Catastrophic Epilepsies of Childhood.

The tragedy of epilepsy emerges from the combination of its high prevalence, impact upon sufferers and their families, and unpredictability. Childhood epilepsies are frequently severe, presenting in infancy with pharmaco-resistant seizures; are often accompanied by debilitating neuropsychiatric and systemic comorbidities; and carry a grave risk of mortality. Here, we review the most current basic science and translational research findings on several of the most catastrophic forms of pediatric epilepsy. We focus largely on genetic epilepsies and the research that is discovering the mechanisms linking disease genes to epilepsy syndromes. We also describe the strides made toward developing novel pharmacological and interventional treatment strategies to treat these disorders. The research reviewed provides hope for a complete understanding of, and eventual cure for, these childhood epilepsy syndromes.

Treating Rhythmic and Periodic EEG Patterns in Comatose Survivors of Cardiac Arrest.

BACKGROUND: Whether the treatment of rhythmic and periodic electroencephalographic (EEG) patterns in comatose survivors of cardiac arrest improves outcomes is uncertain. METHODS: We conducted an open-label trial of suppressing rhythmic and periodic EEG patterns detected on continuous EEG monitoring in comatose survivors of cardiac arrest. Patients were randomly assigned in a 1:1 ratio to a stepwise strategy of antiseizure medications to suppress this activity for at least 48 consecutive hours plus standard care (antiseizure-treatment group) or to standard care alone (control group); standard care included targeted temperature management in both groups. The primary outcome was neurologic outcome according to the score on the Cerebral Performance Category (CPC) scale at 3 months, dichotomized as a good outcome (CPC score indicating no, mild, or moderate disability) or a poor outcome (CPC score indicating severe disability, coma, or death). Secondary outcomes were mortality, length of stay in the intensive care unit (ICU), and duration of mechanical ventilation. RESULTS: We enrolled 172 patients, with 88 assigned to the antiseizure-treatment group and 84 to the control group. Rhythmic or periodic EEG activity was detected a median of 35 hours after cardiac arrest; 98 of 157 patients (62%) with available data had myoclonus. Complete suppression of rhythmic and periodic EEG activity for 48 consecutive hours occurred in 49 of 88 patients (56%) in the antiseizure-treatment group and in 2 of 83 patients (2%) in the control group. At 3 months, 79 of 88 patients (90%) in the antiseizure-treatment group and 77 of 84 patients (92%) in the control group had a poor outcome (difference, 2 percentage points; 95% confidence interval, -7 to 11; P = 0.68). Mortality at 3 months was 80% in the antiseizure-treatment group and 82% in the control group. The mean length of stay in the ICU and mean duration of mechanical ventilation were slightly longer in the antiseizure-treatment group than in the control group. CONCLUSIONS: In comatose survivors of cardiac arrest, the incidence of a poor neurologic outcome at 3 months did not differ significantly between a strategy of suppressing rhythmic and periodic EEG activity with the use of antiseizure medication for at least 48 hours plus standard care and standard care alone. (Funded by the Dutch Epilepsy Foundation; TELSTAR ClinicalTrials.gov number, NCT02056236.).

Characterizing Frontal Lobe Seizure Semiology in Children.

OBJECTIVE: The objective was to analyze seizure semiology in pediatric frontal lobe epilepsy patients, considering age, to localize the seizure onset zone for surgical resection in focal epilepsy. METHODS: Fifty patients were identified retrospectively, who achieved seizure freedom after frontal lobe resective surgery at Great Ormond Street Hospital. Video-electroencephalography recordings of preoperative ictal seizure semiology were analyzed, stratifying the data based on resection region (mesial or lateral frontal lobe) and age at surgery (≤4 vs >4). RESULTS: Pediatric frontal lobe epilepsy is characterized by frequent, short, complex seizures, similar to adult cohorts. Children with mesial onset had higher occurrence of head deviation (either direction: 55.6% vs 17.4%; p = 0.02) and contralateral head deviation (22.2% vs 0.0%; p = 0.03), ictal body-turning (55.6% vs 13.0%; p = 0.006; ipsilateral: 55.6% vs 4.3%; p = 0.0003), and complex motor signs (88.9% vs 56.5%; p = 0.037). Both age groups (≤4 and >4 years) showed hyperkinetic features (21.1% vs 32.1%), contrary to previous reports. The very young group showed more myoclonic (36.8% vs 3.6%; p = 0.005) and hypomotor features (31.6% vs 0.0%; p = 0.003), and fewer behavioral features (36.8% vs 71.4%; p = 0.03) and reduced responsiveness (31.6% vs 78.6%; p = 0.002). INTERPRETATION: This study presents the most extensive semiological analysis of children with confirmed frontal lobe epilepsy. It identifies semiological features that aid in differentiating between mesial and lateral onset. Despite age-dependent differences, typical frontal lobe features, including hyperkinetic seizures, are observed even in very young children. A better understanding of pediatric seizure semiology may enhance the accuracy of onset identification, and enable earlier presurgical evaluation, improving postsurgical outcomes. ANN NEUROL 2024;95:1138-1148.

