks, we systematically applied modular analysis to quantify network segregation, node role classification to identify hub regions, and machine learning methods to evaluate the discriminative power of the identified connectivity differences. The results showed that the external attention state exhibited significantly stronger global causal connectivity and a topological profile dominated by connector hubs. In contrast, the internal attention state displayed higher modularity and a prevalence of peripheral nodes, reflecting a segregated network architecture. Eight pairs of brain region connections showed significant differences between the two states, primarily involving the parietal-temporal network. A support vector machine (SVM) classifier achieved 77.8% accuracy in distinguishing attention states under cross-subject conditions using the identified directed connectivity features, demonstrating the discriminative power of network differences. Feature importance analysis identified the intrinsic dynamics of the hippocampus (HIP) and its directed outflow to the middle temporal gyrus (MTG) as the most significant discriminative features. Consequently, the hippocampus operates in concert with temporal and parietal regions to mediate these transitions, suggesting that flexible cognitive control depends on the dynamic coupling between memory systems and cortical networks. These results provide potential neural biomarkers for attention-related disorders and advance our mechanistic understanding of how the brain adaptively organizes information flow to meet varying cognitive demands.

Predators attack across diverse spatiotemporal scales, prompting prey to respond through simple motor reactions (e.g., fleeing) or more complex cognitive processes (e.g., strategic planning). Recent studies suggest that escape relies on two distinct circuits: the reactive and cognitive fear circuits. However, their specific roles in different stages of escaping remain unclear. In this study, we recorded SEEG from epilepsy patients while they performed a modified flight initiation distance task. We identified cognitive fear regions, including the vmPFC and hippocampus, that encoded threat levels during the information processing stage. In the actual escaping stage, especially under rapid attack, the reactive fear circuit, including the midcingulate cortex and amygdala, was prominently activated. Notably, under rapid attack, we observed significant theta-band information flow from the amygdala to the vmPFC, suggesting dynamic communication between the reactive and cognitive fear circuits. These findings illuminate the distinct and complementary roles of the reactive and cognitive fear circuits in facilitating successful human escape.

Cooperation and competition are essential social behaviors in human society. This study utilized hyperscanning and stereo-electroencephalography (SEEG) to investigate intra- and inter-brain neural dynamics underlying these behaviors within the insula and inferior frontal gyrus (IFG), regions critical for executive function and mentalizing. We found distinct high-gamma responses and connectivity patterns, with a stronger influence from IFG to insula during competition and more balanced interactions during cooperation. Inter-brain synchronization shows significantly higher insula gamma synchronization during competition and higher IFG gamma synchronization during cooperation. Cross-frequency coupling suggests that these gamma synchronizations result from intra- and inter-brain interactions. Competition stems from intra-brain alpha-gamma coupling from IFG to insula and inter-brain IFG alpha synchronization, while cooperation is driven by intra-brain beta-gamma coupling from insula to IFG and inter-brain insula beta synchronization. Our findings provide insights into the neural basis of cooperation and competition, highlighting the roles of both insula and IFG.

Epilepsy, affecting approximately 52 millions worldwide, is characterized by an excitatory/inhibitory (E/I) imbalance in the epileptogenic zone (EZ). While elevated extracellular glutamate has been observed during seizures, traditional detection methods lack the temporal resolution required to capture sub-millisecond-scale quantal release events that underlie synaptic transmission. Most of the existing enzyme-based electrochemical sensors also face limitations in response speed and high cost. Here, we developed a novel ultra-fast glutamate sensor by constructing a nanoscale glutamate oxidase layer on carbon fiber electrodes using a rapid and low-cost chitosan-based electrodeposition strategy. This approach reduced enzyme consumption by over 10-fold and shortened fabrication time to under 3 min, while maintaining excellent electrochemical performance and sub-millisecond response speed to quantal glutamate release. We applied the sensor in resected brain tissues from six patients with focal cortical dysplasia, one of the most common etiologies of drug-resistant epilepsy, and successfully recorded pathological alterations in both tonic and phasic glutamate release. The phasic signals occurring on a sub-millisecond scale—significantly faster than the second-scaled signals measured in earlier work—represent amperometric signals associated with quantal glutamate release, thereby referring to the discharge of the contents of an individual glutamatergic synaptic vesicle. Notably, to the best of our knowledge, this is the first report of quantal glutamate release events measured with sub-millisecond resolution in the human brain ex vivo. Our findings provide new insights into E/I imbalance mechanisms and demonstrate the sensor's utility for probing neuropathology in neurological disorders.

