Epilepsia最新文献

Objective: The unpredictability of seizures is one of the most challenging aspects of uncontrolled epilepsy for patients. Prior work forecasting seizure risk has measured changes in passive intracranial electroencephalographic (EEG) signals, but currently, there are no such clinical devices available. Based upon dynamical theory, we hypothesized that the response of the brain to perturbing stimulation provides a robust measurement of seizure risk that outperforms the results from passive EEG.

Methods: To test the hypothesis, we performed more than 8 weeks of periodic electrical stimulation and continuous EEG recordings in epileptic rats induced by intrahippocampal injection of tetanus toxin, in which seizures started spontaneously.

Results: Using the perturbation-evoked responses as a predictive biomarker of seizure risk, we built a preictal detection system that had excellent accuracy (area under the receiver operating characteristic curve > .95) at distinguishing the preictal from the interictal states. In comparison, a similar preictal detection system that used only passive features from the same experimental animals was unable to identify the preictal state better than chance.

Significance: Our results advocate for perturbation to be used for seizure prediction purposes, which could improve the efficacy of seizure forecasting when applied clinically.

Faciobrachial dystonic seizures (FBDS), paroxysmal dizziness spells, and thermal sensory attacks are highly frequent and stereotypic phenomena experienced in leucine-rich glioma inactivated 1 (LGI1)-antibody encephalitis. This study aims to describe the electrophysiologic mechanism underlying these pathognomonic symptoms. LGI1-antibody encephalitis patients with active symptoms were enrolled from two separate centers in South Korea and the United States. Patients were evaluated with simultaneous magnetoencephalography (306 channels) and electroencephalography. Regional alterations in neuronal excitability represented by interictal epileptiform discharges were present in the faciobrachial area of the motor cortex, insula, and somatosensory cortex, somatotopically aligned with each of the ictal semiologies observed in patients. FBDS and other LGI1-antibody encephalitis-specific spells localized to cortical regions neuroanatomically corresponding to ictal semiologies: the faciobrachial homunculus (FBDS), insular cortex (paroxysmal dizziness spells), and somatosensory cortex (thermal sensory attacks). Our findings support the ictal hypothesis underlying these unique phenomena.

Cars are increasingly equipped with technology that can be used to analyze driver behavior and alertness, often referred to as driver monitoring systems (DMS). Although initially mainly used to track drivers' attention, DMS are now expanding in the hope of detecting additional forms of driver impairment that may jeopardize driving, such as drowsiness and those caused by sudden medical emergencies. To explore the potential for the latter, we conducted a pilot study to investigate whether technology in modern vehicles, such as eye tracking and driving behavior sensing, can detect abnormalities during seizures. We included 10 patients with focal epilepsy, all of whom had high seizure frequencies and a history of focal impaired awareness seizures. In three subjects, we recorded three definite and one possible electrographic seizure. All seizures were focal, with no motor features. We evaluated driving performance, saccade frequency, eye blink rate, and gaze direction. No clear impact of seizures on driving performance was observed, and eye-related measures showed inconsistent changes. Future studies should explore additional indicators and assess the potential to detect more severe seizures that may have a greater impact on driving performance.

Objective: To assess long-term safety of antiseizure medication (ASM) discontinuation after resolution of acute provoked neonatal seizures and prior to hospital discharge.

Methods: Prospective, observational, comparative effectiveness cohort study of neonates with acute provoked seizures born from July 2015 to March 2018, and followed until September 2024, at nine U.S. Neonatal Seizure Registry centers with Level IV neonatal intensive care units and Level IV pediatric epilepsy programs. Duration of ASM treatment was quantified as (1) discontinuation before discharge from the neonatal seizure admission or (2) maintenance at the time of hospital discharge. Outcomes were adjusted for propensity to receive ASM at discharge. Propensity for ASM maintenance was defined among enrolled participants by a logistic regression model including seizure etiology, gestational age, therapeutic hypothermia, worst electroencephalography (EEG) background, days of EEG seizures, and discharge neurological exam (all p ≤ .1 in a joint model, except etiology, which was included for face validity). The primary outcome was non-inferiority of cognition (Wechsler Preschool and Primary Scale of Intelligence assessed at age 5-6 years). Secondary outcomes were non-inferiority of functional development (Vineland Adaptive Behavior Scale, 3rd Edition, assessed at 3-8 years) and post-neonatal epilepsy (assessed at 1-8 years).

Results: Among 284 children with at least one follow-up, outcomes were similar in the discontinued vs maintained ASM groups for full-scale IQ at age 5 years (adjusted difference +10 points), functional development at ages 3-8 years (adjusted difference 0 points), and post-neonatal epilepsy at ages 1-8 years (adjusted hazard ratio .93, 95% confidence interval [CI] .48-1.80).

