Clustered de novo start-loss variants in GLUL result in a developmental and epileptic encephalopathy via stabilization of glutamine synthetase.

Glutamine synthetase (GS), encoded by GLUL, catalyzes the conversion of glutamate to glutamine. GS is pivotal for the generation of the neurotransmitters glutamate and gamma-aminobutyric acid and is the primary mechanism of ammonia detoxification in the brain. GS levels are regulated post-translationally by an N-terminal degron that enables the ubiquitin-mediated degradation of GS in a glutamine-induced manner. GS deficiency in humans is known to lead to neurological defects and death in infancy, yet how dysregulation of the degron-mediated control of GS levels might affect neurodevelopment is unknown. We ascertained nine individuals with severe developmental delay, seizures, and white matter abnormalities but normal plasma and cerebrospinal fluid biochemistry with de novo variants in GLUL. Seven out of nine were start-loss variants and two out of nine disrupted 5' UTR splicing resulting in splice exclusion of the initiation codon. Using transfection-based expression systems and mass spectrometry, these variants were shown to lead to translation initiation of GS from methionine 18, downstream of the N-terminal degron motif, resulting in a protein that is stable and enzymatically competent but insensitive to negative feedback by glutamine. Analysis of human single-cell transcriptomes demonstrated that GLUL is widely expressed in neuro- and glial-progenitor cells and mature astrocytes but not in post-mitotic neurons. One individual with a start-loss GLUL variant demonstrated periventricular nodular heterotopia, a neuronal migration disorder, yet overexpression of stabilized GS in mice using in utero electroporation demonstrated no migratory deficits. These findings underline the importance of tight regulation of glutamine metabolism during neurodevelopment in humans.

Functional Characteristics of the Nav1.1 p.Arg1596Cys Mutation Associated with Varying Severity of Epilepsy Phenotypes.

Mutations of the SCN1A gene, which encodes the voltage-dependent Na+ channel's α subunit, are associated with diverse epileptic syndromes ranging in severity, even intra-family, from febrile seizures to epileptic encephalopathy. The underlying cause of this variability is unknown, suggesting the involvement of additional factors. The aim of our study was to describe the properties of mutated channels and investigate genetic causes for clinical syndromes' variability in the family of five SCN1A gene p.Arg1596Cys mutation carriers. The analysis of additional genetic factors influencing SCN1A-associated phenotypes was conducted through exome sequencing (WES). To assess the impact of mutations, we used patch clamp analysis of mutated channels expressed in HEK cells and in vivo neural excitability studies (NESs). In cells expressing the mutant channel, sodium currents were reduced. NESs indicated increased excitability of peripheral motor neurons in mutation carriers. WES showed the absence of non-SCA1 pathogenic variants that could be causative of disease in the family. Variants of uncertain significance in three genes, as potential modifiers of the most severe phenotype, were identified. The p.Arg1596Cys substitution inhibits channel function, affecting steady-state inactivation kinetics. Its clinical manifestations involve not only epileptic symptoms but also increased excitability of peripheral motor fibers. The role of Nav1.1 in excitatory neurons cannot be ruled out as a significant factor of the clinical phenotype.

High-density electroencephalographic functional networks in genetic generalized epilepsy: Preserved whole-brain topology hides local reorganization.

