High-frequency oscillations in a spectrum of pediatric epilepsies characterized by sleep-activated spikes in scalp EEG

Hypotheses of pathophysiological mechanisms in epileptic encephalopathies: A review

INTRODUCTION

Epileptic encephalopathy (EE) is a serious clinical issue that manifests as part of developmental and epileptic encephalopathy (DEE), particularly in childhood epilepsy. In EE, neurocognitive functions and behavior are impaired by intense epileptiform electroencephalogram (EEG) activity. Hypotheses of pathophysiological mechanisms behind EE are reviewed to contribute to an effective solution for EE.

REVIEW

Current hypotheses are as follows: 1) neuronal dysfunction based on genetic abnormalities that may affect neurocognitive functions and epilepsy separately; 2) impairment of synaptic homeostasis during sleep that may be responsible for DEE/EE with spike-and-wave activation in sleep; 3) abnormal subcortical regulation of the cerebral cortex; 4) abnormal cortical metabolism and hemodynamics with impairment of the neural network including default mode network; 5) neurotransmitter imbalance and disordered neural excitability; 6) the effects of neuroinflammation that may be caused by epileptic seizures and in turn aggravate epileptogenesis; 7) the interaction between physiological and pathological high-frequency EEG activity; etc. The causal relationship between epileptiform EEG activity and neurocognitive dysfunctions is small in DEE based on genetic abnormalities and it is largely unestablished in the other hypothetical mechanisms.

CONCLUSION

We have not yet found answers to the question of whether the single-central or multiple derangements are present and what seizures and intense epileptiform EEG abnormalities mean in EE. We need to continue our best efforts in both aspects to elucidate the pathophysiological mechanisms of DEE/EE and further develop epilepsy treatment and precision medicine.

Continuous Spike-Waves during Slow Sleep Today: An Update

In the context of childhood epilepsy, the concept of continuous spike-waves during slow sleep (CSWS) includes several childhood-onset heterogeneous conditions that share electroencephalograms (EEGs) characterized by a high frequency of paroxysmal abnormalities during sleep, which have negative effects on the cognitive development and behavior of the child. These negative effects may have the characteristics of a clear regression or of a slowdown in development. Seizures are very often present, but not constantly. The above makes it clear why CSWS have been included in epileptic encephalopathies, in which, by definition, frequent EEG paroxysmal abnormalities have an unfavorable impact on cognitive functions, including socio-communicative skills, causing autistic features, even regardless of the presence of clinically overt seizures. Although several decades have passed since the original descriptions of the electroclinical condition of CSWS, there are still many areas that are little-known and deserve to be further studied, including the EEG diagnostic criteria, the most effective electrophysiological parameter for monitoring the role of the thalamus in CSWS pathogenesis, its long-term evolution, the nosographic location of Landau-Kleffner syndrome, standardized neuropsychological and behavioral assessments, and pharmacological and non-pharmacological therapies.

Scalp EEG-recorded high-frequency oscillations can predict seizure activity in Panayiotopoulos syndrome

OBJECTIVE

We studied the relationship between the clinical course of Panayiotopoulos syndrome (PS) and high-frequency oscillations (HFOs) captured during interictal scalp electroencephalography (EEG) to determine the feasibility of using HFOs to detect seizure activity in PS.

METHODS

We analyzed the interictal scalp EEGs of 18 children with PS. Age parameters, seizure frequencies, and antiepileptic drugs were compared between the HFO-positive (HFOPG) and HFO-negative (HFONG) groups.

RESULTS

Thirteen patients (72.2%) had HFOs while five patients (27.8%) had no HFOs in 194 interictal EEG records. We found no statistically significant differences in the mean age of epilepsy onset and last seizure, seizure frequency, or frequency of status epilepticus. However, the seizure activity period of the HFOPG was significantly longer than that of the HFONG. Patients with an HFO duration longer than 2 years were intractable to treatment. In most cases, seizures did not occur in the absence of HFOs, even when the spikes remained.

