High frequency oscillations (80–500 Hz) in the preictal period in patients with focal seizures

Purpose:   Intracranial depth macroelectrode recordings from patients with focal seizures demonstrate interictal and ictal high frequency oscillations (HFOs, 80–500 Hz). These HFOs are more frequent in the seizure-onset zone (SOZ) and reported to be linked to seizure genesis. We evaluated whether HFO activity changes in a systematic way during the preictal period.
Methods:   Fifteen minutes of preictal intracranial electroencephalography (EEG) recordings were evaluated in seven consecutive patients with well-defined SOZ. EEG was filtered at 500 Hz and sampled at 2,000 Hz. Ripples (80–250 Hz) and fast ripples (250–500 Hz) were visually marked, and spectral analysis was performed in seizure-onset as well as nonseizure-onset channels. Linear regressions fitted to the power trends corresponding to intervals of 1, 5, and 15 min before the seizure onset was calculated.
Results:   Total rates of HFOs were significantly higher in the SOZ than outside. Preictal increases and decreases in HFO rates and band power could be detected in all patients, and they were not limited to the SOZs. These measures were very variable, and no systematic trends were observed when comparing patients or seizures in the same patient.
Discussion:   High frequencies in the range of 80–500 Hz are present during the preictal period and are more prominent in the SOZ. They do not change in a systematic way before seizure onset for the horizons we tested. The 80–500 Hz band may be used for the localization of seizure-onset areas but may be more difficult to use for seizure prediction purposes.     

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 (80-500 Hz) are an indicator of seizure onset areas independent of spikes in the human epileptic brain

Purpose: High‐frequency oscillations (HFOs) known as ripples (80–250 Hz) and fast ripples (250–500 Hz) can be recorded from macroelectrodes inserted in patients with intractable focal epilepsy. They are most likely linked to epileptogenesis and have been found in the seizure onset zone (SOZ) of human ictal and interictal recordings. HFOs occur frequently at the time of interictal spikes, but were also found independently. This study analyses the relationship between spikes and HFOs and the occurrence of HFOs in nonspiking channels. Methods: Intracerebral EEGs of 10 patients with intractable focal epilepsy were studied using macroelectrodes. Rates of HFOs within and outside spikes, the overlap between events, event durations, and the percentage of spikes carrying HFOs were calculated and compared according to anatomical localization, spiking activity, and relationship to the SOZ. Results: HFOs were found in all patients, significantly more within mesial temporal lobe structures than in neocortex. HFOs could be seen in spiking as well as nonspiking channels in all structures. Rates and durations of HFOs were significantly higher in the SOZ than outside. It was possible to establish a rate of HFOs to identify the SOZ with better sensitivity and specificity than with the rate of spikes. Discussion: HFOs occurred to a large extent independently of spikes. They are most frequent in mesial temporal structures. They are prominent in the SOZ and provide additional information on epileptogenicity independently of spikes. It was possible to identify the SOZ with a high specificity by looking at only 10 min of HFO activity.     

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

ObjectiveHigh frequency oscillations (HFO) between 80–500 Hz are markers of epileptic areas in intracranial and maybe also scalp EEG. We investigate simultaneous recordings of scalp and intracranial EEG and hypothesize that scalp HFOs provide important additional clinical information in the presurgical setting.MethodsSpikes and HFOs were visually identified in all intracranial scalp EEG channels. Analysis of correlation of event location between intracranial and scalp EEG as well as relationship between events and the SOZ and zone of surgical removal was performed.Results24 patients could be included, 23 showed spikes and 19 HFOs on scalp recordings. In 15/19 patients highest scalp HFO rate was located over the implantation side, with 13 patients having the highest scalp and intracranial HFO rate over the same region. 17 patients underwent surgery, 7 became seizure free. Patients with poor post-operative outcome showed significantly more regions with HFO than those with seizure free outcome.ConclusionsScalp HFOs are mostly located over the SOZ. Widespread scalp HFOs are indicative of a larger epileptic network and associated with poor postsurgical outcome.SignificanceAnalysis of scalp HFO add clinically important information about the extent of epileptic areas during presurgical simultaneous scalp and intracranial EEG recordings.     