OBJECTIVE: Genetic generalized epilepsy (GGE) accounts for approximately 20% of adult epilepsy cases and is considered a disorder of large brain networks, involving both hemispheres. Most studies have not shown any difference in functional whole-brain network topology when compared to healthy controls. Our objective was to examine whether this preserved global network topology could hide local reorganizations that balance out at the global network level. METHODS: We recorded high-density electroencephalograms from 20 patients and 20 controls, and reconstructed the activity of 118 regions. We computed functional connectivity in windows free of interictal epileptiform discharges in broad, delta, theta, alpha, and beta frequency bands, characterized the network topology, and used the Hub Disruption Index (HDI) to quantify the topological reorganization. We examined the generalizability of our results by reproducing a 25-electrode clinical system. RESULTS: Our study did not reveal any significant change in whole-brain network topology among GGE patients. However, the HDI was significantly different between patients and controls in all frequency bands except alpha (p < .01, false discovery rate [FDR] corrected, d < -1), and accompanied by an increase in connectivity in the prefrontal regions and default mode network. This reorganization suggests that regions that are important in transferring the information in controls were less so in patients. Inversely, the crucial regions in patients are less so in controls. These findings were also found in delta and theta frequency bands when using 25 electrodes (p < .001, FDR corrected, d < -1). SIGNIFICANCE: In GGE patients, the overall network topology is similar to that of healthy controls but presents a balanced local topological reorganization. This reorganization causes the prefrontal areas and default mode network to be more integrated and segregated, which may explain executive impairment associated with GGE. Additionally, the reorganization distinguishes patients from controls even when using 25 electrodes, suggesting its potential use as a diagnostic tool.

Molecular and Phenotypic Characterization of the RORB-Related Disorder.

BACKGROUND AND OBJECTIVES: Heterozygous variants in RAR-related orphan receptor B (RORB) have recently been associated with susceptibility to idiopathic generalized epilepsy. However, few reports have been published so far describing pathogenic variants of this gene in patients with epilepsy and intellectual disability (ID). In this study, we aimed to delineate the epilepsy phenotype associated with RORB pathogenic variants and to provide arguments in favor of the pathogenicity of variants. METHODS: Through an international collaboration, we analyzed seizure characteristics, EEG data, and genotypes of a cohort of patients with heterozygous variants in RORB. To gain insight into disease mechanisms, we performed ex vivo cortical electroporation in mouse embryos of 5 selected variants, 2 truncating and 3 missense, and evaluated on expression and quantified changes in axonal morphology. RESULTS: We identified 35 patients (17 male, median age 10 years, range 2.5-23 years) carrying 32 different heterozygous variants in RORB, including 28 single-nucleotide variants or small insertions/deletions (12 missense, 12 frameshift or nonsense, 2 splice-site variants, and 2 in-frame deletions), and 4 microdeletions; de novo in 18 patients and inherited in 10. Seizures were reported in 31/35 (89%) patients, with a median age at onset of 3 years (range 4 months-12 years). Absence seizures occurred in 25 patients with epilepsy (81%). Nineteen patients experienced a single seizure type: absences, myoclonic absences, or absences with eyelid myoclonia and focal seizures. Nine patients had absence seizures combined with other generalized seizure types. One patient had presented with absences associated with photosensitive occipital seizures. Three other patients had generalized tonic-clonic seizures without absences. ID of variable degree was observed in 85% of the patients. Expression studies in cultured neurons showed shorter axons for the 5 tested variants, both truncating and missense variants, supporting an impaired protein function. DISCUSSION: In most patients, the phenotype of the RORB-related disorder associates absence seizures with mild-to-moderate ID. In silico and in vitro evaluation of the variants in our cohort, including axonal morphogenetic experiments in cultured neurons, supports their pathogenicity, showing a hypomorphic effect.

Prenatal diagnosis of developmental and epileptic encephalopathy 9 with a 10.05-Mb microdeletion at Xq21.31q22.1 inherited from mother: A case report and literature review.

BACKGROUND: Developmental and epileptic encephalopathy 9 (DEE9) is characterized by early infantile seizures and mild-to-severe neuropsychiatric symptoms. Despite being an X-linked dominant disorder, DEE9 mainly affects heterozygous females or mosaic males, while hemizygous males are less affected. PCDH19 gene has been documented as the causative gene. METHODS: Karyotyping analysis and copy number variation sequencing (CNV-seq) were performed on a pregnant woman with epilepsy, together with her husband, son, and fetus. RESULTS: A disease-causing microdeletion, seq[GRCh37] del(X)(q21.31q22.1) (90310001-100360000), was identified in the pregnant woman and her female fetus. The microdeletion includes the entire PCDH19 gene and is classified as "pathogenic" according to the American College of Medical Genetics and Genomics guidelines. CONCLUSION: In this case study, we have not only identified the epilepsy type of the woman as DEE9 but have also made an unfavorable prognosis for her fetus. Our findings from this prenatal case provide valuable clinical resources for prenatal diagnosis and genetic counseling, while also implying the potential of CNV-seq as a viable method for uncovering PCDH19-related epilepsy.