Ictal Central Apnea Is Predictive of Mesial Temporal Seizure Onset: An Intracranial Investigation.

OBJECTIVE: Ictal central apnea (ICA) is a semiological sign of focal epilepsy, associated with temporal and frontal lobe seizures. In this study, using qualitative and quantitative approaches, we aimed to assess the localizational value of ICA. We also aimed to compare ICA clinical utility in relation to other seizure semiological features of focal epilepsy. METHODS: We analyzed seizures in patients with medically refractory focal epilepsy undergoing intracranial stereotactic electroencephalographic (SEEG) evaluations with simultaneous multimodal cardiorespiratory monitoring. A total of 179 seizures in 72 patients with reliable artifact-free respiratory signal were analyzed. RESULTS: ICA was seen in 55 of 179 (30.7%) seizures. Presence of ICA predicted a mesial temporal seizure onset compared to those without ICA (odds ratio = 3.8, 95% confidence interval = 1.3-11.6, p = 0.01). ICA specificity was 0.82. ICA onset was correlated with increased high-frequency broadband gamma (60-150Hz) activity in specific mesial or basal temporal regions, including amygdala, hippocampus, and fusiform and lingual gyri. Based on our results, ICA has an almost 4-fold greater association with mesial temporal seizure onset zones compared to those without ICA and is highly specific for mesial temporal seizure onset zones. As evidence of symptomatogenic areas, onset-synchronous increase in high gamma activity in mesial or basal temporal structures was seen in early onset ICA, likely representing anatomical substrates for ICA generation. INTERPRETATION: ICA recognition may help anatomoelectroclinical localization of clinical seizure onset to specific mesial and basal temporal brain regions, and the inclusion of these regions in SEEG evaluations may help accurately pinpoint seizure onset zones for resection. ANN NEUROL 2024;95:998-1008.

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity.

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

Newly identified disorder of copper metabolism caused by variants in CTR1, a high-affinity copper transporter.

The high-affinity copper transporter CTR1 is encoded by CTR1 (SLC31A1), a gene locus for which no detailed genotype-phenotype correlations have previously been reported. We describe identical twin male infants homozygous for a novel missense variant NM_001859.4:c.284 G > A (p.Arg95His) in CTR1 with a distinctive autosomal recessive syndrome of infantile seizures and neurodegeneration, consistent with profound central nervous system copper deficiency. We used clinical, biochemical and molecular methods to delineate the first recognized examples of human CTR1 deficiency. These included clinical phenotyping, brain imaging, assays for copper, cytochrome c oxidase (CCO), and mitochondrial respiration, western blotting, cell transfection experiments, confocal and electron microscopy, protein structure modeling and fetal brain and cerebral organoid CTR1 transcriptome analyses. Comparison with two other critical mediators of cellular copper homeostasis, ATP7A and ATP7B, genes associated with Menkes disease and Wilson disease, respectively, revealed that expression of CTR1 was highest. Transcriptome analyses identified excitatory neurons and radial glia as brain cell types particularly enriched for copper transporter transcripts. We also assessed the effects of Copper Histidinate in the patients' cultured cells and in the patients, under a formal clinical protocol. Treatment normalized CCO activity and enhanced mitochondrial respiration in vitro, and was associated with modest clinical improvements. In combination with present and prior studies, these infants' clinical, biochemical and molecular phenotypes establish the impact of this novel variant on copper metabolism and cellular homeostasis and illuminate a crucial role for CTR1 in human brain development. CTR1 deficiency represents a newly defined inherited disorder of brain copper metabolism.

Ambulatory seizure detection.

