High-frequency oscillations and other electrophysiological biomarkers of epilepsy: underlying mechanisms

Weak coupling of neurons enables very high-frequency and ultra-fast oscillations through the interplay of synchronized phase shifts

Recently, in the past decade, high-frequency oscillations (HFOs), very high-frequency oscillations (VHFOs), and ultra-fast oscillations (UFOs) were reported in epileptic patients with drug-resistant epilepsy. However, to this day, the physiological origin of these events has yet to be understood. Our study establishes a mathematical framework based on bifurcation theory for investigating the occurrence of VHFOs and UFOs in depth EEG signals of patients with focal epilepsy, focusing on the potential role of reduced connection strength between neurons in an epileptic focus. We demonstrate that synchronization of a weakly coupled network can generate very and ultra high-frequency signals detectable by nearby microelectrodes. In particular, we show that a bistability region enables the persistence of phase-shift synchronized clusters of neurons. This phenomenon is observed for different hippocampal neuron models, including Morris-Lecar, Destexhe-Paré, and an interneuron model. The mechanism seems to be robust for small coupling, and it also persists with random noise affecting the external current. Our findings suggest that weakened neuronal connections could contribute to the production of oscillations with frequencies above 1000 Hz, which could advance our understanding of epilepsy pathology and potentially improve treatment strategies. However, further exploration of various coupling types and complex network models is needed.

Interictal high-frequency oscillations, spikes, and connectivity profiles: A fingerprint of epileptogenic brain pathologies

OBJECTIVE

Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug-resistant epilepsy patients. Epileptic spikes, high-frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies.

METHODS

Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug-resistant epilepsy with seizure-free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross-correlation, and phase consistency) were computed for neighboring electrode pairs.

RESULTS

Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy.

SIGNIFICANCE

The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery.

Exploring Ripple Waves in the Human Brain

Ripples are brief (<150 ms) high-frequency oscillatory neural activities in the brain with a range of 140 to 200 Hz in rodents and 80 to 140 Hz in humans. Ripples are regarded as playing an essential role in several aspects of memory function, mainly in the hippocampus. This type of ripple generally occurs with sharp waves and is called a sharp-wave ripple (SPW-R). Extensive research of SPW-Rs in the rodent brain while actively awake has also linked the function of these SPW-Rs to navigation and decision making. Although many studies with rodents unveiled SPW-R function, research in humans on this subject is still sparse. Therefore, unveiling SPW-R function in the human hippocampus is warranted. A certain type of ripples may also be a biomarker of epilepsy. This type of ripple is called a pathological ripple (p-ripple). p-ripples have a wider range of frequency (80-500 Hz) than SPW-Rs, and the range of frequency is especially higher in brain regions that are intrinsically linked to epilepsy onset. Brain regions producing ripples are too small for scalp electrode recording, and intracranial recording is typically needed to detect ripples. In addition, SPW-Rs in the human hippocampus have been recorded from patients with epilepsy who may have p-ripples. Differentiating SPW-Rs and p-ripples is often not easy. We need to develop more sophisticated methods to record SPW-Rs to differentiate them from p-ripples. This paper reviews the general features and roles of ripple waves.

Interictal HFO and FDG-PET correlation predicts surgical outcome following SEEG

OBJECTIVE

This study aimed to investigate the quantitative relationship between interictal ¹⁸ F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and interictal high-frequency oscillations (HFOs) from stereo-electroencephalography (SEEG) recordings in patients with refractory epilepsy.

METHODS

We retrospectively included 32 patients. FDG-PET data were quantified through statistical parametric mapping (SPM) t test modeling with normal controls. Interictal SEEG segments with four, 10-min segments were selected randomly. HFO detection and classification procedures were automatically performed. Channel-based HFOs separating ripple (80-250 Hz) and fast ripple (FR; 250-500 Hz) counts were correlated with the surrounding metabolism T score at the individual and group level, respectively. The association was further validated across anatomic seizure origins and sleep vs wake states. We built a joint feature FR × T reflecting the FR and hypometabolism concordance to predict surgical outcomes in 28 patients who underwent surgery.

RESULTS

We found a negative correlation between interictal FDG-PET and HFOs through the linear mixed-effects model (R²  = .346 and .457 for ripples and FRs, respectively, p < .001); these correlations were generalizable to different epileptogenic-zone lobar localizations and vigilance states. The FR × T inside the resection volume could be used as a predictor for surgical outcomes with an area under the curve of 0.81.