Interictal high‐frequency oscillations (HFOs) as predictors of high frequency and conventional seizure onset zones

We investigated the relationship between the interictal high‐frequency oscillations (HFOs) and the seizure onset zones (SOZs) defined by the ictal HFOs or conventional frequency activity (CFA), and evaluated the usefulness of the interictal HFOs as spatial markers of the SOZs. We analysed seizures showing discrete HFOs at onset on intracranial EEGs acquired at ≥1000‐Hz sampling rate in a training cohort of 10 patients with temporal and extratemporal epilepsy. We classified each ictal channel as: HFO+ (HFOs at onset with subsequent evolution), HFO‐ (HFOs at onset without evolution), CFA (1.6–70‐Hz activity at onset with evolution), or non‐ictal. We defined the SOZs as: hSOZ (HFO+ channels only), hfo+&‐SOZ (HFO+ and HFO‐ channels), and cSOZ (CFA channels). Using automated methods, we detected the interictal HFOs and extracted five features: density, connectivity, peak frequency, log power, and amplitude. We created logistic regression models using these features, and tested their performance in a separate replication cohort of three patients. The models containing the five interictal HFO features reliably differentiated the channels located inside the SOZ from those outside in the training cohort (p<0.001), reaching the highest accuracy for the classification of hSOZ. Log power and connectivity had the highest odds ratios, both being higher for the channels inside the SOZ compared with those outside the SOZ. In the replication cohort of novel patients, the same models differentiated the HFO+ from HFO‐ channels, and predicted the extents of the hSOZ and hfo+&‐SOZ (F1 measure >0.5) but not the cSOZ. Our study shows that the interictal HFOs are useful in defining the spatial extent of the SOZ, and predicting whether or not a given channel in a novel patient would be involved in the seizure. The findings support the existence of an abnormal network of tightly‐linked ictal and interictal HFOs in patients with intractable epilepsy.     

Topographic movie of ictal high-frequency oscillations on the brain surface using subdural EEG in neocortical epilepsy

PURPOSE: To understand the rapid dynamic changes of ictal intracranial high-frequency oscillations (HFOs) in neocortical epilepsy. METHODS: We integrated multiple band frequency analysis and brain-surface topographic maps of HFOs from ictal subdural EEG (SDEEG) recordings. We used SDEEG to record partial seizures consisting of right-arm jerks with secondary generalization in a 17-year-old right-handed girl. We selected 20-s EEG sections that included preclinical seizure recordings. We averaged the HFO power between 60 and 120 Hz for 25 selected electrodes, made topographic maps from these averaged powers, and superimposed the maps on the brain-surface image. We filmed consecutive HFO maps at a 10-ms frame rate. RESULTS: Before clinical seizure onset, high-power HFOs emerged at the superior portion of the left precentral gyrus, then appeared in the middle of the left postcentral gyrus, and subsequently reverberated between both regions as well as the posterior portion of the left postcentral gyrus. Right-arm extension and facial grimacing started as the HFO power decreased. As generalized tonic-clonic seizures evolved, HFO power increased but remained within the central region. CONCLUSIONS: Topographic movies of intracranial HFOs on the brain surface allow visualization of the dynamic ictal changes in neocortical epilepsy.     

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.     

Resection of ictal high-frequency oscillations leads to favorable surgical outcome in pediatric epilepsy

Purpose: Intracranial electroencephalography (EEG) is performed as part of an epilepsy surgery evaluation when noninvasive tests are incongruent or the putative seizure‐onset zone is near eloquent cortex. Determining the seizure‐onset zone using intracranial EEG has been conventionally based on identification of specific ictal patterns with visual inspection. High‐frequency oscillations (HFOs, >80 Hz) have been recognized recently as highly correlated with the epileptogenic zone. However, HFOs can be difficult to detect because of their low amplitude. Therefore, the prevalence of ictal HFOs and their role in localization of epileptogenic zone on intracranial EEG are unknown. Methods: We identified 48 patients who underwent surgical treatment after the surgical evaluation with intracranial EEG, and 44 patients met criteria for this retrospective study. Results were not used in surgical decision making. Intracranial EEG recordings were collected with a sampling rate of 2,000 Hz. Recordings were first inspected visually to determine ictal onset and then analyzed further with time‐frequency analysis. Forty‐one (93%) of 44 patients had ictal HFOs determined with time‐frequency analysis of intracranial EEG. Key Findings: Twenty‐two (54%) of the 41 patients with ictal HFOs had complete resection of HFO regions, regardless of frequency bands. Complete resection of HFOs (n = 22) resulted in a seizure‐free outcome in 18 (82%) of 22 patients, significantly higher than the seizure‐free outcome with incomplete HFO resection (4/19, 21%). Significance: Our study shows that ictal HFOs are commonly found with intracranial EEG in our population largely of children with cortical dysplasia, and have localizing value. The use of ictal HFOs may add more promising information compared to interictal HFOs because of the evidence of ictal propagation and followed by clinical aspect of seizures. Complete resection of HFOs is a favorable prognostic indicator for surgical outcome.     

