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Epileptic seizures are debilitating because of the clinical symptoms they produce. These symptoms, in turn, may stem directly from disruptions in neural coding. Recent evidence has suggested that the specific temporal order, or sequence, of spiking across a population of cortical neurons may encode information. Here, we investigate how seizures disrupt neuronal spiking sequences in the human brain by recording multi-unit activity from the cerebral cortex in five male participants undergoing monitoring for seizures. We find that pathological discharges during seizures are associated with bursts of spiking activity across a population of cortical neurons. These bursts are organized into highly consistent and stereotyped temporal sequences. As the seizure evolves, spiking sequences diverge from the sequences observed at baseline and become more spatially organized. The direction of this spatial organization matches the direction of the ictal discharges, which spread over the cortex as traveling waves. Our data therefore suggest that seizures can entrain cortical spiking sequences by changing the spatial organization of neuronal firing, providing a possible mechanism by which seizures create symptoms., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Over 15 million patients with epilepsy worldwide do not respond to drugs. Successful surgical treatment requires complete removal or disconnection of the seizure onset zone (SOZ), brain region(s) where seizures originate. Unfortunately, surgical success rates vary between 30 and 70% because no clinically validated biological marker of the SOZ exists. We develop and retrospectively validate a new electroencephalogram (EEG) marker-neural fragility-in a retrospective analysis of 91 patients by using neural fragility of the annotated SOZ as a metric to predict surgical outcomes. Fragility predicts 43 out of 47 surgical failures, with an overall prediction accuracy of 76% compared with the accuracy of clinicians at 48% (successful outcomes). In failed outcomes, we identify fragile regions that were untreated. When compared to 20 EEG features proposed as SOZ markers, fragility outperformed in predictive power and interpretability, which suggests neural fragility as an EEG biomarker of the SOZ., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Treatment of patients with drug-resistant focal epilepsy relies upon accurate seizure localization. Ictal activity captured by intracranial EEG has traditionally been interpreted to suggest that the underlying cortex is actively involved in seizures. Here, we hypothesize that such activity instead reflects propagated activity from a relatively focal seizure source, even during later time points when ictal activity is more widespread. We used the time differences observed between ictal discharges in adjacent electrodes to estimate the location of the hypothesized focal source and demonstrated that the seizure source, localized in this manner, closely matches the clinically and neurophysiologically determined brain region giving rise to seizures. Moreover, we determined this focal source to be a dynamic entity that moves and evolves over the time course of a seizure. Our results offer an interpretation of ictal activity observed by intracranial EEG that challenges the traditional conceptualization of the seizure source., (Published by Oxford University Press on behalf of the Guarantors of Brain 2021.)

CLN3 disease is a pediatric neurodegenerative condition wherein seizures are common. The most common disease-causing variant is an ~1-kb deletion in CLN3. We investigated seizure phenotype in relation to genotype and to adaptive behavior, MR spectroscopy and CSF biochemical markers in a CLN3 cohort. We performed seizure phenotyping using clinical history, EEG, and the Unified Batten Disease Rating Scale (UBDRS) seizure score. We assessed correlations of seizure severity with disease severity (UBDRS capability), adaptive behavior composite score (ABC; Vineland-3), glutamate+glutamine+GABA and N-acetylaspartate+N-acetylaspartyl glutamate (MR spectroscopy), and CSF neurofilament light chain (NEFL) levels. In 20 participants, median age was 10.7 years (IQR = 7.8). Eighteen completed baseline EEG; 12 had a 1-year follow-up. Seizures were reported in 14 (8 1-kb deletion homozygotes), with median age at onset of 10.0 (IQR = 6.8). Epileptiform discharges were noted in 15 (9 homozygotes). Bilateral tonic clonic (n = 11) and nonmotor seizures (n = 7) were most common. UBDRS seizure score correlated with age (rp = 0.50; [0.08,0.77]; P = .02), UBDRS capability (rp = -0.57; [-0.81,-0.17]; P = .009) and ABC (rp = -0.66; [-0.85,-0.31]; P = .001) scores, glutamate+glutamine+GABA (rp = -0.54; [-0.80,-0.11]; P = .02) and N-acetylaspartate+N-acetylaspartyl glutamate (rp = -0.54; [-0.80,-0.11]; P = .02), and CSF NEFL (rp = 0.65; [0.29,0.85]; P = .002) levels. After controlling for age, correlations with ABC and CSF NEFL remained significant. In our CLN3 cohort, seizures and epileptiform discharges were frequent and often started by age 10 years without significant difference between genotypes. ABC and CSF NEFL correlate with UBDRS seizure score, reflecting the role of seizures in the neurodegenerative process. Longitudinal evaluations in a larger cohort are needed to confirm these findings., (© 2021 SSIEM.)

