A comparison between automated detection methods of high-frequency oscillations (80-500 Hz) during seizures

Microscale dynamics of electrophysiological markers of epilepsy

OBJECTIVE

Interictal discharges (IIDs) and high frequency oscillations (HFOs) are established neurophysiologic biomarkers of epilepsy, while microseizures are less well studied. We used custom poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) microelectrodes to better understand these markers' microscale spatial dynamics.

METHODS

Electrodes with spatial resolution down to 50 µm were used to record intraoperatively in 30 subjects. IIDs' degree of spread and spatiotemporal paths were generated by peak-tracking followed by clustering. Repeating HFO patterns were delineated by clustering similar time windows. Multi-unit activity (MUA) was analyzed in relation to IID and HFO timing.

RESULTS

We detected IIDs encompassing the entire array in 93% of subjects, while localized IIDs, observed across < 50% of channels, were seen in 53%. IIDs traveled along specific paths. HFOs appeared in small, repeated spatiotemporal patterns. Finally, we identified microseizure events that spanned 50-100 µm. HFOs covaried with MUA, but not with IIDs.

CONCLUSIONS

Overall, these data suggest that irritable cortex micro-domains may form part of an underlying pathologic architecture which could contribute to the seizure network.

SIGNIFICANCE

These results, supporting the possibility that epileptogenic cortex comprises a mosaic of irritable domains, suggests that microscale approaches might be an important perspective in devising novel seizure control therapies.

Recent advances in the noninvasive detection of high-frequency oscillations in the human brain

In recent decades, a significant body of evidence based on invasive clinical research has showed that high-frequency oscillations (HFOs) are a promising biomarker for localization of the seizure onset zone (SOZ), and therefore, have the potential to improve postsurgical outcomes in patients with epilepsy. Emerging clinical literature has demonstrated that HFOs can be recorded noninvasively using methods such as scalp electroencephalography (EEG) and magnetoencephalography (MEG). Not only are HFOs considered to be a useful biomarker of the SOZ, they also have the potential to gauge disease severity, monitor treatment, and evaluate prognostic outcomes. In this article, we review recent clinical research on noninvasively detected HFOs in the human brain, with a focus on epilepsy. Noninvasively detected scalp HFOs have been investigated in various types of epilepsy. HFOs have also been studied noninvasively in other pathologic brain disorders, such as migraine and autism. Herein, we discuss the challenges reported in noninvasive HFO studies, including the scarcity of MEG and high-density EEG equipment in clinical settings, low signal-to-noise ratio, lack of clinically approved automated detection methods, and the difficulty in differentiating between physiologic and pathologic HFOs. Additional studies on noninvasive recording methods for HFOs are needed, especially prospective multicenter studies. Further research is fundamental, and extensive work is needed before HFOs can routinely be assessed in clinical settings; however, the future appears promising.

Electromagnetic activity: a possible player in epilepsy

Epilepsy is a common disease with frequent occurrences. Many precipitating factors contribute to epileptic seizures, such as hyperventilation and alcohol consumption. An increasing number of studies have also found that electromagnetic activity in the environment can also affect epileptic seizures. However, many neuromodulatory devices that produce electromagnetic fields have been applied in the diagnosis and treatment of epilepsy. In this paper, we performed literature search in the PubMed, Medline and EMBASE databases and reviewed retrospective, prospective, or cross-sectional studies and case reports on the effects of electromagnetic activity on epilepsy. The application of electromagnetic activity in the diagnosis and treatment of epilepsy is also reviewed.

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

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

Seizure onset location shapes dynamics of initiation

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

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

OBJECTIVE

To investigate the Graph Index Complexity (uGIC) as a marker of high frequency oscillatory (HFO) activity, the seizure onset zone (SOZ), and surgical outcome.

METHODS

The 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.

RESULTS

There 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).

CONCLUSION

The 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.

SIGNIFICANCE

The uGIC is an objective surrogate marker of HFO activity independent of identifying discrete HFO events.

