Epileptic high‐frequency oscillations in intraoperative electrocorticography: The effect of propofol

Purpose: Epileptic high‐frequency oscillations (HFOs; 80–500 Hz) may be used to guide neurosurgeons during epilepsy surgery to identify epileptogenic tissue. We studied the effect of the anesthetic agent propofol on the occurrence of HFOs in intraoperative electrocorticography (ECoG). Methods: We selected patients who were undergoing surgery for temporal lobe epilepsy with a standardized electrode grid placement. Intraoperative ECoG was recorded at 2,048 Hz following cessation of propofol. The number and distribution of interictal spikes, ripples (R [80–250 Hz]), and fast ripples (FRs; 250–500 Hz) were analyzed. The amount of events on mesiotemporal channels and lateral neocortical channels were compared between patients with a suspected mesiotemporal and lateral epileptogenic area (Student’s t‐test), and HFOs were compared with the irritative zone, using correlation between amounts of events per channel, to provide evidence for the epileptic nature of the HFOs. Next, the amount of events within the first minute and the last minute were compared to each other and the change in events over the entire epochs was analyzed using correlation analyses of 10 epochs during the emergence periods (Spearman rank test). We studied whether the duration of HFOs changed over time. The change in events within presumed epileptogenic area was compared to the change outside this area (Student’s t‐test). Periods of burst suppression and continuous background activity were compared between and within patients (t‐test). Key Findings: Twelve patients were included: five with suspected mesiotemporal epileptogenic area and three with suspected lateral epileptogenic area (and four were “other”). Spikes, ripples, and FRs were related to the suspected epileptogenic areas, and HFO zones were related to the irritative zones. Ripples and FRs increased during emergence from propofol anesthesia (mean number of ripples from first minute–last minute: 61.5–73.0, R = 0.46, p < 0.01; FRs: 3.1–5.7, R = 0.30, p < 0.01) and spikes remained unchanged (80.1–79.9, R = ?0.05, p = 0.59). There was a decrease in number of channels with spikes (R = ?0.18, p = 0.05), but no change in ripples (R = ?0.13, p = 0.16) or FRs (R = 0.11, p = 0.45). There was no change in the durations of HFOs. The amount of HFOs in the presumed epileptogenic areas did not change more than the amount outside the presumed epileptogenic area, whereas spikes paradoxically decreased more within the suspected epileptogenic area. Six patients showing burst‐suppression had lower rates of ripples than six other patients with continuous background activity (p = 0.02). No significant difference was found between burst suppression and continuous background activity in four patients, but there was a trend toward showing more ripples during continuous background activity (p = 0.16). Significance: Propofol, known for its antiepileptic effects, reduces the number of epileptic HFOs, but has no effect on spikes. This enforces the hypothesis that, in epilepsy, HFOs mirror the disease activity and HFOs might be useful for monitoring antiepileptic drug treatment. It is feasible to record HFOs during surgery, but propofol infusion should be interrupted for some minutes to improve detection.     

High‐frequency oscillations: What is normal and what is not?

High-frequency oscillations (HFOs) in the 80–200 Hz range can be recorded from normal hippocampus and parahippocampal structures of humans and animals. They are believed to reflect inhibitory field potentials, which facilitate information transfer by synchronizing neuronal activity over long distances. HFOs in the range of 250–600 Hz (fast ripples, FRs) are pathologic and are readily recorded from hippocampus and parahippocampal structures of patients with mesial temporal lobe epilepsy, as well as rodent models of this disorder. These oscillations, and similar HFOs recorded from neocortex of patients, appear to identify brain tissue capable of spontaneous ictogenesis and are believed to reflect the neuronal substrates of epileptogenesis and epileptogenicity. The distinction between normal and pathologic HFOs (pHFOs), however, cannot be made on the basis of frequency alone, as oscillations in the FR frequency range can be recorded from some areas of normal neocortex, whereas oscillations in the ripple frequency range are present in epileptic dentate gyrus where normal ripples never occur and, therefore, appear to be pathologic. The suggestion that FRs may be harmonics of normal ripples is unlikely, because of their spatially distinct generators, and evidence that FRs reflect synchronized firing of abnormally bursting neurons rather than inhibitory field potentials. These synchronous population spikes, however, can fire at ripple frequencies, and their harmonics appear to give rise to FRs. Investigations into the fundamental neuronal processes responsible for pHFOs could provide insights into basic mechanisms of epilepsy. The potential for pHFOs to act as biomarkers for epileptogenesis and epileptogenicity is also discussed.     

