Interictal epileptogenic fast oscillations on neonatal and infantile EEGs in hemimegalencephaly

Case Report: High-Gamma Oscillations on an Ictal Electroencephalogram in a Newborn Patient With Hypoxic-Ischemic Encephalopathy

Fast oscillations (FOs) >40 Hz in electroencephalograms (EEGs) are associated with ictogenesis and epileptogenesis in adults and children with epilepsy. However, only a few previous studies showed FOs in neonates. Reported frequencies of such neonatal FOs were in the low-gamma (<60 Hz) band and, therefore, they were not high compared to those in pediatric patients. We herein report a newborn patient with severe hypoxic-ischemic encephalopathy (HIE), who showed pathological FOs with a frequency in the high-gamma band. She was born at a gestational age of 39 weeks 4 days by emergency cesarean section because of non-reassuring fetal status. She had focal motor seizures involving unilateral upper and lower limbs lasting for tens of seconds on days 0, 1, 4, 5, 8, and 9 and subclinical seizures on days 4-11. Phenobarbital (PB) was intravenously administered on days 0, 2, 4, 5, and 6. We found FOs that were superimposed on the ictal delta activities using visual inspection and time-frequency analysis on 8-11 days of age. Among them, we detected high-gamma (71.4-100 Hz) oscillations that appeared to be temporally independent of low-gamma activities in the ictal EEG on 11 days of age. To the best of our knowledge, this is one of the earliest reports showing pathological FOs with a frequency of >60 Hz in the high-gamma band in human neonatal seizures, which were previously observed in animal studies. Further studies are needed to elucidate the pathophysiology of ictal FOs in neonatal seizures.

HFO to Measure Seizure Propensity and Improve Prognostication in Patients With Epilepsy

The study of high frequency oscillations (HFO) in the electroencephalogram (EEG) as biomarkers of epileptic activity has merely focused on their spatial location and relationship to the epileptogenic zone. It has been suggested in several ways that the amount of HFO at a certain point in time may reflect the disease activity or severity. This could be clinically useful in several ways, especially as noninvasive recording of HFO appears feasible. We grouped the potential hypotheses into 4 categories: (1) HFO as biomarkers to predict the development of epilepsy; (2) HFO as biomarkers to predict the occurrence of seizures; (3) HFO as biomarkers linked to the severity of epilepsy, and (4) HFO as biomarkers to evaluate outcome of treatment. We will review the literature that addresses these 4 hypotheses and see to what extent HFO can be used to measure seizure propensity and help determine prognosis of this unpredictable disease.

Electrocorticographic Dynamics as a Novel Biomarker in Five Models of Epileptogenesis

Postinjury epilepsy (PIE) is a devastating sequela of various brain insults. While recent studies offer novel insights into the mechanisms underlying epileptogenesis and discover potential preventive treatments, the lack of PIE biomarkers hinders the clinical implementation of such treatments. Here we explored the biomarker potential of different electrographic features in five models of PIE. Electrocorticographic or intrahippocampal recordings of epileptogenesis (from the insult to the first spontaneous seizure) from two laboratories were analyzed in three mouse and two rat PIE models. Time, frequency, and fractal and nonlinear properties of the signals were examined, in addition to the daily rate of epileptiform spikes, the relative power of five frequency bands (theta, alpha, beta, low gamma, and high gamma) and the dynamics of these features over time. During the latent pre-seizure period, epileptiform spikes were more frequent in epileptic compared with nonepileptic rodents; however, this feature showed limited predictive power due to high inter- and intra-animal variability. While nondynamic rhythmic representation failed to predict epilepsy, the dynamics of the theta band were found to predict PIE with a sensitivity and specificity of >90%. Moreover, theta dynamics were found to be inversely correlated with the latency period (and thus predict the onset of seizures) and with the power change of the high-gamma rhythm. In addition, changes in theta band power during epileptogenesis were associated with altered locomotor activity and distorted circadian rhythm. These results suggest that changes in theta band during the epileptogenic period may serve as a diagnostic biomarker for epileptogenesis, able to predict the future onset of spontaneous seizures.SIGNIFICANCE STATEMENT Postinjury epilepsy is an unpreventable and devastating disorder that develops following brain injuries, such as traumatic brain injury and stroke, and is often associated with neuropsychiatric comorbidities. As PIE affects as many as 20% of brain-injured patients, reliable biomarkers are imperative before any preclinical therapeutics can find clinical translation. We demonstrate the capacity to predict the epileptic outcome in five different models of PIE, highlighting theta rhythm dynamics as a promising biomarker for epilepsy. Our findings prompt the exploration of theta dynamics (using repeated electroencephalographic recordings) as an epilepsy biomarker in brain injury patients.