MEEGIPS-A Modular EEG Investigation and Processing System for Visual and Automated Detection of High Frequency Oscillations

High frequency oscillations (HFOs) are electroencephalographic correlates of brain activity detectable in a frequency range above 80 Hz. They co-occur with physiological processes such as saccades, movement execution, and memory formation, but are also related to pathological processes in patients with epilepsy. Localization of the seizure onset zone, and, more specifically, of the to-be resected area in patients with refractory epilepsy seems to be supported by the detection of HFOs. The visual identification of HFOs is very time consuming with approximately 8 h for 10 min and 20 channels. Therefore, automated detection of HFOs is highly warranted. So far, no software for visual marking or automated detection of HFOs meets the needs of everyday clinical practice and research. In the context of the currently available tools and for the purpose of related local HFO study activities we aimed at converging the advantages of clinical and experimental systems by designing and developing a comprehensive and extensible software framework for HFO analysis that, on the one hand, focuses on the requirements of clinical application and, on the other hand, facilitates the integration of experimental code and algorithms. The development project included the definition of use cases, specification of requirements, software design, implementation, and integration. The work comprised the engineering of component-specific requirements, component design, as well as component- and integration-tests. A functional and tested software package is the deliverable of this activity. The project MEEGIPS, a Modular EEG Investigation and Processing System for visual and automated detection of HFOs, introduces a highly user friendly software that includes five of the most prominent automated detection algorithms. Future evaluation of these, as well as implementation of further algorithms is facilitated by the modular software architecture.

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

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

Generalizability of High Frequency Oscillation Evaluations in the Ripple Band

Objective: We examined the interrater reliability and generalizability of high-frequency oscillation (HFO) visual evaluations in the ripple (80–250 Hz) band, and established a framework for the transition of HFO analysis to routine clinical care. We were interested in the interrater reliability or epoch generalizability to describe how similar the evaluations were between reviewers, and in the reviewer generalizability to represent the consistency of the internal threshold each individual reviewer.

Methods: We studied 41 adult epilepsy patients (mean age: 35.6 years) who underwent intracranial electroencephalography. A morphology detector was designed and used to detect candidate HFO events, lower-threshold events, and distractor events. These events were subsequently presented to six expert reviewers, who visually evaluated events for the presence of HFOs. Generalizability theory was used to characterize the epoch generalizability (interrater reliability) and reviewer generalizability (internal threshold consistency) of visual evaluations, as well as to project the numbers of epochs, reviewers, and datasets required to achieve strong generalizability (threshold of 0.8).

Results: The reviewer generalizability was almost perfect (0.983), indicating there were sufficient evaluations to determine the internal threshold of each reviewer. However, the interrater reliability for 6 reviewers (0.588) and pairwise interrater reliability (0.322) were both poor, indicating that the agreement of 6 reviewers is insufficient to reliably establish the presence or absence of individual HFOs. Strong interrater reliability (≥0.8) was projected as requiring a minimum of 17 reviewers, while strong reviewer generalizability could be achieved with <30 epoch evaluations per reviewer.

Significance: This study reaffirms the poor reliability of using small numbers of reviewers to identify HFOs, and projects the number of reviewers required to overcome this limitation. It also provides a set of tools which may be used for training reviewers, tracking changes to interrater reliability, and for constructing a benchmark set of epochs that can serve as a generalizable gold standard, against which other HFO detection algorithms may be compared. This study represents an important step toward the reconciliation of important but discordant findings from HFO studies undertaken with different sets of HFOs, and ultimately toward transitioning HFO analysis into a meaningful part of the clinical epilepsy workup.

Progress and Remaining Challenges in the Application of High Frequency Oscillations as Biomarkers of Epileptic Brain

High-frequency oscillations (HFOs: 100 - 600 Hz) have been widely proposed as biomarkers of epileptic brain tissue. In addition, HFOs over a broader range of frequencies spanning 30 - 2000 Hz are potential biomarkers of both physiological and pathological brain processes. The majority of the results from humans with focal epilepsy have focused on HFOs recorded directly from the brain with intracranial EEG (iEEG) in the high gamma (65 - 100 Hz), ripple (100 - 250 Hz), and fast ripple (250 - 600 Hz) frequency ranges. These results are supplemented by reports of HFOs recorded with iEEG in the low gamma (30 - 65Hz) and very high frequency (500 - 2000 Hz) ranges. Visual detection of HFOs is laborious and limited by poor inter-rater agreement; and the need for accurate, reproducible automated HFOs detection is well recognized. In particular, the clinical translation of HFOs as a biomarker of the epileptogenic brain has been limited by the ability to reliably detect and accurately classify HFOs as physiological or pathological. Despite these challenges, there has been significant progress in the field, which is the subject of this review. Furthermore, we provide data and corresponding analytic code in an effort to promote reproducible research and accelerate clinical translation.

Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances

In recent years, new recording technologies have advanced such that oscillations of neuronal networks can be identified from simultaneous, multisite recordings at high temporal and spatial resolutions. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings also depends on the development of new mathematical methods capable of extracting meaningful information related to time, frequency and space. In this review, we aim to bridge this gap by focusing on the new analysis tools developed for the automated detection of high-frequency oscillations (HFOs, >40Hz) in local field potentials. For this, we provide a revision of different aspects associated with physiological and pathological HFOs as well as the several stages involved in their automatic detection including preprocessing, selection, rejection and analysis through time-frequency processes. Beyond basic research, the automatic detection of HFOs would greatly assist diagnosis of epilepsy disorders based on the recognition of these typical pathological patterns in the electroencephalogram (EEG). Also, we emphasize how these HFO detection methods can be applied and the properties that might be inferred from neuronal signals, indicating potential future directions.

High-frequency oscillations and seizure-like discharges in the entorhinal cortex of the in vitro isolated guinea pig brain

We analyzed the patterns of seizure-like activity and associated high-frequency oscillations (HFOs) induced by the K⁺ channel blocker 4-aminopyridine (4AP, 50μM) or the GABA_A receptor antagonist bicuculline methiodide (BMI, 50μM) in the in vitro isolated guinea pig brain preparation. Extracellular field recordings were obtained from the medial entorhinal cortex (EC) using glass pipettes or silicon probes; 4AP or BMI were applied through the basilar artery. Ripples (80-200Hz) or fast ripples (250-500Hz) occurred at higher rates shortly before ictal events induced by 4AP or BMI, respectively. In addition, during the ictal period, ripples were mostly associated with 4AP-induced ictal events whereas fast ripples predominated during ictal discharges induced by BMI. Finally, ripples occurred at higher rates during the clonic phase of 4AP-induced ictal events compared to the tonic phase, while higher rates of fast ripples characterized the clonic phase in both 4AP- and BMI-induced ictal discharges. These differences in HFO occurrence presumably reflect the diverse action of these two convulsants on GABA_A receptor signaling.

High frequency oscillations can pinpoint seizures progressing to status epilepticus

Status epilepticus (SE) is defined as a seizure lasting more than 5min or a period of recurrent seizures without recovery between them. SE is a serious emergency condition that requires immediate intervention; therefore, identifying SE electrophysiological markers may translate in prompt care to stop it. Here, we analyzed the EEG signals recorded from the CA3 region of the hippocampus and the entorhinal cortex in rats that responded to systemic administration of 4-aminopyridine (4AP) by generating either isolated seizures or seizures progressing to SE. We found that high frequency oscillations (HFOs) - which can be categorized as ripples (80-200Hz) and fast ripples (250-500Hz) - had different patterns of occurrence in the two groups (n=5 for each group). Specifically, fast ripples in CA3 and entorhinal cortex of the SE group occurred at higher rates than ripples, both during the ictal and post-ictal periods when compared to the HFOs recorded from the isolated seizure group. Our data reveal that different patterns of HFO occurrence can pinpoint seizures progressing to SE, thus suggesting the involvement of different neuronal networks at the termination of seizure discharges.

Conundrums of high-frequency oscillations (80-800 Hz) in the epileptic brain

Pathological high-frequency oscillations (HFOs) (80-800 Hz) are considered biomarkers of epileptogenic tissue, but the underlying complex neuronal events are not well understood. Here, we identify and discuss several outstanding issues or conundrums in regards to the recording, analysis, and interpretation of HFOs in the epileptic brain to critically highlight what is known and what is not about these enigmatic events. High-frequency oscillations reflect a range of neuronal processes contributing to overlapping frequencies from the lower 80 Hz to the very fast spectral frequency bands. Given their complex neuronal nature, HFOs are extremely sensitive to recording conditions and analytical approaches. We provide a list of recommendations that could help to obtain comparable HFO signals in clinical and basic epilepsy research. Adopting basic standards will facilitate data sharing and interpretation that collectively will aid in understanding the role of HFOs in health and disease for translational purpose.