PURPOSE OF REVIEW: To review recent advances in the field of seizure detection in ambulatory patients with epilepsy. RECENT FINDINGS: Recent studies have shown that wrist or arm wearable sensors, using 3D-accelerometry, electrodermal activity or photoplethysmography, in isolation or in combination, can reliably detect focal-to-bilateral and generalized tonic-clonic seizures (GTCS), with a sensitivity over 90%, and false alarm rates varying from 0.1 to 1.2 per day. A headband EEG has also demonstrated a high sensitivity for detecting and help monitoring generalized absence seizures. In contrast, no appropriate solution is yet available to detect focal seizures, though some promising findings were reported using ECG-based heart rate variability biomarkers and subcutaneous EEG. SUMMARY: Several FDA and/or EU-certified solutions are available to detect GTCS and trigger an alarm with acceptable rates of false alarms. However, data are still missing regarding the impact of such intervention on patients' safety. Noninvasive solutions to reliably detect focal seizures in ambulatory patients, based on either EEG or non-EEG biosignals, remain to be developed. To this end, a number of challenges need to be addressed, including the performance, but also the transparency and interpretability of machine learning algorithms.

Technological Vanguard: the outstanding performance of the LTY-CNN model for the early prediction of epileptic seizures.

BACKGROUND: Epilepsy is a common neurological disorder that affects approximately 60 million people worldwide. Characterized by unpredictable neural electrical activity abnormalities, it results in seizures with varying intensity levels. Electroencephalography (EEG), as a crucial technology for monitoring and predicting epileptic seizures, plays an essential role in improving the quality of life for people with epilepsy. METHOD: This study introduces an innovative deep learning model, a lightweight triscale yielding convolutional neural network" (LTY-CNN), that is specifically designed for EEG signal analysis. The model integrates a parallel convolutional structure with a multihead attention mechanism to capture complex EEG signal features across multiple scales and enhance the efficiency achieved when processing time series data. The lightweight design of the LTY-CNN enables it to maintain high performance in environments with limited computational resources while preserving the interpretability and maintainability of the model. RESULTS: In tests conducted on the SWEC-ETHZ and CHB-MIT datasets, the LTY-CNN demonstrated outstanding performance. On the SWEC-ETHZ dataset, the LTY-CNN achieved an accuracy of 99.9%, an area under the receiver operating characteristic curve (AUROC) of 0.99, a sensitivity of 99.9%, and a specificity of 98.8%. Furthermore, on the CHB-MIT dataset, it recorded an accuracy of 99%, an AUROC of 0.932, a sensitivity of 99.1%, and a specificity of 93.2%. These results signify the remarkable ability of the LTY-CNN to distinguish between epileptic seizures and nonseizure events. Compared to other existing epilepsy detection classifiers, the LTY-CNN attained higher accuracy and sensitivity. CONCLUSION: The high accuracy and sensitivity of the LTY-CNN model demonstrate its significant potential for epilepsy management, particularly in terms of predicting and mitigating epileptic seizures. Its value in personalized treatments and widespread clinical applications reflects the broad prospects of deep learning in the health care sector. This also highlights the crucial role of technological innovation in enhancing the quality of life experienced by patients.

ALG13-Congenital Disorder of Glycosylation (ALG13-CDG): Updated clinical and molecular review and clinical management guidelines.

ALG13-Congenital Disorder of Glycosylation (CDG), is a rare X-linked CDG caused by pathogenic variants in ALG13 (OMIM 300776) that affects the N-linked glycosylation pathway. Affected individuals present with a predominantly neurological manifestation during infancy. Epileptic spasms are a common presenting symptom of ALG13-CDG. Other common phenotypes include developmental delay, seizures, intellectual disability, microcephaly, and hypotonia. Current management of ALG13-CDG is targeted to address patients' symptoms. To date, less than 100 individuals have been reported with ALG13-CDG. In this article, an international group of experts in CDG reviewed all reported individuals affected with ALG13-CDG and suggested diagnostic and management guidelines for ALG13-CDG. The guidelines are based on the best available data and expert opinion. Neurological symptoms dominate the phenotype of ALG13-CDG where epileptic spasm is confirmed to be the most common presenting symptom of ALG13-CDG in association with hypotonia and developmental delay. We propose that ACTH/prednisolone treatment should be trialed first, followed by vigabatrin, however ketogenic diet has been shown to have promising results in ALG13-CDG. In order to optimize medical management, we also suggest early cardiac, gastrointestinal, skeletal, and behavioral assessments in affected patients.