Size of cortical generators of epileptic interictal events and visibility on scalp EEG

Growing evidence indicates that fast oscillations (>80 Hz) can be recorded interictally in the scalp EEG of patients with epilepsy, and that they may point to the seizure-onset zone. However, mechanisms underpinning the emergence of scalp fast oscillations, and whether they differ from those of interictal epileptic discharges (IEDs), are yet to be understood. The visibility of cortical electric activity on scalp EEG recordings is dependent on two factors: the characteristics of the cortical generator and the background level. We studied this issue using scalp EEG recordings and detailed simulations, with a finite element model including 8 million elements and 8 different tissues. We observed an almost linear relationship between the amplitude of scalp electric potential and the extent of the generator on the cortex. However, this relationship is subject to substantial variability, with variations in factors greater than 3 occurring simply by changing the location on the cortex of generators of fixed extent. In addition, we showed that the background power in scalp EEG recordings decreases at higher frequency bands, being inversely proportional to a power of 2.5 of the frequency. In the specific case of fast oscillations, they can be detected within the lower noise level of the ripple band (80-200 Hz) even though their median amplitude on scalp EEG recordings is more than 10 times smaller than IEDs and consistent with cortical generators of approximately 1 cm(2). In conclusion, the physics governing the propagation of electrical activity from the brain to the scalp are consistent with the hypothesis that scalp fast oscillations and intracranial high-frequency oscillations (HFOs, 80-500 Hz) are expressions of common generators. Given the potential role of HFOs as biomarkers in epilepsy, the possibility to obtain some of the associated information from scalp EEG is of high clinical significance.

Localization of MEG pathologic gamma oscillations in adult epilepsy patients with focal cortical dysplasia

We aimed to evaluate the clinical value of gamma oscillations in MEG for intractable neocortical epilepsy patients with cortical dysplasia by comparing gamma and interictal spike events. A retrospective analysis of MEG recordings of 30 adult neocortical epilepsy patients was performed. Gamma (30–70 Hz) and interictal spike events were independently identified, their independent or concurrent presence determined, and their source localization rates compared. Of 30 patients, gamma activities were detected in 28 patients and interictal spikes in 24 patients. Gamma events alone appeared in 5 patients, interictal spikes alone in 1 patient, and no events in 1 patient. Gamma co-occurred with interictal spikes in 20.1 ± 22.1% and interictal spikes co-occurred with gamma in 15.0 ± 19.2%. Rates of event localization within the resection cavity were significantly different (p = 0.042) between gamma (63.3 ± 32.6%) and interictal spike (47.0 ± 41.3%) events. In 4 of the 5 gamma-only patients the mean localization rate was 42.5%. Compared with the interictal spike localization rate, 4 of 9 seizure-free patients had higher gamma localization rates, 4 had the same rate, and 1 had a lower rate. Individual gamma events can be detected independently from interictal spike presence. Gamma can be localized to the resection cavity at least comparably to or more frequently than that from interictal spikes. Even when interictal spikes were undetected, gamma sources were localized to the resection cavity. Gamma oscillations may be a useful indicator of epileptogenic focus.

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Gamma oscillations can be detected independently from interictal spikes in MEG.

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Gamma events were localized to the seizure onset zone and resting state network area.

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Gamma oscillation in MEG can be an important indicator of an epileptogenic focus.

High gamma activity of 60-70 Hz in the area surrounding a cortical tuber in an infant with tuberous sclerosis

Purpose

To detect the epileptogenic region causing epileptic spasms in an infant with tuberous sclerosis (TS).

Methods

We applied a multiple band frequency analysis to video electroencephalographic (EEG) recordings of the infant’s scalp. We also performed computed tomography (CT), magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and magnetoencephalography (MEG) of the brain in order to ascertain the epileptic focus.

Results

During the periodic spasms, we identified fast ictal activity with frequencies of 60–70 Hz in the right centroparietal region. This region was part of the area surrounding the largest cortical tuber that was identified on CT and MRI and was located in the right frontal lobe. An area of increased blood perfusion that was observed with SPECT and dipole sources that were determined with interictal MEG were also located in this area. In addition, ictal frequency oscillations (FOs) with high gamma activity were identified over the cortex surrounding the largest tuber. After a lesionectomy of this tuber, the periodic spasms disappeared, and no FOs were detected over this area.

