High-frequency oscillations in idiopathic partial epilepsy of childhood

The Prevalence and Risk Factors of Electrical Status Epilepticus During Slow-Wave Sleep in Self-Limited Epilepsy With Centrotemporal Spikes

Objective. To investigate the prevalence and risk factors for electrical status epilepticus during slow-wave sleep (ESES) in patients with self-limited epilepsy with centrotemporal spikes (SeLECTS). Methods. The clinical and follow-up data of children with SeLECTS were collected between 2017 and 2021. Patients were divided into typical ESES, atypical ESES, and non-ESES groups according to spike-wave indices (SWI). Clinical and electroencephalography characteristics were retrospectively analyzed. Logistic regression was used to identify risk factors for ESES. Results. A total of 95 patients with SeLECTS were enrolled. Seven patients (7.4%) developed typical ESES, 30 (31.6%) developed atypical ESES, 25 (26.3%) developed ESES at the first visit, and 12 (12.6%) developed ESES during treatment and follow-up. Multivariate logistic regression analysis showed that the risk factors for SeLECTS combined with ESES were Rolandic double or multiple spikes (OR = 8.626, 95% CI: 2.644-28.147, P < .001) and Rolandic slow waves (OR = 53.550, 95% CI: 6.339-452.368, P < .001). There were no significant differences in seizure characteristics, electroencephalogram (EEG) findings, or cognitive impairment between the atypical and typical ESES groups. Conclusion. More than one-third of the SeLECTS patients combined with ESES. Both atypical and typical ESES scores can affect cognitive function. On electroencephalography, interictal Rolandic double/multiple spikes and slow-wave abnormalities may indicate SeLECTS with ESES.

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.

Exploring Ripple Waves in the Human Brain

Ripples are brief (<150 ms) high-frequency oscillatory neural activities in the brain with a range of 140 to 200 Hz in rodents and 80 to 140 Hz in humans. Ripples are regarded as playing an essential role in several aspects of memory function, mainly in the hippocampus. This type of ripple generally occurs with sharp waves and is called a sharp-wave ripple (SPW-R). Extensive research of SPW-Rs in the rodent brain while actively awake has also linked the function of these SPW-Rs to navigation and decision making. Although many studies with rodents unveiled SPW-R function, research in humans on this subject is still sparse. Therefore, unveiling SPW-R function in the human hippocampus is warranted. A certain type of ripples may also be a biomarker of epilepsy. This type of ripple is called a pathological ripple (p-ripple). p-ripples have a wider range of frequency (80-500 Hz) than SPW-Rs, and the range of frequency is especially higher in brain regions that are intrinsically linked to epilepsy onset. Brain regions producing ripples are too small for scalp electrode recording, and intracranial recording is typically needed to detect ripples. In addition, SPW-Rs in the human hippocampus have been recorded from patients with epilepsy who may have p-ripples. Differentiating SPW-Rs and p-ripples is often not easy. We need to develop more sophisticated methods to record SPW-Rs to differentiate them from p-ripples. This paper reviews the general features and roles of ripple waves.

Association of Scalp High-Frequency Oscillation Detection and Characteristics With Disease Activity in Pediatric Epilepsy

INTRODUCTION

High-frequency oscillation (HFO) in scalp electroencephalography is a promising new noninvasive prognostic epilepsy biomarker, but further data are needed to ascertain the utility of this parameter. The present work investigated the association between epileptic activity and scalp HFO in pediatric patients with various types of epilepsy, using multivariable regression models to correct for possible confounding factors.

METHODS

The authors analyzed 97 subjects who were divided into groups with active epilepsy (within 1 year of seizure), seizure-free epilepsy (>1 year without seizure), and nonepilepsy. Regarding the frequency of seizure occurrence as an indicator of epileptic activity, we categorized subjects into four groups (Daily/Weekly, Monthly, Yearly, and Rarely).

RESULTS

Multiple linear regression analysis showed that the scalp HFO detection rate was significantly higher in patients with active epilepsy than in those with nonepilepsy (β [95% confidence interval] = 2.77 [1.79-4.29]; P < 0.001). The association between scalp HFO detection rate and frequency of seizure occurrence was highest in the Daily/Weekly group (β [95% confidence interval] = 3.38 [1.57-7.27]; P = 0.002), followed by Monthly and Yearly groups (β [95% confidence interval] = 2.42 [1.02-5.73]; P = 0.046 and 0.36 [0.16-0.83]; P = 0.017). In addition, HFO duration, number of peaks, and number of channels detected were significantly higher in patients with active epilepsy.

CONCLUSIONS

Pediatric patients with active epilepsy and high frequency of seizure occurrence exhibited a higher scalp HFO detection rate. These results may help to establish HFO detectable by noninvasive scalp electroencephalography as a biomarker of active epilepsy in pediatric patients.

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.

Self-limited childhood epilepsies are disorders of the perisylvian communication system, carrying the risk of progress to epileptic encephalopathies-Critical review

"Sleep plasticity is a double-edged sword: a powerful machinery of neural build-up, with a risk to epileptic derailment." We aimed to review the types of self-limited focal epilepsies..."i.e. keep as two separate paragraphs" We aimed to review the types of self-limited focal epilepsies: (1) self-limited focal childhood epilepsy with centrotemporal spikes, (2) atypical Rolandic epilepsy, and (3) electrical status epilepticus in sleep with mental consequences, including Landau-Kleffner-type acquired aphasia, showing their spectral relationship and discussing the debated topics. Our endeavor is to support the system epilepsy concept in this group of epilepsies, using them as models for epileptogenesis in general. The spectral continuity of the involved conditions is evidenced by several features: language impairment, the overarching presence of centrotemporal spikes and ripples (with changing electromorphology across the spectrum), the essential timely and spatial independence of interictal epileptic discharges from seizures, NREM sleep relatedness, and the existence of the intermediate-severity "atypical" forms. These epilepsies might be the consequences of a genetically determined transitory developmental failure, reflected by widespread neuropsychological symptoms originating from the perisylvian network that have distinct time and space relations from secondary epilepsy itself. The involved epilepsies carry the risk of progression to severe, potentially irreversible encephalopathic forms.

Spike height improves prediction of future seizure risk

OBJECTIVE

We evaluated whether interictal epileptiform discharge (IED) rate and morphological characteristics predict seizure risk.