Identification of potential disease-associated variants in idiopathic generalized epilepsy using targeted sequencing.

Many questions remain regarding the genetics of idiopathic generalized epilepsy (IGE), a subset of genetic generalized epilepsy (GGE). We aimed to identify the candidate coding variants of epilepsy panel genes in a cohort of affected individuals, using variant frequency information from a control cohort of the same region. We performed whole-exome sequencing analysis of 121 individuals and 10 affected relatives, focusing on variants of 950 candidate genes associated with epilepsy according to the Genes4Epilepsy curated panel. We identified 168 candidate variants (CVs) in 137 of 950 candidate genes in 88 of 121 affected individuals with IGE, of which 61 were novel variants. Notably, we identified five CVs in known GGE-associated genes (CHD2, GABRA1, RORB, SCN1A, and SCN1B) in five individuals and CVs shared by affected individuals in each of four family cases for other epilepsy candidate genes. The results of this study demonstrate that IGE is a disease with high heterogeneity and provide IGE-associated CVs whose pathogenicity should be proven by future studies, including advanced functional analysis. The low detection rate of CVs in the GGE-associated genes (4.1%) in this study suggests the current incompleteness of the Genes4Epilepsy panel for the diagnosis of IGE in clinical practice.

Coexistence of temporal lobe epilepsy and idiopathic generalized epilepsy.

OBJECTIVE: We investigated the frequency of coexistence of temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) in a retrospective database study. We also explored the underlying pathomechanisms of the coexistence of TLE and IGE based on the available information, using bioinformatics tools. METHODS: The first phase of the investigation was a retrospective study. All patients with an electro-clinical diagnosis of epilepsy were studied at the outpatient epilepsy clinic at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2023. In the second phase, we searched the following databases for genetic variations (epilepsy-associated genetic polymorphisms) that are associated with TLE or syndromes of IGE: DisGeNET, genome-wide association study (GWAS) Catalog, epilepsy genetic association database (epiGAD), and UniProt. We also did a separate literature search using PubMed. RESULTS: In total, 3760 patients with epilepsy were registered at our clinic; four patients with definitely mixed TLE and IGE were identified; 0.1% of all epilepsies. We could identify that rs1883415 of ALDH5A1, rs137852779 of EFHC1, rs211037 of GABRG2, rs1130183 of KCNJ10, and rs1045642 of ABCB1 genes are shared between TLE and syndromes of IGE. CONCLUSION: While coexistence of TLE and IGE is a rare phenomenon, this could be explained by shared genetic variations.

Early-Life Epilepsies.

Epilepsies are a diverse group of neurological disorders characterized by recurrent seizures. One-third of epilepsies are refractory to standard antiseizure medications. Epilepsy incidence is age-dependent with high incidence in neonates and infants. Epilepsy syndromes are classified based on clinical, electrographic, neuroimaging, age-dependent features of onset and the possibility of remission. Advances in genetic testing technology and improved access to clinical genetic testing, including whole exome sequencing, have facilitated a fundamental shift in gene discovery of monogenetic and polygenetic epilepsy, leading to precision medicine therapy and improved outcomes. Here, we review the self-limited epilepsy syndromes and developmental and epileptic encephalopathies that begin in the neonatal-infantile period with an emphasis on genetic etiology and the shifting landscape of treatment options based on genetic findings. [Pediatr Ann. 2023;52(10):e381-e387.].

