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.     

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.     

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.     

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.     

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.     

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.     

Improving the identification of High Frequency Oscillations

ObjectiveHigh Frequency Oscillations (HFOs), including Ripples (80–250 Hz) and Fast Ripples (250–500 Hz), can be recorded from intracranial macroelectrodes in patients with intractable epilepsy. We implemented a procedure to establish the duration for which a stable measurement of rate of HFOs is achieved.MethodsTo determine concordance, Kappa coefficient was computed. The information gained when increasing the duration was analyzed in terms of HFO rates and ranking of channels with respect to HFO and spike rates.ResultsIn a group of 30 patients, Kappa was 0.7 for ripples, 0.7 for fast ripples and 0.67 for spikes. Five minutes provided the same information as 10 min in terms of rates in 9/10 patients and with respect to ranking of channels in 8/10 patients; 5/30 patients did not achieve stable measurements of HFOs or spikes and needed marking for 10 min.ConclusionWe propose that 5 min provides in most cases the same information as a longer interval when identifying HFOs and spikes in slow wave sleep, and present methods to identify when this is not the case.SignificanceThis procedure is useful to control for consistency between readers and to evaluate if the selected interval provides stable information, for automatic and visual identification of events.     

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.     

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.     

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.     

Intracerebrally recorded high frequency oscillations: Simple visual assessment versus automated detection

Objective

We compared the possible contribution (in the detection of seizure onset zone – SOZ) of simple visual assessment of intracerebrally recorded high-frequency oscillations (HFO) with standard automated detection.

Methods

We analyzed stereo-EEG (SEEG) recordings from 20 patients with medically intractable partial seizures (10 temporal/10 extratemporal). Independently using simple visual assessment and automated detection of HFO, we identified the depth electrode contacts with maximum occurrences of ripples (R) and fast ripples (FR). The SOZ was determined by independent visual identification in standard SEEG recordings, and the congruence of results from visual versus automated HFO detection was compared.

Results

Automated detection of HFO correctly identified the SOZ in 14 (R)/10 (FR) out of 20 subjects; a simple visual assessment of SEEG recordings in the appropriate frequency ranges correctly identified the SOZ in 13 (R)/9 (FR) subjects.

Conclusions

Simple visual assessment of SEEG traces and standard automated detection of HFO seem to contribute comparably to the identification of the SOZ in patients with focal epilepsies. When using macroelectrodes in neocortical extratemporal epilepsies, the SOZ might be better determined by the ripple range.

Significance

Standard automated detection of HFO enables the evaluation of HFO characteristics in whole data. This detection allows general purpose and objective evaluation, without any bias from the neurophysiologist’s experiences and practice.     

Continuous high-frequency activity in mesial temporal lobe structures

Purpose: Many recent studies have reported the importance of high‐frequency oscillations (HFOs) in the intracerebral electroencephalography (EEG) of patients with epilepsy. These HFOs have been defined as events that stand out from the background. We have noticed that this background often consists itself of high‐frequency rhythmic activity. The purpose of this study is to perform a first evaluation of the characteristics of high‐frequency continuous or semicontinuous background activity. Methods: Because the continuous high‐frequency pattern was noted mainly in mesial temporal structures, we reviewed the EEG studies from these structures in 24 unselected patients with electrodes implanted in these regions. Sections of background away from interictal spikes were marked visually during periods of slow‐wave sleep and wakefulness. They were then high‐passed filtered at 80 Hz and categorized as having high‐frequency rhythmic activity in one of three patterns: continuous/semicontinuous, irregular, sporadic. Wavelet entropy, which measures the degree of rhythmicity of a signal, was calculated for the marked background sections. Key Findings: Ninety‐six bipolar channels were analyzed. The continuous/semicontinuous pattern was found frequently (29/96 channels during wake and 34/96 during sleep). The different patterns were consistent between sleep and wakefulness. The continuous/semicontinuous pattern was found significantly more often in the hippocampus than in the parahippocampal gyrus and was rarely found in the amygdala. The types of pattern were not influenced by whether a channel was within the seizure‐onset zone, or whether it was a lesional channel. The continuous/semicontinuous pattern was associated with a higher frequency of spikes and with high rates of ripples and fast ripples. Significance: It appears that high‐frequency activity (above 80 Hz) does not appear only in the form of brief paroxysmal events but also in the form of continuous rhythmic activity or very long bursts. In this study limited to mesial temporal structures, we found a clear anatomic preference for the hippocampus. Although associated with spikes and with distinct HFOs, this pattern was not clearly associated with the seizure‐onset zone. Future studies will need to evaluate systematically the presence of this pattern, as it may have a pathophysiologic significance and it will also have an important influence on the very definition of HFOs.     