METHODS

We evaluated 10 features from automatically detectable IEDs in a stereotyped population with self-limited epilepsy with centrotemporal spikes (SeLECTS). We tested whether the average value or the most extreme values from each feature predicted future seizure risk in cross-sectional and longitudinal models.

RESULTS

10,748 individual centrotemporal IEDs were analyzed from 59 subjects at 81 timepoints. In cross-sectional models, increases in average spike height, spike duration, slow wave rising slope, slow wave falling slope, and the most extreme values of slow wave rising slope each improved prediction of an increased risk of a future seizure compared to a model with age alone (p < 0.05, each). In longitudinal model, spike rising height improved prediction of future seizure risk compared to a model with age alone (p = 0.04) CONCLUSIONS: Spike height improves prediction of future seizure risk in SeLECTS. Several other morphological features may also improve prediction and should be explored in larger studies.

SIGNIFICANCE

Discovery of a relationship between novel IED features and seizure risk may improve clinical prognostication, visual and automated IED detection strategies, and provide insights into the underlying neuronal mechanisms that contribute to IED pathology.

Epileptic high-frequency oscillations occur in neonates with a high risk for seizures

Introduction

Scalp high-frequency oscillations (HFOs, 80-250 Hz) are increasingly recognized as EEG markers of epileptic brain activity. It is, however, unclear what level of brain maturity is necessary to generate these oscillations. Many studies have reported the occurrence of scalp HFOs in children with a correlation between treatment success of epileptic seizures and the reduction of HFOs. More recent studies describe the reliable detection of HFOs on scalp EEG during the neonatal period.

Methods

In the present study, continuous EEGs of 38 neonates at risk for seizures were analyzed visually for the scalp HFOs using 30 min of quiet sleep EEG. EEGs of 14 patients were of acceptable quality to analyze HFOs.

Results

The average rate of HFOs was 0.34 ± 0.46/min. About 3.2% of HFOs occurred associated with epileptic spikes. HFOs were significantly more frequent in EEGs with abnormal vs. normal background activities (p = 0.005).

Discussion

Neonatal brains are capable of generating HFOs. HFO could be a viable biomarker for neonates at risk of developing seizures. Our preliminary data suggest that HFOs mainly occur in those neonates who have altered background activity. Larger data sets are needed to conclude whether HFO occurrence is linked to seizure generation and whether this might predict the development of epilepsy.

Drug-resistant epilepsy and the hypothesis of intrinsic severity: What about the high-frequency oscillations?

Drug‐resistant epilepsy (DRE) affects approximately one‐third of the patients with epilepsy. Based on experimental findings from animal models and brain tissue from patients with DRE, different hypotheses have been proposed to explain the cause(s) of drug resistance. One is the intrinsic severity hypothesis that posits that drug resistance is an inherent property of epilepsy related to disease severity. Seizure frequency is one measure of epilepsy severity, but frequency alone is an incomplete measure of severity and does not fully explain basic research and clinical studies on drug resistance; thus, other measures of epilepsy severity are needed. One such measure could be pathological high‐frequency oscillations (HFOs), which are believed to reflect the neuronal disturbances responsible for the development of epilepsy and the generation of spontaneous seizures. In this manuscript, we will briefly review the intrinsic severity hypothesis, describe basic and clinical research on HFOs in the epileptic brain, and based on this evidence discuss whether HFOs could be a clinical measure of epilepsy severity. Understanding the mechanisms of DRE is critical for producing breakthroughs in the development and testing of novel strategies for treatment.

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.

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.

Brain state-dependent high-frequency activity as a biomarker for abnormal neocortical networks in an epileptic spasms animal model

OBJECTIVE

Epileptic spasms are a hallmark of a severe epileptic state. A previous study showed neocortical up and down states defined by unit activity play a role in the generation of spasms. However, recording unit activity is challenging in clinical settings, and more accessible neurophysiological signals are needed for the analysis of these brain states.

METHODS

In the tetrodotoxin model, we used 16-channel microarrays to record electrophysiological activity in the neocortex during interictal periods and spasms. High-frequency activity (HFA) in the frequency range of fast ripples (200-500 Hz) was analyzed, as were slow wave oscillations (1-8 Hz), and correlated with the neocortical up and down states defined by multiunit activity (MUA).

RESULTS

HFA and MUA had high temporal correlation during interictal and ictal periods. Both increased strikingly during interictal up states and ictal events but were silenced during interictal down states and preictal pauses, and their distributions were clustered at the peak of slow oscillations in local field potential recordings. In addition, both HFA power and MUA firing rates were increased to a greater extent during spasms than interictal up states. During non-rapid eye movement sleep, the HFA rhythmicity faithfully followed the MUA up and down states, but during rapid eye movement sleep when MUA up and down states disappeared the HFA rhythmicity was largely absent. We also observed an increase in the number of HFA down state minutes prior to ictal onset, consistent with the results from analyses of MUA down states.

SIGNIFICANCE

This study provides evidence that HFA may serve as a biomarker for the pathological up states of epileptic spasms. The availability of HFA recordings makes this a clinically practical technique. These findings will likely provide a novel approach for localizing and studying epileptogenic neocortical networks not only in spasms patients but also in other types of epilepsy.

High-Frequency Oscillations on Interictal Epileptiform Discharges in Routinely Acquired Scalp EEG: Can It Be Used as a Prognostic Marker?

Introduction

Despite all the efforts for optimizing epilepsy management in children over the past decades, there is no clear consensus regarding whether to treat or not to treat epileptiform discharges (EDs) after a first unprovoked seizure or the optimal duration of therapy with anti-seizure medication (ASM). It is therefore highly needed to find markers on scalp electroencephalogram (EEG) that can help identify pathological EEG discharges that require treatment.

Aim of the study

This retrospective study aimed to identify whether the coexistence of ripples/high-frequency oscillations (HFOs) with interictal EDs (IEDs) in routinely acquired scalp EEG is associated with a higher risk of seizure recurrence and could be used as a prognostic marker.

Methods

100 children presenting with new onset seizure to Children’s Medical Center- Dallas during 2015–2016, who were not on ASM and had focal EDs on an awake and sleep EEG recorded with sample frequency of 500 HZ, were randomly identified by database review. EEGs were analyzed blinded to the data of the patients. HFOs were visually identified using review parameters including expanded time base and adjusted filter settings.