CONCLUSIONS

HFOs are related to the seizure activity period in patients with PS.

SIGNIFICANCE

We propose that HFOs are a biomarker of epileptogenicity and an indicator for drug reduction because seizures did not occur if HFOs disappeared even if the spikes remained.

Correlation between scalp high-frequency oscillations and prognosis in patients with benign epilepsy of childhood with centrotemporal spikes

AIMS

The study aimed to explore whether high-frequency oscillations (HFOs) can predict seizure risk and atypical manifestations of benign epilepsy of childhood with centrotemporal spikes (BECTS).

METHODS

We recruited 60 patients and divided them into three groups: (1) seizure-free BECTS, (2) active typical BECTS, and (3) active atypical forms of BECTS. Electroencephalogram was used to record the number, location, average amplitude, and duration of spikes, and spike ripples were analyzed using time-frequency technology. Multivariable logistic regression analysis was used to investigate independent predictive factors for prognosis.

RESULTS

The number of sleep spike ripples, rather than spikes, was an independent risk factor for the active period of the disease (odds ratio [OR] = 4.714, p = 0.003) and atypical forms of BECTS (OR = 1.455, p = 0.049); the optimal thresholds for the spike ripple rate were >0 (area under the curve [AUC] = 0.885, sensitivity = 96.15%, specificity = 73.33%) and >0.6/min (AUC = 0.936, sensitivity = 84.21%, specificity = 96.15%), respectively. Furthermore, in typical BECTS, the spike ripple rate showed significant negative correlations with time since the last seizure (ρ = -0.409, p = 0.009) and age (ρ = -0.379, p = 0.016), while the spike rate did not.

CONCLUSION

Spike ripple was a marker for distinguishing typical and atypical forms of BECTS and reflected the risk of seizure recurrence better than the spike alone. The present findings might assist clinicians in BECTS treatment.

Sevoflurane-induced high-frequency oscillations, effective connectivity and intraoperative classification of epileptic brain areas

OBJECTIVE

To determine how sevoflurane anesthesia modulates intraoperative epilepsy biomarkers on electrocorticography, including high-frequency oscillation (HFO) effective connectivity (EC), and to investigate their relation to epileptogenicity and anatomical white matter.

METHODS

We studied eight pediatric drug-resistant focal epilepsy patients who achieved seizure control after invasive monitoring and resective surgery. We visualized spatial distributions of the electrocorticography biomarkers at an oxygen baseline, three time-points while sevoflurane was increasing, and at a plateau of 2 minimum alveolar concentration (MAC) sevoflurane. HFO EC was combined with diffusion-weighted imaging, in dynamic tractography.

RESULTS

Intraoperative HFO EC diffusely increased as a function of sevoflurane concentration, although most in epileptogenic sites (defined as those included in the resection); their ability to classify epileptogenicity was optimized at sevoflurane 2 MAC. HFO EC could be visualized on major white matter tracts, as a function of sevoflurane level.

CONCLUSIONS

The results strengthened the hypothesis that sevoflurane-activated HFO biomarkers may help intraoperatively localize the epileptogenic zone.

SIGNIFICANCE

Our results help characterize how HFOs at non-epileptogenic and epileptogenic networks respond to sevoflurane. It may be warranted to establish a normative HFO atlas incorporating the modifying effects of sevoflurane and major white matter pathways, as critical reference in epilepsy presurgical evaluation.

Gastrointestinal and Autonomic Symptoms-How to Improve the Diagnostic Process in Panayiotopoulos Syndrome?