In vivo ketogenic diet treatment attenuates pathologic sharp waves and high frequency oscillations in in vitro hippocampal slices from epileptic Kv1.1α knockout mice

The ketogenic diet (KD) is an effective therapy for pediatric refractory epilepsies; however, whether the KD changes the pathologic network oscillations generated by an epileptic brain remains unknown. We have reported that hippocampal CA3 regions of epileptic Kv1.1α knockout (KO) mice generate pathologic sharp waves (SPWs) and high‐frequency oscillations (HFOs) that have higher incidence, longer duration, and fast ripples compared to wild‐type (WT). Synaptic activity of hyperexcitable KO mossy fibers significantly decreased CA3 principal cell spike‐timing reliability, which contributed to this network pathology. In addition, we have demonstrated that the KD reduces seizures by 75% in KO mice. Here, we determined whether 10‐ to 14‐day in vivo KD treatment exerts disease‐modifying effects that alter the spontaneous SPW‐HFO complexes generated by the hippocampal CA3 region of KO mice in vitro using extracellular multielectrode array recordings. We found that KD treatment significantly attenuated the pathologic features of KO SPWs and ripples and reduced the incidence of fast ripples. The KD also improved spike‐timing reliability of KO CA3 principal cells, decreased mossy fiber excitability, increased mossy fiber‐CA3 paired‐pulse ratios, and reduced coupling of field excitatory postsynaptic potentials and population spikes in the CA3 region. Collectively, these data indicate that KD treatment modulates CA3‐generated pathologic oscillations by dampening hyperactive mossy fiber synapses. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here .     

High-frequency oscillations recorded with surface EEG in neonates with seizures

ObjectiveNeonatal seizures are often the first symptom of perinatal brain injury. High-frequency oscillations (HFOs) are promising new biomarkers for epileptogenic tissue and can be found in intracranial and surface EEG. To date, we cannot reliably predict which neonates with seizures will develop childhood epilepsy. We questioned whether epileptic HFOs can be generated by the neonatal brain and potentially predict epilepsy.MethodsWe selected 24 surface EEGs sampled at 2048 Hz with 175 seizures from 16 neonates and visually reviewed them for HFOs. Interictal epochs were also reviewed.ResultsWe found HFOs in thirteen seizures (7%) from four neonates (25%). 5025 ictal ripples (rate 10 to 1311/min; mean frequency 135 Hz; mean duration 66 ms) and 1427 fast ripples (rate 8 to 356/min; mean frequency 298 Hz; mean duration 25 ms) were marked. Two neonates (13%) showed interictal HFOs (285 ripples and 25 fast ripples). Almost all HFOs co-occurred with sharp transients. We could not find a relationship between neonatal HFOs and outcome yet.ConclusionsNeonatal HFOs co-occur with ictal and interictal sharp transients.SignificanceThe neonatal brain can generate epileptic ripples and fast ripples, particularly during seizures, though their occurrence is not common and potential clinical value not evident yet.     

