Statistical mapping of ictal high-frequency oscillations in epileptic spasms

Nodding syndrome: A role for environmental biotoxins that dysregulate MECP2 expression?

Nodding syndrome is an epileptic encephalopathy associated with neuroinflammation and tauopathy. This initially pediatric brain disease, which has some clinical overlap with Methyl-CpG-binding protein 2 (MECP2) Duplication Syndrome, has impacted certain impoverished East African communities coincident with local civil conflict and internal displacement, conditions that forced dependence on contaminated food and water. A potential role in Nodding syndrome for certain biotoxins (freshwater cyanotoxins plus/minus mycotoxins) with neuroinflammatory, excitotoxic, tauopathic, and MECP2-dysregulating properties, is considered here for the first time.

Electroclinical Features of Infantile Epileptic Spasms Syndrome

Epileptic spasms are a unique, age-dependent manifestation of epilepsies in infancy and early childhood, commonly occurring as part of infantile epileptic spasms syndrome. Developmental stagnation and subsequent decline may occur in children with epileptic spasms, partly due to the abundant high-amplitude interictal epileptiform and slow wave abnormalities. Early recognition and treatment of epileptic spasms, along with the reversal of the electroencephalography (EEG) findings, are critical for improving outcomes. Recognizing hypsarrhythmia and its variations is key to confirming the diagnosis. The various patterns of hypsarrhythmia are not etiology specific, but could indicate the severity of the disease. Several scoring systems have been proposed to improve the inter-rater reliability of recognizing hypsarrhythmia and to assess EEG progress in response to treatment. Ictal patterns during spasms are brief and composed of slow waves, sharp transients, fast activity, and voltage attenuation, either in isolation or more commonly as a combination of these waveforms. Ictal patterns are commonly diffuse, but may be lateralized to one hemisphere in children with structural etiology. A subset of patients with epileptic spasms has a surgically remediable etiology, with readily identifiable lesions on neuroimaging in most cases. Asymmetry in epileptic spasms, concurrent focal seizures, and asymmetric interictal and ictal EEG findings may be present, but a lack of focality in electrophysiological findings is not uncommon. Intracranial EEG features of epileptic spasms have been described, but the utility of intracranial EEG monitoring in surgical candidates with overt focal epileptogenic lesions on magnetic resonance imaging is questionable, and surgery could be performed using noninvasive data.

Optimizing detection and deep learning-based classification of pathological high-frequency oscillations in epilepsy

OBJECTIVE

This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery.

METHODS

We analyzed interictal HFOs (80-500 Hz) in 15 children with medication-resistant focal epilepsy who underwent chronic intracranial electroencephalogram via subdural grids. The HFOs were assessed using the short-term energy (STE) and Montreal Neurological Institute (MNI) detectors and examined for spike association and time-frequency plot characteristics. A deep learning (DL)-based classification was applied to purify pathological HFOs. Postoperative seizure outcomes were correlated with HFO-resection ratios to determine the optimal HFO detection method.

RESULTS

The MNI detector identified a higher percentage of pathological HFOs than the STE detector, but some pathological HFOs were detected only by the STE detector. HFOs detected by both detectors had the highest spike association rate. The Union detector, which detects HFOs identified by either the MNI or STE detector, outperformed other detectors in predicting postoperative seizure outcomes using HFO-resection ratios before and after DL-based purification.

CONCLUSIONS

HFOs detected by standard automated detectors displayed different signal and morphological characteristics. DL-based classification effectively purified pathological HFOs.

SIGNIFICANCE

Enhancing the detection and classification methods of HFOs will improve their utility in predicting postoperative seizure outcomes.

Optimizing Detection and Deep Learning-based Classification of Pathological High-Frequency Oscillations in Epilepsy

Objective

This study aimed to explore sensitive detection methods and deep learning (DL)-based classification for pathological high-frequency oscillations (HFOs).

Methods

We analyzed interictal HFOs (80-500 Hz) in 15 children with medication-resistant focal epilepsy who underwent resection after chronic intracranial electroencephalogram via subdural grids. The HFOs were assessed using the short-term energy (STE) and Montreal Neurological Institute (MNI) detectors and examined for pathological features based on spike association and time-frequency plot characteristics. A DL-based classification was applied to purify pathological HFOs. Postoperative seizure outcomes were correlated with HFO-resection ratios to determine the optimal HFO detection method.

Results

The MNI detector identified a higher percentage of pathological HFOs than the STE detector, but some pathological HFOs were detected only by the STE detector. HFOs detected by both detectors exhibited the most pathological features. The Union detector, which detects HFOs identified by either the MNI or STE detector, outperformed other detectors in predicting postoperative seizure outcomes using HFO-resection ratios before and after DL-based purification.

Conclusions

HFOs detected by standard automated detectors displayed different signal and morphological characteristics. DL-based classification effectively purified pathological HFOs.

Significance

Enhancing the detection and classification methods of HFOs will improve their utility in predicting postoperative seizure outcomes.

HIGHLIGHTS

HFOs detected by the MNI detector showed different traits and higher pathological bias than those detected by the STE detectorHFOs detected by both MNI and STE detectors (the Intersection HFOs) were deemed the most pathologicalA deep learning-based classification was able to distill pathological HFOs, regard-less of the initial HFO detection methods.

Animal Models in Epileptic Spasms and the Development of Novel Treatment Options

SUMMARY

The infantile spasms (IS) syndrome is a catastrophic developmental epileptic encephalopathy syndrome characterized by an age-specific expression of epileptic spasms that are associated with extremely abnormal, oftentimes described as chaotic, interictal EEG pattern known as hypsarrhythmia. Patients with IS generally have poor neurodevelopmental outcomes, in large part because of the frequent epileptic spasms and interictal EEG abnormalities. Current first-line treatments such as adrenocorticotropic hormone or vigabatrin are often ineffective and are associated with major toxic side effects. There is therefore a need for better and safer treatments for patients with IS, especially for the intractable population. Hope is on the horizon as, over the past 10 years, there has been robust progress in the development of etiology-specific animal models of IS. These models have been used to identify potential new treatments for IS and are beginning to provide some important insights into the pathophysiological substrates for this disease. In this review, we will highlight strengths and weaknesses of the currently available animal models of IS in addition to new insights into the pathophysiology and treatment options derived from these models.

Electroclinical Features in Epilepsy Surgery Candidates With Epileptic Spasms

SUMMARY

Electroclinical features in surgical candidates with epileptic spasms differ significantly from the other focal epilepsy phenotypes. EEG findings tend to be more diffuse and less localizing in children with epileptic spasms. These are illustrated with five case studies to highlight three different categories of findings on interictal and ictal EEG: lateralizing , nonlateralizing , and false lateralizing . Hemihypsarrhythmia on interictal EEG is the most striking lateralizing abnormality that occurs in a minority of surgical candidates. Persistent focal epileptiform discharges in one region or asymmetric physiologic rhythms decreased over the abnormal hemisphere may provide localization clues. Ictal EEG patterns are diffuse and nonlocalizing in over half of the patients. Ictal patterns are best expressed in the posterior head regions even in patients with epileptogenic zone in anterior regions. Semiologically, epileptic spasms tend to be symmetrical in majority of surgical candidates. Asymmetric spasms and coexisting focal seizures (concurrent or remote), when present, may provide localization findings. False lateralizing interictal or ictal EEG abnormalities, paradoxically higher over the healthier hemisphere, occur in the setting of large encephaloclastic/volume loss lesions. In these patients, the diffuse discharges are less expressed over the abnormal hemisphere with less cerebral tissue. Recognition of such false lateralizing findings is important to avoid excluding appropriate surgical candidates based on the EEG findings alone. Epileptogenic lesions are visible on brain MRI in majority of surgical candidates with epileptic spasms. Electroclinical findings are often concordant with the lesion, but discordant findings are not uncommon in children with epileptic spasms.