Third-party punishment (TPP) is a critical component of social regulation and justice, in-tegrating moral reasoning and emotional salience. However, the neural developmental basis underpinning this complex process remains largely unknown. Using rare intracranial stereo-electroencephalography (SEEG) in 14 children and 17 adults, we investigated the developing neural circuits of TPP. We found that broad-band gamma activity in the amygdala and ventromedial prefrontal cortex (vmPFC) encodes inferred intentions, with different patterns across age groups. Furthermore, the vmPFC, insula, and inferior parietal lobule (IPL) integrate punishment efficacy, also showing significant developmental differences. Combining task and resting state functional connectivity analyses, we further found age-dependent interactions among the amygdala-insula and IPL-vmPFC neural couplings during decision-making. These findings provide valuable intracranial evidence that the maturation of moral decision-making stems from the developmental refinement of subcortical-cortical circuits that integrate emotional and cognitive evaluations, explaining the shift from intuitive decisions in children to context-sensitive judgments in adults. ### Competing Interest Statement The authors have declared no competing interest. Science and Technology Development Fund (FDCT) of Macau, 0127/2020/A3, 0041/2022/A, 0112/2024/RIA2 Natural Science Foundation of Guangdong Province, 2021A1515012509 Shenzhen-Hong Kong-Macao Science and Technology Innovation Project (Category C), SGDX2020110309280100 MYRG of University of Macau, MYRG2022-00188- ICI

Introduction Epilepsy is one of the most common serious brain conditions. Focal cortical dysplasia(FCD) is the most common diagnosis in children among patients with drug-resistant epilepsy who require surgical treatment. However, the pathogenic genes and the interaction between different cells of FCD are not clear, especially the immune mechanism of FCD remains nascent. We further analyze FCD data in terms of genes, cellular changes and immune infiltration by integrating bulk and single-cell sequencing data. Methods The scRNA-seq dataset GSE201048 and bulk RNA-seq dataset GSE62019 were combined to perform deconvolution to infer the cell composition ratio of samples in bulk RNA-seq of FCD. We used AUCell analysis, GO and KEGG enrichment analysis, cell communication analysis and WGCNA to analyze pericyte function and pericyte cell communication. PPI was used to identify hub genes. GSVA and The Pearson correlation analysis were used to identify relationships between hub genes and pericyte. We used logistic regression to construct a diagnostic model based on hub genes. Finally, we performed immune infiltration analysis. Results Pericytes were significantly reduced in FCD. Neutrophils cells were significantly different between the FCD group and the control group ( p < 0.05 ), and the degree of immune infiltration was higher in the FCD group. PPI network analysis identified 5 hub genes related to pericytes. Through LASSO regression analysis, we established a risk score model containing five genes. Conclusion This study provides a new perspective to study the molecular mechanism and cell changes in FCD. It was found for the first time that pericytes play an important role in FCD.

Balloon cells (BCs) are specific pathological marker of cortical malformations during brain development, often associated with epilepsy and development delay. Although a large number of studies have investigated the role of BCs in these diseases, the specific function of BCs as either epileptogenic or antiepileptic remains controversial. Therefore, we reviewed literatures on BCs, delved into the molecular mechanisms and signaling pathways, and updated their profile in several aspects. Firstly, BCs are heterogeneous and some of them show progenitor/stem cell characteristics. Secondly, BCs are relatively silent in electrophysiology but not completely isolated from their surroundings. Notably, abnormal mTOR signaling and aberrant immunogenic process have been observed within BCs-containing malformations of cortical development (MCDs). The question whether BCs function as the evildoer or the defender in BCs-containing MCDs is further discussed. Importantly, this review provides perspectives on future investigations of the potential role of BCs in epilepsy.