Neurosteroids differentially modulate fast and slow interictal discharges in the hippocampal CA3 area

Two types of spontaneous interictal discharge, identified as fast and slow events, can be recorded from the hippocampal CA3 area in rat brain slices during application of 4‐aminopyridine (4AP) (50 μm ). Here, we addressed how neurosteroids modulate the occurrence of these interictal events and of the associated high‐frequency oscillations (HFOs) (ripples, 80–200 Hz; fast ripples, 250–500 Hz). Under control conditions (i.e. during 4AP application), ripples and fast ripples were detected in 12.3 and 17.5% of fast events, respectively; in contrast, the majority of slow events (> 98%) did not co‐occur with HFOs. Application of 0.1, 1 or 5 μm allotetrahydrodeoxycorticosterone (THDOC) to 4AP‐treated slices caused a dose‐dependent decrease in the duration of the fast events and an increase in the occurrence of ripples, but not fast ripples; in contrast, the duration of slow events increased. THDOC potentiated the slow events that were recorded during pharmacological blockade of glutamatergic transmission, but had no effect on interictal discharges occurring during GABA_A receptor antagonism. These results demonstrate that potentiation of GABA_A receptor‐mediated signaling by THDOC differentially affects slow and fast interictal discharges; these differences may provide insights into how hyperexcitable activity is influenced by neurosteroids.     

Spontaneous and evoked high-frequency oscillations in the tetanus toxin model of epilepsy

Purpose: High‐frequency oscillations (HFOs) are an emerging biomarker for epileptic tissue. Yet the mechanism by which HFOs are produced is unknown, and their rarity makes them difficult to study. Our objective was to examine the occurrence of HFOs in relation to action potentials (APs) and the effect of microstimulation in the tetanus toxin (TT) model of epilepsy, a nonlesional model with a short latency to spontaneous seizures. Methods: Rats were injected with TT into dorsal hippocampus and implanted with a 16‐channel (8 × 2) multielectrode array, one row each in CA3 and CA1. After onset of spontaneous seizures (3–9 days), recordings were begun of APs and local field potentials, analyzed for the occurrence of interictal spikes and HFOs. Recordings were made during microstimulation of each electrode using customized, open‐source software. Results: Population bursts of APs during interictal spikes were phase‐locked with HFOs, which were observable almost exclusively with high‐amplitude interictal spikes. Furthermore, HFOs could reliably be produced by microstimulation of the hippocampus, providing evidence that these oscillations can be controlled temporally by external means. Discussion: We show for the first time the occurrence of HFOs in the TT epilepsy model, an attractive preparation for their experimental investigation and, importantly, one with a different etiology than that of status models, providing further evidence of the generality of HFOs. The ability to provoke HFOs with microstimulation may prove useful for better understanding of HFOs by directly evoking them in the lab, and designing high‐throughput techniques for presurgical localization of the epileptic focus.     

Update on the mechanisms and roles of high‐frequency oscillations in seizures and epileptic disorders

High‐frequency oscillations (HFOs) are a type of brain activity that is recorded from brain regions capable of generating seizures. Because of the close association of HFOs with epileptogenic tissue and ictogenesis, understanding their cellular and network mechanisms could provide valuable information about the organization of epileptogenic networks and how seizures emerge from the abnormal activity of these networks. In this review, we summarize the most recent advances in the field of HFOs and provide a critical evaluation of new observations within the context of already established knowledge. Recent improvements in recording technology and the introduction of optogenetics into epilepsy research have intensified experimental work on HFOs. Using advanced computer models, new cellular substrates of epileptic HFOs were identified and the role of specific neuronal subtypes in HFO genesis was determined. Traditionally, the pathogenesis of HFOs was explored mainly in patients with temporal lobe epilepsy and in animal models mimicking this condition. HFOs have also been reported to occur in other epileptic disorders and models such as neocortical epilepsy, genetically determined epilepsies, and infantile spasms, which further support the significance of HFOs in the pathophysiology of epilepsy. It is increasingly recognized that HFOs are generated by multiple mechanisms at both the cellular and network levels. Future studies on HFOs combining novel high‐resolution in vivo imaging techniques and precise control of neuronal behavior using optogenetics or chemogenetics will provide evidence about the causal role of HFOs in seizures and epileptogenesis. Detailed understanding of the pathophysiology of HFOs will propel better HFO classification and increase their information yield for clinical and diagnostic purposes.     