Periodic electroencephalographic discharges and epileptic spasms involve cortico-striatal-thalamic loops on Arterial Spin Labeling Magnetic Resonance Imaging

Periodic discharges are a rare peculiar electroencephalogram pattern, occasionally associated with motor or other clinical manifestations, usually observed in critically ill patients. Their underlying pathophysiology remains poorly understood. Epileptic spasms in clusters and periodic discharges with motor manifestations share similar electroencephalogram pattern and some aetiologies of unfavourable prognosis such as subacute sclerosing panencephalitis or herpes encephalitis. Arterial spin labelling magnetic resonance imaging identifies localizing ictal and inter-ictal changes in neurovascular coupling, therefore assumed able to reveal concerned cerebral structures. Here, we retrospectively analysed ictal and inter-ictal arterial spin labelling magnetic resonance imaging in patients aged 6 months to 15 years (median 3 years 4 months) with periodic discharges including epileptic spasms, and compared these findings with those of patients with drug-resistant focal epilepsy who never presented periodic discharges nor epileptic spasms as well as to those of age-matched healthy controls. Ictal electroencephalogram was recorded either simultaneously with arterial spin labelling magnetic resonance imaging or during the close time lapse of patients' periodic discharges, whereas inter-ictal examinations were performed during the patients' active epilepsy but without seizures during the arterial spin labelling magnetic resonance imaging. Ictal arterial spin labelling magnetic resonance imaging was acquired in five patients with periodic discharges [subacute sclerosing panencephalitis (1), stroke-like events (3), West syndrome with cortical malformation (1), two of them also had inter-ictal arterial spin labelling magnetic resonance imaging]. Inter-ictal group included patients with drug-resistant epileptic spasms of various aetiologies (14) and structural drug-resistant focal epilepsy (8). Cortex, striatum and thalamus were segmented and divided in six functional subregions: prefrontal, motor (rostral, caudal), parietal, occipital and temporal. Rest cerebral blood flow values, absolute and relative to whole brain, were compared with those of age-matched controls for each subregion. Main findings were diffuse striatal as well as cortical motor cerebral blood flow increase during ictal examinations in generalized periodic discharges with motor manifestations (subacute sclerosing panencephalitis) and focal cerebral blood flow increase in corresponding cortical-striatal-thalamic subdivisions in lateralized periodic discharges with or without motor manifestations (stroke-like events and asymmetrical epileptic spasms) with straight topographical correlation with the electroencephalogram focus. For inter-ictal examinations, patients with epileptic spasms disclosed cerebral blood flow changes in corresponding cortical-striatal-thalamic subdivisions (absolute-cerebral blood flow decrease and relative-cerebral blood flow increase), more frequently when compared with the group of drug-resistant focal epilepsies, and not related to Vigabatrin treatment. Our results suggest that corresponding cortical-striatal-thalamic circuits are involved in periodic discharges with and without motor manifestations, including epileptic spasms, opening new insights in their pathophysiology and new therapeutical perspectives. Based on these findings, we propose a model for the generation of periodic discharges and of epileptic spasms combining existing pathophysiological models of cortical-striatal-thalamic network dynamics.

Startle-Induced Epileptic Spasms: A Clinical and Video-EEG Study

Objective

This study aimed to delineate the detailed characteristics of startle-induced epileptic spasms (ES) and explore the brain regions where startle-induced ES originated.

Methods

Among 581 patients with ES registered in our database, 30 were diagnosed with startle-induced ES according to video-electroencephalogram (EEG) and seizure semiology and were included in this study. Patients' clinical characteristics and ictal high-frequency oscillations (HFOs) were analyzed.

Results

Mean age at the onset of startle-induced ES was 28.1 months. Half of the patients had structural etiology, two of whom were diagnosed with co-existing structural and genetic etiologies. The focal neuroimaging abnormalities were predominant in the frontal cortex (9/15, 60.0%). Fifteen patients (50%) had prominent interictal epileptiform discharges in the frontal and anterior temporal. Ictal HFOs counts of the startle-induced ES in the anterior region were significantly higher than those in the posterior regions (p < 0.05). Five patients (16.7%) became seizure-free ≥6 months, and ten (33.3%) showed startle-induced ES cessation ≥6 months. All patients except one had mild to severe psychomotor developmental delay after the onset of seizures.

Conclusion

Patients with startle-induced ES typically had brain lesions and showed drug-resistant. The neuroimaging and EEG findings, including ictal HFOs, support that startle-induced ES often originates from the frontal cortex.

Diffusion tractography predicts propagated high-frequency activity during epileptic spasms

OBJECTIVE

Determine the structural networks that constrain propagation of ictal oscillations during epileptic spasm events, and compare observed propagation patterns across patients with successful or unsuccessful surgical outcomes.

METHODS

Subdural electrode recordings of 18 young patients (age 1-11 years) were analyzed during epileptic spasm events to determine ictal networks and quantify the amplitude and onset time of ictal oscillations across the cortical surface. Corresponding structural networks were generated with diffusion MRI tractography by seeding the cortical region associated with the earliest average oscillation onset time, and white matter pathways connecting active electrode regions within the ictal network were isolated. Properties of this structural network were used to predict oscillation onset times and amplitudes, and this relationship was compared across patients who did and did not achieve seizure freedom following resective surgery.

RESULTS

Onset propagation patterns were relatively consistent across each patients' spasm events. An electrode's average ictal oscillation onset latency was most significantly associated with the length of direct corticocortical tracts connecting to the area with the earliest average oscillation onset (p < .001, model R²  = 0.54). Moreover, patients demonstrating a faster propagation of ictal oscillation signals within the corticocortical network were more likely to have seizure recurrence following resective surgery (p = .039). Ictal oscillation amplitude was also associated with connecting tractography length and weighted fractional anisotropy (FA) measures along these pathways (p = .002/.030, model R²  = 0.31/0.25). Characteristics of analogous corticothalamic pathways did not show significant associations with ictal oscillation onset latency or amplitude.

SIGNIFICANCE

Spatiotemporal propagation patterns of high-frequency activity in epileptic spasms align with length and FA measures from onset-originating corticocortical pathways. Considering data in this individualized framework may help inform surgical decision making and expectations of surgical outcomes.

Altered neocortical oscillations and cellular excitability in an in vitro Wwox knockout mouse model of epileptic encephalopathy

Loss of function mutations of the WW domain-containing oxidoreductase (WWOX) gene are associated with severe and fatal drug-resistant pediatric epileptic encephalopathy. Epileptic seizures are typically characterized by neuronal hyperexcitability; however, the specific contribution of WWOX to that hyperexcitability has yet to be investigated. Using a mouse model of neuronal Wwox-deletion that exhibit spontaneous seizures, in vitro whole-cell and field potential electrophysiological characterization identified spontaneous bursting activity in the neocortex, a marker of the underlying network hyperexcitability. Spectral analysis of the neocortical bursting events highlighted increased phase-amplitude coupling, and a propagation from layer II/III to layer V. These bursts were NMDAR and gap junction dependent. In layer II/III pyramidal neurons, Wwox knockout mice demonstrated elevated amplitude of excitatory post-synaptic currents, whereas the frequency and amplitude of inhibitory post-synaptic currents were reduced, as compared to heterozygote and wild-type littermate controls. Furthermore, these neurons were depolarized and demonstrated increased action potential frequency, sag current, and post-inhibitory rebound. These findings suggest WWOX plays an essential role in balancing neocortical excitability and provide insight towards developing therapeutics for those suffering from WWOX disorders.