Ripple classification helps to localize the seizure‐onset zone in neocortical epilepsy

Purpose: Fast ripples are reported to be highly localizing to the epileptogenic or seizure‐onset zone (SOZ) but may not be readily found in neocortical epilepsy, whereas ripples are insufficiently localizing. Herein we classified interictal neocortical ripples by associated characteristics to identify a subtype that may help to localize the SOZ in neocortical epilepsy. We hypothesize that ripples associated with an interictal epileptiform discharge (IED) are more pathologic, since the IED is not a normal physiologic event. Methods: We studied 35 patients with epilepsy with neocortical epilepsy who underwent invasive electroencephalography (EEG) evaluation by stereotactic EEG (SEEG) or subdural grid electrodes. Interictal fast ripples and ripples were visually marked during slow‐wave sleep lasting 10–30 min. Neocortical ripples were classified as type I when superimposed on epileptiform discharges such as paroxysmal fast, spike, or sharp wave, and as type II when independent of epileptiform discharges. Key Findings: In 21 patients with a defined SOZ, neocortical fast ripples were detected in the SOZ of only four patients. Type I ripples were detected in 14 cases almost exclusively in the SOZ or primary propagation area (PP) and marked the SOZ with higher specificity than interictal spikes. In contrast, type II ripples were not correlated with the SOZ. In 14 patients with two or more presumed SOZs or nonlocalizable onset pattern, type I but not type II ripples also occurred in the SOZs. We found the areas with only type II ripples outside of the SOZ (type II‐O ripples) in SEEG that localized to the primary motor cortex and primary visual cortex. Significance: Neocortical fast ripples and type I ripples are specific markers of the SOZ, whereas type II ripples are not. Type I ripples are found more readily than fast ripples in human neocortical epilepsy. Type II‐O ripples may represent spontaneous physiologic ripples in the human neocortex.     

Graph index complexity as a novel surrogate marker of high frequency oscillations in delineating the seizure onset zone

ObjectiveTo investigate the Graph Index Complexity (uGIC) as a marker of high frequency oscillatory (HFO) activity, the seizure onset zone (SOZ), and surgical outcome.MethodsThe SOZ, rates of HFOs at two thresholds (broad, strict), and uGIC were determined using EEG data from 41 patients. The correlation between HFOs and uGIC were calculated. HFOs and uGIC were compared within and outside the SOZ. Postsurgical outcome was compared to the colocalization of HFOs and resected SOZ.ResultsThere was significant correlation between uGIC and both broad (r = 0.69, p < 0.0005) and strict HFOs (r = 0.48, p < 0.0005). All were significantly greater within the SOZ overall, but only in 17/41 (strict, uGIC) or 18/41 (broad) patients. HFO markers were significantly greater within the SOZ for 8/15 patients with positive postsurgical outcomes, but not for any patients with negative outcomes (0/5).ConclusionThe uGIC is a marker of HFO activity, while HFOs and uGIC are markers of the SOZ overall. Colocalization of HFOs and the SOZ has strong positive predictive value for postsurgical outcome, but poor negative predictive value.SignificanceThe uGIC is an objective surrogate marker of HFO activity independent of identifying discrete HFO events.     

Spontaneous ripples in the hippocampus correlate with epileptogenicity and not memory function in patients with refractory epilepsy

IntroductionHigh-frequency oscillations (HFOs, 80–500 Hz) are newly-described EEG markers of epileptogenicity. The proportion of physiological and pathological HFOs is unclear, as frequency analysis is insufficient for separating the two types of events. For instance, ripples (80–250 Hz) also occur physiologically during memory consolidation processes in medial temporal lobe structures. We investigated the correlation between HFO rates and memory performance.MethodsPatients investigated with bilateral medial temporal electrodes and an intellectual capacity allowing for memory testing were included. High-frequency oscillations were visually marked, and rates of HFOs were calculated for each channel during slow-wave sleep. Patients underwent three verbal and three nonverbal memory tests. They were grouped into severe impairment, some impairment, mostly intact, or intact for verbal and nonverbal memory. We calculated a Pearson correlation between HFO rates in the hippocampi and the memory category and compared HFO rates in each hippocampus with the corresponding (verbal — left, nonverbal — right) memory result using Wilcoxon rank-sum test.ResultsTwenty patients were included; ten had bilateral, five had unilateral, and five had no memory impairment. Unilateral memory impairment was verbal in one patient and nonverbal in four. There was no correlation between HFO rates and memory performance in seizure onset areas. There was, however, a significant negative correlation between the overall memory performance and ripple rates (r = − 0.50, p = 0.03) outside the seizure onset zone.ConclusionOur results suggest that the majority of spontaneous hippocampal ripples, as defined in the present study, may reflect pathological activity, taking into account the association with memory impairment. The absence of negative correlation between memory performance and HFO rates in seizure onset areas could be explained by HFO rates in the SOZ being generally so high that differences between areas with remaining and impaired memory function cannot be seen.     