Results

The average age of patients was 6.3 years (±4.35 SD). HFOs were visually identified in 19% of the studied patients with an inter-rater reliability of 99% for HFO negative discharges and 78% agreement for identification of HFOs. HFOs were identified more often in the younger age group; however, they were identified in 11% of patients >5 years old. They were more frequently associated with spikes than with sharp waves and more often with higher amplitude EDs. Patients with HFOs were more likely to have a recurrence of seizures in the year after the first seizure (P < 0.05) and to continue to have seizures after 2 years (P < 0.0001). There was no statistically significant difference between the two groups with regards to continuing ASM after 2 years.

Conclusion

Including analysis for HFOs in routine EEG interpretation may increase the yield of the study and help guide the decision to either start or discontinue ASM. In the future, this may also help to identify pathological discharges with deleterious effects on the growing brain and set a new target for the management of epilepsy.

Automatic detection of interictal ripples on scalp EEG to evaluate the effect and prognosis of ACTH therapy in patients with infantile spasms

OBJECTIVE

We aimed to explore the feasibility of using scalp-recorded high-frequency oscillations (HFOs) to evaluate the efficacy and prognosis of adrenocorticotropic hormone (ACTH) treatment in patients with infantile spasms.

METHODS

Thirty-nine children with infantile spasms were enrolled and divided into seizure-free and non-seizure-free groups after ACTH treatment. Patients who were seizure-free were further divided into relapse and non-relapse subgroups based on the observations made during a 6-month follow-up period. Scalp ripples were detected and compared during the interictal periods before and after 2 weeks of treatment.

RESULTS

After ACTH treatment, the number and channels of ripples were significantly lower, whereas the percentage decrease in the number, spectral power, and channels of ripples was significantly higher in the seizure-free group than in the non-seizure-free group. In addition, the relapse subgroup showed higher number and spectral power and wider distribution of ripples than did the non-relapse subgroup. Changes in HFOs in terms of number, spectral power, and channel of ripples were closely related to the severity of epilepsy and can indicate disease susceptibility.

SIGNIFICANCE

Scalp HFOs can be used as an effective biomarker to monitor the effect and evaluate the prognosis of ACTH therapy in patients with infantile spasms.

Spike and wave discharges and fast ripples during posttraumatic epileptogenesis

OBJECTIVE

The goal of the present study was to determine whether spike and wave discharges (SWDs) and SWDs with superimposed fast ripples (SWDFRs) could be biomarkers of posttraumatic epileptogenesis.

METHODS

Fluid percussion injury was conducted on 13-14-week old male Sprague Dawley rats. Immediately after traumatic brain injury (TBI), they were implanted with microelectrodes in the neocortex, hippocampus, and striatum bilaterally. Age-matched sham rats with the same electrode implantation montage acted as controls. Wideband brain electrical activity was recorded intermittently from Day 1 of TBI, and continued from 2 to 21 weeks after TBI. SWD and SWDFR analysis was performed during the first 2 weeks to investigate whether the occurrence of this pattern predicted development of epilepsy. The remaining 3-21 weeks were used for identifying which rats became epileptic (E+ group) and which did not (E- group).

RESULTS

The E+ group (n = 9) showed a significant increase in SWD rate in prefrontal cortex during Weeks 1 and 2 after TBI. The E- group showed a significant increase in SWD rate only in the second week. One hundred percent of rats in the E+ group displayed SWDFRs beginning from the first week after TBI. The SWDFR pattern was observed in all recorded brain areas: prefrontal and perilesional cortices, hippocampus, and striatum. None of rats in the E- group showed coexistence of fast ripples with SWDs.

SIGNIFICANCE

Occurrence of SWDFRs after TBI, but not an increase in the rate of SWDs, could be a noninvasive electroencephalographic biomarker of posttraumatic epileptogenesis.

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.

High-Density EEG in Current Clinical Practice and Opportunities for the Future

SUMMARY

High-density EEG (HD-EEG) recordings use a higher spatial sampling of scalp electrodes than a standard 10-20 low-density EEG montage. Although several studies have demonstrated improved localization of the epileptogenic cortex using HD-EEG, widespread implementation is impeded by cost, setup and interpretation time, and lack of specific or sufficient procedural billing codes. Despite these barriers, HD-EEG has been in use at several institutions for years. These centers have noted utility in a variety of clinical scenarios where increased spatial resolution from HD-EEG has been required, justifying the extra time and cost. We share select scenarios from several centers, using different recording techniques and software, where HD-EEG provided information above and beyond the standard low-density EEG. We include seven cases where HD-EEG contributed directly to current clinical care of epilepsy patients and highlight two novel techniques which suggest potential opportunities to improve future clinical care. Cases illustrate how HD-EEG allows clinicians to: case 1-lateralize falsely generalized interictal epileptiform discharges; case 2-improve localization of falsely generalized epileptic spasms; cases 3 and 4-improve localization of interictal epileptiform discharges in anatomic regions below the circumferential limit of standard low-density EEG coverage; case 5-improve noninvasive localization of the seizure onset zone in lesional epilepsy; cases 6 and 7-improve localization of the seizure onset zone to guide invasive investigation near eloquent cortex; case 8-identify epileptic fast oscillations; and case 9-map language cortex. Together, these nine cases illustrate that using both visual analysis and advanced techniques, HD-EEG can play an important role in clinical management.

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.

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.

Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography

OBJECTIVE

Fast Oscillations (FO) >40 Hz are a promising biomarker of the epileptogenic zone (EZ). Evidence using scalp electroencephalography (EEG) remains scarce. We assessed if electrical source imaging of FO using 256-channel high-density EEG (HD-EEG) is useful for EZ identification.

METHODS

We analyzed HD-EEG recordings of 10 focal drug-resistant epilepsy patients with seizure-free postsurgical outcome. We marked FO candidate events at the time of epileptic spikes and verified them by screening for an isolated peak in the time-frequency plot. We performed electrical source imaging of spikes and FO within the Maximum Entropy of the Mean framework. Source localization maps were validated against the surgical cavity.

RESULTS

We identified FO in five out of 10 patients who had a superficial or intermediate deep generator. The maximum of the FO maps was localized inside the cavity in all patients (100%). Analysis with a reduced electrode coverage using the 10-10 and 10-20 system showed a decreased localization accuracy of 60% and 40% respectively.

CONCLUSIONS

FO recorded with HD-EEG localize the EZ. HD-EEG is better suited to detect and localize FO than conventional EEG approaches.