Epileptic Pattern Recognition and Discovery of the Local Field Potential in Amygdala Kindling Process

Epileptogenesis, which occurs in an epileptic brain, is an important focus for epilepsy. The spectral analysis has been popularly applied to study the electrophysiological activities. However, the resolution is dominated by the window function of the algorithm used and the sample size. In this report, a temporal waveform analysis method is proposed to investigate the relationship of electrophysiological discharges and motor outcomes with a kindling process. Wistar rats were subjected to electrical amygdala kindling to induce temporal lobe epilepsy. During the kindling process, different morphologies of afterdischarges (ADs) were found and a recognition method, using template matching techniques combined with morphological comparators, was developed to automatically detect the epileptic patterns. The recognition results were compared to manually labeled results, and 79%-91% sensitivity was found. In addition, the initial ADs (the first 10 s) of different seizure stages were specifically utilized for recognition, and an average of 85% sensitivity was achieved. Our study provides an alternative viewpoint away from frequency analysis and time-frequency analysis to investigate epileptogenesis in an epileptic brain. The recognition method can be utilized as a preliminary inspection tool to identify remarkable changes in a patient's electrophysiological activities for clinical use. Moreover, we demonstrate the feasibility of predicting behavioral seizure stages from the early epileptiform discharges.

High-frequency oscillations in epilepsy and surgical outcome. A meta-analysis

High frequency oscillations (HFOs) are estimated as a potential marker for epileptogenicity. Current research strives for valid evidence that these HFOs could aid the delineation of the to-be resected area in patients with refractory epilepsy and improve surgical outcomes. In the present meta-analysis, we evaluated the relation between resection of regions from which HFOs can be detected and outcome after epilepsy surgery. We conducted a systematic review of all studies that related the resection of HFO-generating areas to postsurgical outcome. We related the outcome (seizure freedom) to resection ratio, that is, the ratio between the number of channels on which HFOs were detected and, among these, the number of channels that were inside the resected area. We compared the resection ratio between seizure free and not seizure free patients. In total, 11 studies were included. In 10 studies, ripples (80-200 Hz) were analyzed, and in 7 studies, fast ripples (>200 Hz) were studied. We found comparable differences (dif) and largely overlapping confidence intervals (CI) in resection ratios between outcome groups for ripples (dif = 0.18; CI: 0.10-0.27) and fast ripples (dif = 0.17; CI: 0.01-0.33). Subgroup analysis showed that automated detection (dif = 0.22; CI: 0.03-0.41) was comparable to visual detection (dif = 0.17; CI: 0.08-0.27). Considering frequency of HFOs (dif = 0.24; CI: 0.09-0.38) was related more strongly to outcome than considering each electrode that was showing HFOs (dif = 0.15; CI = 0.03-0.27). The effect sizes found in the meta-analysis are small but significant. Automated detection and application of a detection threshold in order to detect channels with a frequent occurrence of HFOs is important to yield a marker that could be useful in presurgical evaluation. In order to compare studies with different methodological approaches, detailed and standardized reporting is warranted.

Carbonic anhydrase inhibition by acetazolamide reduces in vitro epileptiform synchronization

Depolarizing GABAA receptor-mediated currents are contributed by HCO3(-) efflux, and play a role in initiating ictal-like epileptiform events in several cortical structures supporting the view that GABAA receptor signaling actively participates to epileptiform synchronization. We employed here field potential recordings to analyze the effects of the carbonic anhydrase inhibitor acetazolamide (10 μM) on the epileptiform activity generated in vitro by piriform and entorhinal cortices (PC and EC, respectively) during application of the K(+) channel blocker 4-aminopyridine (4AP, 50 μM). Under these experimental conditions ictal- and interictal-like discharges along with high-frequency oscillations (ripples: 80-200 Hz, fast ripples: 250-500 Hz) occurred in these two regions. In both PC and EC, acetazolamide: (i) reduced the duration and the interval of occurrence of ictal discharges along with the associated ripples and fast ripples; (ii) decreased the interval of occurrence of interictal discharges and the rates of associated fast ripples; and (iii) diminished the duration and amplitude of pharmacologically isolated GABAergic events while increasing their interval of occurrence. Our results indicate that acetazolamide effectively controls 4AP-induced epileptiform synchronization in PC and EC. We propose that this action may rest on decreased GABAA receptor-mediated HCO3(-) efflux leading to diminished depolarization of principal cells and, perhaps, of interneurons.