One of the most common epileptic disorders in the pediatric population is Panayiotopoulos syndrome. Clinical manifestations of this idiopathic illness include predominantly autonomic symptoms and dysfunction of the cardiorespiratory system. Another feature constitutes prolonged seizures that usually occur at sleep. It is crucial to differentiate the aforementioned disease from other forms of epilepsy, especially occipital and structural epilepsy and non-epileptic disorders. The diagnostic process is based on medical history, clinical examination, neuroimaging and electroencephalography-though results of the latter may be unspecific. Patients with Panayiotopoulos syndrome (PS) do not usually require treatment, as the course of the disease is, in most cases, mild, and the prognosis is good. The purpose of this review is to underline the role of central autonomic network dysfunction in the development of Panayiotopoulos syndrome, as well as the possibility of using functional imaging techniques, especially functional magnetic resonance imaging (fMRI), in the diagnostic process. These methods could be crucial for understanding the pathogenesis of PS. More data arerequired to create algorithms that will be able to predict the exposure to various complications of PS. It also concerns the importance of electroencephalography (EEG) as a tool to distinguish Panayiotopoulos syndrome from other childhood epileptic syndromes and non-epileptic disorders.

High-frequency oscillations detected by electroencephalography as biomarkers to evaluate treatment outcome, mirror pathological severity and predict susceptibility to epilepsy

High-frequency oscillations (HFOs) in the electroencephalography (EEG) have been extensively investigated as a potential biomarker of epileptogenic zones. The understanding of the role of HFOs in epilepsy has been advanced considerably over the past decade, and the use of scalp EEG facilitates recordings of HFOs. HFOs were initially applied in large scale in epilepsy surgery and are now being utilized in other applications. In this review, we summarize applications of HFOs in 3 subtopics: (1) HFOs as biomarkers to evaluate epilepsy treatment outcome; (2) HFOs as biomarkers to measure seizure propensity; (3) HFOs as biomarkers to reflect the pathological severity of epilepsy. Nevertheless, knowledge regarding the above clinical applications of HFOs remains limited at present. Further validation through prospective studies is required for its reliable application in the clinical management of individual epileptic patients.

Sleep-related hypermotor epilepsy and non-rapid eye movement parasomnias: Differences in the periodic and aperiodic component of the electroencephalographic power spectra

Over the last two decades, our understanding of clinical and pathophysiological aspects of sleep-related epileptic and non-epileptic paroxysmal behaviours has improved considerably, although it is far from complete. Indeed, even if many core characteristics of sleep-related hypermotor epilepsy and non-rapid eye movement parasomnias have been clarified, some crucial points remain controversial, and the overlap of the behavioural patterns between these disorders represents a diagnostic challenge. In this work, we focused on segments of multichannel sleep electroencephalogram free from clinical episodes, from two groups of subjects affected by sleep-related hypermotor epilepsy (N = 15) and non-rapid eye movement parasomnias (N = 16), respectively. We examined sleep stages N2 and N3 of the first part of the night (cycles 1 and 2), and assessed the existence of differences in the periodic and aperiodic components of the electroencephalogram power spectra between the two groups, using the Fitting Oscillations & One Over f (FOOOF) toolbox. A significant difference in the gamma frequency band was found, with an increased relative power in sleep-related hypermotor epilepsy subjects, during both N2 (p < .001) and N3 (p < .001), and a significant higher slope of the aperiodic component in non-rapid eye movement parasomnias, compared with sleep-related hypermotor epilepsy, during N3 (p = .012). We suggest that the relative power of the gamma band and the slope extracted from the aperiodic component of the electroencephalogram signal may be helpful to characterize differences between subjects affected by non-rapid eye movement parasomnias and those affected by sleep-related hypermotor epilepsy.

A study on the relationship between non-epileptic fast (40 - 200 Hz) oscillations in scalp EEG and development in children

OBJECTIVE

Physiological gamma and ripple activities may be linked to neurocognitive functions. This study investigated the relationship between development and non-epileptic, probably physiological, fast (40-200 Hz) oscillations (FOs) including gamma (40 - 80 Hz) and ripple (80 - 200 Hz) oscillations in scalp EEG in children with neurodevelopmental disorders.