SIGNIFICANCE

This study acts as proof-of-concept that FO localization using 256-channel HD-EEG is a viable marker of the EZ.

Scalp Ripples Can Predict Development of Epilepsy After First Unprovoked Seizure in Childhood

OBJECTIVE

Identification of children at risk of developing epilepsy after a first unprovoked seizure can be challenging. Interictal epileptiform discharges are associated with higher risk but have limited sensitivity and specificity. High frequency oscillations (HFOs) are newer biomarkers for epileptogenesis. We prospectively evaluated the predictive value of HFOs for developing epilepsy in scalp electroencephalogram (EEG) of children after a first unprovoked seizure.

METHODS

After their first seizure, 56 children were followed prospectively over 12 months and then grouped in "epilepsy" or "no epilepsy." Initial EEGs were visually analyzed for spikes, spike ripples, and ripples. Inter-group comparisons of spike-rates and HFO-rates were done by Mann-Whitney U test. Predictive values and optimal thresholds were calculated by receiver operating characteristic (ROC) curves.

RESULTS

In the epilepsy group (n = 26, 46%), mean rates of ripples (0.3 vs 0.09 / minute, p < 0.0001) and spike ripples (0.6 vs 0.06 / minute, p < 0.05) were significantly higher, with no difference in spike rates (1.7 vs 3.0 / minute, p = 0.38). Of those 3 markers, ripples showed the best predictive value (area under the curve [AUC]_ripples = 0.88). The optimal threshold for ripples was calculated to be ≥ 0.125 / minute with a sensitivity of 87% and specificity of 85%. Ripple rates were negatively correlated to days passing before epilepsy-diagnosis (R = -0.59, p < 0.0001) and time to a second seizure (R = -0.64, 95% confidence interval [CI] = -0.77 to 0.43, p < 0.0001).

INTERPRETATION

We could show that in a cohort of children with a first unprovoked seizure, ripples predict the development of epilepsy better than spikes or spike ripples and might be useful biomarkers in the estimation of prognosis and question of treatment. ANN NEUROL 2021;89:134-142.

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.

Scalp EEG interictal high frequency oscillations as an objective biomarker of infantile spasms

OBJECTIVE

To investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms.

METHODS

We retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80-500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3-4 Hz and 0.5-1 Hz as quantified with modulation indices (MIs).

RESULTS

Twenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p < 0.001 by HFO rate; p < 0.01 by MIs at 3-4 Hz; p = 0.02 by MIs at 0.5-1 Hz). The presence of active spasms was predicted by the logistic regression models incorporating HFO-related metrics (AUC: 0.80-0.98) better than that incorporating hypsarrhythmia (AUC: 0.61). The predictive performance of the best model remained favorable (87.5% accuracy) after a cross-validation procedure.

CONCLUSIONS

Increased rate of HFOs and coupling between HFOs and SWA are associated with active epileptic spasms.

SIGNIFICANCE

Scalp-recorded HFOs may serve as an objective EEG biomarker for active epileptic spasms.

Sleep and Epilepsy Link by Plasticity

We aimed to explore the link between NREM sleep and epilepsy. Based on human and experimental data we propose that a sleep-related epileptic transformation of normal neurological networks underlies epileptogenesis. Major childhood epilepsies as medial temporal lobe epilepsy (MTLE), absence epilepsy (AE) and human perisylvian network (PN) epilepsies - made us good models to study. These conditions come from an epileptic transformation of the affected functional systems. This approach allows a system-based taxonomy instead of the outworn generalized-focal classification. MTLE links to the memory-system, where epileptic transformation results in a switch of normal sharp wave-ripples to epileptic spikes and pathological high frequency oscillations, compromising sleep-related memory consolidation. Absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) belong to the corticothalamic system. The burst-firing mode of NREM sleep normally producing sleep-spindles turns to an epileptic working mode ejecting bilateral synchronous spike-waves. There seems to be a progressive transition from AE to JME. Shared absences and similar bilateral synchronous discharges show the belonging of the two conditions, while the continuous age windows - AE affecting schoolchildren, JME the adolescents - and the increased excitability in JME compared to AE supports the notion of progression. In perisylvian network epilepsies - idiopathic focal childhood epilepsies and electrical status epilepticus in sleep including Landau-Kleffner syndrome - centrotemporal spikes turn epileptic, with the potential to cause cognitive impairment. Postinjury epilepsies modeled by the isolated cortex model highlight the shared way of epileptogenesis suggesting the derailment of NREM sleep-related homeostatic plasticity as a common step. NREM sleep provides templates for plasticity derailing to epileptic variants under proper conditions. This sleep-origin explains epileptiform discharges' link and similarity with NREM sleep slow oscillations, spindles and ripples. Normal synaptic plasticity erroneously overgrowing homeostatic processes may derail toward an epileptic working-mode manifesting the involved system's features. The impact of NREM sleep is unclear in epileptogenesis occurring in adolescence and adulthood, when plasticity is lower. The epileptic process interferes with homeostatic synaptic plasticity and may cause cognitive impairment. Its type and degree depends on the affected network's function. We hypothesize a vicious circle between sleep end epilepsy. The epileptic derailment of normal plasticity interferes with sleep cognitive functions. Sleep and epilepsy interconnect by the pathology of plasticity.

Electroencephalographic abnormalities are correlated with cognitive deficits in children with benign childhood epilepsy with centrotemporal spikes: A clinical study of 61 cases

OBJECTIVE

The objective of this study was to explore the effect of spikes on cognition in patients with benign childhood epilepsy with centrotemporal spikes (BECTS) and to identify electroencephalography (EEG) markers enabling early detection of cognitive impairment.

METHODS

Sixty-one children with BECTS diagnoses and 60 age- and education-matched healthy controls were enrolled. Four-hour EEG recordings were analyzed for each patient to check for interictal spikes, high-frequency oscillations (HFOs), nondipole spikes, and other atypical EEG features and to examine the spike-wave index of nonrapid eye movement (NREM) sleep. All 121 children underwent a series of neuropsychological tests to assess cognitive function.