The clinical phenotype of Gaucher disease type 3 (GD3), a neuronopathic lysosomal storage disorder, encompasses a wide array of neurological manifestations including neuro-ophthalmological findings, developmental delay, and seizures including progressive myoclonic epilepsy. Electroencephalography (EEG) is a widely available tool used to identify abnormalities in cerebral function, as well as epileptiform abnormalities indicating an increased risk of seizures. We characterized the EEG findings in GD3, reviewing 67 patients with 293 EEGs collected over nearly 50 years. Over 93% of patients had some form of EEG abnormality, most consisting of background slowing (90%), followed by interictal epileptiform discharges (IEDs) (54%), and photoparoxysmal responses (25%). The seven patients without background slowing were all under age 14 (mean 6.7 years). There was a history of seizures in 37% of this cohort; only 30% of these had IEDs on EEG. Conversely, only 56% of patients with IEDs had a history of seizures. These observed EEG abnormalities document an important aspect of the natural history of GD3 and could potentially assist in identifying neurological involvement in a patient with subtle clinical findings. Additionally, this comprehensive description of longitudinal EEG data provides essential baseline data for understanding central nervous system involvement in neuronopathic GD., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: Due to variability in the patterns of propagation of interictal epileptiform discharges (IEDs), qualitative definition of the irritative zone has been challenging. Here, we introduce a quantitative approach toward exploration of the dynamics of IED propagation within the irritative zone., Methods: We examined intracranial EEG (iEEG) in nine participants undergoing invasive monitoring for seizure localization. We used an automated IED detector and a community detection algorithm to identify populations of electrodes exhibiting IED activity that co-occur in time, and to group these electrodes into communities., Results: Within our algorithmically-identified communities, IED activity in the seizure onset zone (SOZ) tended to lead IED activity in other functionally coupled brain regions. The tendency of pathological activity to arise in the SOZ, and to spread to non-SOZ tissues, was greater in the asleep state., Conclusions: IED activity, and, by extension, the variability observed between the asleep and awake states, is propagated from a core seizure focus to nearby less pathological brain regions., Significance: Using an unsupervised, computational approach, we show that the spread of IED activity through the epilepsy network varies with physiologic state., (Published by Elsevier B.V.)

Objective: Phelan-McDermid Syndrome (PMS) is a rare genetic condition associated with loss of function mutations, including deletions, in the chromosome 22q13 region. This PMS phenotype includes intellectual disability, often minimal to absent verbal skills, and other neurologic features including autism spectrum disorder and seizures. Reports indicate seizures and abnormal electroencephalograms (EEGs) in this population, but previous studies do not describe EEG findings during sleep or prognostic value of abnormal EEG over any time period., Methods: During a natural history study, 16 consecutively enrolled participants (mean age 10years) with PMS underwent both routine (approximately 25min) and overnight (average 9.65h) video-EEG, in addition to genetic testing, neurodevelopmental assessment, neurological examination, and epilepsy phenotyping. Over 240h of EEG, data was recorded. Comparison of findings from the routine EEG was made with prolonged EEG acquired during awake and sleep the same night. In a subset of nine participants, the overnight EEG was repeated one or more years later to observe the natural evolution and prognostic value of any abnormalities noted at baseline., Results: A history of epilepsy, with multiple seizure types, was confirmed in seven of the 16 participants, giving a prevalence of 43.8% in this cohort. All but one EEG was abnormal (15 of 16), and 75% (12 of 16) showed epileptiform activity. Of these, only 25% of participants (3 of 12) showed definitive epileptiform discharges during the routine study. Overnight EEGs (sleep included) did not show any clinical events consistent with seizures or electrophic seizures, however, overnight EEG showed either more frequent and/or more definitive epileptiform activity in 68.75% (11 of 16) participants. All seven of the 16 participants who had previously been diagnosed with epilepsy showed epileptiform abnormalities. In addition to a wide range of epileptiform activity observed, generalized slowing with poor background organization was frequently noted. Follow-up EEG confirmed persistence of abnormal discharges, but none of the abnormal EEGs showed evolution to electrographic seizures. Clinically, there was no emergence of epilepsy or significant developmental regression noted in the time frame observed., Conclusions: This is the first and most abundant prolonged awake and sleep video-EEG data recorded in a PMS cohort to date. The importance of overnight prolonged EEGs is highlighted by findings from this study, as they can be used to document the varied topographies of EEG abnormalities in conditions such as PMS, which are often missed during routine EEG studies. While the long-term significance of the EEG abnormalities found (beyond 1year) remains uncertain despite their persistence over time, these findings do underscore the current clinical recommendation that overnight prolonged EEG studies (with sleep) should be conducted in individuals with PMS., (Copyright © 2017. Published by Elsevier Inc.)