Significance: Prolonged administration of ASM for several months after resolution of acute provoked neonatal seizures may expose infants to unnecessary medications. These results provide additional evidence for safety of discontinuing ASM for most neonates soon after the resolution of acute provoked seizures-a practice that is recommended in the International League Against Epilepsy (ILAE) guideline for neonatal seizure management.

Objective: Drug-resistant epilepsy (DRE) affects approximately one-third of patients with epilepsy. The molecular heterogeneity underlying DRE remains poorly defined, largely due to limited access to resected brain tissue and substantial genetic diversity. Current classifications rely primarily on clinical symptoms and histopathological features rather than molecular mechanisms, constraining mechanistic insight and the development of targeted therapies. This study aimed to develop a transcriptome-based, machine learning-guided framework for molecular classification of DRE.

Methods: We performed comprehensive RNA sequencing on 153 surgically resected samples from 95 patients with DRE. Two transcriptomic subtypes were identified through unsupervised clustering. We also leveraged a weighted correlation network-based framework and systematic transcriptional signature comparison and developed a classification model using machine learning algorithms.

Results: Unsupervised clustering revealed two molecular subtypes that diverged from traditional pathological classifications, indicating an alternative transcriptomic basis for epilepsy pathogenesis. A classification model was constructed based on four key differentially regulated pathways: (1) neuroactive ligand-receptor interaction, (2) cAMP signaling, (3) γ-aminobutyric acid (GABA)ergic synapse, and (4) calcium signaling. Among the tested algorithms, the random forest model demonstrated superior performance, achieving 96% classification accuracy with an area under the curve (AUC) of .95.

Significance: These molecular subtypes and their pathways could serve as key molecular hallmarks of epilepsy, offering valuable insights for developing targeted therapies. Moreover, our findings introduce a novel framework for classifying epilepsy based on its molecular nature, potentially connecting the clinical symptoms with the underlying causes more effectively.

Objective: Anterior temporal lobe resection (ATLR) is an effective treatment for drug-resistant temporal lobe epilepsy (TLE) but carries a substantial risk of language impairment, particularly in naming. Understanding and predicting the impact of ATLR on language functions remains a major clinical challenge.

Methods: In this study, we used functional magnetic resonance imaging (fMRI) to investigate the short-term effects of ATLR on the organization of the functional language connectome with a focus on the role of the nondominant hemisphere. We studied 44 patients with TLE due to unilateral hippocampal sclerosis (24 left, 20 right) who underwent language fMRI and neuropsychological testing preoperatively and 4 months after ATLR. We examined functional connectivity changes pre- and postsurgery and their relationship with neuropsychological performance.

Results: ATLR induced widespread alterations in functional connectivity, with distinct ipsilateral disruptions and contralateral compensatory changes. Left ATLR reduced mainly interhemispheric temporal connectivity, whereas right ATLR primarily affected bilateral frontal connections. Postoperatively, left ATLR showed increased intrahemispheric frontotemporal connectivity, and right ATLR exhibited more widespread intra- and interhemispheric increases. In left TLE, better preoperative naming was associated with stronger connectivity of the right (nondominant) temporal lobe and between the left inferior frontal cortex and bilateral posterior hippocampi. Postoperatively, reduced right frontotemporal integration was linked to greater naming decline, underscoring a compensatory role of the nondominant hemisphere. Finally, a machine learning model using preoperative functional connectivity fingerprints outperformed demographic and clinical variables in predicting clinically significant naming decline following ATLR.

Significance: Our findings highlight the critical role of the right temporal lobe in supporting naming function after left ATLR and suggest that preoperative assessment of its connectivity may improve prediction of postoperative language outcomes.

Objective: Although slow waves in δ (.5-4 Hz) characterize non-rapid eye movement (NREM) sleep, in patients with sleep-related epilepsy, seizures most frequently emerge during NREM stage 2, known to be promoted by δ-band instability. Meanwhile, the epileptogenic zone (EZ) shows localized bistability in β-γ-band (15-200 Hz) neuronal oscillations, indicating a catastrophic shift toward seizure. We aim to clarify the mechanistic link between δ-band synchrony and β-γ-band bistability in epilepsy.

Methods: We studied a cohort of 14 patients with sleep hypermotor epilepsy (22.3 ± 10.8 years old, seven males). Seven- to 9-h stereoelectroencephalographic sleep recordings were segmented into 10-min uninterrupted, interictal N2 and N3 epochs, and phase synchrony, phase-amplitude coupling (PAC), and bistability were assessed. Canonical correlation was examined to answer whether PAC links δ phase to β-γ bistability.