A novel de novo HCN2 loss-of-function variant causing developmental and epileptic encephalopathy treated with a ketogenic diet.

Missense variants of hyperpolarization-activated, cyclic nucleotide-gated (HCN) ion channels cause variable phenotypes, ranging from mild generalized epilepsy to developmental and epileptic encephalopathy (DEE). Although variants of HCN1 are an established cause of DEE, those of HCN2 have been reported in generalized epilepsies. Here we describe the first case of DEE caused by the novel de novo heterozygous missense variant c.1379G>A (p.G460D) of HCN2. Functional characterization in transfected HEK293 cells and neonatal rat cortical neurons revealed that HCN2 p.G460D currents were strongly reduced compared to wild-type, consistent with a dominant negative loss-of-function effect. Immunofluorescence staining showed that mutant channels are retained within the cell and do not reach the membrane. Moreover, mutant HCN2 also affect HCN1 channels, by reducing the Ih current expressed by the HCN1-HCN2 heteromers. Due to the persistence of frequent seizures despite pharmacological polytherapy, the patient was treated with a ketogenic diet, with a significant and long-lasting reduction of episodes. In vitro experiments conducted in a ketogenic environment demonstrated that the clinical improvement observed with this dietary regimen was not mediated by a direct action on HCN2 activity. These results expand the clinical spectrum related to HCN2 channelopathies, further broadening our understanding of the pathogenesis of DEE.

Unraveling the role of non-coding rare variants in epilepsy.

The discovery of new variants has leveled off in recent years in epilepsy studies, despite the use of very large cohorts. Consequently, most of the heritability is still unexplained. Rare non-coding variants have been largely ignored in studies on epilepsy, although non-coding single nucleotide variants can have a significant impact on gene expression. We had access to whole genome sequencing (WGS) from 247 epilepsy patients and 377 controls. To assess the functional impact of non-coding variants, ExPecto, a deep learning algorithm was used to predict expression change in brain tissues. We compared the burden of rare non-coding deleterious variants between cases and controls. Rare non-coding highly deleterious variants were significantly enriched in Genetic Generalized Epilepsy (GGE), but not in Non-Acquired Focal Epilepsy (NAFE) or all epilepsy cases when compared with controls. In this study we showed that rare non-coding deleterious variants are associated with epilepsy, specifically with GGE. Larger WGS epilepsy cohort will be needed to investigate those effects at a greater resolution. Nevertheless, we demonstrated the importance of studying non-coding regions in epilepsy, a disease where new discoveries are scarce.

Multi-spectral diffusion MRI mega-analysis in genetic generalized epilepsy: Relation to outcomes.

BACKGROUND AND OBJECTIVES: Genetic generalized epilepsy (GGE) is the most common form of generalized epilepsy. Although individual patients with GGE typically present without structural alterations, group differences have been demonstrated in GGE and some GGE subtypes like juvenile myoclonic epilepsy (GGE-JME). Previous studies usually involved only small cohorts from single centers and therefore could not assess imaging markers of multiple GGE subtypes. METHODS: We performed a diffusion MRI mega-analysis in 192 participants consisting of 126 controls and 66 patients with GGE from four different cohorts and two different epilepsy centers. We applied whole-brain multi-site harmonization and analyzed fractional anisotropy (FA), as well as mean, radial and axial diffusivity (MD/RD/AD) to assess differences between controls, patients with GGE and the common GGE subtypes, i.e. GGE with generalized tonic-clonic seizures only (GGE-GTCS), GGE-JME and absence epilepsy (GGE-AE). We also analyzed relationships with patients' response to anti-seizure-medication (ASM). RESULTS: Relative to controls, we identified decreased anisotropy and increased RD in patients with GGE. We found no significant effects of disease duration, age of onset or seizure frequency on diffusion metrics. Patients with JME had increased MD and RD when compared to controls, while patients with GGE-GTCS showed decreased MD/AD when compared to controls. Compared to patients with GGE-AE, patients with GGE-GTCS had lower AD/MD. Compared to patients with GGE-GTCS, patients with GGE-JME had higher MD/RD and AD. Moreover, we found lower FA in patients with refractory when compared to patients with non-refractory GGE in the right cortico-spinal tract, but no significant differences in patients with active versus controlled epilepsy. DISCUSSION: We provide evidence that clinically defined GGE as a whole and GGE-subtypes harbor marked microstructural differences detectable with diffusion MRI. Moreover, we found an association between microstructural changes and treatment resistance. Our findings have important implications for future full-resolution multi-site studies when assessing GGE, its subtypes and ASM refractoriness.