OBJECTIVE:The primary objective of this retrospective analysis was to evaluate the incidence and lateralization value of peri-ictal yawning (PY) in people with temporal lobe epilepsy (TLE). PY has only occasionally been reported as a manifestation of focal epilepsy. We aimed to determine whether PY could serve as an indicator to help lateralize seizure onset during epileptic seizures. METHODS:Among 236 consecutive TLE patients admitted for video-EEG monitoring, we analyzed the clinical characteristics, along with scalp video-EEG, magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET), Wada test, and stereo EEG (SEEG) in patients with PY. RESULTS:Among the 236 patients, 26 (11.0%) exhibited PY, and 36 of 1018 recorded seizures (3.5%) were associated with PY. Of the 26 patients with PY, 19 (73.1%) had non-dominant TLE, while 7 (26.9%) had dominant TLE. The majority of these patients presented with staring, arrest, and automatisms during their seizures with accompanying vegetative signs. PY occurred either during the ictal or postictal phase in all patients. Exception for 10 seizures (10/36, 27.8%) at the early stage (less than 25% total duration), PY was primarily linked to the late ictal and postictal phases. Surgical intervention was performed in 12 patients, 9 of whom (75%) achieved seizure freedom (Engel class I), with 7 of these 9 (77.8%) having non-dominant TLE. SIGNIFICANCE:Yawning is a physiological phenomenon typically not associated with epilepsy. The present series suggests that PY is relatively uncommon in TLE, but may represent a rare vegetative sign, particularly in cases with non-dominant TLE. Further investigation with a larger cohort of surgically confirmed cases and using intracranial EEG is essential to deepen our understanding of this phenomenon. PLAIN LANGUAGE SUMMARY:Yawning is a typical physiological response that is generally not linked to epilepsy. However, it can occasionally indicate seizure activity, particularly in TLE. PY happens more often observed in non-dominant TLE and usually occurs in the later stages of a seizure or just after it. It may hold potential as a lateralizing marker in TLE.

BackgroundTuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions.MethodsWe acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis.ResultsIn TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p < 0.05) in Plasma cells, T cells regulatory (Tregs), and Macrophages M2 were observed between diagnostic groups. Microglia cells were highly correlated with lipid metabolism functions.ConclusionsOur research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy.

BackgroundEpilepsy stands as an intricate disorder of the central nervous system, subject to the influence of diverse risk factors and a significant genetic predisposition. Within the pathogenesis of temporal lobe epilepsy (TLE), the apoptosis of neurons and glial cells in the brain assumes pivotal importance. The identification of differentially expressed apoptosis-related genes (DEARGs) emerges as a critical imperative, providing essential guidance for informed treatment decisions.MethodsWe obtained datasets related to epilepsy, specifically GSE168375 and GSE186334. Utilizing differential expression analysis, we identified a set of 249 genes exhibiting significant variations. Subsequently, through an intersection with apoptosis-related genes, we pinpointed 16 genes designated as differentially expressed apoptosis-related genes (DEARGs). These DEARGs underwent a comprehensive array of analyses, including enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, prediction of miRNA and transcription factors, and molecular docking analysis.ResultsIn the epilepsy datasets examined, we successfully identified 16 differentially expressed apoptosis-related genes (DEARGs). Subsequent validation in the external dataset GSE140393 revealed the diagnostic potential of five biomarkers (CD38, FAIM2, IL1B, PAWR, S100A8) with remarkable accuracy, exhibiting an impressive area under curve (AUC) (The overall AUC of the model constructed by the five key genes was 0.916, and the validation set was 0.722). Furthermore, a statistically significant variance (p < 0.05) was observed in T cell CD4 naive and eosinophil cells across different diagnostic groups. Exploring interaction networks uncovered intricate connections, including gene-miRNA interactions (164 interactions involving 148 miRNAs), gene-transcription factor (TF) interactions (22 interactions with 20 TFs), and gene-drug small molecule interactions (15 interactions involving 15 drugs). Notably, IL1B and S100A8 demonstrated interactions with specific drugs.ConclusionIn the realm of TLE, we have successfully pinpointed noteworthy differentially expressed apoptosis-related genes (DEARGs), including CD38, FAIM2, IL1B, PAWR, and S100A8. A comprehensive understanding of the implications associated with these identified genes not only opens avenues for advancing our comprehension of the underlying pathophysiology but also bears considerable potential in guiding the development of innovative diagnostic methodologies and therapeutic interventions for the effective management of epilepsy in the future.