RESULTS

Patients with a high NREM sleep discharge index (≥55%) in the first sleep cycle exhibited significantly lower scores for arithmetic calculation, executive function, and attention and memory tests than patients with a low discharge index (<55%). Eight patients with HFOs exhibited even poorer performance than HFO-negative patients for arithmetic calculation, executive function, vocabulary comprehension, visual perception, vocal perception, spatial memory ability, and response ability. Children with bilateral discharge exhibited poorer ability in three-dimensional spatial imaging test, poorer memory, and slower response than did those with unilateral discharge (P < .05). Nondipole spikes, multiple asynchronous discharges, and generalized spike-wave discharges respectively had an impact on calculation ability, memory, and reaction ability respectively (P < .05).

CONCLUSIONS

Spike frequencies in stage 3 and 4 sleep varied from those observed in stage 1 and 2 sleep; the highest spike frequency was in stage 2 sleep. High NREM sleep discharge index (i.e., ≥55%) and HFOs were linked to the highest risk for cognitive deficit, while bilateral discharges, nondipole spikes, multiple asynchronous discharges, and generalized spike-wave discharges were less indicative of cognitive impairment.

Scalp EEG high frequency oscillations as a biomarker of treatment response in epileptic encephalopathy with continuous spike-and-wave during sleep (CSWS)

PURPOSE

We investigated whether the presence of interictal scalp EEG high frequency oscillations (HFOs) in children with epileptic encephalopathy with continuous spike-and-wave during sleep (CSWS) can predict seizure and cognitive outcome after steroid therapy.

METHODS

Twenty-two children with CSWS were prospectively enrolled and received methylprednisolone therapy. Interictal scalp HFOs, spike wave index (SWI) and intelligence quotient (IQ) were assessed before and after the treatment. The children were divided into two groups based on the early seizure reduction ratio at 2 weeks (≥50%, "response group"; otherwise "non-response group"). The "response group" was further divided into two subgroups ("relapse" and "non-relapse" subgroups) according to the late seizure outcome (after 3 months).

RESULTS

Interictal HFOs and electrical status epilepticus in sleep (ESES) (defined as SWI ≥ 85%) were detected in all children at the baseline. In the response with relapse group (n = 11), the detection ratio of HFOs was significantly higher than that of ESES at 2 weeks (81.2 vs. 27.3%), 3 months (90.9 vs. 36.4%), and 6 months (100 vs. 54.5%) post-therapy. In the non-response group (n = 4), both HFOs and ESES persisted in all children. The average IQ improved significantly only in the response with non-relapse group. The persistence of HFOs negatively correlated with both the average IQ, yet the persistence of ESES did not.

CONCLUSION

Interictal scalp HFOs may be a favorable non-invasive biomarker of predicting seizure and cognitive outcome in CSWS.

Functional and Structural Network Disorganizations in Typical Epilepsy With Centro-Temporal Spikes and Impact on Cognitive Neurodevelopment

Epilepsy with Centrotemporal Spikes (ECTS) is the most common form of self-limited focal epilepsy. The pathophysiological mechanisms by which ECTS induces neuropsychological impairment in 15-30% of affected children remain unclear. The objective of this study is to review the current state of knowledge concerning the brain structural and functional changes that may be involved in cognitive dysfunctions in ECTS. Structural brain imaging suggests the presence of subtle neurodevelopmental changes over the epileptogenic zone and over distant regions in ECTS. This structural remodeling likely occurs prior to the diagnosis and evolves over time, especially in patients with cognitive impairment, suggesting that the epileptogenic processes might interfere with the dynamics of the brain development and/or the normal maturation processes. Functional brain imaging demonstrates profound disorganization accentuated by interictal epileptic spikes (IES) in the epileptogenic zone and in remote networks in ECTS. Over the epileptogenic zone, the literature demonstrates changes in term of neuronal activity and synchronization, which are effective several hundred milliseconds before the IES. In the same time window, functional changes are also observed in bilateral distant networks, notably in the frontal and temporal lobes. Effective connectivity demonstrates that the epileptogenic zone constitutes the key area at the origin of IES propagation toward distant cortical regions, including frontal areas. Altogether, structural and functional network disorganizations, in terms of: (i) power spectral values, (ii) functional and effective connectivity, are likely to participate in the cognitive impairment commonly reported in children with ECTS. These results suggest a central and causal role of network disorganizations related to IES in the neuropsychological impairment described in ECTS children.

Scalp recorded spike ripples predict seizure risk in childhood epilepsy better than spikes

In the past decade, brief bursts of fast oscillations in the ripple range have been identified in the scalp EEG as a promising non-invasive biomarker for epilepsy. However, investigation and clinical application of this biomarker have been limited because standard approaches to identify these brief, low amplitude events are difficult, time consuming, and subjective. Recent studies have demonstrated that ripples co-occurring with epileptiform discharges ('spike ripple events') are easier to detect than ripples alone and have greater pathological significance. Here, we used objective techniques to quantify spike ripples and test whether this biomarker predicts seizure risk in childhood epilepsy. We evaluated spike ripples in scalp EEG recordings from a prospective cohort of children with a self-limited epilepsy syndrome, benign epilepsy with centrotemporal spikes, and healthy control children. We compared the rate of spike ripples between children with epilepsy and healthy controls, and between children with epilepsy during periods of active disease (active, within 1 year of seizure) and after a period of sustained seizure-freedom (seizure-free, >1 year without seizure), using semi-automated and automated detection techniques. Spike ripple rate was higher in subjects with active epilepsy compared to healthy controls (P = 0.0018) or subjects with epilepsy who were seizure-free ON or OFF medication (P = 0.0018). Among epilepsy subjects with spike ripples, each month seizure-free decreased the odds of a spike ripple by a factor of 0.66 [95% confidence interval (0.47, 0.91), P = 0.021]. Comparing the diagnostic accuracy of the presence of at least one spike ripple versus a classic spike event to identify group, we found comparable sensitivity and negative predictive value, but greater specificity and positive predictive value of spike ripples compared to spikes (P = 0.016 and P = 0.006, respectively). We found qualitatively consistent results using a fully automated spike ripple detector, including comparison with an automated spike detector. We conclude that scalp spike ripple events identify disease and track with seizure risk in this epilepsy population, using both semi-automated and fully automated detection methods, and that this biomarker outperforms analysis of spikes alone in categorizing seizure risk. These data provide evidence that spike ripples are a specific non-invasive biomarker for seizure risk in benign epilepsy with centrotemporal spikes and support future work to evaluate the utility of this biomarker to guide medication trials and tapers in these children and predict seizure risk in other at-risk populations.