A Subpopulation of Spikes Predicts Successful Epilepsy Surgery Outcome.

OBJECTIVE: Epileptic spikes are the traditional interictal electroencephalographic (EEG) biomarker for epilepsy. Given their low specificity for identifying the epileptogenic zone (EZ), they are given only moderate attention in presurgical evaluation. This study aims to demonstrate that it is possible to identify specific spike features in intracranial EEG that optimally define the EZ and predict surgical outcome. METHODS: We analyzed spike features on stereo-EEG segments from 83 operated patients from 2 epilepsy centers (37 Engel IA) in wakefulness, non-rapid eye movement sleep, and rapid eye movement sleep. After automated spike detection, we investigated 135 spike features based on rate, morphology, propagation, and energy to determine the best feature or feature combination to discriminate the EZ in seizure-free and non-seizure-free patients by applying 4-fold cross-validation. RESULTS: The rate of spikes with preceding gamma activity in wakefulness performed better for surgical outcome classification (4-fold area under receiver operating characteristics curve [AUC] = 0.755 ± 0.07) than the seizure onset zone, the current gold standard (AUC = 0.563 ± 0.05, p = 0.015) and the ripple rate, an emerging seizure-independent biomarker (AUC = 0.537 ± 0.07, p = 0.006). Channels with a spike-gamma rate exceeding 1.9/min had an 80% probability of being in the EZ. Combining features did not improve the results. INTERPRETATION: Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom. This rate could be applied to determine the minimal number of spiking channels requiring resection. In addition to quantitative analysis, this feature is easily accessible to visual analysis, which could aid clinicians during presurgical evaluation. ANN NEUROL 2023;93:522-535.

Characterization of seizures and EEG findings in creatine transporter deficiency due to SLC6A8 mutation.

Seizures occur in up to 59% of boys with creatine transporter deficiency (CTD). While seizure phenotypes have been previously described, electroencephalogram (EEG) findings have only been reported in several case reports. In this prospective observational study, we report seizure characteristics and EEG findings in combination with neurobehavioral and SLC6A8 pathogenic variants in twenty males with CTD. Eighteen study participants (SP) underwent video-EEG, and seven had follow-up EEG recordings. Seizures typically occurred by age of 2 years. Thirteen (65%) had non-febrile seizures, requiring anti-seizure medications in nine. Four had febrile seizures. Seizures were bilateral tonic-clonic in 7 SP and focal impaired awareness in 5 SP; often responding to 1 to 2 antiseizure medications. EEG showed slowing in 5 SP, beta activity in 6 SP, and focal/multifocal, and/or generalized epileptiform activity in 9 SP. Follow-up EEGs in 7 SP showed emergence of epileptiform activity in 1 SP, and increased activity in 2 SP. In conclusion, seizures were frequent in our cohort but tended to respond to antiseizure medications. Longitudinal follow up provided further insight into emergence of seizures and EEG abnormalities soliciting future studies with long term follow up. Biomarkers of epileptogenicity in CTD are needed to predict seizures in this population.

Undiagnosed Disease Network collaborative approach in diagnosing rare disease in a patient with a mosaic CACNA1D variant.

The Undiagnosed Disease Network (UDN) is comprised of clinical and research experts collaborating to diagnose rare disease. The UDN is funded by the National Institutes of Health and includes 12 different clinical sites (About Us, 2022). Here we highlight the success of collaborative efforts within the UDN Clinical Site at Vanderbilt University Medical Center (VUMC) in utilizing a cohort of experts in bioinformatics, structural biology, and genetics specialists in diagnosing rare disease. Our UDN team identified a de novo mosaic CACNA1D variant c.2299T>C in a 5-year-old female with a history of global developmental delay, dystonia, dyskinesis, and seizures. Using a collaborative multidisciplinary approach, our VUMC UDN team diagnosed the participant with Primary Aldosteronism, Seizures, and Neurologic abnormalities (PASNA) OMIM: 615474 due to a rare mosaic CACNA1D variant (O'Neill, 2013). Interestingly, this patient was mosaic, a phenotypic trait previously unreported in PASNA cases. This report highlights the importance of a multidisciplinary approach in diagnosing rare disease.

Home recording of 3-Hz spike-wave discharges in adults with absence epilepsy using the wearable Sensor Dot.