Scalp‐recorded high‐frequency oscillations in childhood sleep‐induced electrical status epilepticus

Because high‐frequency oscillations (HFOs) may affect normal brain functions, we examined them using electroencephalography (EEG) in epilepsy with continuous spike‐waves during slow‐wave sleep (CSWS), a condition that can cause neuropsychological regression. In 10 children between 6 and 9 years of age with epilepsy with CSWS or related disorders, we investigated HFOs in scalp EEG spikes during slow‐wave sleep through temporal expansion of the EEG traces with a low‐cut frequency filter at 70 Hz as well as through time‐frequency power spectral analysis. HFOs (ripples) concurrent with spikes were detected in the temporally expanded traces, and the frequency of the high‐frequency peak with the greatest power in each patient’s spectra ranged from 97.7 to 140.6 Hz. This is the first report on the detection of HFOs from scalp EEG recordings in epileptic patients. We speculate that epileptic HFOs may interfere with higher brain functions in epilepsy with CSWS.     

Differentiation of specific ripple patterns helps to identify epileptogenic areas for surgical procedures

ObjectiveHigh frequency oscillations (HFOs) at 80–500 Hz are promising markers of epileptic areas. Several retrospective studies reported that surgical removal of areas generating HFOs was associated with a good seizure outcome. Recent reports suggested that ripple (80–200 Hz) HFO patterns co-existed with different background EEG activities. We hypothesized that the coexisting background EEG pattern may distinguish physiological from epileptic ripples.MethodsRates of HFOs were analyzed in intracranial EEG recordings of 22 patients. Additionally, ripple patterns were classified for each channel depending either as coexisting with a flat or oscillatory background activity. A multi-variate analysis was performed to determine whether removal of areas showing the above EEG markers correlated with seizure outcome.ResultsRemoval of areas generating high rates of ‘fast ripples (>200 Hz)’ and ‘ripples on a flat background activity’ showed a significant correlation with a seizure-free outcome. In contrast, removal of high rates of ‘ripples’ or ‘ripple patterns in a continuously oscillating background’ was not significantly associated with seizure outcome.ConclusionRipples occurring in an oscillatory background activity may be suggestive of physiological activity, while those on a flat background reflect epileptic activity.SignificanceConsideration of coexisting background patterns may improve the delineation of the epileptogenic areas using ripple oscillations.     

Redaction of false high frequency oscillations due to muscle artifact improves specificity to epileptic tissue

ObjectiveHigh Frequency Oscillations (HFOs) are a promising biomarker of epilepsy. HFOs are typically acquired on intracranial electrodes, but contamination from muscle artifacts is still problematic in HFO analysis. This paper evaluates the effect of myogenic artifacts on intracranial HFO detection and how to remove them.MethodsIntracranial EEG was recorded in 31 patients. HFOs were detected for the entire recording using an automated algorithm. When available, simultaneous scalp EEG was used to identify periods of muscle artifact. Those markings were used to train an automated scalp EMG detector and an intracranial EMG detector. Specificity to epileptic tissue was evaluated by comparison with seizure onset zone and resected volume in patients with good outcome.ResultsEMG artifacts are frequent and produce large numbers of false HFOs, especially in the anterior temporal lobe. The scalp and intracranial EMG detectors both had high accuracy. Removing false HFOs improved specificity to epileptic tissue.ConclusionsEvaluation of HFOs requires accounting for the effect of muscle artifact. We present two tools that effectively mitigate the effect of muscle artifact on HFOs.SignificanceRemoving muscle artifacts improves the specificity of HFOs to epileptic tissue. Future HFO work should account for this effect, especially when using automated algorithms or when scalp electrodes are not present.     

