Cortical contribution to scalp EEG gamma rhythms associated with epileptic spasms

Epileptic seizures detection and the analysis of optimal seizure prediction horizon based on frequency and phase analysis

Changes in the frequency composition of the human electroencephalogram are associated with the transitions to epileptic seizures. Cross-frequency coupling (CFC) is a measure of neural oscillations in different frequency bands and brain areas, and specifically phase-amplitude coupling (PAC), a form of CFC, can be used to characterize these dynamic transitions. In this study, we propose a method for seizure detection and prediction based on frequency domain analysis and PAC combined with machine learning. We analyzed two databases, the Siena Scalp EEG database and the CHB-MIT database, and used the frequency features and modulation index (MI) for time-dependent quantification. The extracted features were fed to a random forest classifier for classification and prediction. The seizure prediction horizon (SPH) was also analyzed based on the highest-performing band to maximize the time for intervention and treatment while ensuring the accuracy of the prediction. Under comprehensive consideration, the results demonstrate that better performance could be achieved at an interval length of 5 min with an average accuracy of 85.71% and 95.87% for the Siena Scalp EEG database and the CHB-MIT database, respectively. As for the adult database, the combination of PAC analysis and classification can be of significant help for seizure detection and prediction. It suggests that the rarely used SPH also has a major impact on seizure detection and prediction and further explorations for the application of PAC are needed.

EEG biomarkers for the diagnosis and treatment of infantile spasms

Early diagnosis and treatment are critical for young children with infantile spasms (IS), as this maximizes the possibility of the best possible child-specific outcome. However, there are major barriers to achieving this, including high rates of misdiagnosis or failure to recognize the seizures, medication failure, and relapse. There are currently no validated tools to aid clinicians in assessing objective diagnostic criteria, predicting or measuring medication response, or predicting the likelihood of relapse. However, the pivotal role of EEG in the clinical management of IS has prompted many recent studies of potential EEG biomarkers of the disease. These include both visual EEG biomarkers based on human visual interpretation of the EEG and computational EEG biomarkers in which computers calculate quantitative features of the EEG. Here, we review the literature on both types of biomarkers, organized based on the application (diagnosis, treatment response, prediction, etc.). Visual biomarkers include the assessment of hypsarrhythmia, epileptiform discharges, fast oscillations, and the Burden of AmplitudeS and Epileptiform Discharges (BASED) score. Computational markers include EEG amplitude and power spectrum, entropy, functional connectivity, high frequency oscillations (HFOs), long-range temporal correlations, and phase-amplitude coupling. We also introduce each of the computational measures and provide representative examples. Finally, we highlight remaining gaps in the literature, describe practical guidelines for future biomarker discovery and validation studies, and discuss remaining roadblocks to clinical implementation, with the goal of facilitating future work in this critical area.

Deletion of Phospholipase C β1 in the Thalamic Reticular Nucleus Induces Absence Seizures

Absence seizures are caused by abnormal synchronized oscillations in the thalamocortical (TC) circuit, which result in widespread spike-and-wave discharges (SWDs) on electroencephalography (EEG) as well as impairment of consciousness. Thalamic reticular nucleus (TRN) and TC neurons are known to interact dynamically to generate TC circuitry oscillations during SWDs. Clinical studies have suggested the association of Plcβ1 with early-onset epilepsy, including absence seizures. However, the brain regions and circuit mechanisms related to the generation of absence seizures with Plcβ1 deficiency are unknown. In this study, we found that loss of Plcβ1 in mice caused spontaneous complex-type seizures, including convulsive and absence seizures. Importantly, TRN-specific deletion of Plcβ1 led to the development of only spontaneous SWDs, and no other types of seizures were observed. Ex vivo slice patch recording demonstrated that the number of spikes, an intrinsic TRN neuronal property, was significantly reduced in both tonic and burst firing modes in the absence of Plcβ1. We conclude that the loss of Plcβ1 in the TRN leads to decreased excitability and impairs normal inhibitory neuronal function, thereby disrupting feedforward inhibition of the TC circuitry, which is sufficient to cause hypersynchrony of the TC system and eventually leads to spontaneous absence seizures. Our study not only provides a novel mechanism for the induction of SWDs in Plcβ1-deficient patients but also offers guidance for the development of diagnostic and therapeutic tools for absence epilepsy.