Calgary score and modified calgary score in the differential diagnosis between syncope and genetic generalized epilepsy in children.

The purpose of the study is to explore the use of Calgary scoring (CS) and Modified Calgary scoring (MCS) in the differentiation of genetic generalized epilepsy and syncope in children. The study involved 117 patients aged < 18 years who presented to our hospital's pediatric neurology outpatient clinic with TLOC between June 2020 and June 2022. In addition to CS and MCS scoring, all patients were subjected to statistical analysis based on their age, sex, number of episodes and distribution during the day, duration of syncope, and family history. Seventy-one patients with syncope and 46 with epilepsy were included in the study. At a CS value > - 1, sensitivity was 86.9% and specificity 63.4%, while at an MCS value > - 1, sensitivity was 76.1% and specificity 71.8%. CS had less specificity and sensitivity in predicting epilepsy when focal epilepsies were excluded. Abnormal behavior noted by bystanders, including witnessed unresponsive, unusual posturing, or limb jerking? (Q5) emerged as the most important question for the detection of epilepsy. Compared with other syncope findings, loss of consciousness during prolonged sitting or standing (Q9) emerged as the most important for the detection of syncope.

Multidisciplinary molecular consultation increases the diagnosis of pediatric epileptic encephalopathy and neurodevelopmental disorders.

BACKGROUND: Epilepsy (EP) is a common neurological disease in which 70-80% are thought to have a genetic cause. In patients with epilepsy, neurodevelopmental delay (NDD) was prevalent. Next generation of sequencing has been widely used in diagnosing EP/NDD. However, the diagnostic yield remains to be 40%-50%. Many reanalysis pipelines and software have been developed for automated reanalysis and decision making for the diseases. Nevertheless, it is a highly challenging task for smaller genetic centers or a routine pediatric practice. To address the clinical and genetic "diagnostic odyssey," we organized a Multidisciplinary Molecular Consultation (MMC) team for molecular consultation for 202 children with EP/NDD patients referred by lower level hospitals. METHODS: All the patients had undergone an aligned and sequential consultations and discussions by a "triple reanalysis" procedure by clinical, genetic specialists, and researchers. RESULTS: Among the 202 cases for MMC, we totally identified 47 cases (23%) harboring causative variants in 24 genes and 15 chromosomal regions after the MMC. In the 15 cases with positive CNVs, 3 cases harbor the deletions or duplications in 16p11.2, and 2 cases for 1p36. The bioinformatical reanalysis revealed 47 positive cases, in which 12 (26%) were reported to be negative, VUS or incorrectly positive in pre-MMC reports. Additionally, among 87 cases with negative cases, 4 (5%) were reported to be positive in pre-MMC reports. CONCLUSION: We established a workflow allowing for a "one-stop" collaborative assessments by experts of multiple fields and helps for correct the diagnosis of cases with falsenegative and -positive and VUS genetic reports and may have significant influences for intervention, prevention and genetic counseling of pediatric epilepsy and neurodevelopmental disorders.

SCN1A-deficient excitatory neuronal networks display mutation-specific phenotypes.