METHODS

Participants were 124 children with autism spectrum disorder (ASD) and/or attention deficit/hyperactivity disorder (ADHD). Gamma and ripple oscillations were explored from 60-second-long sleep EEG data in each subject using a semi-automatic detection tool supplemented with visual confirmation and time-frequency analysis.

RESULTS

Gamma and ripple oscillations were detected in 25 (20.2%) and 22 (17.7%) children, respectively. The observation of one or more occurrence(s) of ripple oscillations, but not gamma oscillations, was significantly related to lower age at EEG recording (odds ratio, OR: 0.727 [95% confidence interval, CI: 0.568-0.929]), higher intelligence/developmental quotient (OR: 1.041, 95% CI: 1.002-1.082), and lack of a diagnosis with ADHD (OR: 0.191, 95% CI: 0.039 - 0.937) according to a binominal logistic regression analysis that included diagnosis with ASD, sex, history of perinatal complications, history of febrile seizures, and use of a sedative agent for the EEG recording as the other non-significant parameters. Diagnostic group was not related to frequency or power of spectral peaks of FOs.

CONCLUSION

The production of non-epileptic scalp ripples was confirmed to be associated with brain development and function/dysfunction in childhood. Further investigation is necessary to interpret all of the information on higher brain functions that may be embedded in scalp FOs.

Exclusion of the Possibility of "False Ripples" From Ripple Band High-Frequency Oscillations Recorded From Scalp Electroencephalogram in Children With Epilepsy

Aim

Ripple-band epileptic high-frequency oscillations (HFOs) can be recorded by scalp electroencephalography (EEG), and tend to be associated with epileptic spikes. However, there is a concern that the filtration of steep waveforms such as spikes may cause spurious oscillations or “false ripples.” We excluded such possibility from at least some ripples by EEG differentiation, which, in theory, enhances high-frequency signals and does not generate spurious oscillations or ringing.

Methods

The subjects were 50 pediatric patients, and ten consecutive spikes during sleep were selected for each patient. Five hundred spike data segments were initially reviewed by two experienced electroencephalographers using consensus to identify the presence or absence of ripples in the ordinary filtered EEG and an associated spectral blob in time-frequency analysis (Session A). These EEG data were subjected to numerical differentiation (the second derivative was denoted as EEG″). The EEG″ trace of each spike data segment was shown to two other electroencephalographers who judged independently whether there were clear ripple oscillations or uncertain ripple oscillations or an absence of oscillations (Session B).

Results

In Session A, ripples were identified in 57 spike data segments (Group A-R), but not in the other 443 data segments (Group A-N). In Session B, both reviewers identified clear ripples (strict criterion) in 11 spike data segments, all of which were in Group A-R (p < 0.0001 by Fisher’s exact test). When the extended criterion that included clear and/or uncertain ripples was used in Session B, both reviewers identified 25 spike data segments that fulfilled the criterion: 24 of these were in Group A-R (p < 0.0001).

Discussion

We have demonstrated that real ripples over scalp spikes exist in a certain proportion of patients. Ripples that were visualized consistently using both ordinary filters and the EEG″ method should be true, but failure to clarify ripples using the EEG″ method does not mean that true ripples are absent.

Conclusion

The numerical differentiation of EEG data provides convincing evidence that HFOs were detected in terms of the presence of such unusually fast oscillations over the scalp and the importance of this electrophysiological phenomenon.