Automated detection of ripple oscillations in long-term scalp EEG from patients with infantile spasms

Objective.Scalp high-frequency oscillations (HFOs) are a promising biomarker of epileptogenicity in infantile spasms (IS) and many other epilepsy syndromes, but prior studies have relied on visual analysis of short segments of data due to the prevalence of artifacts in EEG. Here we set out to robustly characterize the rate and spatial distribution of HFOs in large datasets from IS subjects using fully automated HFO detection techniques.Approach.We prospectively collected long-term scalp EEG data from 12 subjects with IS and 18 healthy controls. For patients with IS, recording began prior to diagnosis and continued through initiation of treatment with adrenocorticotropic hormone (ACTH). The median analyzable EEG duration was 18.2 h for controls and 84.5 h for IS subjects (∼1300 h total). Ripples (80-250 Hz) were detected in all EEG data using an automated algorithm.Main results.HFO rates were substantially higher in patients with IS compared to controls. In IS patients, HFO rates were higher during sleep compared to wakefulness (median 5.5 min^-1and 2.9 min^-1, respectively;p = 0.002); controls did not exhibit a difference in HFO rate between sleep and wakefulness (median 0.98 min^-1and 0.82 min^-1, respectively). Spatially, IS patients exhibited significantly higher rates of HFOs in the posterior parasaggital region and significantly lower HFO rates in frontal channels, and this difference was more pronounced during sleep. In IS subjects, ACTH therapy significantly decreased the rate of HFOs.Significance.Here we provide a detailed characterization of the spatial distribution and rates of HFOs associated with IS, which may have relevance for diagnosis and assessment of treatment response. We also demonstrate that our fully automated algorithm can be used to detect HFOs in long-term scalp EEG with sufficient accuracy to clearly discriminate healthy subjects from those with IS.

Complex observation of scalp fast (40-150 Hz) oscillations in West syndrome and related disorders with structural brain pathology

We investigated the relationship between the scalp distribution of fast (40-150 Hz) oscillations (FOs) and epileptogenic lesions in West syndrome (WS) and related disorders. Subjects were 9 pediatric patients with surgically confirmed structural epileptogenic pathology (age at initial electroencephalogram [EEG] recording: mean 7.1 months, range 1-22 months). The diagnosis was WS in 7 patients, Ohtahara syndrome in 1, and a transitional state from Ohtahara syndrome to WS in the other. In the scalp EEG data of these patients, we conservatively detected FOs, and then examined the distribution of FOs. In five patients, the scalp distribution of FOs was consistent and concordant with the lateralization of cerebral pathology. In another patient, FOs were consistently dominant over the healthy cerebral hemisphere, and the EEG was relatively low in amplitude over the pathological atrophic hemisphere. In the remaining 3 patients, the dominance of FOs was inconsistent and, in 2 of these patients, the epileptogenic hemisphere was reduced in volume, which may result from atrophy or hypoplasia. The correspondence between the scalp distribution of FOs and the epileptogenic lesion should be studied, taking the type of lesion into account. The factors affecting scalp FOs remain to be elucidated.

Unilobar surgery for symptomatic epileptic spasms

Objective

To assess factors associated with favorable seizure outcome after surgery for symptomatic epileptic spasms and improve knowledge on pathophysiology of this seizure type.

Methods

Inclusion criteria were: (1) age between 6 months and 15 years at surgery; (2) active epileptic spasms; (3) follow‐up after surgery >1 year.

Results

We retrospectively studied 80 children (aged 1.3 ± 2 years at seizure onset; 5.8 ± 4 years at surgery, 11.7 ± 5.7 years at last follow up). Magnetic resonance imaging (MRI) revealed structural abnormalities in 77/80 patients (96.3%; unilateral in 69: 89.6%). We performed invasive recordings in 24 patients (30%). In 21 patients in whom MRI or histopathology detected a lesion, electrodes exploring it constantly captured initial ictal activity at spasm onset. Fifty‐eight patients (72.5%) underwent unilobar and 22 (27.5%) multilobar or hemispheric procedures. At last follow‐up, 49 patients (61.3%) were in Engel class I. Multivariate logistic models showed completeness of resection of the seizure onset zone (OR = 0.016, 95%CI: 0.002, 0.122) and of the MRI visible lesion (OR = 0.179, 95% CI: 0.032, 0.999) to be significantly associated with Engel class IA outcome. Unfavorable outcome was associated with an older age at surgery, when it reflected a longer duration of epilepsy (OR = 1.383, 95% CI: 0.994,1.926).