Pitfalls of high-pass filtering for detecting epileptic oscillations: A technical note on “false” ripples

ObjectivesTo analyze interictal High frequency oscillations (HFOs) as observed in the medial temporal lobe of epileptic patients and animals (ripples, 80–200 Hz and fast ripples, 250–600 Hz). To show that the identification of interictal HFOs raises some methodological issues, as the filtering of sharp transients (e.g., epileptic spikes or artefacts) or signals with harmonics can result in “false” ripples. To illustrate and quantify the occurrence of false ripples on filtered EEG traces.MethodsWe have performed high-pass filtering on both simulated and real data. We have also used two alternate methods: time-frequency analysis and matching pursuit.ResultsTwo types of events were shown to produce oscillations after filtering that could be confounded with actual oscillatory activity: sharp transients and harmonics of non-sinusoidal signals.ConclusionsHigh-pass filtering of EEG traces for detection of oscillatory activity should be performed with great care. Filtered traces should be compared to original traces for verification of presence of transients. Additional techniques such as time-frequency transforms or sparse decompositions are highly beneficial.SignificanceOur study draws the attention on an issue of great importance in the marking of HFOs on EEG traces. We illustrate complementary methods that can help both researchers and clinicians.     

Dynamic changes of ictal high-frequency oscillations in neocortical epilepsy: using multiple band frequency analysis

PURPOSE: To characterize the spatial and temporal course of ictal high-frequency oscillations (HFOs) recorded by subdural EEG in children with intractable neocortical epilepsy. METHODS: We retrospectively studied nine children (four girls, five boys; 4-17 yr) who presented with intractable extrahippocampal localization-related epilepsy and who underwent extraoperative video subdural EEG (1000 Hz sampling rate) and cortical resection. We performed multiple band frequency analysis (MBFA) to evaluate the frequency, time course, and distribution of ictal HFOs. We compared ictal HFO changes before and after clinical onset and postsurgical seizure outcomes. RESULTS: Seventy-eight of 79 seizures showed HFOs. We observed wide-band HFOs ( approximately 250 Hz, approximately 120 electrodes) in six patients either with partial seizures alone (three patients) or with epileptic spasms (three patients). Three patients with partial seizures that secondarily generalized had wide-band HFOs ( approximately 170 Hz) before clinical onset and sustained narrow-band HFOs (60-164 Hz) with electrodecremental events after clinical onset ( approximately 28 electrodes). In four postoperatively seizure-free patients, more electrodes recorded higher-frequency HFOs inside the resection area than outside before and after clinical seizure onset. In five patients with residual seizures, electrodes recorded more HFOs that were of higher or equal frequency outside the surgical area than inside after clinical onset. CONCLUSION: For partial seizures alone and epileptic spasms, more electrodes recorded only wide-band HFOs; for partial seizures that secondarily generalized, fewer electrodes recorded wide-band HFOs, but in these seizures electrodes also recorded subsequent sustained narrow-band ictal HFOs. Resection of those brain regions having electrodes with ictal, higher HFOs resulted in postsurgical seizure-free outcomes.     

High-frequency (80-500 Hz) oscillations and epileptogenesis in temporal lobe epilepsy

High-frequency oscillations (HFOs), termed ripples (80-200 Hz) and fast ripples (250-600 Hz), are recorded in the EEG of epileptic patients and in animal epilepsy models; HFOs are thought to reflect pathological activity and seizure onset zones. Here, we analyzed the temporal and spatial evolution of interictal spikes with and without HFOs in the rat pilocarpine model of temporal lobe epilepsy. Depth electrode recordings from dentate gyrus (DG), CA3 region, subiculum and entorhinal cortex (EC), were obtained from rats between the 4th and 15th day after a status epilepticus (SE) induced by i.p. injection of pilocarpine. The first seizure occurred 6.1 ± 2.5 days after SE (n = 7 rats). Five of 7 animals exhibited interictal spikes that co-occurred with fast ripples accounting for 4.9 ± 4.6% of all analyzed interictal spikes (n = 12,886) while all rats showed interictal spikes co-occurring with ripples, accounting for 14.3 ± 3.4% of all events. Increased rates of interictal spikes without HFOs in the EC predicted upcoming seizures on the following day, while rates of interictal spikes with fast ripples in CA3 reflected periods of high seizure occurrence. Finally, interictal spikes co-occurring with ripples did not show any specific relation to seizure occurrence. Our findings identify different temporal and spatial developmental patterns for the rates of interictal spikes with or without HFOs in relation with seizure occurrence. These distinct categories of interictal spikes point at dynamic processes that should bring neuronal networks close to seizure generation.     