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.     

Spatial localization and time-dependant changes of electrographic high frequency oscillations in human temporal lobe epilepsy

Purpose:   High frequency oscillations (HFOs) >200 Hz are believed to be associated with epileptic processes. The spatial distribution of HFOs and their evolution over time leading up to seizure onset is unknown. Also, recording HFOs through conventional intracranial electrodes is not well established. We therefore wished to determine whether HFOs could be recorded using commercially available depth macroelectrodes. We also examined the spatial distribution and temporal progression of HFOs during the transition to seizure activity.
Methods:   Intracranial electroencephalography (EEG) recordings of 19 seizures were obtained from seven patients with temporal lobe epilepsy using commercial depth or subdural electrodes. EEG recordings were analyzed for frequency content in five spectral bands spanning DC-500 Hz. We examined the spatial distribution of the different spectral bands 5 s before and 5 s after seizure onset. Temporal changes in the spectral bands were studied in the 30-s period leading up to seizure onset.
Results:   Three main observations were made. First, HFOs (100–500 Hz) can be recorded using commercial depth and subdural grid electrodes. Second, HFOs, but not <100 Hz oscillations, were localized to channels of ictal onset (100–200, 400–500 Hz, p < 0.05; 300–400 Hz, p < 0.001). Third, temporal analysis showed increased HFO power for approximately 8 s prior to electrographic onset (p < 0.05).
Conclusions:   These results suggest that HFOs can be recorded by depth macroelectrodes. Also, HFOs are localized to the region of primary ictal onset and can exhibit increased power during the transition to seizure. Thus, HFOs likely represent important precursors to seizure initiation.     

Effect of sleep stage on interictal high-frequency oscillations recorded from depth macroelectrodes in patients with focal epilepsy

Purpose :  To investigate the effect of sleep stage on the properties of high-frequency oscillations (HFOs) recorded from depth macroelectrodes in patients with focal epilepsy.
Methods :  Ten-minute epochs of wakefulness (W), stage 1–2 non-REM (N1-N2), stage 3 non-REM (N3) and REM sleep (R) were identified from stereo-electroencephalography (SEEG) data recorded at 2 kHz in nine patients. Rates of spikes, ripples (>80 Hz), and fast ripples (>250 Hz) were calculated, as were HFO durations, degree of spike–HFO overlap, HFO rates inside and outside of spikes, and inside and outside of the seizure-onset zone (SOZ).
Results :  Ripples were observed in nine patients and fast ripples in eight. Spike rate was highest in N1-N2 in 5 of 9 patients, and in N3 in 4 of 9 patients, whereas ripple rate was highest in N1-N2 in 4 of 9 patients, in N3 in 4 of 9 patients, and in W in 1 of 9 patients. Fast ripple rate was highest in N1-N2 in 4 of 8 patients, and in N3 in 4 of 8 patients. HFO properties changed significantly with sleep stage, although the absolute effects were small. The difference in HFO rates inside and outside of the SOZ was highly significant (p < 0.000001) in all stages except for R and, for fast ripples, only marginally significant (p = 0.018) in W.
Conclusions :  Rates of HFOs recorded from depth macroelectrodes are highest in non-REM sleep. HFO properties were similar in stages N1-N2 and N3, suggesting that accurate sleep staging is not necessary. The spatial specificity of HFO, particularly fast ripples, was affected by sleep stage, suggesting that recordings excluding REM sleep and wakefulness provide a more reliable indicator of the SOZ.     