KCC2 function modulates in vitro ictogenesis

GABAA receptor-mediated inhibition is active and may contribute to epileptiform synchronization. The efficacy of inhibition relies on low levels of intracellular Cl(-), which are controlled by KCC2 activity. This evidence has led us to analyze with field potential recordings the effects induced by the KCC2 blockers VU0240551 (10 μM) or bumetanide (50 μM) and by the KCC2 enhancer CLP257 (100 μM) on the epileptiform discharges generated by piriform and entorhinal cortices (PC and EC, respectively) in an in vitro brain slice preparation. Ictal- and interictal-like discharges along with high-frequency oscillations (HFOs, ripples: 80-200 Hz, fast ripples: 250-500 Hz) were recorded from these two regions during application of 4-aminopyridine (4AP, 50 μM). Blocking KCC2 activity with either VU024055 or high doses of bumetanide abolished ictal discharge in both PC and EC; in addition, these experimental procedures decreased the interval of occurrence and duration of interictal discharges. In contrast, enhancing KCC2 activity with CLP257 increased ictal discharge duration in both regions. Finally, blocking KCC2 activity decreased the duration and amplitude of pharmacologically isolated synchronous GABAergic events whereas enhancing KCC2 activity led to an increase in their duration. Our data demonstrate that in vitro ictogenesis is abolished or facilitated by inhibiting or enhancing KCC2 activity, respectively. We propose that these effects may result from the reduction of GABAA receptor-dependent increases in extracellular K(+) that are known to rest on KCC2 function.

Neurosteroidal modulation of in vitro epileptiform activity is enhanced in pilocarpine-treated epileptic rats

We employed field potential recordings in brain slices obtained from pilocarpine-treated epileptic (4-5weeks following a pilocarpine-induced status epilepticus) and age-matched, non-epileptic control (NEC) rats to establish the effects of the neurosteroid allotetrahydrodeoxycorticosterone (THDOC) on the epileptiform activity - including high frequency oscillations (HFOs; ripples: 80-200Hz, fast ripples: 250-500Hz) - induced by 4-aminopyridine (4AP) in piriform (PC) and entorhinal (EC) cortices. Both structures are highly susceptible to generate seizures and may also be involved in epileptogenesis. We found that THDOC application to pilocarpine-treated slices: (i) decreased interictal discharge frequency in PC while increasing it in EC; (ii) abolished ictal discharges in both areas in approx. one third of the experiments and reduced them in frequency and duration in the remaining experiments; and (iii) increased the occurrence of ripples and fast ripples associated to interictal events, and modified their pattern of occurrence during ictal discharges in both PC and EC. These effects were either weaker or absent in NEC tissue. Our results demonstrate that THDOC plays a structure-dependent modulatory role in epileptiform synchronization in the pilocarpine-treated epileptic rat brain where its actions are more pronounced than in NEC tissue. This evidence supports the application of neurosteroids as potential antiepileptic tools.

Distinct EEG seizure patterns reflect different seizure generation mechanisms

Low-voltage fast (LVF)- and hypersynchronous (HYP)-seizure onset patterns can be recognized in the EEG of epileptic animals and patients with temporal lobe epilepsy. Ripples (80-200 Hz) and fast ripples (250-500 Hz) have been linked to each pattern, with ripples predominating during LVF seizures and fast ripples predominating during HYP seizures in the rat pilocarpine model. This evidence led us to hypothesize that these two seizure-onset patterns reflect the contribution of neural networks with distinct transmitter signaling characteristics. Here, we tested this hypothesis by analyzing the seizure activity induced with the K(+) channel blocker 4-aminopyridine (4AP, 4-5 mg/kg ip), which enhances both glutamatergic and GABAergic transmission, or the GABAA receptor antagonist picrotoxin (3-5 mg/kg ip); rats were implanted with electrodes in the hippocampus, the entorhinal cortex, and the subiculum. We found that LVF onset occurred in 82% of 4AP-induced seizures whereas seizures after picrotoxin were always HYP. In addition, high-frequency oscillation analysis revealed that 4AP-induced LVF seizures were associated with higher ripple rates compared with fast ripples (P < 0.05), whereas picrotoxin-induced seizures contained higher rates of fast ripples compared with ripples (P < 0.05). These results support the hypothesis that two distinct patterns of seizure onset result from different pathophysiological mechanisms.