The Onset of Interictal Spike-Related Ripples Facilitates Detection of the Epileptogenic Zone

Objective: Accurate estimation of the epileptogenic zone (EZ) is essential for favorable outcomes in epilepsy surgery. Conventional ictal electrocorticography (ECoG) onset is generally used to detect the EZ but is insufficient in achieving seizure-free outcomes. By contrast, high-frequency oscillations (HFOs) could be useful markers of the EZ. Hence, we aimed to detect the EZ using interictal spikes and investigated whether the onset area of interictal spike-related HFOs was within the EZ. Methods: The EZ is considered to be included in the resection area among patients with seizure-free outcomes after surgery. Using a complex demodulation technique, we developed a method to determine the onset channels of interictal spike-related ripples (HFOs of 80-200 Hz) and investigated whether they are within the resection area. Results: We retrospectively examined 12 serial patients who achieved seizure-free status after focal resection surgery. Using the method that we developed, we determined the onset channels of interictal spike-related ripples and found that for all 12 patients, they were among the resection channels. The onset frequencies of ripples were in the range of 80-150 Hz. However, the ictal onset channels (evaluated based on ictal ECoG patterns) and ripple onset channels coincided in only 3 of 12 patients. Conclusions: Determining the onset area of interictal spike-related ripples could facilitate EZ estimation. This simple method that utilizes interictal ECoG may aid in preoperative evaluation and improve epilepsy surgery outcomes.

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.

Refining epileptogenic high-frequency oscillations using deep learning: a reverse engineering approach

Intracranially recorded interictal high-frequency oscillations have been proposed as a promising spatial biomarker of the epileptogenic zone. However, its visual verification is time-consuming and exhibits poor inter-rater reliability. Furthermore, no method is currently available to distinguish high-frequency oscillations generated from the epileptogenic zone (epileptogenic high-frequency oscillations) from those generated from other areas (non-epileptogenic high-frequency oscillations). To address these issues, we constructed a deep learning-based algorithm using chronic intracranial EEG data via subdural grids from 19 children with medication-resistant neocortical epilepsy to: (i) replicate human expert annotation of artefacts and high-frequency oscillations with or without spikes, and (ii) discover epileptogenic high-frequency oscillations by designing a novel weakly supervised model. The ‘purification power’ of deep learning is then used to automatically relabel the high-frequency oscillations to distill epileptogenic high-frequency oscillations. Using 12 958 annotated high-frequency oscillation events from 19 patients, the model achieved 96.3% accuracy on artefact detection (F1 score = 96.8%) and 86.5% accuracy on classifying high-frequency oscillations with or without spikes (F1 score = 80.8%) using patient-wise cross-validation. Based on the algorithm trained from 84 602 high-frequency oscillation events from nine patients who achieved seizure-freedom after resection, the majority of such discovered epileptogenic high-frequency oscillations were found to be ones with spikes (78.6%, P < 0.001). While the resection ratio of detected high-frequency oscillations (number of resected events/number of detected events) did not correlate significantly with post-operative seizure freedom (the area under the curve = 0.76, P = 0.06), the resection ratio of epileptogenic high-frequency oscillations positively correlated with post-operative seizure freedom (the area under the curve = 0.87, P = 0.01). We discovered that epileptogenic high-frequency oscillations had a higher signal intensity associated with ripple (80–250 Hz) and fast ripple (250–500 Hz) bands at the high-frequency oscillation onset and with a lower frequency band throughout the event time window (the inverted T-shaped), compared to non-epileptogenic high-frequency oscillations. We then designed perturbations on the input of the trained model for non-epileptogenic high-frequency oscillations to determine the model’s decision-making logic. The model confidence significantly increased towards epileptogenic high-frequency oscillations by the artificial introduction of the inverted T-shaped signal template (mean probability increase: 0.285, P < 0.001), and by the artificial insertion of spike-like signals into the time domain (mean probability increase: 0.452, P < 0.001). With this deep learning-based framework, we reliably replicated high-frequency oscillation classification tasks by human experts. Using a reverse engineering technique, we distinguished epileptogenic high-frequency oscillations from others and identified its salient features that aligned with current knowledge.

Spontaneous modulations of high-frequency cortical activity

OBJECTIVE

We clarified the clinical and mechanistic significance of physiological modulations of high-frequency broadband cortical activity associated with spontaneous saccadic eye movements during a resting state.

METHODS

We studied 30 patients who underwent epilepsy surgery following extraoperative electrocorticography and electrooculography recordings. We determined whether high-gamma activity at 70-110 Hz preceding saccade onset would predict upcoming ocular behaviors. We assessed how accurately the model incorporating saccade-related high-gamma modulations would localize the primary visual cortex defined by electrical stimulation.

RESULTS

The dynamic atlas demonstrated transient high-gamma suppression in the striatal cortex before saccade onset and high-gamma augmentation subsequently involving the widespread posterior brain regions. More intense striatal high-gamma suppression predicted the upcoming saccade directed to the ipsilateral side and lasting longer in duration. The bagged-tree-ensemble model demonstrated that intense saccade-related high-gamma modulations localized the visual cortex with an accuracy of 95%.

CONCLUSIONS

We successfully animated the neural dynamics supporting saccadic suppression, a principal mechanism minimizing the perception of blurred vision during rapid eye movements. The primary visual cortex per se may prepare actively in advance for massive image motion expected during upcoming prolonged saccades.

SIGNIFICANCE

Measuring saccade-related electrocorticographic signals may help localize the visual cortex and avoid misperceiving physiological high-frequency activity as epileptogenic.

Preoperative evaluation and surgical strategy for epileptic spasms in children

Epileptic spasm (ES) is one of the most common types of seizures in children. It is primarily characterized by brief axial contractions lasting less than 2 s and recurring in short clusters. It usually occurs in children of 3 to 12 months of age, although it can also occur after the age of 1 year. In general, children with ES develop other symptoms of epilepsy, such as tonic, tonic‐clonic, or focal seizures, after 3 to 5 years of age. ES in children is often damaging and usually results in developmental regression. First‐line treatments for spasm seizures include adrenocorticotropic hormone (ACTH) and vigabatrin. However, many patients fail to respond to these medications, and continued to have spasms associated with progressive neurodevelopmental degeneration. Therefore, it is important to consider whether children with drug resistance meet surgical indications to consider surgical treatment in such conditions. In this study, we reviewed and summarized the importance of preoperative evaluation in order to provide surgical options for treatment of children with ES.

Application of High-Frequency Oscillations on Scalp EEG in Infant Spasm: A Prospective Controlled Study

Objective

We quantitatively analyzed high-frequency oscillations (HFOs) using scalp electroencephalography (EEG) in patients with infantile spasms (IS).

Methods

We enrolled 60 children with IS hospitalized from January 2019 to August 2020. Sixty healthy age-matched children comprised the control group. Time-frequency analysis was used to quantify γ, ripple, and fast ripple (FR) oscillation energy changes.

Results

γ, ripple, and FR oscillations dominated in the temporal and frontal lobes. The average HFO energy of the sleep stage is lower than that of the wake stage in the same frequency bands in both the normal control (NC) and IS groups (P < 0.05). The average HFO energy of the IS group was significantly higher than that of the NC group in γ band during sleep stage (P < 0.01). The average HFO energy of S and Post-S stage were higher than that of sleep stage in γ band (P < 0.05). In the ripple band, the average HFO energy of Pre-S, S, and Post-S stage was higher than that of sleep stage (P < 0.05). Before treatment, there was no significant difference in BASED score between the effective and ineffective groups. The interaction of curative efficacy × frequency and the interaction of curative efficacy × state are statistically significant. The average HFO energy of the effective group was lower than that of the ineffective group in the sleep stage (P < 0.05). For the 16 children deemed "effective" in the IS group, the average HFO energy of three frequency bands was not significantly different before compared with after treatment.