Results: Compared to non-EZ, the EZ exhibited larger 15-200-Hz bistability along with stronger 2-8-Hz and 15-100-Hz synchrony throughout N2 and N3. Compared to N3, N2 showed stronger PAC between 2-30-Hz phases in the non-EZ and 5-150-Hz amplitudes in the EZ. Canonical correlations between δ phase modulated PAC, and both bistability and synchrony were identified during N2 (r = .86 and .82) and N3 (r = .84 and .80), with the strongest contributors being 2-4-Hz synchrony and bistability in 2-4-Hz and 15-200-Hz bands. Correlations between interictal spikes and canonical covariates of bistability and PAC (r² = .62 for N2 and .56 for N3) validated their relevance to epileptogenicity.

Significance: δ-Band synchrony and β-γ-band bistability are not isolated epileptogenic mechanisms but likely act synergistically, playing a pivotal role in seizure generation through the coupling of δ phases and β-γ amplitudes across large networks, with significant contributions from nonepileptogenic tissues.

Objective: Focal cortical dysplasia (FCD) causes drug-resistant epilepsy requiring presurgical evaluation. Invasive electroencephalographic (EEG) studies demonstrate that sleep modulates epileptic activity, including interictal epileptiform discharges (IEDs), fast oscillations (FOs) in the beta (14-40 Hz) and gamma (40-80 Hz) frequency bands, and seizures. This study aimed to quantify sleep-associated changes in IEDs, FOs, and seizures in FCD patients using noninvasive magnetoencephalography (MEG).

Methods: Nineteen patients with FCD were prospectively recruited and underwent simultaneous MEG/EEG recordings lasting 89 ± 19 min during daytime sleep. Sleep stages were classified from the EEG. Beamformer source signals were computed from the MEG signal to enhance sensitivity for visual detection of IEDs, FOs in the beta and gamma frequency bands, and seizures. Magnetic source imaging (MSI) was performed using the Maximum Entropy on the Mean (MEM) method, which is particularly sensitive to the spatial extent of sources, enabling accurate localization of epileptic activity.

Results: N1 sleep was reached in 17 of 19 patients and N2 sleep in 14 of 19 patients. Compared to wakefulness, sleep recordings showed significantly higher rates of FOs and seizures (both p < .05), whereas IED rates showed nonsignificant trends. Ten patients demonstrated FOs or seizures, and 12 showed IEDs. MSI of IEDs demonstrated consistent accuracy across vigilance states, with median Euclidean distances of 12.74 mm (interquartile range [IQR] = 22.74) in wake and 8.34 mm (IQR = 27.58) in sleep, and no systematic amplitude or spatial extent changes. Wavelet-MEM enabled frequency-specific source imaging, with FOs and seizures localizing concordantly to FCD lesions in five of seven and seven of eight patients, respectively.

Significance: Daytime sleep MEG recordings are clinically feasible and significantly enhance the detection of seizures (37% of patients) and FOs compared to wakefulness. Sleep protocols enable noninvasive capture of ictal patterns-the gold standard for epileptogenic zone localization-alongside increased FO rates. These findings support incorporating sleep into standard MEG protocols for presurgical epilepsy evaluation.

Objective: The aim of this study was to assess the impact of introducing a pregnancy pictogram on medication packaging on the prescription and dispensation of antiseizure medications and on the maternal and neonatal outcomes for women exposed to these medications.

Methods: This is a national retrospective cohort study, based on the French National Health Data System, with a "before/after the introduction of the pictogram" design. Women aged between 15 and 55 years who had a pregnancy outcome between 2014 and 2017 ("before pictogram" period) and between 2018 and 2021 ("after pictogram" period) and who had received at least two antiseizure medication dispensations before their pregnancy were included. We compared the rates of antiseizure medication discontinuation and continuation during pregnancy, the average doses used, and maternal and neonatal outcomes between the two periods.

Results: The rate of women who had received at least two dispensations of a medication indicated for epilepsy before their pregnancy remained stable between the two periods (.7%). There was a significant decrease in valproic acid prescriptions (5.4% vs. 1.3%) during pregnancy and, conversely, an increase in lamotrigine (29.9% vs. 31.5%) and levetiracetam (10.9% vs. 14.5%) prescriptions. Prescriptions by specialists such as neurologists increased significantly (22.8% vs. 28%) between the two periods. There was an increase of more than 2.7% in the continuation of antiseizure medication (37.6% vs. 40.3%, p < .0001) and conversely a decrease in the rate of women who stopped their antiseizure treatment before or during pregnancy in the "after pictogram" period (59.4% vs. 56.7%, p < .0001). Rates of maternal and neonatal outcomes remained similar between the two periods.

Significance: The introduction of a pregnancy pictogram in France in 2017 was not associated with an increase in discontinuation of antiseizure medications, less adequate treatment, or poorer maternal or neonatal outcomes in pregnant women receiving these medications before pregnancy.