Value of electrical stimulation and high frequency oscillations (80–500 Hz) in identifying epileptogenic areas during intracranial EEG recordings

Purpose: Electrical stimulation (ES) is used during intracranial electroencephalography (EEG) investigations to delineate epileptogenic areas and seizure‐onset zones (SOZs) by provoking afterdischarges (ADs) or patients’ typical seizure. High frequency oscillations (HFOs—ripples, 80–250 Hz; fast ripples, 250–500 Hz) are linked to seizure onset. This study investigates whether interictal HFOs are more frequent in areas with a low threshold to provoke ADs or seizures. Methods: Intracranial EEG studies were filtered at 500 Hz and sampled at 2,000 Hz. HFOs were visually identified. Twenty patients underwent ES, with gradually increasing currents. Results were interpreted as agreeing or disagreeing with the intracranial study (clinical‐EEG seizure onset defined the SOZ). Current thresholds provoking an AD or seizure were correlated with the rate of HFOs of each channel. Results: ES provoked a seizure in 12 and ADs in 19 patients. Sixteen patients showed an ES response inside the SOZ, and 10 had additional areas with ADs. The response was more specific for mesiotemporal than for neocortical channels. HFO rates were negatively correlated with thresholds for ES responses; especially in neocortical regions; areas with low threshold and high HFO rate were colocalized even outside the SOZ. Discussion: Areas showing epileptic HFOs colocalize with those reacting to ES. HFOs may represent a pathologic correlate of regions showing an ES response; both phenomena suggest a more widespread epileptogenicity.     

On the ictogenic properties of the piriform cortex in vitro

Purpose: The piriform cortex (PC) is known to be epileptic‐prone and it may be involved in the manifestation of limbic seizures. Herein, we have characterized some electrophysiologic and pharmacologic properties of the spontaneous epileptiform activity generated by PC networks maintained in vitro. Methods: We performed field potential recordings from the PC in coronal or sagittal rat brain slices along with pharmacologic manipulations of γ‐aminobutyric acid (GABA)ergic and glutamatergic signaling during application of the convulsant drug 4‐aminopyridine (4AP, 50 μm ). Key Findings: Coronal and sagittal preparations generated interictal‐like and ictal‐like epileptiform discharges with similar duration and frequency. Ictal‐like discharges in sagittal slices were initiated mostly in the PC anterior subregion, whereas interictal activity did not have any preferential site of origin. In sagittal slices, high frequency oscillations (HFOs) at 80–200 Hz were detected mainly at the beginning of the ictal discharge in both posterior and anterior subregions. N‐Methyl‐d ‐aspartate (NMDA) receptor antagonism abolished ictal discharges, but failed to influence interictal activity. In the absence of ionotropic glutamatergic transmission, PC networks generated slow, GABA receptor–dependent events. Finally, GABA_A receptor antagonism during application of 4AP only, abolished ictal discharges and disclosed recurrent interictal activity. Significance: Our findings demonstrate that PC networks can sustain in vitro epileptiform activity induced by 4AP. HFOs, which emerge at the onset of ictal activity, may be involved in PC ictogenesis. As reported in several cortical structures, ionotropic glutamatergic neurotransmission is necessary but not sufficient for ictal discharge generation, a process that also requires operative GABA_A receptor–mediated signaling.     