Significance

Scalp EEG can record HFOs. The energy of HFOs can distinguish physiological HFOs from pathological ones more accurately than frequency. On scalp EEG, γ oscillations can better detect susceptibility to epilepsy than ripple and FR oscillations. HFOs can trigger spasms. The analysis of average HFO energy can be used as a predictor of the effectiveness of epilepsy treatment.

Objective interictal electrophysiology biomarkers optimize prediction of epilepsy surgery outcome

Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving post-operative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3–4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across non-epileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the non-epileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of post-operative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.

Epileptogenic modulation index and synchronization in hypsarrhythmia of West syndrome secondary to perinatal arterial ischemic stroke

OBJECTIVE

Perinatal arterial ischemic stroke (PAIS) is associated with epileptic spasms of West syndrome (WS) and long term Focal epilepsy (FE). The mechanism of epileptogenic network generation causing hypsarrhythmia of WS is unknown. We hypothesized that Modulation index (MI) [strength of phase-amplitude coupling] and Synchronization likelihood (SL) [degree of connectivity] could interrogate the epileptogenic network in hypsarrhythmia of WS secondary to PAIS.

METHODS

We analyzed interictal scalp electroencephalography (EEG) in 10 WS and 11 FE patients with unilateral PAIS. MI between gamma (30-70 Hz) and slow waves (3-4 Hz) was calculated to measure phase-amplitude coupling. SL between electrode pairs was analyzed in 9-frequency bands (5-delta, theta, alpha, beta, gamma) to examine inter- and intra-hemispheric connectivity.

RESULTS

MI was higher in affected hemispheres in WS (p = 0.006); no differences observed in FE. Inter-hemispheric SL of 3-delta, theta, alpha, beta, gamma bands was significantly higher in WS (p < 0.001). In WS, modified Z-Score of intra-hemispheric SL values in 3-delta, theta, alpha, beta and gamma in the affected hemispheres were significantly higher than those in the unaffected hemispheres (p < 0.001) as well as 0.5-4 Hz (p = 0.004).

CONCLUSIONS

The significantly higher modulation in affected hemisphere and stronger inter- and intra-hemispheric connectivity generate hypsarrhythmia of WS secondary to PAIS.

SIGNIFICANCE

Epileptogenic cortical-subcortical transcallosal networks from affected hemisphere post-PAIS provokes infantile spasms.

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.

Effects of depth electrode montage and single-pulse electrical stimulation sites on neuronal responses and effective connectivity

OBJECTIVE

To determine the optimal depth electrode montages for the assessment of effective connectivity based on single-pulse electrical stimulation (SPES). To determine the effect of SPES locations on the extent of resulting neuronal propagations.

METHODS

We studied 14 epilepsy patients who underwent invasive monitoring with depth electrodes and measurement of cortico-cortical evoked potentials (CCEPs) and cortico-cortical spectral responses (CCSRs). We determined the effects of electrode montage and stimulus sites on the CCEP/CCSR amplitudes.

RESULTS

Bipolar and Laplacian montages effectively reduced the degree of SPES-related signal deflections at extra-cortical levels, including outside the brain, while maintaining those at the cortical level. SPES of structures more proximal to the deep white matter, compared to the cortical surface, elicited greater CCEPs and CCSRs.

CONCLUSIONS

On depth electrode recording, bipolar and Laplacian montages are suitable for measurement of near-field CCEPs and CCSRs. SPES of the white matter axons may induce neuronal propagations to extensive regions of the cerebral cortex.

SIGNIFICANCE

This study helps to establish the practical guidelines on the diagnostic use of CCEPs/CCSRs.

Seizures triggered by eating - A rare form of reflex epilepsy: A systematic review

Eating epilepsy is a rare disorder, characterised by reflex seizures induced by food intake. It is highly heterogenous, with clinical signs and EEG findings varying between patients. However, common features do emerge from the reported literature. The aim of this systematic review was to bring together this information to facilitate understanding and recognition. We therefore searched electronic databases (PubMed, Scopus, Medline) for relevant studies using keywords 'epilepsy', 'seizure' and 'eating' in March 2020. Human studies, written in English, that reported on cohorts of patients with eating epilepsy were included. Fifty-two unique papers were consequently identified, describing seizure characteristics and diagnostic features in 378 patients. Eating seizures began in the second decade of life, with a higher incidence in males. They were typically focal-onset, and most commonly of the focal impaired awareness type. Pharmacological therapy with one or multiple agents was noted in 80 % of cases, with poor control reported in approximately 25 % of patients. While this retrospective work highlights key features, it is important that future studies implicate video EEG to fully evaluate this highly unique and interesting disorder.

Stable high frequency background EEG activity distinguishes epileptic from healthy brain regions

High-frequency oscillations are markers of epileptic tissue. Recently, different patterns of EEG background activity were described from which high-frequency oscillations occur: high-frequency oscillations with continuously oscillating background were found to be primarily physiological, those from quiet background were linked to epileptic tissue. It is unclear, whether these interactions remain stable over several days and during different sleep-wake stages. High-frequency oscillation patterns (oscillatory vs. quiet background) were analysed in 23 patients implanted with depth and subdural grid electrodes. Pattern scoring was performed on every channel in 10 s intervals in three separate day- and night-time EEG segments. An entropy value, measuring variability of patterns per channel, was calculated. A low entropy value indicated a stable occurrence of the same pattern in one channel, whereas a high value indicated pattern instability. Differences in pattern distribution and entropy were analysed for 143 280 10 s intervals with allocated patterns from inside and outside the seizure onset zone, different electrode types and brain regions. We found a strong association between high-frequency oscillations out of quiet background activity, and channels of the seizure onset zone (35.2% inside versus 9.7% outside the seizure onset zone, P < 0.001), no association was found for high-frequency oscillations from continuous oscillatory background (P = 0.563). The type of background activity remained stable over the same brain region over several days and was independent of sleep stage and recording technique. Stability of background activity was significantly higher in channels of the seizure onset zone (entropy mean value 0.56 ± 0.39 versus 0.64 ± 0.41; P < 0.001). This was especially true for the presumed epileptic high-frequency oscillations out of quiet background (0.57 ± 0.39 inside versus 0.72 ± 0.37 outside the seizure onset zone; P < 0.001). In contrast, presumed physiological high-frequency oscillations from continuous oscillatory backgrounds were significantly more stable outside the seizure onset zone (0.72 ± 0.45 versus 0.48 ± 0.53; P < 0.001). The overall low entropy values suggest that interactions between high-frequency oscillations and background activity are a stable phenomenon specific to the function of brain regions. High-frequency oscillations occurring from a quiet background are strongly linked to the seizure onset zone whereas high-frequency oscillations from an oscillatory background are not. Pattern stability suggests distinct underlying mechanisms. Analysing short time segments of high-frequency oscillations and background activity could help distinguishing epileptic from physiologically active brain regions.

Epilepsy as a disease affecting neural networks: A neurophysiological perspective

INTRODUCTION

The brain is a series of networks of functionally and anatomically connected, bilaterally represented structures; in epilepsy, activity of any part of the brain affects activity in the other parts. This is relevant for understanding the pathophysiology, diagnosis, and prognosis of the disease.

OBJECTIVE

In this study, we present a state-of-the-art review of the neurophysiological view of epilepsy as a disease affecting neural networks.

RESULTS

We describe the basic and advanced principles of epilepsy as a disease affecting neural networks, based on the use of different clinical and mathematical techniques from a neurophysiological perspective, and signal the limitations of these findings in the clinical context.

CONCLUSIONS

Epilepsy is a disease affecting complex neural networks. Understanding these will enable better management and prognostic confidence.

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.