Interpretation

Data emerging from invasive recordings and the good seizure outcome following removal of discrete epileptogenic lesions support a focal cortical origin of spasms. In patients with discrete epileptogenic lesions, the pragmatic approach to surgery should follow the same principles applied to focal epilepsy favoring, whenever possible, unilobar, one‐stage resections.

Neuromagnetic high-frequency oscillations correlate with seizure severity in absence epilepsy

OBJECTIVE

This study quantified the clinical correlation of interictal and ictal neuromagnetic activities from low- to very-high-frequency ranges in childhood absence epilepsy (CAE).

METHODS

Twelve patients with clinically diagnosed drug-naïve CAE were studied using a 275-channel whole-head magnetoencephalography (MEG) system. MEG data were digitized at 6000 Hz and analyzed at both sensor and source levels with multi-frequency analyses.

RESULTS

Neuromagnetic changes from interictal to ictal periods predominantly occurred in medial prefrontal cortex and parieto-occipito-temporal junction in absence seizures. The changes were statistically significant in low-frequency bands only (<30 Hz, p<0.0001). There was a significant correlation between the source strength of ictal high-frequency oscillations (HFOs) in 200-1000 Hz and the number of daily seizures (r=0.734, p<0.01).

CONCLUSIONS

CAE has focal neuromagnetic sources. The transition from interictal to ictal periods is associated with the elevation of low-frequency brain activities. The strength of HFOs reflects the severity of absence seizures.

SIGNIFICANCE

Low- and high-frequency MEG signals reveal distinct brain activities in CAE. HFOs is a new biomarker for the study of absence seizures.

Generation of Local CA1 γ Oscillations by Tetanic Stimulation

Neuronal network oscillations are important features of brain activity in health and disease and can be modulated by a range of clinically used drugs. A protocol is provided to generate a model for studying CA1 γ oscillations (20-80 Hz). These γ oscillations are stable for at least 30 min and depend upon excitatory and inhibitory synaptic activity in addition to activation of pacemaker currents. Tetanically stimulated oscillations have a number of reproducible and easily quantifiable characteristics including spike count, oscillation duration, latency and frequency that report upon the network state. The advantages of the electrically stimulated oscillations include stability, reproducibility and episodic acquisition enabling robust characterization of network function. This model of CA1 γ oscillations can be used to study cellular mechanisms and to systematically investigate how neuronal network activity is altered in disease and by drugs. Disease state pharmacology can be readily incorporated by the use of brain slices from genetically modified or interventional animal models to enable selection of drugs that specifically target disease mechanisms.

Usefulness of multiple frequency band source localizations in ictal MEG

OBJECTIVE

We evaluated the diagnostic value of multiple frequency band MEG source localization within a wide time window during the preictal period.

METHODS

Data for 13 epilepsy patients who showed an ictal event during MEG were analyzed. Several seconds of preictal data were localized in the theta, alpha, beta, and gamma bands by using wavelet transformation and the sLORETA algorithm. The same analysis was performed with narrow time and frequency band. Localization concordances to the surgically resected area were compared.

RESULTS

Source localization in the gamma band for a 10s window before ictal onset showed best concordance to the resection cavity. Eight of 13 patients showed sub-lobar concordance in the 10s gamma band localization, whereas 3 showed concordance in the narrow time and frequency analysis. Four of 7 patients with focal cortical dysplasia (FCD) achieved seizure-free outcome, and all 4 showed sub-lobar concordance.

CONCLUSIONS

A 10s time window gamma source localization method can be used to delineate the epileptogenic zone.

SIGNIFICANCE

The use of a long period during preictal gamma source localization has the potential to become a localizing biomarker of the epileptogenic zone in candidates for surgical intervention, especially in MRI-suspected FCD.