Conclusions

Scalp EEG, which identified the ictal onset zone by detecting fast activity that was suggestive of FOs, was useful for detecting the epileptogenic region in an infant with TS.

Automatic detection of fast oscillations (40-200 Hz) in scalp EEG recordings

OBJECTIVE

We aim to automatically detect fast oscillations (40-200 Hz) related to epilepsy on scalp EEG recordings.

METHODS

The detector first finds localized increments of the signal power in narrow frequency bands. A simple classification based on two features, a narrowband to wideband signal amplitude ratio and an absolute narrowband signal amplitude, then allows for an important reduction in the number of false positives.

RESULTS

When compared to an expert, the performance in 15 focal epilepsy patients resulted in 3.6 false positives per minute at 95% sensitivity, with at least 40% of the detected events being true positives. In most of the patients the channels showing the highest number of events according to the expert and the automatic detector were the same.

CONCLUSIONS

A high sensitivity is achieved with the proposed automatic detector, but results should be reviewed by an expert to remove false positives.

SIGNIFICANCE

The time required to mark fast oscillations on scalp EEG recordings is drastically reduced with the use of the proposed detector. Thus, the automatic detector is a useful tool in studies aiming to create a better understanding of the fast oscillations visible on the scalp.

Interictal scalp fast oscillations as a marker of the seizure onset zone

OBJECTIVE

This study aims to identify if oscillations at frequencies higher than the traditional EEG can be recorded on the scalp EEG of patients with focal epilepsy and to analyze the association of these oscillations with interictal discharges and the seizure onset zone (SOZ).

METHODS

The scalp EEG of 15 patients with focal epilepsy was studied. We analyzed the rates of gamma (40-80 Hz) and ripple (>80 Hz) oscillations, their co-occurrence with spikes, the number of channels with fast oscillations inside and outside the SOZ, and the specificity, sensitivity, and accuracy of gamma, ripples, and spikes to determine the SOZ.

RESULTS

Gamma and ripples frequently co-occurred with spikes (77.5% and 63% of cases). For all events, the proportion of channels with events was consistently higher inside than outside the SOZ: spikes (100% vs 70%), gamma (82% vs 33%), and ripples (48% vs 11%); p < 0.0001. The mean rates (events/min) were higher inside than outside the SOZ: spikes (2.64 ± 1.70 vs 0.69 ± 0.26, p = 0.02), gamma (0.77 ± 0.71 vs 0.20 ± 0.25, p = 0.02), and ripples (0.08 ± 0.12 vs 0.04 ± 0.09, p = 0.04). The sensitivity to identify the SOZ was spikes 100%, gamma 82%, and ripples 48%; the specificity was spikes 30%, gamma 68%, and ripples 89%; and the accuracy was spikes 43%, gamma 70%, and ripples 81%.

CONCLUSION

The rates and the proportion of channels with gamma and ripple fast oscillations are higher inside the SOZ, indicating that they can be used as interictal scalp EEG markers for the SOZ. These fast oscillations are less sensitive but much more specific and accurate than spikes to delineate the SOZ.

Rapid oscillatory activity in delta brushes of premature and term neonatal EEG

We compared frequency and power of neonatal EEG delta brush rapid oscillatory activity (ROA) using multiple band frequency analysis (MBFA) in three groups; pre-term (PT, post-conceptional age 33-35.6 weeks, n=5); full-term (FT, 39.4-40.6 weeks, n=5) and pre-term or full-term with phenobarbital exposure (PB, n=5). Mean number of delta brushes analyzed was 29.4 (range 26-47) in PT, 20.8 (14-33) in FT and 20 (7-37) in PB. Mean frequency+/-standard deviation (s.d.) was 16.9+/-2.1 Hz (range 15-20 Hz) in PT, 17.3+/-1.9 Hz (15-20 Hz) in FT and 16.1+/-1.6 Hz (14-19 Hz) in PB. Mean power+/-s.d. was 22.9+/-6.2 microV(2) (range 16-39 microV(2)) in PT, 11.9+/-4.1 microV(2) (7-19 microV(2)) in FT and 17.1+/-6.2 microV(2) (9-26 microV(2)) in PB. Power was significantly higher in PT than FT (p<0.005). Power after merging PB into respective PT (PT', n=8) and FT (FT', n=7) groups, remained significantly higher in PT' (mean+/-s.d. 21.8+/-7.4 microV(2)) than FT' (11.4+/-3.6 microV(2)) (p<0.05). We characterise ROA in delta brushes in maturing neonates using MBFA, which may provide additional information for assessing future seizure recurrence and epilepsy risk.