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.     

High‐frequency oscillations: The state of clinical research

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

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.     

Prospective observational study: Fast ripple localization delineates the epileptogenic zone

ObjectiveTo 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.MethodsInterictal 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.ResultsInterictal 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).ConclusionsProspective visual analysis of interictal FRs was feasible, and it seemed to accurately localize epileptogenic zones.SignificanceTopological extent of epileptogenic region may exceed what is discernible by multimodal neuroimaging.     

Topographic movie of intracranial ictal high-frequency oscillations with seizure semiology: epileptic network in Jacksonian seizures

Purpose: We developed a technique to produce images of dynamic changes in ictal high‐frequency oscillations (HFOs) >40 Hz recorded on subdural electroencephalography (EEG) that are time‐locked to the ictal EEG and ictal semiology video. We applied this technique to Jacksonian seizures to demonstrate ictal HFO propagation along the homunculus in the primary sensory‐motor cortex to visualize the underlying epileptic network. Methods: We analyzed intracranial ictal EEGs from two patients with intractable Jacksonian seizures who underwent epilepsy surgery. We calculated the degrees of increase in amplitude within 40–80, 80–200, and 200–300 Hz frequency bands compared to the interictal period and converted them into topographic movies projected onto the brain surface picture. We combined these data with the ictal EEGs and video of the patient demonstrating ictal semiology. Key Findings: The ictal HFOs began in the sensory cortex and appeared concomitantly with the sensory aura. They then propagated to the motor cortex at the same time that focal motor symptoms evolved. As the seizure progressed, the ictal HFOs spread or reverberated in the rolandic region. However, even when the seizure became secondarily generalized, the ictal HFOs were confined to the rolandic region. In both cases, there was increased amplitude of higher frequency bands during seizure initiation compared to seizure progression. Significance: This combined movie showed the ictal HFO propagation corresponding to the ictal semiology in Jacksonian seizures and revealed the epileptic network involved in seizure initiation and progression. This method may advance understanding of neural network activities relating to clinical seizure generation and propagation.     

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.     

Hippocampal high frequency oscillations in unilateral and bilateral mesial temporal lobe epilepsy

ObjectiveThe main aim of this study was to investigate the potential differences in terms of interictal high frequency oscillations (HFOs) between both hippocampi in unilateral (U-MTLE) and bilateral mesial temporal lobe epilepsy (B-MTLE).MethodsSixteen patients with MTLE underwent bilateral hippocampal depth electrode implantation as part of epilepsy surgery evaluation. Interictal HFOs were detected automatically. The analyses entail comparisons of the rates and spatial distributions of ripples and fast ripples (FR) in hippocampi and amygdalae, with respect to the eventual finding of hippocampal sclerosis (HS).ResultsIn U-MTLE, higher ripple and FR rates were found in the hippocampi ipsilateral to the seizure onset than in the contralateral hippocampi. Non-epileptic hippocampi in U-MTLE were distinguished by significantly lower ripple rate than in the remaining analyzed hippocampi. There were not differences between the hippocampi in B-MTLE. In the hippocampi with proven HS, higher FR rates were observed in the ventral than in the dorsal parts.ConclusionsNon-epileptic hippocampi in U-MTLE demonstrated significantly lower ripple rates than those epileptic in U-MTLE and B-MTLE.SignificanceLow interictal HFO occurrence might be considered as a marker of the non-epileptic hippocampi in MTLE.     

Detection of changes of high-frequency activity by statistical time-frequency analysis in epileptic spikes

ObjectiveA novel type of statistical time-frequency analysis was developed to elucidate changes of high-frequency EEG activity associated with epileptic spikes.MethodsThe method uses the Gabor Transform and detects changes of power in comparison to background activity using t-statistics that are controlled by the false discovery rate (FDR) to correct type I error of multiple testing. The analysis was applied to EEGs recorded at 2000 Hz from three patients with mesial temporal lobe epilepsy.ResultsSpike-related increase of high-frequency oscillations (HFOs) was clearly shown in the FDR-controlled t-spectra: it was most dramatic in spikes recorded from the hippocampus when the hippocampus was the seizure onset zone (SOZ). Depression of fast activity was observed immediately after the spikes, especially consistently in the discharges from the hippocampal SOZ. It corresponded to the slow wave part in case of spike-and-slow-wave complexes, but it was noted even in spikes without apparent slow waves. In one patient, a gradual increase of power above 200 Hz preceded spikes.ConclusionsFDR-controlled t-spectra clearly detected the spike-related changes of HFOs that were unclear in standard power spectra.SignificanceWe developed a promising tool to study the HFOs that may be closely linked to the pathophysiology of epileptogenesis.