Attentional control, guided by top-down processes, enables selective focus on pertinent information, while habituation, influenced by bottom-up factors and prior experiences, shapes cognitive responses by emphasizing stimulus relevance. These two fundamental processes collaborate to regulate cognitive behavior, with the prefrontal cortex and its subregions playing a pivotal role. Nevertheless, the intricate neural mechanisms underlying the interaction between attentional control and habituation are still a subject of ongoing exploration. To our knowledge, there is a dearth of comprehensive studies on the functional connectivity between subsystems within the prefrontal cortex during attentional control processes in both primates and humans. Utilizing stereo-electroencephalogram (SEEG) recordings during the Stroop task, we observed top-down dominance effects and corresponding connectivity patterns among the orbitofrontal cortex (OFC), the middle frontal gyrus (MFG), and the inferior frontal gyrus (IFG) during heightened attentional control. These findings highlighting the involvement of OFC in habituation through top-down attention. Our study unveils unique connectivity profiles, shedding light on the neural interplay between top-down and bottom-up attentional control processes, shaping goal-directed attention.

Dravet syndrome (DS), previously known as severe myoclonic epilepsy in infancy (SMEI), is considered the most serious "epileptic encephalopathy." Here, we present a man with a de novo SCN1A mutation who was diagnosed with DS at the age of 29. In addition to pharmaco-resistant seizures and cognitive delay, he also developed moderate to severe motor and gait problems, such as crouching gait and Pisa syndrome. Moreover, it deteriorated significantly following an epileptic seizure. The patient presented with severe flexion of the head and trunk in the sagittal plane and fulfilled the diagnostic criteria for camptocormia and antecollis. After a week, it spontaneously alleviated partially. We applied levodopa to the patient and had a good response. Functional Gait Assessment (FGA) was assessed at three different times: 4 days after the seizure, 1 week after the seizure, and after taking levodopa for 2 years. The results were 4, 12, and 19 points, respectively. We postulated that: (1) gait and motor deficits are somehow influenced by recurrent epileptic episodes;(2) the nigrostriatal dopamine system is involved. To our knowledge, we were the ones who first reported this phenomenon.