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 GABAA receptor antagonism. These results demonstrate that potentiation of GABAA 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.

Epileptiform synchronization and high-frequency oscillations in brain slices comprising piriform and entorhinal cortices

We employed field potential recordings in extended in vitro brain slices form Sprague-Dawley rats containing the piriform and entorhinal cortices (PC and EC, respectively) to identify the characteristics of epileptiform discharges and concomitant high-frequency oscillations (HFOs, ripples: 80-200Hz, fast ripples: 250-500Hz) during bath application of 4-aminopyridine (4AP, 50μM). Ictal-like discharges occurred in PC and EC either synchronously or independently of each other; synchronous ictal discharges always emerged from a synchronous "fast" interictal background whereas asynchronous ictal discharges were preceded by a "slow" interictal event. In addition, asynchronous ictal discharges had longer duration and interval of occurrence than synchronous ictal discharges, and contained a higher proportion of ripples and fast ripples. Cutting the connections between PC and EC made synchronicity disappear and increased ictal discharges duration in the EC but failed in changing HFO occurrence in both areas. Finally, antagonizing ionotropic glutamatergic receptors abolished ictal activity in all experiments, increased the duration and rate of occurrence of interictal discharges occurring in PC-EC interconnected slices while it did not influence the slow asynchronous interictal discharges in both areas. Our results identify some novel in vitro interactions between olfactory (PC) and limbic (EC) structures that presumably contribute to in vivo ictogenesis as well.

A reliable approach to distinguish between transient with and without HFOs using TQWT and MCA

Recent studies have reported that discrete high frequency oscillations (HFOs) in the range of 80-500Hz may serve as promising biomarkers of the seizure focus in humans. Visual scoring of HFOs is tiring, time consuming, highly subjective and requires a great deal of mental concentration. Due to the recent explosion of HFOs research, development of a robust automated detector is expected to play a vital role in studying HFOs and their relationship to epileptogenesis. Therefore, a handful of automated detectors have been introduced in the literature over the past few years. In fact, all the proposed methods have been associated with high false-positive rates, which essentially arising from filtered sharp transients like spikes, sharp waves and artifacts. In order to specifically minimize false positive rates and improve the specificity of HFOs detection, we proposed a new approach, which is a combination of tunable Q-factor wavelet transform (TQWT), morphological component analysis (MCA) and complex Morlet wavelet (CMW). The main findings of this study can be summarized as follows: The proposed method results in a sensitivity of 96.77%, a specificity of 85.00% and a false discovery rate (FDR) of 07.41%. Compared to this, the classical CMW method applied directly on the signals without pre-processing by TQWT-MCA achieves a sensitivity of 98.71%, a specificity of 18.75%, and an FDR of 29.95%. The proposed method may be considered highly accurate to distinguish between transients with and without HFOs. Consequently, it is remarkably reliable and robust for the detection of HFOs.

Human intracranial high frequency oscillations (HFOs) detected by automatic time-frequency analysis

OBJECTIVES

High frequency oscillations (HFOs) have been proposed as a new biomarker for epileptogenic tissue. The exact characteristics of clinically relevant HFOs and their detection are still to be defined.

METHODS

We propose a new method for HFO detection, which we have applied to six patient iEEGs. In a first stage, events of interest (EoIs) in the iEEG were defined by thresholds of energy and duration. To recognize HFOs among the EoIs, in a second stage the iEEG was Stockwell-transformed into the time-frequency domain, and the instantaneous power spectrum was parameterized. The parameters were optimized for HFO detection in patient 1 and tested in patients 2-5. Channels were ranked by HFO rate and those with rate above half maximum constituted the HFO area. The seizure onset zone (SOZ) served as gold standard.

RESULTS

The detector distinguished HFOs from artifacts and other EEG activity such as interictal epileptiform spikes. Computation took few minutes. We found HFOs with relevant power at frequencies also below the 80-500 Hz band, which is conventionally associated with HFOs. The HFO area overlapped with the SOZ with good specificity > 90% for five patients and one patient was re-operated. The performance of the detector was compared to two well-known detectors.