Electroencephalography in neonatal epilepsies

Neonatal epilepsies - neonatal seizures caused by remote symptomatic etiologies - are infrequent compared with those caused by acute symptomatic etiologies. The etiologies of neonatal epilepsies are classified into structural, genetic, and metabolic. Electroencephalography (EEG) and amplitude-integrated EEG (aEEG) are essential for the diagnosis and monitoring of neonatal epilepsies. Electroencephalography / aEEG findings may differ substantially among infants, even within infants with variants in a single gene. Unusual EEG/aEEG findings, such as downward seizure patterns on aEEG, can be found. Neonatal seizures are exclusively of focal onset. An International League Against Epilepsy task force proposed that the seizure type is typically determined by the predominant clinical feature and is classified into motor or non-motor presentations. Ictal EEG usually demonstrates a sudden, repetitive, evolving, and stereotyped activities with a minimum duration of 10 s. In epileptic spasms and myoclonic seizures, the cut-off point of 10 s cannot be applied. One must always be aware of electro-clinical dissociation in neonates suspected to have seizures. Amplitude-integrated EEG is also useful for the diagnosis and monitoring of neonatal epilepsies but aEEG cannot be recommended as the mainstay because of its relatively low sensitivity and specificity. At present, EEG findings are not pathognomonic, although some characteristic ictal or interictal EEG findings have been reported in several neonatal epilepsies. Deep learning will be expected to be introduced into EEG interpretation in near future. Objective EEG classification derived from deep learning may help to clarify EEG characteristics in some specific cases of neonatal epilepsy.

Expert consensus on clinical applications of high-frequency oscillations in epilepsy

Studies in animal models of epilepsy and pre-surgical patients have unanimously found a strong correlation between high-frequency oscillations (HFOs, > 80 Hz) and the epileptogenic zone, suggesting that HFOs can be a potential biomarker of epileptogenicity and epileptogenesis. This consensus includes the definition and standard detection techniques of HFOs, the localizing value of pathological HFOs for epileptic foci, and different ways to distinguish physiological from epileptic HFOs. The latest clinical applications of HFOs in epilepsy and the related findings are also discussed. HFOs will advance our understanding of the pathophysiology of epilepsy.

Pitfalls in Scalp High-Frequency Oscillation Detection From Long-Term EEG Monitoring

Aims: Intracranially recorded high-frequency oscillations (>80 Hz) are considered a candidate epilepsy biomarker. Recent studies claimed their detectability on the scalp surface. We aimed to investigate the applicability of high-frequency oscillation analysis to routine surface EEG obtained at an epilepsy monitoring unit. Methods: We retrospectively analyzed surface EEGs of 18 patients with focal epilepsy and six controls, recorded during sleep under maximal medication withdrawal. As a proof of principle, the occurrence of motor task-related events during wakefulness was analyzed in a subsample of six patients with seizure- or syncope-related motor symptoms. Ripples (80-250 Hz) and fast ripples (>250 Hz) were identified by semi-automatic detection. Using semi-parametric statistics, differences in spontaneous and task-related occurrence rates were examined within subjects and between diagnostic groups considering the factors diagnosis, brain region, ripple type, and task condition. Results: We detected high-frequency oscillations in 17 out of 18 patients and in four out of six controls. Results did not show statistically significant differences in the mean rates of event occurrences, neither regarding the laterality of the epileptic focus, nor with respect to active and inactive task conditions, or the moving hand laterality. Significant differences in general spontaneous incidence [WTS(1) = 9.594; p = 0.005] that indicated higher rates of fast ripples compared to ripples, notably in patients with epilepsy compared to the control group, may be explained by variations in data quality. Conclusion: The current analysis methods are prone to biases. A common agreement on a standard operating procedure is needed to ensure reliable and economic detection of high-frequency oscillations.

Engagement of cortico-cortical and cortico-subcortical networks in a patient with epileptic spasms: An integrated neurophysiological study

OBJECTIVE

We aimed to delineate the engagement of cortico-cortical and cortico-subcortical networks in the generation of epileptic spasms (ES) using integrated neurophysiological techniques.

METHODS

Seventeen-year-old male patient with intractable ES underwent chronic subdural electrode implantation for presurgical evaluation. Networks were evaluated in ictal periods using high-frequency oscillation (HFO) analysis and in interictal periods using magnetoencephalography (MEG) and simultaneous electroencephalography, and functional magnetic resonance imaging (EEG-fMRI). Cortico-cortical evoked potentials (CCEPs) were recorded to trace connections among the networks.

RESULTS

Ictal HFO revealed a network comprising multilobar cortical regions (frontal, parietal, and temporal), but sparing the positive motor area. Interictally, MEG and EEG-fMRI revealed spike-and-wave-related activation in these cortical regions. Analysis of CCEPs provided evidence of connectivity within the cortico-cortical network. Additionally, EEG-fMRI results indicate the involvement of subcortical structures, such as bilateral thalamus (predominantly right) and midbrain.

CONCLUSIONS

In this case study, integrated neurophysiological techniques provided converging evidence for the involvement of a cortico-cortical network (sparing the positive motor area) and a cortico-subcortical network in the generation of ES in the patient.

SIGNIFICANCE

Cortico-cortical and cortico-subcortical pathways, with the exception of the direct descending corticospinal pathway from the positive motor area, may play important roles in the generation of ES.

Seizure onset location shapes dynamics of initiation

OBJECTIVE

Ictal electrographic patterns are widely thought to reflect underlying neural mechanisms of seizures. Here we studied the degree to which seizure patterns are consistent in a given patient, relate to particular brain regions and if two candidate biomarkers (high-frequency oscillations, HFOs; infraslow activity, ISA) and network activity, as assessed with cross-frequency interactions, can discriminate between seizure types.

METHODS

We analyzed temporal changes in low and high frequency oscillations recorded during seizures, as well as phase-amplitude coupling (PAC) to monitor the interactions between delta/theta and ripple/fast ripple frequency bands at seizure onset.

RESULTS

Seizures of multiple electrographic patterns were observed in a given patient and brain region. While there was an increase in HFO rate across different electrographic patterns, there are specific relationships between types of HFO activity and onset region. Similarly, changes in PAC dynamics were more closely related to seizure onset region than they were to electrographic patterns while ISA was a poor indicator for seizure onset.

CONCLUSIONS

Our findings suggest that the onset region sculpts neurodynamics at seizure initiation and that unique features of the cytoarchitecture and/or connectivity of that region play a significant role in determining seizure mechanism.

SIGNIFICANCE

To learn how seizures are initiated, researchers would do well to consider other aspects of their manifestation, in addition to their electrographic patterns. Examination of onset pattern in conjunction with the interactions between different oscillatory frequencies in the context of different brain regions might be more informative and lead to more reliable clinical inference as well as novel therapeutic approaches.

Interictal scalp fast ripple occurrence and high frequency oscillation slow wave coupling in epileptic spasms

OBJECTIVE

Intracranial high frequency oscillation (HFO) occurrence rate (OR) and slow wave activity (SWA) coupling are potential markers of epileptogenicity in epileptic spasms (ES). Scalp ripple (R) detection and SWA coupling have been described in ES; however, the feasibility of scalp fast ripple (FR) detection and measurement of scalp FR coupling to SWA is not known. We evaluated interictal scalp R and FR OR and SWA coupling in pre-treatment EEG in children with short-term treatment-refractory ES compared to short-term treatment non-refractory ES.

METHODS

We retrospectively identified children with ES and identified HFOs using a semi-automated HFO detector on pre-treatment scalp EEG during sleep. We evaluated HFO OR and event-triggered modulation index (MI) to quantify R (100-250 Hz) and FR (250-600 Hz) coupling strength with different SWA passbands (0.5-1, 1-2, 2-3, 3-4, and 4-8 Hz). We used HFO phasor transform and circular statistics to evaluate phase coupling angle distributions.