OBJECTIVES:Although hemispheric surgeries are among the most effective procedures for drug-resistant epilepsy (DRE) in the pediatric population, there is a large variability in seizure outcomes at the group level. A recently developed HOPS score provides individualized estimation of likelihood of seizure freedom to complement clinical judgement. The objective of this study was to develop a freely accessible online calculator that accurately predicts the probability of seizure freedom for any patient at 1-, 2-, and 5-years post-hemispherectomy. METHODS:Retrospective data of all pediatric patients with DRE and seizure outcome data from the original Hemispherectomy Outcome Prediction Scale (HOPS) study were included. The primary outcome of interest was time-to-seizure recurrence. A multivariate Cox proportional-hazards regression model was developed to predict the likelihood of post-hemispheric surgery seizure freedom at three time points (1-, 2- and 5- years) based on a combination of variables identified by clinical judgment and inferential statistics predictive of the primary outcome. The final model from this study was encoded in a publicly accessible online calculator on the International Network for Epilepsy Surgery and Treatment (iNEST) website (https://hops-calculator.com/). RESULTS:The selected variables for inclusion in the final model included the five original HOPS variables (age at seizure onset, etiologic substrate, seizure semiology, prior non-hemispheric resective surgery, and contralateral fluorodeoxyglucose-positron emission tomography [FDG-PET] hypometabolism) and three additional variables (age at surgery, history of infantile spasms, and magnetic resonance imaging [MRI] lesion). Predictors of shorter time-to-seizure recurrence included younger age at seizure onset, prior resective surgery, generalized seizure semiology, FDG-PET hypometabolism contralateral to the side of surgery, contralateral MRI lesion, non-lesional MRI, non-stroke etiologies, and a history of infantile spasms. The area under the curve (AUC) of the final model was 73.0%. SIGNIFICANCE:Online calculators are useful, cost-free tools that can assist physicians in risk estimation and inform joint decision-making processes with patients and families, potentially leading to greater satisfaction. Although the HOPS data was validated in the original analysis, the authors encourage external validation of this new calculator.

Background:Posterior cortex epilepsy (PCE) primarily comprises seizures originating from the occipital, parietal, and/or posterior edge of the temporal lobe. Electroclinical dissociation and subtle imaging representation render the diagnosis of PCE challenging. Improved methods for accurately identifying patients with PCE are necessary. Objectives:To develop a novel voxel-based image postprocessing method for better visual identification of the neuroimaging abnormalities associated with PCE. Design:Multicenter, retrospective study. Methods:Clinical and imaging features of 165 patients with PCE were retrospectively reviewed and collected from five epilepsy centers. A total of 37 patients (32.4% female, 20.2 ± 8.9 years old) with magnetic resonance imaging (MRI)-negative PCE were finally included for analysis. Image postprocessing features were calculated over a neighborhood for each voxel in the multimodality data. The postprocessed maps comprised structural deformation, hyperintense signal, and hypometabolism. Five raters from three different centers were blinded to the clinical diagnosis and determined the neuroimaging abnormalities in the postprocessed maps. Results:The average accuracy of correct identification was 55.7% (range from 43.2 to 62.2%) and correct lateralization was 74.1% (range from 64.9 to 81.1%). The Cronbach's alpha was 0.766 for the correct identification and 0.683 for the correct lateralization with similar results of the interclass correlation coefficient, thus indicating reliable agreement between the raters. Conclusion:The image postprocessing method developed in this study can potentially improve the visual detection of MRI-negative PCE. The technique could lead to an increase in the number of patients with PCE who could benefit from the surgery.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

To develop and validate a model to predict seizure freedom in children undergoing cerebral hemispheric surgery for the treatment of drug‐resistant epilepsy.

CNTNAP2 (coding for protein Caspr2), a member of the neurexin family, plays an important role in the balance of excitatory and inhibitory post-synaptic currents (E/I balance). Here, we describe a novel pathogenic missense mutation in an infant with spontaneous recurrent seizures (SRSs) and intellectual disability. Genetic testing revealed a missense mutation, c.2329 C>G (p. R777G), in the CNTNAP2 gene. To explore the effect of this novel mutation, primary cultured neurons were transfected with wild type homo CNTNAP2 or R777G mutation and the morphology and function of neurons were evaluated. When compared with the vehicle control group or wild type group, the neurites and the membrane currents, including spontaneous excitatory post-synaptic currents (sEPSCs) and inhibitory post-synaptic currents (sIPSCs), in CNTNAP2 R777G mutation group were all decreased or weakened. Moreover, the action potentials (APs) were also impaired in CNTNAP2 R777G group. Therefore, CNTNAP2 R777G may lead to the imbalance of excitatory and inhibitory post-synaptic currents in neural network contributing to SRSs.