SIGNIFICANCE

The degree of hypometabolism is associated with HFO generation rate, especially for FRs. This relationship would be meaningful for selection of SEEG candidates and for optimizing SEEG scheme planning. The concordance between FRs and hypometabolism inside the resection volume could provide prognostic information regarding surgical outcome.

Intracranial electrophysiological recordings on a swine model of mesial temporal lobe epilepsy

Objective

To test the feasibility and reliability of intracranial electrophysiological recordings in an acute status epilepticus model on laboratory swine.

Method

Intrahippocampal injection of kainic acid (KA) was performed on 17 male Bama pigs (Sus scrofa domestica) weighing between 25 and 35 kg. Two stereoelectroencephalography (SEEG) electrodes with a total of 16 channels were implanted bilaterally along the sensorimotor cortex to the hippocampus. Brain electrical activity was recorded 2 h daily for 9-28 days. Three KA dosages were tested to evaluate the quantities capable of evoking status epilepticus. Local field potentials (LFPs) were recorded and compared before and after the KA injection. We quantified the epileptic patterns, including the interictal spikes, seizures, and high-frequency oscillations (HFOs), up to 4 weeks after the KA injection. Test-retest reliability using intraclass correlation coefficients (ICCs) were performed on interictal HFO rates to evaluate the recording stability of this model.

Results

The KA dosage test suggested that a 10 μl (1.0 μg/μl) intrahippocampal injection could successfully evoke status epilepticus lasting from 4 to 12 h. At this dosage, eight pigs (50% of total) had prolonged epileptic events (tonic-chronic seizures + interictal spikes n = 5, interictal spikes alone n = 3) in the later 4 weeks of the video-SEEG recording period. Four pigs (25% of total) had no epileptic activities, and another four (25%) had lost the cap or did not complete the experiments. Animals that showed epileptiform events were grouped as E + (n = 8) and the four animals showing no signs of epileptic events were grouped as E- (n = 4). A total of 46 electrophysiological seizures were captured in the 4-week post-KA period from 4 E + animals, with the earliest onset on day 9. The seizure durations ranged from 12 to 45 s. A significant increase of hippocampal HFOs rate (num/min) was observed in the E+ group during the post-KA period (weeks 1, 2,4, p < 0.05) compared to the baseline. But the E-showed no change or a decrease (in week 2, p = 0.43) compared to their baseline rate. The between-group comparison showed much higher HFO rates in E + vs. E - (F = 35, p < 0.01). The high ICC value [ICC (1, k) = 0.81, p < 0.05] quantified from the HFO rate suggested that this model had a stable measurement of HFOs during the four-week post-KA periods.

Significance

This study measured intracranial electrophysiological activity in a swine model of KA-induced mesial temporal lobe epilepsy (mTLE). Using the clinical SEEG electrode, we distinguished abnormal EEG patterns in the swine brain. The high test-retest reliability of HFO rates in the post-KA period suggests the utility of this model for studying mechanisms of epileptogenesis. The use of swine may provide satisfactory translational value for clinical epilepsy research.

EEG biomarker candidates for the identification of epilepsy

Electroencephalography (EEG) is one of the main pillars used for the diagnosis and study of epilepsy, readily employed after a possible first seizure has occurred. The most established biomarker of epilepsy, in case seizures are not recorded, are interictal epileptiform discharges (IEDs). In clinical practice, however, IEDs are not always present and the EEG may appear completely normal despite an underlying epileptic disorder, often leading to difficulties in the diagnosis of the disease. Thus, finding other biomarkers that reliably predict whether an individual suffers from epilepsy even in the absence of evident epileptic activity would be extremely helpful, since they could allow shortening the period of diagnostic uncertainty and consequently decreasing the risk of seizure. To date only a few EEG features other than IEDs seem to be promising candidates able to distinguish between epilepsy, i.e. > 60 % risk of recurrent seizures, or other (pathological) conditions. The aim of this narrative review is to provide an overview of the EEG-based biomarker candidates for epilepsy and the techniques employed for their identification.