RESULTS

We identified 15 children with ES with pre-treatment EEG recorded at 2000 Hz. Thirteen out of 15 patients had HFOs and were included for analysis. There were six treatment responders and seven nonresponders three months after treatment initiation. Responders and nonresponders were similar in age (6.1 vs 7.2 mo), ES diagnosis duration (0.7 vs 2.6 mo), and HFO OR (R: 1.07 vs 2.30/min, FR: 0.43 vs 1.96/min). No differences between responders and nonresponders were seen in HFO MI at different SWA. Coupling of R and FR to 2-3 Hz SWA demonstrated increased incidence rate ratio in nonresponders relative to responders at distinct phase coupling angle distributions.

CONCLUSIONS

This study demonstrates the feasibility of interictal scalp R and FR detection and quantification of scalp R and FR coupling to SWA in ES.

SIGNIFICANCE

HFO phase coupling with SWA may be useful as a marker of potential treatment refractoriness in patients with ES.

Cortical high-frequency oscillation loops initiate spasm seizures

Some epileptic spasms are classified into focal-onset seizures. However, the cortical network underlying this kind of spasm seizure is not yet clear. Four patients with epileptic spasms who underwent intracranial electrode implantation and focal resection surgery were studied. All the patients had good outcomes, and three of them with intellectual disability showed improved intelligence after surgery. The power spectra characteristics of electrocorticography and the dynamic functional network changes of epileptic spasms were investigated. Electrocorticography power in the resected zone peaked 0.5 seconds before the clinical seizure onset and was especially prominent in the γ and ripple bands. The functional network analysis showed particular dynamic patterns of high-frequency activity among the resected zone, sensorimotor cortex, and the other region. In the gamma band, during the interictal segment, the information flow from the resected zone and the other region to the sensorimotor cortex was prominent. During the preictal segment, the information flow from the resected zone and sensorimotor cortex to the other region became stronger. In the ripple band, during the interictal segment, the information flow from the resected zone to the sensorimotor cortex and the other region was high. During the preictal segment, the information flow between the resected zone and sensorimotor cortex became stronger. Our results suggest that the sensorimotor cortex is a requisite for spasm seizure initiation, and the ripple activity loop between the resected zone and sensorimotor cortex may give rise to the seizure onset with the help of the gamma activity loop between the sensorimotor cortex and the other region for activation spreading.

Active direct current (DC) shifts and "Red slow": two new concepts for seizure mechanisms and identification of the epileptogenic zone

An accurate identification of the epileptogenic zone is essential for patients with intractable epilepsy who are candidates to neurosurgery. EEG recordings can provide predictive biomarkers of the epileptogenic zone. Wide-band EEG makes it possible to record from infraslow (including DC shifts) to high frequency (HFO, over 300 Hz) oscillations for diagnostic purposes in patients with epilepsy. Although the presence of HFOs have been proposed to sign the epileptogenic zone, DC-like recordings demonstrate that DC shifts precede HFOs at seizure onset. This led to the proposal that "ictal active DC shifts" are causally related to seizure onset as opposed to "ictal passive DC shifts". Thus, active DC shifts may constitute predictive biomarkers of the epileptogenic zone in epilepsy. Since DC shift is commonly associated to a rise in extracellular potassium, potassium homeostasis regulated by Kir4.1 channels in astrocytes may play an key role at seizure onset. In addition, we hypothesize that, during the interictal period, the co-occurrence of slow events and interictal HFOs, so-called "Red slow", may also delineate an epileptogenic zone, even if a seizure would not be actually recorded.

Symmetry of ictal slow waves may predict the outcomes of corpus callosotomy for epileptic spasms

We aimed to analyse the ictal electrographic changes on scalp electroencephalography (EEG), focusing on high-voltage slow waves (HVSs) in children with epileptic spasms (ES) and tonic spasms (TS) and then identified factors associated with corpus callosotomy (CC) outcomes. We enrolled 17 patients with ES/TS who underwent CC before 20 years of age. Post-CC Engel’s classification was as follows: I in 7 patients, II in 2, III in 4, and IV in 4. Welch’s t-test was used to analyse the correlation between ictal HVSs and CC outcomes based on the following three symmetrical indices: (1) negative peak delay: interhemispheric delay between negative peaks; (2) amplitude ratio: interhemispheric ratio of amplitude values for the highest positive peaks; and (3) duration ratio: interhemispheric ratio of slow wave duration. Ages at CC ranged from 17–237 months. Four to 15 ictal EEGs were analysed for each patient. The negative peak delay, amplitude ratio and duration ratio ranged from 0–530 ms, 1.00–7.40 and 1.00–2.74, respectively. The negative peak delay, amplitude ratio and duration ratio were significantly higher in the seizure residual group (p = 0.017, <0.001, <0.001, respectively). Symmetry of ictal HVSs may predict favourable outcomes following CC for ES/TS.

Epileptogenicity Maps of Intracerebral Fast Activities (60-100 Hz) at Seizure Onset in Epilepsy Surgery Candidates

Fast activities (FA) at seizure onset have been increasingly described as a useful signature of the epileptogenic zone (EZ) in patients undergoing intracranial EEG recordings. Different computer-based signal analysis methods have thus been developed for objectively quantifying ictal FA. Whether these methods detect FA in all forms of focal epilepsies, whether they provide similar information than visual analysis (VA), and whether they might help for the surgical decision remain crucial issues. We thus conducted a retrospective study in 21 consecutive patients suffering from drug-resistant seizures studied by SEEG recordings. Ictal FA were quantified using the Epileptogenicity Maps (EM) method that we recently developed and which generates, by adopting a neuroimaging approach, statistical parametric maps of FA ranging from 60 to 100 Hz (FA⁶⁰⁻¹⁰⁰). Ictal FA were analyzed blindly using VA and EM, and the prognostic significance of removing areas exhibiting FA⁶⁰⁻¹⁰⁰ at seizure onset was evaluated. A significant ictal FA⁶⁰⁻¹⁰⁰ activation was found in all patients, and in 92.6% of all the 68 seizures recorded, whatever the epilepsy type. The overlap ratio (OR) between VA and EM was significantly better for defining the regions spared at seizure onset than those from which seizure arose (p < 0.001), especially in temporal or temporal “plus” epilepsies. EM and VA were much more discordant to define the EZ, with a mean number of electrode contacts involved at seizure onset significantly higher with EM than with VA (p = <0.0001). Seizure outcome correlated with the resection ratio for FA⁶⁰⁻¹⁰⁰, which was significantly higher in seizure-free (Engel's class Ia) than in non seizure-free patients (class Ic-IV) (p = 0.048). The quantification of FA at seizure onset can bring information additional to clinical expertise that might contribute to define accurately the cortical region to be resected.

Quantitative analysis of intracranial electrocorticography signals using the concept of statistical parametric mapping

Statistical parametric mapping (SPM) is a technique with which one can delineate brain activity statistically deviated from the normative mean, and has been commonly employed in noninvasive neuroimaging and EEG studies. Using the concept of SPM, we developed a novel technique for quantification of the statistical deviation of an intracranial electrocorticography (ECoG) measure from the nonepileptic mean. We validated this technique using data previously collected from 123 patients with drug-resistant epilepsy who underwent resective epilepsy surgery. We determined how the measurement of statistical deviation of modulation index (MI) from the non-epileptic mean (rated by z-score) improved the performance of seizure outcome classification model solely based on conventional clinical, seizure onset zone (SOZ), and neuroimaging variables. Here, MI is a summary measure quantifying the strength of in-situ coupling between high-frequency activity at >150 Hz and slow wave at 3-4 Hz. We initially generated a normative MI atlas showing the mean and standard deviation of slow-wave sleep MI of neighboring non-epileptic channels of 47 patients, whose ECoG sampling involved all four lobes. We then calculated 'MI z-score' at each electrode site. SOZ had a greater 'MI z-score' compared to non-SOZ in the remaining 76 patients. Subsequent multivariate logistic regression analysis and receiver operating characteristic analysis to the combined data of all patients revealed that the full regression model incorporating all predictor variables, including SOZ and 'MI z-score', best classified the seizure outcome with sensitivity/specificity of 0.86/0.76. The model excluding 'MI z-score' worsened its sensitivity/specificity to 0.86/0.48. Furthermore, the leave-one-out analysis successfully cross-validated the full regression model. Measurement of statistical deviation of MI from the non-epileptic mean on invasive recording is technically feasible. Our analytical technique can be used to evaluate the utility of ECoG biomarkers in epilepsy presurgical evaluation.