OBJECTIVE: Home monitoring of 3-Hz spike-wave discharges (SWDs) in patients with refractory absence epilepsy could improve clinical care by replacing the inaccurate seizure diary with objective counts. We investigated the use and performance of the Sensor Dot (Byteflies) wearable in persons with absence epilepsy in their home environment. METHODS: Thirteen participants (median age = 22 years, 11 female) were enrolled at the university hospitals of Leuven and Freiburg. At home, participants had to attach the Sensor Dot and behind-the-ear electrodes to record two-channel electroencephalogram (EEG), accelerometry, and gyroscope data. Ground truth annotations were created during a visual review of the full Sensor Dot recording. Generalized SWDs were annotated if they were 3 Hz and at least 3 s on EEG. Potential 3-Hz SWDs were flagged by an automated seizure detection algorithm, (1) using only EEG and (2) with an additional postprocessing step using accelerometer and gyroscope to discard motion artifacts. Afterward, two readers (W.V.P. and L.S.) reviewed algorithm-labeled segments and annotated true positive detections. Sensitivity, precision, and F1 score were calculated. Patients had to keep a seizure diary and complete questionnaires about their experiences. RESULTS: Total recording time was 394 h 42 min. Overall, 234 SWDs were captured in 11 of 13 participants. Review of the unimodal algorithm-labeled recordings resulted in a mean sensitivity of .84, precision of .93, and F1 score of .89. Visual review of the multimodal algorithm-labeled segments resulted in a similar F1 score and shorter review time due to fewer false positive labels. Participants reported that the device was comfortable and that they would be willing to wear it on demand of their neurologist, for a maximum of 1 week or with intermediate breaks. SIGNIFICANCE: The Sensor Dot improved seizure documentation at home, relative to patient self-reporting. Additional benefits were the short review time and the patients' device acceptance due to user-friendliness and comfortability.

Call for the use of the ILAE terminology for seizures and epilepsies by health care professionals and regulatory agencies to benefit patients and caregivers.

The International League Against Epilepsy (ILAE) introduced a classification for seizure types in 2017 and updated the classification for epilepsy syndromes in 2022. These classifications aim to improve communication among healthcare professionals and help patients better describe their condition. So far, regulatory agencies have used different terminology. This paper stresses the crucial need for consistently adopting ILAE terminology in both regulatory processes and clinical practice. It highlights how language plays a significant role in healthcare communication and how standardized terminology can enhance patient comprehension. The ongoing review of guidelines by regulatory bodies offers a timely opportunity. Aligning regulatory terminologies holds the potential to facilitate discussions on future drug development and harmonize practices across diverse regions, ultimately fostering improved care and research outcomes in epilepsy treatment.

Focal electroclinical features in generalized tonic-clonic seizures: Decision flowchart for a diagnostic challenge.

OBJECTIVE: Bilateral tonic-clonic seizures with focal semiology or focal interictal electroencephalography (EEG) can occur in both focal and generalized epilepsy types, leading to diagnostic errors and inappropriate therapy. We investigated the prevalence and prognostic values of focal features in patients with idiopathic generalized epilepsy (IGE), and we propose a decision flowchart to distinguish between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal EEG or semiology. METHODS: We retrospectively analyzed video-EEG recordings of 101 bilateral tonic-clonic seizures from 60 patients (18 with IGE, 42 with focal epilepsy). Diagnosis and therapeutic response were extracted after ≥1-year follow-up. The decision flowchart was based on previous observations and assessed concordance between interictal and ictal EEG. RESULTS: Focal semiology in IGE was observed in 75% of seizures and 77.8% of patients, most often corresponding to forced head version (66.7%). In patients with multiple seizures, direction of head version was consistent across seizures. Focal interictal epileptiform discharges (IEDs) were observed in 61.1% of patients with IGE, whereas focal ictal EEG onset only occurred in 13% of seizures and 16.7% of patients. However, later during the seizures, a reproducible pattern of 7-Hz lateralized ictal rhythm was observed in 56% of seizures, associated with contralateral head version. We did not find correlation between presence of focal features and therapeutic response in IGE patients. Our decision flowchart distinguished between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal features with an accuracy of 96.6%. SIGNIFICANCE: Focal semiology associated with bilateral tonic-clonic seizures and focal IEDs are common features in patients with IGE, but focal ictal EEG onset is rare. None of these focal findings appears to influence therapeutic response. By assessing the concordance between interictal and ictal EEG findings, one can accurately distinguish between focal and generalized epilepsies.