Implementation of a Morphological Filter for Removing Spikes from the Epileptic Brain Signals to Improve Identification Ripples

Epilepsy is a very common disease affecting at least 1% of the population, comprising a number of over 50 million people. As many patients suffer from the drug-resistant version, the number of potential treatment methods is very small. However, since not only the treatment of epilepsy, but also its proper diagnosis or observation of brain signals from recordings are important research areas, in this paper, we address this very problem by developing a reliable technique for removing spikes and sharp transients from the baseline of the brain signal using a morphological filter. This allows much more precise identification of the so-called epileptic zone, which can then be resected, which is one of the methods of epilepsy treatment. We used eight patients with 5 KHz data set and depended upon the Staba 2002 algorithm as a reference to detect the ripples. We found that the average sensitivity and false detection rate of our technique are significant, and they are ∼94% and ∼14%, respectively.

Beyond rates: time-varying dynamics of high frequency oscillations as a biomarker of the seizure onset zone

Objective. High frequency oscillations (HFOs) recorded by intracranial electrodes have generated excitement for their potential to help localize epileptic tissue for surgical resection. However, the number of HFOs per minute (i.e. the HFO 'rate') is not stable over the duration of intracranial recordings; for example, the rate of HFOs increases during periods of slow-wave sleep. Moreover, HFOs that are predictive of epileptic tissue may occur in oscillatory patterns due to phase coupling with lower frequencies. Therefore, we sought to further characterize between-seizure (i.e. 'interictal') HFO dynamics both within and outside the seizure onset zone (SOZ).Approach. Using long-term intracranial EEG (mean duration 10.3 h) from 16 patients, we automatically detected HFOs using a new algorithm. We then fit a hierarchical negative binomial model to the HFO counts. To account for differences in HFO dynamics and rates between sleep and wakefulness, we also fit a mixture model to the same data that included the ability to switch between two discrete brain states that were automatically determined during the fitting process. The ability to predict the SOZ by model parameters describing HFO dynamics (i.e. clumping coefficients and coefficients of variation) was assessed using receiver operating characteristic curves.Main results. Parameters that described HFO dynamics were predictive of SOZ. In fact, these parameters were found to be more consistently predictive than HFO rate. Using concurrent scalp EEG in two patients, we show that the model-found brain states corresponded to (1) non-REM sleep and (2) awake and rapid eye movement sleep. However the brain state most likely corresponding to slow-wave sleep in the second model improved SOZ prediction compared to the first model for only some patients.Significance. This work suggests that delineation of SOZ with interictal data can be improved by the inclusion of time-varying HFO dynamics.

Drug-resistant epilepsy and the hypothesis of intrinsic severity: What about the high-frequency oscillations?

Drug‐resistant epilepsy (DRE) affects approximately one‐third of the patients with epilepsy. Based on experimental findings from animal models and brain tissue from patients with DRE, different hypotheses have been proposed to explain the cause(s) of drug resistance. One is the intrinsic severity hypothesis that posits that drug resistance is an inherent property of epilepsy related to disease severity. Seizure frequency is one measure of epilepsy severity, but frequency alone is an incomplete measure of severity and does not fully explain basic research and clinical studies on drug resistance; thus, other measures of epilepsy severity are needed. One such measure could be pathological high‐frequency oscillations (HFOs), which are believed to reflect the neuronal disturbances responsible for the development of epilepsy and the generation of spontaneous seizures. In this manuscript, we will briefly review the intrinsic severity hypothesis, describe basic and clinical research on HFOs in the epileptic brain, and based on this evidence discuss whether HFOs could be a clinical measure of epilepsy severity. Understanding the mechanisms of DRE is critical for producing breakthroughs in the development and testing of novel strategies for treatment.

The role of voltage-gated chloride channels in the epileptogenesis of temporal lobe epilepsy

BACKGROUND

Temporal lobe epilepsy (TLE) is the most common intractable epilepsy in adults, and elucidation of the underlying pathological mechanisms is needed. Voltage-gated chloride channels (ClC) play diverse physiological roles in neurons. However, less is known regarding their functions in the epilepogenesis of TLE.

METHODS

ClC-mediated current and the spontaneous inhibitory synaptic currents (sIPSC) in hippocampal neurons of epileptic lesions were investigated by electrophysiological recording. The EEG data were analyzed by Z-scored wavelet and Fourier transformations. The expression of ClC-3, a member of ClC gene family, was detected by immunostaining and western blot.