Pathological high frequency oscillations associate with increased GABA synaptic activity in pediatric epilepsy surgery patients

Pathological high-frequency oscillations (HFOs), specifically fast ripples (FRs, >250 Hz), are pathognomonic of an active epileptogenic zone. However, the origin of FRs remains unknown. Here we explored the correlation between FRs recorded with intraoperative pre-resection electrocorticography (ECoG) and spontaneous synaptic activity recorded ex vivo from cortical tissue samples resected for the treatment of pharmacoresistant epilepsy. The cohort included 47 children (ages 0.22-9.99 yr) with focal cortical dysplasias (CD types I and II), tuberous sclerosis complex (TSC) and non-CD pathologies. Whole-cell patch clamp recordings were obtained from pyramidal neurons and interneurons in cortical regions that were positive or negative for pathological HFOs, defined as FR band oscillations (250-500 Hz) at ECoG. The frequency of spontaneous excitatory and inhibitory postsynaptic currents (sEPSCs and IPSCs, respectively) was compared between HFO+ and HFO- regions. Regardless of pathological substrate, regions positive for FRs displayed significantly increased frequencies of sIPSCs compared with regions negative for FRs. In contrast, the frequency of sEPSCs was similar in both regions. In about one third of cases (n = 17), pacemaker GABA synaptic activity (PGA) was observed. In the vast majority (n = 15), PGA occurred in HFO+ areas. Further, fast-spiking interneurons displayed signs of hyperexcitability exclusively in HFO+ areas. These results indicate that, in pediatric epilepsy patients, increased GABA synaptic activity is associated with interictal FRs in the epileptogenic zone and suggest an active role of GABAergic interneurons in the generation of pathological HFOs. Increased GABA synaptic activity could serve to dampen excessive excitability of cortical pyramidal neurons in the epileptogenic zone, but it could also promote neuronal network synchrony.

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.

Prospective observational study: Fast ripple localization delineates the epileptogenic zone

OBJECTIVE

To investigate spatial correlation between interictal HFOs and neuroimaging abnormalities, and to determine if complete removal of prospectively identified interictal HFOs correlates with post-surgical seizure-freedom.

METHODS

Interictal fast ripples (FRs: 250-500 Hz) in 19 consecutive children with pharmacoresistant focal epilepsy who underwent extra-operative electrocorticography (ECoG) recording were prospectively analyzed. The interictal FRs were sampled at 2000 Hz and were visually identified during 10 min of slow wave sleep. Interictal FRs, MRI and FDG-PET were delineated on patient-specific reconstructed three-dimensional brain MRI.

RESULTS

Interictal FRs were observed in all patients except one. Thirteen out of 18 patients (72%) exhibited FRs beyond the extent of neuroimaging abnormalities. Fifteen of 19 children underwent resective surgery, and survival analysis with log-rank test demonstrated that complete resection of cortical sites showing interictal FRs correlated with longer post-operative seizure-freedom (p < 0.01). Complete resection of seizure onset zones (SOZ) also correlated with longer post-operative seizure-freedom (p = 0.01), yet complete resection of neuroimaging abnormalities did not (p = 0.43).

CONCLUSIONS

Prospective visual analysis of interictal FRs was feasible, and it seemed to accurately localize epileptogenic zones.

SIGNIFICANCE

Topological extent of epileptogenic region may exceed what is discernible by multimodal neuroimaging.

Ripple-related firing of identified deep CA1 pyramidal cells in chronic temporal lobe epilepsy in mice

OBJECTIVE

Temporal lobe epilepsy (TLE) is often associated with memory deficits. Reactivation of memory traces in the hippocampus occurs during sharp-wave ripples (SWRs; 140-250 Hz). To better understand the mechanisms underlying high-frequency oscillations and cognitive comorbidities in epilepsy, we evaluated how rigorously identified deep CA1 pyramidal cells (dPCs) discharge during SWRs in control and TLE mice.

METHODS

We used the unilateral intraamygdala kainate model of TLE in video-electroencephalography (EEG) verified chronically epileptic adult mice. Local field potential and single-cell recordings were performed using juxtacellular recordings from awake control and TLE mice resting on a spherical treadmill, followed by post hoc identification of the recorded cells.

RESULTS

Hippocampal SWRs in TLE mice occurred with increased intraripple frequency compared to control mice. The frequency of SWR events was decreased, whereas the overall frequency of SWRs, interictal epileptiform discharges, and high-frequency ripples (250-500 Hz) together was not altered. CA1 dPCs in TLE mice showed significantly increased firing during ripples as well as between the ripple events. The strength of ripple modulation of dPC discharges increased in TLE without alteration of the preferred phase of firing during the ripple waves.

SIGNIFICANCE

These juxtacellular electrophysiology data obtained from identified CA1 dPCs from chronically epileptic mice are in general agreement with recent findings indicating distortion of normal firing patterns during offline SWRs as a mechanism underlying deficits in memory consolidation in epilepsy. Because the primary seizure focus in our experiments was in the amygdala and we recorded from the CA1 region, these results are also in agreement with the presence of altered high-frequency oscillations in areas of secondary seizure spread.

DC shifts, high frequency oscillations, ripples and fast ripples in relation to the seizure onset zone

Efforts to improve epilepsy surgery outcomes have led to increased interest in the study of electroencephalographic oscillations outside the conventional EEG bands. These include fast activity above the gamma band, known as high frequency oscillations (HFOs), and infraslow activity (ISA) below the delta band, sometimes referred to as direct current (DC) or ictal baseline shifts (IBS). HFOs in particular have been extensively studied as potential biomarkers for epileptogenic tissue in light of evidence showing that resection of brain tissue containing HFOs is associated with good surgical outcomes. Not all HFOs are conclusively pathological, however, as they can be recorded in nonepileptic tissue and induced by cognitive, visual, or motor tasks. Consequently, efforts to distinguish between pathological and physiological HFOs have identified several traits specific to pathological HFOs, such as coupling with interictal spikes, association with delta waves, and stereotypical morphologies. On the opposite end of the EEG spectrum, sub-delta oscillations have been shown to co-localize with the seizure onset zones (SOZ) and appear in a narrower spatial distribution than activity in the conventional EEG frequency bands. In this report, we review studies that implicate HFOs and ISA in ictogenesis and discuss current limitations such as inter-observer variability and poor standardization of recording techniques. Furthermore, we propose that HFOs and ISA should be analyzed in addition to activity in the conventional EEG band during intracranial presurgical EEG monitoring to identify the best possible surgical margin.

Interictal spike connectivity in human epileptic neocortex

OBJECTIVE

Interictal spikes are a biomarker of epilepsy, yet their precise roles are poorly understood. Using long-term neocortical recordings from epileptic patients, we investigated the spatial-temporal propagation patterns of interictal spiking.

METHODS

Interictal spikes were detected in 10 epileptic patients. Short time direct directed transfer function was used to map the spatial-temporal patterns of interictal spike onset and propagation across different cortical topographies.

RESULTS

Each patient had unique interictal spike propagation pattern that was highly consistent across times, regardless of the frequency band. High spiking brain regions were often not spike onset regions. We observed frequent spike propagations to shorter distances and that the central sulcus forms a strong barrier to spike propagation. Spike onset and seizure onset seemed to be distinct networks in most cases.