Amplitude of high frequency oscillations as a biomarker of the seizure onset zone

ObjectiveStudies of high frequency oscillations (HFOs) in epilepsy have primarily tested the HFO rate as a biomarker of the seizure onset zone (SOZ), but the rate varies over time and is not robust for all individual subjects. As an alternative, we tested the performance of HFO amplitude as a potential SOZ biomarker using two automated detection algorithms.MethodHFOs were detected in intracranial electroencephalogram (iEEG) from 11 patients using a machine learning algorithm and a standard amplitude-based algorithm. For each detector, SOZ and non-SOZ channels were classified using the rate and amplitude of high frequency events, and performance was compared using receiver operating characteristic curves.ResultsThe amplitude of detected events was significantly higher in SOZ. Across subjects, amplitude more accurately classified SOZ/non-SOZ than rate (higher values of area under the ROC curve and sensitivity, and lower false positive rates). Moreover, amplitude was more consistent across segments of data, indicated by lower coefficient of variation.ConclusionAs an SOZ biomarker, HFO amplitude offers advantages over HFO rate: it exhibits higher classification accuracy, more consistency over time, and robustness to parameter changes.SignificanceThis biomarker has the potential to increase the generalizability of HFOs and facilitate clinical implementation as a tool for SOZ localization.     

Epileptic spasms in older pediatric patients: MEG and ictal high-frequency oscillations suggest focal-onset seizures in a subset of epileptic spasms

OBJECTIVES: To elucidate the pathophysiology of intractable epileptic spasms in older children by describing the interictal magnetoencephalography spike sources (MEGSSs), intracranial EEG ictal-onset zones (IOZs) and their ictal high-frequency oscillations (HFOs) and surgical outcomes. METHODS: We studied five patients (4.5-14 years) who underwent surgery following intracranial video-EEG (VEEG) monitoring. We analyzed clinical profiles, MRIs, scalp and intracranial VEEGs, and MEGSSs. We localized ictal HFOs using a sampling rate of 1000 Hz and multiple band frequency analysis (MBFA). RESULTS: Seizure onset ranged from 0.4 to 8 years. Three patients presented with asymmetrical spasms. Interictal scalp VEEG recorded predominantly unilateral epileptiform discharges in four; generalized and multifocal in one. Ictal scalp VEEG showed generalized high-amplitude slow waves with superimposed fast waves in four patients; hemispheric electrodecremental episodes in one. MRI findings were normal in three, hemispheric polymicrogyria and periventricular heterotopia in one each. All patients had unilateral MEGSS clusters. Ictal HFOs, ranging from 150 to 250 Hz, localized over Rolandic and frontal regions in four, with one also having extensive temporo-occipital HFOs. After cortical resection, three patients were seizure free; one had >90% reduction in seizure frequency. One patient experienced residual seizures after resection of the hemispheric ictal HFO region. CONCLUSION: Unilateral clusters of MEGSSs overlapped regional IOZs in older patients with epileptic spasms. High spatio-temporal MBFA before and during spasms revealed the regional ictal HFOs. Seizure-free outcomes following resection of zone with MEGSS clusters and ictal HFOs suggested that a subset of epileptic spasms was focal-onset seizures.     

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.     

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.     

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

ObjectiveIntracranial 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.MethodsWe 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.ResultsWe 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.ConclusionsThis study demonstrates the feasibility of interictal scalp R and FR detection and quantification of scalp R and FR coupling to SWA in ES.SignificanceHFO phase coupling with SWA may be useful as a marker of potential treatment refractoriness in patients with ES.     

Clinical Utility of Interictal High-Frequency Oscillations Recorded with Subdural Macroelectrodes in Partial Epilepsy

Background and Purpose

There is growing interest in high-frequency oscillations (HFO) as electrophysiological biomarkers of the epileptic brain. We evaluated the clinical utility of interictal HFO events, especially their occurrence rates, by comparing the spatial distribution with a clinically determined epileptogenic zone by using subdural macroelectrodes.

Methods

We obtained intracranial electroencephalogram data with a high temporal resolution (2000 Hz sampling rate, 0.05-500 Hz band-pass filter) from seven patients with medically refractory epilepsy. Three epochs of 5-minute, artifact-free data were selected randomly from the interictal period. HFO candidates were first detected by an automated algorithm and subsequently screened to discard false detections. Validated events were further categorized as fast ripple (FR) and ripple (R) according to their spectral profiles. The occurrence rate of HFOs was calculated for each electrode contact. An HFO events distribution map (EDM) was constructed for each patient to allow visualization of the spatial distribution of their HFO events.

Results

The subdural macroelectrodes were capable of detecting both R and FR events from the epileptic neocortex. The occurrence rate of HFO events, both FR and R, was significantly higher in the seizure onset zone (SOZ) than in other brain regions. Patient-specific HFO EDMs can facilitate the identification of the location of HFO-generating tissue, and comparison with findings from ictal recordings can provide additional useful information regarding the epileptogenic zone.

Conclusions

The distribution of interictal HFOs was reasonably consistent with the SOZ. The detection of HFO events and construction of spatial distribution maps appears to be useful for the presurgical mapping of the epileptogenic zone.