FINDINGS

ClC-mediated current was increased in the hippocampal neurons of chronic TLE mice. Application of chloride channel blockers, NPPB (5-Nitro-2- [3-phenylpropylamino] benzoic acid) and DIDS (4,4'-Diisothiocyanato-2,2'-stilbenedisulfonic acid disodium salt) reduced ClC-mediated current and increased inhibitory synaptic transmission in TLE mice. NPPB and DIDS reduced the seizure frequency and the average absolute power of ictal high-frequency oscillations (HFOs, 80-500 Hz) in TLE mice. In addition, both drugs induced outwardly rectified currents, which might be tonic inhibitory currents in the hippocampal neurons of TLE patients. Furthermore, the expression of ClC-3 was increased in the hippocampus of TLE mice and patients and positively correlated with both the absolute power and number of ictal HFOs per seizure in the sclerotic hippocampus.

INTERPRETATION

These data suggest that ClC participate in the epilepogenetic process of TLE and the inhibition of ClC may have anti-epileptic effect.

FUNDING

This work was supported by National Natural Science Foundation of China (No. 81601143, No. 81771217).

Increased hippocampal excitability in miR-324-null mice

MicroRNAs are non-coding RNAs that act to downregulate the expression of target genes by translational repression and degradation of messenger RNA molecules. Individual microRNAs have the ability to specifically target a wide array of gene transcripts, therefore allowing each microRNA to play key roles in multiple biological pathways. miR-324 is a microRNA predicted to target thousands of RNA transcripts and is expressed far more highly in the brain than in any other tissue, suggesting that it may play a role in one or multiple neurological pathways. Here we present data from the first global miR-324-null mice, in which increased excitability and interictal discharges were identified in vitro in the hippocampus. RNA sequencing was used to identify differentially expressed genes in miR-324-null mice which may contribute to this increased hippocampal excitability, and 3'UTR luciferase assays and western blotting revealed that two of these, Suox and Cd300lf, are novel direct targets of miR-324. Characterisation of microRNAs that produce an effect on neurological activity, such as miR-324, and identification of the pathways they regulate will allow a better understanding of the processes involved in normal neurological function and in turn may present novel pharmaceutical targets in treating neurological disease.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

Scaling of Network Excitability and Inhibition may Contribute to the Septotemporal Differentiation of Sharp Waves-Ripples in Rat Hippocampus In Vitro

The functional organization of the hippocampus along its longitudinal (septotemporal or dorsoventral) axis is conspicuously heterogeneous. This functional diversification includes the activity of sharp wave and ripples (SPW-Rs), a complex intrinsic network pattern involved in memory consolidation. In this study, using transverse slices from the ventral and the dorsal rat hippocampus and recordings of CA1 field potentials we studied the development of SPW-Rs and possible changes in local network excitability and inhibition, during in vitro maintenance of the hippocampal tissue. We found that SPW-Rs develop gradually in terms of magnitude and rate of occurrence in the ventral hippocampus. On the contrary, neither the magnitude nor the rate of occurrence significantly changed in dorsal hippocampal slices during their in vitro maintenance. The development of SPW-Rs was accompanied by an increase in local network excitability more in the ventral than in the dorsal hippocampus, and an increase in local network inhibition in the ventral hippocampus only. Furthermore, the amplitude of SPWs positively correlated with the level of maximum excitation of the local neuronal network in both segments of the hippocampus, and the local network excitability and inhibition in the ventral but not the dorsal hippocampus. Blockade of α5 subunit-containing GABA_A receptor by L-655,708 significantly reduced the rate of occurrence of SPWs and enhanced the probability of their generation in the form of clusters in the ventral hippocampus without affecting activity in the dorsal hippocampus. The present evidence suggests that a dynamic upregulation of excitation and inhibition in the local neuronal network may significantly contribute to the generation of SPW-Rs, particularly in the ventral hippocampus.

Epilepsy as a disease affecting neural networks: A neurophysiological perspective