Beta oscillations in the sensorimotor cortex correlate with disease and remission in benign epilepsy with centrotemporal spikes

INTRODUCTION

Benign epilepsy with centrotemporal spikes (BECTS) is a common form of childhood epilepsy with the majority of those afflicted remitting during their early teenage years. Seizures arise from the lower half of the sensorimotor cortex of the brain (e.g. seizure onset zone) and the abnormal epileptiform discharges observed increase during NREM sleep. To date no clinical factors reliably predict disease course, making determination of ongoing seizure risk a significant challenge. Prior work in BECTS have shown abnormalities in beta band (14.9-30 Hz) oscillations during movement and rest. Oscillations in this frequency band are modulated by state of consciousness and thought to reflect intrinsic inhibitory mechanisms.

METHODS

We used high density EEG and source localization techniques to examine beta band activity in the seizure onset zone (sensorimotor cortex) in a prospective cohort of children with BECTS and healthy controls during sleep. We hypothesized that beta power in the sensorimotor cortex would be different between patients and healthy controls, and that beta abnormalities would improve with resolution of disease in this self-limited epilepsy syndrome. We further explored the specificity of our findings and correlation with clinical features. Statistical testing was performed using logistic and standard linear regression models.

RESULTS

We found that beta band power in the seizure onset zone is different between healthy controls and BECTS patients. We also found that a longer duration of time spent seizure-free (corresponding to disease remission) correlates with lower beta power in the seizure onset zone. Exploratory spatial analysis suggests this effect is not restricted to the sensorimotor cortex. Exploratory frequency analysis suggests that this phenomenon is also observed in alpha and gamma range activity. We found no relationship between beta power and the presence or rate of epileptiform discharges in the sensorimotor cortex or a test of sensorimotor performance.

CONCLUSION

These results provide evidence that cortical beta power in the seizure onset zone may provide a dynamic physiological biomarker of disease in BECTS.

Localization of the Epileptogenic Zone Using High Frequency Oscillations

For patients with drug-resistant focal epilepsy, surgery is the therapy of choice in order to achieve seizure freedom. Epilepsy surgery foremost requires the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation. The current gold standard for identification of the EZ is the seizure-onset zone (SOZ). The fact, however that surgical outcomes are unfavorable in 40-50% of well-selected patients, suggests that the SOZ is a suboptimal biomarker of the EZ, and that new biomarkers resulting in better postsurgical outcomes are needed. Research of recent years suggested that high-frequency oscillations (HFOs) are a promising biomarker of the EZ, with a potential to improve surgical success in patients with drug-resistant epilepsy without the need to record seizures. Nonetheless, in order to establish HFOs as a clinical biomarker, the following issues need to be addressed. First, evidence on HFOs as a clinically relevant biomarker stems predominantly from retrospective assessments with visual marking, leading to problems of reproducibility and reliability. Prospective assessments of the use of HFOs for surgery planning using automatic detection of HFOs are needed in order to determine their clinical value. Second, disentangling physiologic from pathologic HFOs is still an unsolved issue. Considering the appearance and the topographic location of presumed physiologic HFOs could be immanent for the interpretation of HFO findings in a clinical context. Third, recording HFOs non-invasively via scalp electroencephalography (EEG) and magnetoencephalography (MEG) is highly desirable, as it would provide us with the possibility to translate the use of HFOs to the scalp in a large number of patients. This article reviews the literature regarding these three issues. The first part of the article focuses on the clinical value of invasively recorded HFOs in localizing the EZ, the detection of HFOs, as well as their separation from physiologic HFOs. The second part of the article focuses on the current state of the literature regarding non-invasively recorded HFOs with emphasis on findings and technical considerations regarding their localization.

Epilepsy as a derailment of sleep plastic functions may cause chronic cognitive impairment - A theoretical review

We report on a peculiar way of chronic cognitive impairment associated with interictal epileptic activity during NREM sleep. We review three major groups of epilepsy: mesiotemporal epilepsy (MTLE) involving the epileptic derailment of the hippocampal declarative memory system; childhood developmental epileptic encephalopathies; and the spectrum disorders of the perisylvian communication network with the centrotemporal spike phenomenon, overarching child- and adulthood epilepsies, totaling up the majority of epilepsies in childhood. We outline high impact research-lines on the cognitive harm of epilepsy; causing specific or global cognitive decline through its interference with sleep plastic functions. We highlight the key role of interictal activity in the development of cognitive impairment and the fact that we are unarmed against this harm, antiepileptic pharmaco-therapy being ineffective against the interictal process marked by spikes and high frequency oscillations.

Simultaneously recorded intracranial and scalp high frequency oscillations help identify patients with poor postsurgical seizure outcome

OBJECTIVE

High frequency oscillations (HFO) between 80-500 Hz are markers of epileptic areas in intracranial and maybe also scalp EEG. We investigate simultaneous recordings of scalp and intracranial EEG and hypothesize that scalp HFOs provide important additional clinical information in the presurgical setting.

METHODS

Spikes and HFOs were visually identified in all intracranial scalp EEG channels. Analysis of correlation of event location between intracranial and scalp EEG as well as relationship between events and the SOZ and zone of surgical removal was performed.

RESULTS

24 patients could be included, 23 showed spikes and 19 HFOs on scalp recordings. In 15/19 patients highest scalp HFO rate was located over the implantation side, with 13 patients having the highest scalp and intracranial HFO rate over the same region. 17 patients underwent surgery, 7 became seizure free. Patients with poor post-operative outcome showed significantly more regions with HFO than those with seizure free outcome.

CONCLUSIONS

Scalp HFOs are mostly located over the SOZ. Widespread scalp HFOs are indicative of a larger epileptic network and associated with poor postsurgical outcome.

SIGNIFICANCE

Analysis of scalp HFO add clinically important information about the extent of epileptic areas during presurgical simultaneous scalp and intracranial EEG recordings.

Removing high-frequency oscillations: A prospective multicenter study on seizure outcome

OBJECTIVE

To evaluate the use of interictal high-frequency oscillations (HFOs) in epilepsy surgery for prediction of postsurgical seizure outcome in a prospective multicenter trial.

METHODS

We hypothesized that a seizure-free outcome could be expected in patients in whom the surgical planning included the majority of HFO-generating brain tissue while a poor seizure outcome could be expected in patients in whom only a few such areas were planned to be resected. Fifty-two patients were included from 3 tertiary epilepsy centers during a 1-year period. Ripples (80-250 Hz) and fast ripples (250-500 Hz) were automatically detected during slow-wave sleep with chronic intracranial EEG in 2 centers and acute intraoperative electrocorticography in 1 patient.