Immediate and long-term management practices of acute symptomatic seizures and epileptiform abnormalities: A cross-sectional international survey.

OBJECTIVES: Acute symptomatic seizures (ASyS) and epileptiform abnormalities (EAs) on electroencephalography (EEG) are commonly encountered following acute brain injury. Their immediate and long-term management remains poorly investigated. We conducted an international survey to understand their current management. METHODS: The cross-sectional web-based survey of 21 fixed-response questions was based on a common clinical encounter: convulsive or suspected ASyS following an acute brain injury. Respondents selected the option that best matched their real-world practice. Respondents completing the survey were compared with those who accessed but did not complete it. RESULTS: A total of 783 individuals (44 countries) accessed the survey; 502 completed it. Almost everyone used anti-seizure medications (ASMs) for secondary prophylaxis after convulsive or electrographic ASyS (95.4% and 97.2%, respectively). ASM dose escalation after convulsive ASyS depends on continuous EEG (cEEG) findings: most often increased after electrographic seizures (78% of respondents), followed by lateralized periodic discharges (LPDs; 41%) and sporadic epileptiform discharges (sEDs; 17.5%). If cEEG is unrevealing, one in five respondents discontinue ASMs after a week. In the absence of convulsive and electrographic ASyS, a large proportion of respondents start ASMs due to LPD (66.7%) and sED (44%) on cEEG. At hospital discharge, most respondents (85%) continue ASM without dose change. The recommended duration of outpatient ASM use is as follows: 1-3 months (36%), 3-6 months (30%), 6-12 months (13%), >12 months (11%). Nearly one-third of respondents utilized ancillary testing before outpatient ASM taper, most commonly (79%) a <2 h EEG. Approximately half of respondents had driving restrictions recommended for 6 months after discharge. SIGNIFICANCE: ASM use for secondary prophylaxis after convulsive and electrographic ASyS is a universal practice and is continued upon discharge. Outpatient care, particularly the ASM duration, varies significantly. Wide practice heterogeneity in managing acute EAs reflects uncertainty about their significance and management. These results highlight the need for a structured outpatient follow-up and optimized care pathway for patients with ASyS.

Sleep physiology in patients with epilepsy: Influence of seizures on rapid eye movement (REM) latency and REM duration.

OBJECTIVE: A well-established bidirectional relationship exists between sleep and epilepsy. Patients with epilepsy tend to have less efficient sleep and shorter rapid eye movement (REM) sleep. Seizures are far more likely to arise from sleep transitions and non-REM sleep compared to REM sleep. Delay in REM onset or reduction in REM duration may have reciprocal interactions with seizure occurrence. Greater insight into the relationship between REM sleep and seizure occurrence is essential to our understanding of circadian patterns and predictability of seizure activity. We assessed a cohort of adults undergoing evaluation of drug-resistant epilepsy to examine whether REM sleep prior to or following seizures is delayed in latency or reduced in quantity. METHODS: We used a spectrogram-guided approach to review the video-electroencephalograms of patients' epilepsy monitoring unit admissions for sleep scoring to determine sleep variables. RESULTS: In our cohort of patients, we found group- and individual-level delay of REM latency and reduced REM duration when patients experienced a seizure before the primary sleep period (PSP) of interest or during the PSP of interest. A significant increase in REM latency and decrease in REM quantity were observed on nights where a seizure occurred within 4 h of sleep onset. No change in REM variables was found when investigating seizures that occurred the day after the PSP of interest. Our study is the first to provide insight about a perisleep period, which we defined as 4-h periods before and after the PSP. SIGNIFICANCE: Our results demonstrate a significant relationship between seizures occurring prior to the PSP, during the PSP, and in the 4-h perisleep period and a delay in REM latency. These findings have implications for developing a biomarker of seizure detection as well as longer term seizure risk monitoring.

Recognition memory deficits detected through eye-tracking in well-controlled children with self-limited epilepsy with centrotemporal spikes.