Reinstatement of neural activity is hypothesized to underlie our ability to mentally travel back in time to recover the context of a previous experience. We used intracranial recordings to directly examine the precise spatiotemporal extent of neural reinstatement as 32 participants with electrodes placed for seizure monitoring performed a paired-associates episodic verbal memory task. By cueing recall, we were able to compare reinstatement during correct and incorrect trials, and found that successful retrieval occurs with reinstatement of a gradually changing neural signal present during encoding. We examined reinstatement in individual frequency bands and individual electrodes and found that neural reinstatement was largely mediated by temporal lobe theta and high-gamma frequencies. Leveraging the high temporal precision afforded by intracranial recordings, our data demonstrate that high-gamma activity associated with reinstatement preceded theta activity during encoding, but during retrieval this difference in timing between frequency bands was absent. Our results build upon previous studies to provide direct evidence that successful retrieval involves the reinstatement of a temporal context, and that such reinstatement occurs with precise spatiotemporal dynamics.

Dysembryoplastic neuroepithelial tumours (DNET) are a common cause of tumour-associated epilepsy, and are usually located in the temporal lobes. We present a case of multifocal DNETs in both infra- and supra-tentorial locations, in a 23-year-old man with a coincident Type I Chiari malformation, presenting with medically refractory focal seizures. The extensive anatomical distribution of the lesions suggests a genetic component in their tumourigenesis.

We compared resting state (RS) functional connectivity and task‐based fMRI to lateralize language dominance in 30 epilepsy patients (mean age = 33; SD = 11; 12 female), a measure used for presurgical planning. Language laterality index (LI) was calculated from task fMRI in frontal, temporal, and frontal + temporal regional masks using LI bootstrap method from SPM12. RS language LI was assessed using two novel methods of calculating RS language LI from bilateral Broca's area seed based connectivity maps across regional masks and multiple thresholds (p <.05, p <.01, p <.001, top 10% connections). We compared LI from task and RS fMRI continuous values and dominance classifications. We found significant positive correlations between task LI and RS LI when functional connectivity thresholds were set to the top 10% of connections. Concordance of dominance classifications ranged from 20% to 30% for the intrahemispheric resting state LI method and 50% to 63% for the resting state LI intra‐ minus interhemispheric difference method. Approximately 40% of patients left dominant on task showed RS bilateral dominance. There was no difference in LI concordance between patients with right‐sided and left‐sided resections. Early seizure onset (<6 years old) was not associated with atypical language dominance during task‐based or RS fMRI. While a relationship between task LI and RS LI exists in patients with epilepsy, language dominance is less lateralized on RS than task fMRI. Concordance of language dominance classifications between task and resting state fMRI depends on brain regions surveyed and RS LI calculation method. [ABSTRACT FROM AUTHOR]

Objective Functional magnetic resonance imaging ( fMRI) activation of the mesial temporal lobe ( MTL) may be important for epilepsy surgical planning. We examined MTL activation and lateralization during language fMRI in children and adults with focal epilepsy. Methods One hundred forty-two controls and patients with left hemisphere focal epilepsy (pediatric: epilepsy, n = 17, mean age = 9.9 ± 2.0; controls, n = 48; mean age = 9.1 ± 2.6; adult: epilepsy, n = 20, mean age = 26.7 ± 5.8; controls, n = 57, mean age = 26.2 ± 7.5) underwent 3T fMRI using a language task (auditory description decision task). Image processing and analyses were conducted using Statistical Parametric Mapping (SPM8); regions of interest ( ROIs) included MTL, Broca's area, and Wernicke's area. We assessed group and individual MTL activation, and examined degree of lateralization. Results Patients and controls (pediatric and adult) demonstrated group and individual MTL activation during language fMRI. MTL activation was left lateralized for adults, but less so in children (p's < 0.005). Patients did not differ from controls in either age group. Stronger left-lateralized MTL activation was related to older age (p = 0.02). Language lateralization (Broca's and Wernicke's) predicted 19% of the variance in MTL lateralization for adults (p = 0.001), but for not children. Significance Language fMRI may be used to elicit group and individual MTL activation. The developmental difference in MTL lateralization and its association with language lateralization suggests a developmental shift in lateralization of MTL function, with increased left lateralization across the age span. This shift may help explain why children have better memory outcomes following resection compared to adults. [ABSTRACT FROM AUTHOR]