Dravet syndrome is a severe epileptic encephalopathy, characterized by (febrile) seizures, behavioural problems and developmental delay. Eighty per cent of patients with Dravet syndrome have a mutation in SCN1A, encoding Nav1.1. Milder clinical phenotypes, such as GEFS+ (generalized epilepsy with febrile seizures plus), can also arise from SCN1A mutations. Predicting the clinical phenotypic outcome based on the type of mutation remains challenging, even when the same mutation is inherited within one family. This clinical and genetic heterogeneity adds to the difficulties of predicting disease progression and tailoring the prescription of anti-seizure medication. Understanding the neuropathology of different SCN1A mutations may help to predict the expected clinical phenotypes and inform the selection of best-fit treatments. Initially, the loss of Na+-current in inhibitory neurons was recognized specifically to result in disinhibition and consequently seizure generation. However, the extent to which excitatory neurons contribute to the pathophysiology is currently debated and might depend on the patient clinical phenotype or the specific SCN1A mutation. To examine the genotype-phenotype correlations of SCN1A mutations in relation to excitatory neurons, we investigated a panel of patient-derived excitatory neuronal networks differentiated on multi-electrode arrays. We included patients with different clinical phenotypes, harbouring various SCN1A mutations, along with a family in which the same mutation led to febrile seizures, GEFS+ or Dravet syndrome. We hitherto describe a previously unidentified functional excitatory neuronal network phenotype in the context of epilepsy, which corresponds to seizurogenic network prediction patterns elicited by proconvulsive compounds. We found that excitatory neuronal networks were affected differently, depending on the type of SCN1A mutation, but did not segregate according to clinical severity. Specifically, loss-of-function mutations could be distinguished from missense mutations, and mutations in the pore domain could be distinguished from mutations in the voltage sensing domain. Furthermore, all patients showed aggravated neuronal network responses at febrile temperatures compared with controls. Finally, retrospective drug screening revealed that anti-seizure medication affected GEFS+ patient- but not Dravet patient-derived neuronal networks in a patient-specific and clinically relevant manner. In conclusion, our results indicate a mutation-specific excitatory neuronal network phenotype, which recapitulates the foremost clinically relevant features, providing future opportunities for precision therapies.

Epilepsies of presumed genetic etiology show enrichment of rare variants that occur in the general population.

Previous studies suggested that severe epilepsies, e.g., developmental and epileptic encephalopathies (DEEs), are mainly caused by ultra-rare de novo genetic variants. For milder disease, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 control individuals. Here, we separately analyzed three different groups of epilepsies: severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in control individuals with an allele count ≥ 1 and a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD ≥ 20), and to have an odds ratio in individuals with epilepsy ≥ 2. We identified genes enriched with QRVs primarily in NAFE (n = 72), followed by GGE (n = 32) and DEE (n = 21). This suggests that rare variants may play a more important role for causality of NAFE than for DEE. Moreover, we found that genes harboring QRVs, e.g., HSGP2, FLNA, or TNC, encode proteins that are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE that occur also in the general population, while in DEE and GGE, the contribution of such variants appears more limited.

Association of symptoms of psychiatric disease and electroencephalographic patterns in idiopathic generalized epilepsy.