OBJECTIVE: Children with self-limited epilepsy characterized by centrotemporal spikes (SeLECTS) exhibit cognitive deficits in memory during the active phase, but there is currently a lack of studies and techniques to assess their memory development after well-controlled seizures. In this study, we employed eye-tracking techniques to investigate visual memory and its association with clinical factors and global intellectual ability, aiming to identify potential risk factors by examining encoding and recognition processes. METHODS: A total of 26 recruited patients diagnosed with SeLECTS who had been seizure-free for at least 2 years, along with 24 control subjects, underwent Wechsler cognitive assessment and an eye-movement-based memory task while video-electroencephalographic (EEG) data were recorded. Fixation and pupil data related to eye movements were utilized to detect distinct memory processes and subsequently to compare the cognitive performance of patients exhibiting different regression patterns on EEG. RESULTS: The findings revealed persistent impairments in visual memory among children with SeLECTS after being well controlled, primarily observed in the recognition stage rather than the encoding phase. Furthermore, the age at onset, frequency of seizures, and interictal epileptiform discharges exhibited significant correlations with eye movement data. SIGNIFICANCE: Children with SeLECTS exhibit persistent recognition memory impairment after being well controlled for the disease. Controlling the frequency of seizures and reducing prolonged epileptiform activity may improve memory cognitive development. The application of the eye-tracking technique may provide novel insights into exploring memory cognition as well as underlying mechanisms associated with pediatric epilepsy.

"Is it a seizure?" Prediction tool for seizure likelihood in children aged 1-24 months admitted for electroencephalographic monitoring of paroxysmal, rhythmic, and repetitive events.

OBJECTIVE: Paroxysmal, rhythmic, and repetitive events (PRREs) during infancy can be concerning for possible seizures, especially following perinatal brain injuries. The workup for establishing whether a PRRE represents a seizure involves the use of continuous video-electroencephalography (cVEEG) for event characterization. This study aims to determine the diagnostic yield of cVEEG for evaluating events concerning for seizures in children aged 1-24 months. METHODS: We performed a single-center retrospective chart review (January 1, 2019-December 31, 2020) and included all children aged 1-24 months admitted for PRRE capture and characterization using cVEEG. Chart abstraction included demographics, birth and family history, known brain injury, event semiology, duration, and frequency, as well as interictal electroencephalographic (EEG) features. For each of these variables, odds ratios for seizure prediction were calculated. RESULTS: A total of 243 patients were identified for this study. On cVEEG, n = 160 (65.4%) had a target event of concern captured during an initial admission with cVEEG. Whereas n = 41 (25.8%) patients with events captured were confirmed to have seizures, most patients (n = 119) were confirmed to have nonepileptic events. Several variables predicted seizure likelihood during the initial admission with cVEEG, including event duration (>1 min), frequency (occurring ≥3 times per week), and presence of abnormal interictal findings on cVEEG. For patients who did not receive a diagnosis at the time of initial admission with cVEEG, the likelihood of a subsequent epilepsy diagnosis was associated with specific PRRE semiology (motor active or motor passive), longer event duration (>1 min duration), and the presence of interictal abnormal EEG features on initial cVEEG admission. Prediction tools utilizing scoring systems to stratify risk in infants with suspected seizures due to PRREs are included. SIGNIFICANCE: Unique patient attributes and PRRE characteristics, as well as the presence of EEG interictal abnormalities, can provide valuable insights for discerning children with a higher likelihood of epilepsy diagnosis following cVEEG admission.

Computer vision for automated seizure detection and classification: A systematic review.

Computer vision (CV) shows increasing promise as an efficient, low-cost tool for video seizure detection and classification. Here, we provide an overview of the fundamental concepts needed to understand CV and summarize the structure and performance of various model architectures used in video seizure analysis. We conduct a systematic literature review of the PubMed, Embase, and Web of Science databases from January 1, 2000 to September 15, 2023, to identify the strengths and limitations of CV seizure analysis methods and discuss the utility of these models when applied to different clinical seizure phenotypes. Reviews, nonhuman studies, and those with insufficient or poor quality data are excluded from the review. Of the 1942 records identified, 45 meet inclusion criteria and are analyzed. We conclude that the field has shown tremendous growth over the past 2 decades, leading to several model architectures with impressive accuracy and efficiency. The rapid and scalable detection offered by CV models holds the potential to reduce sudden unexpected death in epilepsy and help alleviate resource limitations in epilepsy monitoring units. However, a lack of standardized, thorough validation measures and concerns about patient privacy remain important obstacles for widespread acceptance and adoption. Investigation into the performance of models across varied datasets from clinical and nonclinical environments is an essential area for further research.