RESULTS

There was a correlation between the removal of HFO-generating regions and seizure-free outcome at the group level for all patients. No correlation was found, however, for the center-specific analysis, and an individual prognostication of seizure outcome was true in only 36 patients (67%). Moreover, some patients became seizure-free without removal of the majority of HFO-generating tissue. The investigation of influencing factors, including comparisons of visual and automatic analysis, using a threshold analysis for areas with high HFO activity, and excluding contacts bordering the resection, did not result in improved prognostication.

CONCLUSIONS

On an individual patient level, a prediction of outcome was not possible in all patients. This may be due to the analysis techniques used. Alternatively, HFOs may be less specific for epileptic tissue than earlier studies have indicated.

High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence

High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.

Timing matters: Impact of anticonvulsant drug treatment and spikes on seizure risk in benign epilepsy with centrotemporal spikes

Objective

Benign epilepsy with centrotemporal spikes (BECTS) is a common, self‐limited epilepsy syndrome affecting school‐age children. Classic interictal epileptiform discharges (IEDs) confirm diagnosis, and BECTS is presumed to be pharmacoresponsive. As seizure risk decreases in time with this disease, we hypothesize that the impact of IEDs and anticonvulsive drug (ACD) treatment on the risk of subsequent seizure will differ based on disease duration.

Methods

We calculate subsequent seizure risk following diagnosis in a large retrospective cohort of children with BECTS (n = 130), evaluating the impact of IEDs and ACD treatment in the first, second, third, and fourth years of disease. We use a Kaplan–Meier survival analysis and logistic regression models. Patients were censored if they were lost to follow‐up or if they changed group status.

Results

Two‐thirds of children had a subsequent seizure within 2 years of diagnosis. The majority of children had a subsequent seizure within 3 years despite treatment. The presence of IEDs on electroencephalography (EEG) did not impact subsequent seizure risk early in the disease. By the fourth year of disease, all children without IEDs remained seizure free, whereas one‐third of children with IEDs at this stage had a subsequent seizure. Conversely, ACD treatment corresponded with lower risk of seizure early in the disease but did not impact seizure risk in later years.

Significance

In this cohort, the majority of children with BECTS had a subsequent seizure despite treatment. In addition, ACD treatment and IEDs predicted seizure risk at specific points of disease duration. Future prospective studies are needed to validate these exploratory findings.

Detection of fast (40-150 Hz) oscillations from the ictal scalp EEG data of myoclonic seizures in pediatric patients

OBJECTIVE

We explored fast (40-150 Hz) oscillations (FOs) from the ictal scalp electroencephalogram (EEG) data of myoclonic seizures in pediatric patients to obtain insight into the pathophysiological mechanisms involved in the generation of myoclonic seizures.

SUBJECTS AND METHODS

The participants were 21 children (11 boys, 10 girls; age ranging from 5 months to 17 years 2 months) with myoclonic seizures associated with generalized (poly)spike-wave bursts in the ictal EEG data. The patients had heterogeneous etiologies and epilepsy diagnoses. In the ictal data, we detected FOs that clearly showed oscillatory morphology in filtered EEG traces and an outstanding spectral blob in time-frequency analysis.

RESULTS

We identified FOs in 61 (88.4%) of all 69 myoclonic seizures. Every patient had at least one myoclonic seizure-associated FO. The observed FOs were embedded in the spike component of (poly)spike-wave discharges, and they had a focal distribution with frontal predominance. They ranged in frequency from 41.0 to 123.0 Hz and involved both the gamma and ripple bands, and their spectral peak frequencies were higher in the group of patients with a genetic background free of apparent fundamental brain pathology than in the group of other patients (p = 0.019).

CONCLUSION

FOs were found to represent at least part of the cortical pathophysiological process in the generation of myoclonic seizures that should involve the thalamocortical network system.

Scalp-recorded high-frequency oscillations in childhood epileptic encephalopathy with continuous spike-and-wave during sleep with different etiologies

OBJECTIVE

To investigate high-frequency oscillations (HFOs) in epileptic encephalopathy with continuous spike-and-wave during sleep (CSWS) with different etiologies.

METHODS

Twenty-one CSWS patients treated with methylprednisolone were divided into structural group and genetic/unknown group. Comparisons were made between the two etiological groups: selected clinical variables including gender, age parameters, seizure frequencies and antiepileptic drugs; distribution of HFOs in pre-methylprednisolone electroencephalography (EEG) and percentage changes of HFOs and spikes after methylprednisolone treatment.

RESULTS

There were 7 patients (33%) in structural group and 14 patients (68%) in genetic/unknown group. No significant difference was found between the two groups regarding selected clinical variables. HFOs were found in 12 patients in pre-methylprednisolone EEG. The distribution of HFOs was focal and accordant with lesions in 5 of structural group, and it was also focal but in different brain regions in 7 of genetic/unknown group. The percentage reduction of total HFOs and spikes was 81% (158/195) and 19% (1956/10,037) in structural group, while 98% (315/323) and 55% (6658/12,258) in genetic/unknown group after methylprednisolone treatment.

CONCLUSION

The etiologies had no distinct correlation with some clinical characteristics in CSWS. HFOs recorded on scalp EEG might not only be used as makers of seizure-onset zone (SOZ), but also have association with functional disruption of brain networks. Both HFOs and spikes reduced more in genetic/unknown patients than that in structural patients after methylprednisolone treatment and HFOs were more sensitive to treatment than spikes.

The role of high-frequency oscillations in epilepsy surgery planning

BACKGROUND

Epilepsy is a serious brain disorder characterized by recurrent unprovoked seizures. Approximately two-thirds of seizures can be controlled with antiepileptic medications (Kwan 2000). For some of the others, surgery can completely eliminate or significantly reduce the occurrence of disabling seizures. Localization of epileptogenic areas for resective surgery is far from perfect, and new tools are being investigated to more accurately localize the epileptogenic zone (the zone of the brain where the seizures begin) and improve the likelihood of freedom from postsurgical seizures. Recordings of pathological high-frequency oscillations (HFOs) may be one such tool.

OBJECTIVES

To assess the ability of HFOs to improve the outcomes of epilepsy surgery by helping to identify more accurately the epileptogenic areas of the brain.