OBJECTIVE: Idiopathic generalized epilepsies (IGE) are genetic epilepsies with alterations of thalamo-frontocortical circuits that play a major role in seizure generation and propagation. Psychiatric diseases and drug resistance are strongly associated, but it remains unknown if they are symptoms of the same pathophysiological process. Hypothesizing that the same network alterations are associated with the frequency of epileptic discharges (ED) and psychiatric symptoms, we here tested the association of self-reported psychiatric symptoms and IGE severity estimated by electroencephalographic (EEG) biomarkers. METHODS: Idiopathic generalized epilepsies patients were asked to fill out four validated psychiatric screening tools assessing symptoms of personality disorders (Standard Assessment of Personality- Abbreviated Scale), depression (Major Depression Inventory), impulsiveness (Barratt Impulsiveness Scale), and anxiety (brief Epilepsy Anxiety Survey Instrument). Blinded to results and clinical data on the patients, we analyzed the patients' EEGs, assessed, and quantified ED. The number and duration of ED divided by the duration of the EEG served as a proxy for the severity of IGE that was correlated with the results of the psychiatric screening. RESULTS: Paired data from 64 patients were available for analysis. The duration of EDs per minute EEG was inversely associated with the time since the last seizure. The number of patients with generalized polyspike trains (n = 2), generalized paroxysmal fast activity (n = 3), and prolonged epileptiform discharges (n = 10) were too low for statistically meaningful analyses. Self-reported symptoms of depression, personality disorder, and impulsivity were not associated with EDs. In contrast, the duration of EDs per minute EEG was associated with self-reported symptoms of anxiety in univariate analyses, not significant, however, following adjustment for time since the last seizure in regression models. SIGNIFICANCE: Self-reported symptoms of psychiatric diseases were not strongly associated with EDs as the best available quantifiable biomarker of IGE severity. As expected, the duration of EDs per minute and anxiety was inversely associated with time since the last seizure. Our data argue against a direct link between the frequency of EDs - as an objective proxy of IGE severity - and psychiatric symptoms.

Spike and wave discharges detection in genetic absence epilepsy rat from Strasbourg and patients with genetic generalized epilepsy.

OBJECTIVE: Generalised spike and wave discharges (SWDs) are pathognomonic EEG signatures for diagnosing absence seizures in patients with Genetic Generalized Epilepsy (GGE). The Genetic Absence Epilepsy Rats from Strasbourg (GAERS) is one of the best-validated animal models of GGE with absence seizures. METHODS: We developed an SWDs detector for both GAERS rodents and GGE patients with absence seizures using a neural network method. We included 192 24-hour EEG sessions recorded from 18 GAERS rats, and 24-hour scalp-EEG data collected from 11 GGE patients. RESULTS: The SWDs detection performance on GAERS showed a sensitivity of 98.01% and a false positive (FP) rate of 0.96/hour. The performance on GGE patients showed 100% sensitivity in five patients, while the remaining patients obtained over 98.9% sensitivity. Moderate FP rates were seen in our patients with 2.21/hour average FP. The detector trained within our patient cohort was validated in an independent dataset, TUH EEG Seizure Corpus (TUSZ), that showed 100% sensitivity in 11 of 12 patients and 0.56/hour averaged FP. CONCLUSIONS: We developed a robust SWDs detector that showed high sensitivity and specificity for both GAERS rats and GGE patients. SIGNIFICANCE: This detector can assist researchers and neurologists with the time-efficient and accurate quantification of SWDs.

Comparison of Resting-State EEG Network Analyses With and Without Parallel MRI in Genetic Generalized Epilepsy.

Genetic generalized epilepsy (GGE) is conceptualized as a brain disorder involving distributed bilateral networks. To study these networks, simultaneous EEG-fMRI measurements can be used. However, inside-MRI EEG suffers from strong MR-related artifacts; it is not established whether EEG-based metrics in EEG-fMRI resting-state measurements are suitable for the analysis of group differences at source-level. We evaluated the impact of the inside-MR measurement condition on statistical group comparisons of EEG on source-level power and functional connectivity in patients with GGE versus healthy controls. We studied the cross-modal spatial relation of statistical group differences in seed-based FC derived from EEG and parallel fMRI. We found a significant increase in power and a frequency-specific change in functional connectivity for the inside MR-scanner compared to the outside MR-scanner condition. For power, we found reduced group difference between GGE and controls both in terms of statistical significance as well as effect size. Group differences for ImCoh remained similar both in terms of statistical significance as well as effect size. We found increased seed-based FC for GGE patients from the thalamus to the precuneus cortex region in fMRI, and in the theta band of simultaneous EEG. Our findings suggest that the analysis of EEG functional connectivity based on ImCoh is suitable for MR-EEG, and that relative group difference in a comparison of patients with GGE against controls are preserved. Spatial correspondence of seed-based FC group differences between the two modalities was found for the thalamus.