High frequency oscillations in intra-operative electrocorticography before and after epilepsy surgery

ObjectiveRemoval of brain tissue showing high frequency oscillations (HFOs; ripples: 80–250 Hz and fast ripples: 250–500 Hz) in preresection electrocorticography (preECoG) in epilepsy patients seems a predictor of good surgical outcome. We analyzed occurrence and localization of HFOs in intra-operative preECoG and postresection electrocorticography (postECoG).MethodsHFOs were automatically detected in one-minute epochs of intra-operative ECoG sampled at 2048 Hz of fourteen patients. Ripple, fast ripple, spike, ripples on a spike (RoS) and not on a spike (RnoS) rates were analyzed in pre- and postECoG for resected and nonresected electrodes.ResultsRipple, spike and fast ripple rates decreased after resection. RnoS decreased less than RoS (74% vs. 83%; p = 0.01). Most fast ripples in preECoG were located in resected tissue. PostECoG fast ripples occurred in one patient with poor outcome. Patients with good outcome had relatively high postECoG RnoS rates, specifically in the sensorimotor cortex.ConclusionsOur observations show that fast ripples in intra-operative ECoG, compared to ripples, may be a better biomarker for epileptogenicity. Further studies have to determine the relation between resection of epileptogenic tissue and physiological ripples generated by the sensorimotor cortex.SignificanceFast ripples in intra-operative ECoG can help identify the epileptogenic zone, while ripples might also be physiological.     

Gap junction networks can generate both ripple‐like and fast ripple‐like oscillations

Fast ripples (FRs) are network oscillations, defined variously as having frequencies of > 150 to > 250 Hz, with a controversial mechanism. FRs appear to indicate a propensity of cortical tissue to originate seizures. Here, we demonstrate field oscillations, at up to 400 Hz, in spontaneously epileptic human cortical tissue in vitro, and present a network model that could explain FRs themselves, and their relation to ‘ordinary’ (slower) ripples. We performed network simulations with model pyramidal neurons, having axons electrically coupled. Ripples (< 250 Hz) were favored when conduction of action potentials, axon to axon, was reliable. Whereas ripple population activity was periodic, firing of individual axons varied in relative phase. A switch from ripples to FRs took place when an ectopic spike occurred in a cell coupled to another cell, itself multiply coupled to others. Propagation could then start in one direction only, a condition suitable for re‐entry. The resulting oscillations were > 250 Hz, were sustained or interrupted, and had little jitter in the firing of individual axons. The form of model FR was similar to spontaneously occurring FRs in excised human epileptic tissue. In vitro, FRs were suppressed by a gap junction blocker. Our data suggest that a given network can produce ripples, FRs, or both, via gap junctions, and that FRs are favored by clusters of axonal gap junctions. If axonal gap junctions indeed occur in epileptic tissue, and are mediated by connexin 26 (recently shown to mediate coupling between immature neocortical pyramidal cells), then this prediction is testable.     

High‐frequency oscillations in idiopathic partial epilepsy of childhood

Purpose: We explored high‐frequency oscillations (HFOs) in scalp sleep electroencephalography (EEG) studies of patients with idiopathic partial epilepsy (IPE) of childhood in order to obtain a better understanding of the pathologic mechanisms underlying IPE. Methods: The subjects were 45 patients, including 32 with benign childhood epilepsy with centrotemporal spikes (BCECTS) and 13 with Panayiotopoulos syndrome (PS). A total of 136 EEG records were investigated through temporal expansion and filtering of traces and time‐frequency spectral analysis. Key Findings: HFOs with frequency of 93.8–152.3 Hz (mean 126.2 ± 13.6 Hz) in the band of ripples were detected in association with spikes in 97 records (71.3%). Time from last seizure to the EEG recording was significantly shorter in those with spike‐related HFOs than in the EEG recordings with spikes without HFOs (p = 0.006). Although time from last seizure reflects age, age at the time of recording was not significantly different between EEG studies with and without HFOs. Peak‐power values of the high‐frequency spots in time‐frequency spectra were significantly negatively correlated with time from last seizure (R² = 0.122, p < 0.001) but not with age at the time of recording. Peak frequencies of the high‐frequency spectral spots were not significantly correlated with age at the time of recording or with time from last seizure. Significance: The close relationship between the generation of spike‐related HFOs and the period of active seizure occurrence indicated that HFOs may tell us more about epileptogenicity in IPE than the spikes themselves. Because there is a spectrum of pediatric epileptic disorders extending from the benign end of BCECTS to the encephalopathic end of epilepsy with continuous spike‐waves during slow‐wave sleep (CSWS), and HFOs that have already been detected in association with CSWS were more prominent than HFOs in IPE, intense spike‐related HFOs may indicate poor prognosis.     