Scalp high-frequency oscillation rates are higher in younger children

High-frequency oscillations in scalp EEG are promising non-invasive biomarkers of epileptogenicity. However, it is unclear how high-frequency oscillations are impacted by age in the paediatric population. We prospectively recorded whole-night scalp EEG in 30 children and adolescents with focal or generalized epilepsy. We used an automated and clinically validated high-frequency oscillation detector to determine ripple rates (80-250 Hz) in bipolar channels. Children < 7 years had higher high-frequency oscillation rates (P = 0.021) when compared with older children. The median test-retest reliability of high-frequency oscillation rates reached 100% (iqr 50) for a data interval duration of 10 min. Scalp high-frequency oscillation frequency decreased with age (r = -0.558, P = 0.002), whereas scalp high-frequency oscillation duration and amplitude were unaffected. The signal-to-noise ratio improved with age (r = 0.37, P = 0.048), and the background ripple band activity decreased with age (r = -0.463, P = 0.011). We characterize the relationship of scalp high-frequency oscillation features and age in paediatric patients. EEG intervals of ≥ 10 min duration are required for reliable measurements of high-frequency oscillation rates. This study is a further step towards establishing scalp high-frequency oscillations as a valid epileptogenicity biomarker in this vulnerable age group.

Recent advances in the noninvasive detection of high-frequency oscillations in the human brain

In recent decades, a significant body of evidence based on invasive clinical research has showed that high-frequency oscillations (HFOs) are a promising biomarker for localization of the seizure onset zone (SOZ), and therefore, have the potential to improve postsurgical outcomes in patients with epilepsy. Emerging clinical literature has demonstrated that HFOs can be recorded noninvasively using methods such as scalp electroencephalography (EEG) and magnetoencephalography (MEG). Not only are HFOs considered to be a useful biomarker of the SOZ, they also have the potential to gauge disease severity, monitor treatment, and evaluate prognostic outcomes. In this article, we review recent clinical research on noninvasively detected HFOs in the human brain, with a focus on epilepsy. Noninvasively detected scalp HFOs have been investigated in various types of epilepsy. HFOs have also been studied noninvasively in other pathologic brain disorders, such as migraine and autism. Herein, we discuss the challenges reported in noninvasive HFO studies, including the scarcity of MEG and high-density EEG equipment in clinical settings, low signal-to-noise ratio, lack of clinically approved automated detection methods, and the difficulty in differentiating between physiologic and pathologic HFOs. Additional studies on noninvasive recording methods for HFOs are needed, especially prospective multicenter studies. Further research is fundamental, and extensive work is needed before HFOs can routinely be assessed in clinical settings; however, the future appears promising.

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.

Longitudinal correspondence of epilepsy and scalp EEG fast (40-200 Hz) oscillations in pediatric patients with tuberous sclerosis complex

INTRODUCTION

Epilepsy associated with tuberous sclerosis complex (TSC) has very complex clinical characteristics. Scalp electroencephalogram (EEG) fast (40-200 Hz) oscillations (FOs) were recently suggested to indicate epilepsy severity. Epileptic FOs may undergo age-dependent longitudinal change in individual patients, however, and the typical pattern of such change is not yet fully clarified. We therefore investigated the age-related correspondence between clinical courses and FOs in pediatric patients with TSC-associated epilepsy.

SUBJECTS AND METHODS

FOs were semi-automatically detected from scalp sleep EEG data recorded from 23 children (15 boys, 8 girls; initial data obtained at <10 years of age) with TSC-associated epilepsy.

RESULTS

The number of FOs per patient that were associated with spikes was significantly greater than that of FOs unassociated with spikes (median 145 and 5, respectively; p = 0.0001 by the Wilcoxon signed-rank test). In the eight patients who had West syndrome (WS) in infancy, FOs associated with spikes were abundant during the WS period prior to adrenocorticotropic hormone therapy, with significantly greater numbers of FOs compared to the post-WS period (median 242 and 0, respectively; p = 0.0078). As there was no such time-dependent difference regarding FOs unassociated with spikes, FOs associated with spikes were identified as epileptic. The detected FOs included both gamma and ripple oscillations with no consistent age-dependent shifts in dominant frequency. There were no apparent age-related changes in FO duration.

CONCLUSIONS

Epileptic scalp FOs are confirmed to correspond to severity of epileptic encephalopathy, particularly in WS, even during the long-term evolutional courses of TSC-associated epilepsy.