INTRODUCTION

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

OBJECTIVE

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

RESULTS

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

CONCLUSIONS

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

Sleep and Epilepsy Link by Plasticity

We aimed to explore the link between NREM sleep and epilepsy. Based on human and experimental data we propose that a sleep-related epileptic transformation of normal neurological networks underlies epileptogenesis. Major childhood epilepsies as medial temporal lobe epilepsy (MTLE), absence epilepsy (AE) and human perisylvian network (PN) epilepsies - made us good models to study. These conditions come from an epileptic transformation of the affected functional systems. This approach allows a system-based taxonomy instead of the outworn generalized-focal classification. MTLE links to the memory-system, where epileptic transformation results in a switch of normal sharp wave-ripples to epileptic spikes and pathological high frequency oscillations, compromising sleep-related memory consolidation. Absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) belong to the corticothalamic system. The burst-firing mode of NREM sleep normally producing sleep-spindles turns to an epileptic working mode ejecting bilateral synchronous spike-waves. There seems to be a progressive transition from AE to JME. Shared absences and similar bilateral synchronous discharges show the belonging of the two conditions, while the continuous age windows - AE affecting schoolchildren, JME the adolescents - and the increased excitability in JME compared to AE supports the notion of progression. In perisylvian network epilepsies - idiopathic focal childhood epilepsies and electrical status epilepticus in sleep including Landau-Kleffner syndrome - centrotemporal spikes turn epileptic, with the potential to cause cognitive impairment. Postinjury epilepsies modeled by the isolated cortex model highlight the shared way of epileptogenesis suggesting the derailment of NREM sleep-related homeostatic plasticity as a common step. NREM sleep provides templates for plasticity derailing to epileptic variants under proper conditions. This sleep-origin explains epileptiform discharges' link and similarity with NREM sleep slow oscillations, spindles and ripples. Normal synaptic plasticity erroneously overgrowing homeostatic processes may derail toward an epileptic working-mode manifesting the involved system's features. The impact of NREM sleep is unclear in epileptogenesis occurring in adolescence and adulthood, when plasticity is lower. The epileptic process interferes with homeostatic synaptic plasticity and may cause cognitive impairment. Its type and degree depends on the affected network's function. We hypothesize a vicious circle between sleep end epilepsy. The epileptic derailment of normal plasticity interferes with sleep cognitive functions. Sleep and epilepsy interconnect by the pathology of plasticity.

Biomarkers for epileptogenesis and its treatment

There are no pharmacological interventions to prevent the development of epilepsy, although many promising compounds have been identified in the animal laboratory. Clinical trials to validate their effectiveness, however, would currently be prohibitively expensive due to the large subject population and duration of follow-up necessary. There is, therefore, the need to identify biomarkers of epileptogenesis that could identify patients at high risk for epilepsy following a potential epileptogenic insult to enrich the subject population, as well as biomarkers that could determine the effectiveness of therapeutic intervention without the need to wait for seizures to occur. Putative biomarkers under investigation for epileptogenesis and its treatment include genetic, molecular, cellular, imaging, and electrophysiological measures that might reliably predict the development or progression of an epileptic condition, the effects of antiepileptogenic treatment, or cure after surgery. To be clinically useful for most purposes, ideal biomarkers should be noninvasive, and it is anticipated that a profile of multiple biomarkers will likely be required. Ongoing animal research involves a number of experimental models of epileptogenesis, with traumatic brain injury, offering the best potential for translational clinical investigations. Collaborative and multicenter research efforts by multidisciplinary teams of basic and clinical neuroscientists with access to robust, well-defined animal models, extensive patient populations, standardized protocols, and cutting-edge analytical methodologies are likely to be most successful. Such biomarker research should also provide insights into fundamental neuronal mechanisms of epileptogenesis suggesting novel targets for antiepileptogenic treatments. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.

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

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

Long-term chemogenetic suppression of spontaneous seizures in a mouse model for temporal lobe epilepsy

OBJECTIVE

More than one-third of patients with temporal lobe epilepsy (TLE) continue to have seizures despite treatment with antiepileptic drugs, and many experience severe drug-related side effects, illustrating the need for novel therapies. Selective expression of inhibitory Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) allows cell-type-specific reduction of neuronal excitability. In this study, we evaluated the effect of chemogenetic suppression of excitatory pyramidal and granule cell neurons of the sclerotic hippocampus in the intrahippocampal mouse model (IHKA) for temporal lobe epilepsy.

METHODS

Intrahippocampal IHKA mice were injected with an adeno-associated viral vector carrying the genes for an inhibitory DREADD hM4Di in the sclerotic hippocampus or control vector. Next, animals were treated systemically with different single doses of clozapine-N-oxide (CNO) (1, 3, and 10 mg/kg) and clozapine (0.03 and 0.1 mg/kg) and the effect on spontaneous hippocampal seizures, hippocampal electroencephalography (EEG) power, fast ripples (FRs) and behavior in the open field test was evaluated. Finally, animals received prolonged treatment with clozapine for 3 days and the effect on seizures was monitored.