SEARCH METHODS

For the latest update, we searched the Cochrane Epilepsy Group Specialized Register (25 July 2016), the Cochrane Central Register of Controlled Trials (CENTRAL) via the Cochrane Register of Studies Online (CRSO, 25 July 2016), MEDLINE (Ovid, 1946 to 25 July 2016), CINAHL Plus (EBSCOhost, 25 July 2016), Web of Science (Thomson Reuters, 25 July 2016), ClinicalTrials.gov (25 July 2016), and the World Health Organization International Clinical Trials Registry Platform ICTRP (25 July 2016).

SELECTION CRITERIA

We included studies that provided information on the outcomes of epilepsy surgery for at least six months and which used high-frequency oscillations in making decisions about epilepsy surgery.

DATA COLLECTION AND ANALYSIS

The primary outcome of the review was the Engel Class Outcome System (class I = no disabling seizures, II = rare disabling seizures, III = worthwhile improvement, IV = no worthwhile improvement). Secondary outcomes were responder rate, International League Against Epilepsy (ILAE) epilepsy surgery outcome, frequency of adverse events from any source and quality of life outcomes. We intended to analyse outcomes via an aggregated data fixed-effect model meta-analysis.

MAIN RESULTS

Two studies representing 11 participants met the inclusion criteria. Both studies were small non-randomised trials, with no control group and no blinding. The quality of evidence for all outcomes was very low. The combination of these two studies resulted in 11 participants who prospectively used ictal HFOs for epilepsy surgery decision making. Results of the postsurgical seizure freedom Engel class I to IV outcome were determined over a period of 12 to 38 months (average 23.4 months) and indicated that six participants had an Engel class I outcome (seizure freedom), two had class II (rare disabling seizures), three had class III (worthwhile improvement). No adverse effects were reported. Neither study compared surgical results guided by HFOs versus surgical results guided without HFOs.

AUTHORS' CONCLUSIONS

No reliable conclusions can be drawn regarding the efficacy of using HFOs in epilepsy surgery decision making at present.

High-frequency oscillations: The state of clinical research

Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal high-frequency oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It highlights the growing literature on the association between HFOs and postsurgical seizure outcome. A recent meta-analysis confirmed a higher resection ratio for HFOs in seizure-free versus non-seizure-free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show high scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure frequency. The time-consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer-assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.

Scalp EEG Ictal gamma and beta activity during infantile spasms: Evidence of focality

OBJECTIVE

We investigated temporal and spatial characteristics of ictal gamma and beta activity on scalp EEG during spasms in patients with West syndrome (WS) to evaluate potential focal cortical onset.

METHODS

A total of 1,033 spasms from 34 patients with WS of various etiologies were analyzed on video-electroencephalography (EEG) using time-frequency analysis. Ictal gamma (35-90 Hz) and beta (15-30 Hz) activities were correlated with visual symmetry of spasms, objective EMG (electromyography) analysis, and etiology of WS.

RESULTS

Prior to the ictal motor manifestation, focal ictal gamma activity emerged from one hemisphere (71%, 24/34) or from midline (26%, 9/34), and was rarely simultaneously bilateral (3%, 1/34). Focal ictal beta activity emerged from either one hemisphere (68%, 23/34) or from midline (32%, 11/34). Onsets of focal ictal gamma and beta activity were most commonly observed around the parietal areas. Focal ictal gamma activity propagated faster than ictal beta activity to adjacent electrodes (median: 65 vs. 170 msec, p < 0.01), and to contralateral hemisphere (median: 100 vs. 170 msec, p = 0.01). Asymmetric peak amplitude of ictal gamma activity in the centroparietal areas (C3-P3 vs. C4-P4) correlated with asymmetric semiology. On the other hand, most of the visually symmetric spasms showed asymmetry in peak amplitude and interhemispheric onset latency difference in both ictal gamma and beta activity.

SIGNIFICANCE

Spasms may be a seizure with focal electrographic onset regardless of visual symmetry. Asymmetric involvement of ictal gamma activity to the centroparietal areas may determine the motor manifestations in WS. Scalp EEG ictal gamma and beta activity may be useful to demonstrate localized seizure onset in infants with WS.

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.

Local and Distant Dysregulation of Synchronization Around Interictal Spikes in BECTS

Objective: High Density electroencephalography (HD EEG) is the reference non-invasive technique to investigate the dynamics of neuronal networks in Benign Epilepsy with Centro-Temporal Spikes (BECTS). Analysis of local dynamic changes surrounding Interictal Epileptic Spikes (IES) might improve our knowledge of the mechanisms that propel neurons to the hypersynchronization of IES in BECTS. Transient distant changes in the dynamics of neurons populations may also interact with neuronal networks involved in various functions that are impaired in BECTS patients.

Methods: HD EEG (64 electrodes) of eight well-characterized BECTS patients (8 males; mean age: 7.2 years, range: 5–9 years) were analyzed. Unilateral IES were selected in 6 patients. They were bilateral and independent in 2 other patients. This resulted in a total of 10 groups of IES. Time-frequency analysis was performed on HD EEG epochs around the peak of the IES (±1000 ms), including phase-locked and non-phase-locked activities to the IES. The time frequency analyses were calculated for the frequencies between 4 and 200 Hz.

Results: Time-frequency analysis revealed two patterns of dysregulation of the synchronization between neuronal networks preceding and following hypersynchronization of interictal spikes (±400 ms) in the epileptogenic zone. Dysregulation consists of either desynchronization (n = 6) or oscillating synchronization (n = 4) (4–50 Hz) surrounding the IES. The 2 patients with bilateral IES exhibited only local desynchronization whatever the IES considered. Distant desynchronization in low frequencies within the same window occurs simultaneously in bilateral frontal, temporal and occipital areas (n = 7).

Significance: Using time-frequency analysis of HD EEG data in a well-defined population of BECTS, we demonstrated repeated complex changes in the dynamics of neuronal networks not only during, but also, before and after the IES. In the epileptogenic zone, our results found more complex reorganization of the local network than initially thought. In line with previous results obtained at a microscopic or macroscopic level, these changes suggested the variability strategies of neuronal assemblies to raise IES. Distant changes from the epileptogenic zone in desynchronization observed in the same time window suggested interactions between larger embedded networks and opened new avenues about their possible role in the underlying mechanism leading to cognitive deficits.