CONCLUSIONS

Compared to methods detecting energy changes in filtered signals, our second stage - analysis in the time-frequency domain - discards spurious detections caused by artifacts or sharp epileptic activity and improves the detection of HFOs. The fast computation and reasonable accuracy hold promise for the diagnostic value of the detector.

Dynamics of interictal spikes and high-frequency oscillations during epileptogenesis in temporal lobe epilepsy

Mesial temporal lobe epilepsy (MTLE) is characterized in humans and in animal models by a seizure-free latent phase that follows an initial brain insult; this period is presumably associated to plastic changes in temporal lobe excitability and connectivity. Here, we analyzed the occurrence of interictal spikes and high frequency oscillations (HFOs; ripples: 80-200Hz and fast ripples: 250-500Hz) from 48h before to 96h after the first seizure in the rat pilocarpine model of MTLE. Interictal spikes recorded with depth EEG electrodes from the hippocampus CA3 area and entorhinal cortex (EC) were classified as type 1 (characterized by a spike followed by a wave) or type 2 (characterized by a spike with no wave). We found that: (i) there was a switch in the distribution of both types of interictal spikes before and after the occurrence of the first seizure; during the latent phase both types of interictal spikes predominated in the EC whereas during the chronic phase both types of spikes predominated in CA3; (ii) type 2 spike duration decreased in both regions from the latent to the chronic phase; (iii) type 2 spikes associated to fast ripples occurred at higher rates in EC compared to CA3 during the latent phase while they occurred at similar rates in both regions in the chronic phase; and (iv) rates of fast ripples outside of spikes were higher in EC compared to CA3 during the latent phase. Our findings demonstrate that the transition from the latent to the chronic phase is paralleled by dynamic changes in interictal spike and HFO expression in EC and CA3. We propose that these changes may represent biomarkers of epileptogenicity in MTLE.

Peri-ictal broadband electrocorticographic activities between 1 and 700 Hz and seizure onset zones in 18 patients

OBJECTIVE

We investigated the relationship between locations of broadband peri-ictal electrocorticographic activities determined by a semi-automatic detection method and seizure onset zones in medically intractable epilepsy patients.

METHODS

We included 18 patients. Peri-ictal periods (-15 to +5s from the ictal onset) were divided into 4 periods of 5s duration each in bandwidth from 1 to 700 Hz divided into 11 bins. Thereafter, we calculated the mean overlapping percentage of the maximum amplitude activity electrodes with the seizure onset zone in the total number of seizures in each patient. Significance was considered at an adjusted p-value of 0.05.

RESULTS

By the maximum amplitude method with the Bonferroni correction, only high-frequency activities (>60 Hz) during -5 to 0 s from the ictal onset were significantly related to seizure onset zones. In post hoc analyses, bands in 60-139 Hz and 4-7 Hz were significantly related to seizure onset zones in the Bonferroni correction. However, after the less conservative Benjamini-Yekutieli correction and with the epileptogenicity index, other bands and periods after -10s from the ictal onset were also related with seizure onset zones.

SIGNIFICANCE

Detailed bands, timings and analytic methods of peri-ictal activities with high relationships to seizure onset zones were identified.

Neurosteroids modulate epileptiform activity and associated high-frequency oscillations in the piriform cortex

Allotetrahydrodeoxycorticosterone (THDOC) belongs to a class of pregnane neurosteroidal compounds that enhance brain inhibition by interacting directly with GABAA signaling, mainly through an increase in tonic inhibitory current. Here, we addressed the role of THDOC in the modulation of interictal- and ictal-like activity and associated high-frequency oscillations (HFOs, 80-500 Hz; ripples: 80-200 Hz, fast ripples: 250-500 Hz) recorded in vitro in the rat piriform cortex, a highly excitable brain structure that is implicated in seizure generation and maintenance. We found that THDOC: (i) increased the duration of interictal discharges in the anterior piriform cortex while decreasing ictal discharge duration in both anterior and posterior piriform cortices; (ii) reduced the occurrence of HFOs associated to both interictal and ictal discharges; and (iii) prolonged the duration of 4-aminopyridine-induced, glutamatergic independent synchronous field potentials that are known to mainly result from the activation of GABAA receptors. Our results indicate that THDOC can modulate epileptiform synchronization in the piriform cortex presumably by potentiating GABAA receptor-mediated signaling. This evidence supports the view that neurosteroids regulate neuronal excitability and thus control the occurrence of seizures.