CONCLUSIONS

Patients in epilepsy have distinct and unique network of causal propagation pattern which are very consistent revealing the underlying epileptic network. Although spike are epileptic biomarkers, spike origin and seizure onset seems to be distinct in most cases.

SIGNIFICANCE

Understanding patterns of interictal spike propagation could lead to the identification patient-specific epileptic networks amenable to surgical or other treatments.

Multimodal localization and surgery for epileptic spasms of focal origin: a review

Epileptic spasms (ES) are a common manifestation of intractable epilepsy in early life and can lead to devastating neurodevelopmental consequences. Epilepsy surgery for ES is challenging because of inherent difficulties in localizing the epileptogenic zone in affected infants and children. However, recent clinical series of resective neurosurgery for ES suggest that not only is surgery a viable option for appropriately selected patients, but postoperative seizure outcomes can be similar to those achieved in other types of focal epilepsy. Increased awareness of ES as a potentially focal epilepsy, along with advances in neuroimaging and invasive monitoring technologies, have led to the ability to surgically treat many patients with ES who were previously not considered surgical candidates. In this study, the authors review the current state of epilepsy surgery for ES. Specifically, they address how advances in neuroimaging and invasive monitoring have facilitated patient selection, presurgical evaluation, and ultimately, resection planning.

Phase-amplitude coupling between interictal high-frequency activity and slow waves in epilepsy surgery

OBJECTIVE

We hypothesized that the modulation index (MI), a summary measure of the strength of phase-amplitude coupling between high-frequency activity (>150 Hz) and the phase of slow waves (3-4 Hz), would serve as a useful interictal biomarker for epilepsy presurgical evaluation.

METHODS

We investigated 123 patients who underwent focal cortical resection following extraoperative electrocorticography recording and had at least 1 year of postoperative follow-up. We examined whether consideration of MI would improve the prediction of postoperative seizure outcome. MI was measured at each intracranial electrode site during interictal slow-wave sleep. We compared the accuracy of prediction of patients achieving International League Against Epilepsy class 1 outcome between the full multivariate logistic regression model incorporating MI in addition to conventional clinical, seizure onset zone (SOZ), and neuroimaging variables, and the reduced logistic regression model incorporating all variables other than MI.

RESULTS

Ninety patients had class 1 outcome at the time of most recent follow-up (mean follow-up = 5.7 years). The full model had a noteworthy outcome predictive ability, as reflected by regression model fit R² of 0.409 and area under the curve (AUC) of receiver operating characteristic plot of 0.838. Incomplete resection of SOZ (P < 0.001), larger number of antiepileptic drugs at the time of surgery (P = 0.007), and larger MI in nonresected tissues relative to that in resected tissue (P = 0.020) were independently associated with a reduced probability of class 1 outcome. The reduced model had a lower predictive ability as reflected by R² of 0.266 and AUC of 0.767. Anatomical variability in MI existed among nonepileptic electrode sites, defined as those unaffected by magnetic resonance imaging lesion, SOZ, or interictal spike discharges. With MI adjusted for anatomical variability, the full model yielded the outcome predictive ability of R² of 0.422, AUC of 0.844, and sensitivity/specificity of 0.86/0.76.

SIGNIFICANCE

MI during interictal recording may provide useful information for the prediction of postoperative seizure outcome.

Magnetoencephalography: Clinical and Research Practices

Magnetoencephalography (MEG) is a neurophysiological technique that detects the magnetic fields associated with brain activity. Synthetic aperture magnetometry (SAM), a MEG magnetic source imaging technique, can be used to construct both detailed maps of global brain activity as well as virtual electrode signals, which provide information that is similar to invasive electrode recordings. This innovative approach has demonstrated utility in both clinical and research settings. For individuals with epilepsy, MEG provides valuable, nonredundant information. MEG accurately localizes the irritative zone associated with interictal spikes, often detecting epileptiform activity other methods cannot, and may give localizing information when other methods fail. These capabilities potentially greatly increase the population eligible for epilepsy surgery and improve planning for those undergoing surgery. MEG methods can be readily adapted to research settings, allowing noninvasive assessment of whole brain neurophysiological activity, with a theoretical spatial range down to submillimeter voxels, and in both humans and nonhuman primates. The combination of clinical and research activities with MEG offers a unique opportunity to advance translational research from bench to bedside and back.

Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

OBJECTIVE

Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking.

APPROACH

We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing.

MAIN RESULTS

Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators.

SIGNIFICANCE

Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically-observable EEG data, with a variety of straightforward computation methods available. This opens possibilities for systematic assessments of ictal discharge propagation in clinical and research settings.

Strong coupling between slow oscillations and wide fast ripples in children with epileptic spasms: Investigation of modulation index and occurrence rate

OBJECTIVE

Epileptic spasms (ES) often become drug-resistant. To reveal the electrophysiological difference between children with ES (ES+) and without ES (ES-), we compared the occurrence rate (OR) of high-frequency oscillations (HFOs) and the modulation index (MI) of coupling between slow and fast oscillations. In ES+, we hypothesized that (1) pathological HFOs are more widely distributed and (2) slow oscillations show stronger coupling with pathological HFOs than in ES-.

METHODS

We retrospectively reviewed 24 children with drug-resistant multilobar onset epilepsy, who underwent intracranial video electroencephalography prior to multilobar resections. We measured the OR of HFOs and determined the electrodes with a high rate of HFOs by cluster analysis. We calculated MI, which reflects the degree of coupling between HFO (ripple/fast ripple [FR]) amplitude and 5 different frequency bands of delta and theta activities (0.5-1 Hz, 1-2 Hz, 2-3 Hz, 3-4 Hz, 4-8 Hz).

RESULTS

In ES+ (n = 10), the OR_(FRs) , the number of electrodes with high-rate FRs, and the MI_{(FRs & 3-4 Hz)} in all electrodes were significantly higher than in ES- (n = 14). In both the ES+ and ES- groups, MI_{(ripples/FRs & 3-4 Hz)} was the highest among the 5 frequency bands. Within the good seizure outcome group, the OR_(FRs) and the MI_{(FRs & 3-4 Hz)} in the resected area in ES+ were significantly higher than in ES- (OR_[FRs] , P = .04; MI_{[FRs & 3-4 Hz]} , P = .04).

SIGNIFICANCE

In ES+, the larger number of high-rate FR electrodes indicates more widespread epileptogenicity than in ES-. High values of OR_(FRs) and MI_{(FRs & 3-4 Hz)} in ES+ compared to ES- are a signature of the severity of epileptogenicity. We proved that ES+ children who achieved seizure freedom following multilobar resections exhibited strong coupling between slow oscillations and FRs.

Anterior corpus callosotomy in patients with drug-resistant epilepsy: Invasive EEG findings and seizure outcomes

Corpus callosotomy (CC) is used in patients with drug-resistant seizures who are not candidates for excisional surgery and failed neurostimulation. We examined ictal scalp and intracranial electroencephalogram (iEEG) recordings in 16 patients being evaluated for anterior CC alone or CC in combination with focal resection, to determine the role of the iEEG in predicting postoperative seizure outcomes. In our cohort, CC improved generalized atonic seizures and focal seizures with impaired awareness but did not alter outcomes for generalized tonic–clonic or tonic seizures. Invasive EEG prior to CC did not refine the prediction of postsurgical seizure outcomes in patients with inconclusive scalp EEG.

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Patients with drug-resistant epilepsy achieved a significant reduction of generalized atonic and focal seizures with impaired awareness following corpus callosotomy.

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The age at epilepsy diagnosis or structural pathology identified on the imaging did not predict postoperative seizure status.

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The ictal findings on invasive EEG prior to corpus callosotomy improved lateralization of seizure onset but did not predict seizure outcomes.