Focal resection of fast ripples on extraoperative intracranial EEG improves seizure outcome in pediatric epilepsy

Purpose: High‐frequency oscillations (HFOs), termed ripples at 80–200 Hz and fast ripples (FRs) at >200/250 Hz, recorded by intracranial electroencephalography (EEG), may be a valuable surrogate marker for the localization of the epileptogenic zone. We evaluated the relationship of the resection of focal brain regions containing high‐rate interictal HFOs and the seizure‐onset zone (SOZ) determined by visual EEG analysis with the postsurgical seizure outcome, using extraoperative intracranial EEG monitoring in pediatric patients and automated HFO detection. Methods: We retrospectively analyzed 28 pediatric epilepsy patients who underwent extraoperative intracranial video‐EEG monitoring prior to focal resection. Utilizing the automated analysis, we identified interictal HFOs during 20 min of sleep EEG and determined the brain regions containing high‐rate HFOs. We investigated spatial relationships between regions with high‐rate HFOs and SOZs. We compared the size of these regions, the surgical resection, and the amount of the regions with high‐rate HFOs/SOZs within the resection area with seizure outcome. Key Findings: Ten patients were completely seizure‐free and 18 were not at 2 years after surgery. The brain regions with high‐rate ripples were larger than those with high‐rate FRs (p = 0.0011) with partial overlap. More complete resection of the regions with high‐rate FRs significantly correlated with a better seizure outcome (p = 0.046). More complete resection of the regions with high‐rate ripples tended to improve seizure outcome (p = 0.091); however, the resection of SOZ did not influence seizure outcome (p = 0.18). The size of surgical resection was not associated with seizure outcome (p = 0.22–0.39). Significance: The interictal high‐rate FRs are a possible surrogate marker of the epileptogenic zone. Interictal ripples are not as specific a marker of the epileptogenic zone as interictal FRs. Resection of the brain regions with high‐rate interictal FRs in addition to the SOZ may achieve a better seizure outcome.     

Interictal high frequency oscillations (HFOs) in patients with focal epilepsy and normal MRI

Objective

We aim to analysis the relationship between HFOs-generating regions and the seizure onset zone (SOZ) in epileptic patients without a visible lesion on MRI.

Methods

Intracerebral EEGs were recorded in 17 patients with intractable focal seizures and normal MRIs. The rates of interictal HFOs and spikes inside and outside the SOZ were analyzed as well as the specificity, sensitivity and accuracy of HFOs and spikes to determine the SOZ.

Results

The mean rate of spikes, ripples and fast ripples (FR) was higher in the SOZ than in the non-SOZ channels. In regard to the identification of the SOZ the sensitivity was 91% for spikes, 91% for ripples and 66% for FR, the specificity was 30% for spikes, 42% for ripples and 80% for FR, and the accuracy was 44% for spikes, 54% for ripples and 76% for FR.

Conclusions

The rates of spikes and HFOs were higher inside than outside the SOZ. However, HFOs are also more specific and accurate than spikes to delineate the SOZ.

Significance

Analysis of interictal HFOs during 5-10 min of sleep recording is a good tool to localize the SOZ in patients with epilepsy and normal MRI, and could potentially reduce the duration of chronic intracerebral EEG recordings.