RESULTS

Treatment with both CNO and clozapine resulted in a robust suppression of hippocampal seizures for at least 15 hours only in DREADD-expressing animals. Moreover, total EEG power and the number of FRs were significantly reduced. CNO and/or clozapine had no effects on interictal hippocampal EEG, seizures, or locomotion/anxiety in the open field test in non-DREADD epileptic IHKA mice. Repeated clozapine treatment every 8 hours for 3 days resulted in almost complete seizure suppression in DREADD animals.

SIGNIFICANCE

This study shows the potency of chemogenetics to robustly and sustainably suppress spontaneous epileptic seizures and pave the way for an epilepsy therapy in which a systemically administered exogenous drug selectively modulates specific cell types in a seizure network, leading to a potent seizure suppression devoid of the typical drug-related side effects.

How can methylprednisolone work on epileptic spasms with malformation of cortical development?

Although steroids are suggested as the treatment of choice for infantile spasms, the mechanism of action is still unclear. Using a rat model of malformation of cortical development with refractory infantile spasms, we evaluated the efficacy of methylprednisolone on spasms susceptibility and behaviors. Additionally, we investigated the in vivo electrophysiological and neurochemical changes of the brain after methylprednisolone treatment. Infant rats with prenatal exposure of methylazoxymethanol at gestational day 15 were used. After a single dose of methylprednisolone or three different doses of methylprednisolone for 3 days, spasms were triggered by intraperitoneal injection of N-methyl-d-aspartic acid. In rats with 3 days of methylprednisolone pretreatment and their controls, behavioral testing was performed at postnatal day 15. In vivo magnetic resonance imaging was conducted at postnatal day 15 after 3 days of methylprednisolone treatment. The rats with single methylprednisolone pretreatment showed significantly delayed onset of spasms and multiple doses of methylprednisolone significantly suppressed the development of spasms in a dose-dependent manner. After multiple methylprednisolone pretreatment and a cluster of N-methyl-d-aspartic acid-induced spasms, the rats showed significantly increased freezing behaviors to conditioned stimuli. Glutamate-weighted chemical exchange saturation transfer revealed significant elevation of glutamate concentration in the cortices of the rats with multiple methylprednisolone pretreatments. Methylprednisolone pretreatment could attenuate N-methyl-d-aspartic acid-induced spasms with in vivo neurochemical and electrophysiological changes, which indicates this steroid's action on the brain and in epilepsy.

Electrical stimulation of the piriform cortex for the treatment of epilepsy: A review of the supporting evidence

In this review, we consider how the piriform cortex is engaged in both focal and generalized epilepsy networks and postulate the various neural pathways that can be effectively neuromodulated by stimulation at this site. This highlights the common involvement of the piriform cortex in epilepsy. We address both current and future preclinical studies of deep brain stimulation (DBS) of the piriform cortex, with attention to the critical features of these trials that will enable them to be of greatest utility in informing clinical translation. Although recent DBS trials have utilized thalamic targets, electrical stimulation of the piriform cortex may also be a useful intervention for people with epilepsy. However, more work is required to develop a solid foundation for this approach before considering human trials.

Physiological and pathological high frequency oscillations in focal epilepsy

Objective

This study investigates high‐frequency oscillations (HFOs; 65–600 Hz) as a biomarker of epileptogenic brain and explores three barriers to their clinical translation: (1) Distinguishing pathological HFOs (pathHFO) from physiological HFOs (physHFO). (2) Classifying tissue under individual electrodes as epileptogenic (3) Reproducing results across laboratories.

Methods

We recorded HFOs using intracranial EEG (iEEG) in 90 patients with focal epilepsy and 11 patients without epilepsy. In nine patients with epilepsy putative physHFOs were induced by cognitive or motor tasks. HFOs were identified using validated detectors. A support vector machine (SVM) using HFO features was developed to classify tissue under individual electrodes as normal or epileptogenic.

Results

There was significant overlap in the amplitude, frequency, and duration distributions for spontaneous physHFO, task induced physHFO, and pathHFO, but the amplitudes of the pathHFO were higher (P < 0.0001). High gamma pathHFO had the strongest association with seizure onset zone (SOZ), and were elevated on SOZ electrodes in 70% of epilepsy patients (P < 0.0001). Failure to resect tissue generating high gamma pathHFO was associated with poor outcomes (P < 0.0001). A SVM classified individual electrodes as epileptogenic with 63.9% sensitivity and 73.7% specificity using SOZ as the target.

Interpretation

A broader range of interictal pathHFO (65–600 Hz) than previously recognized are biomarkers of epileptogenic brain, and are associated with SOZ and surgical outcome. Classification of HFOs into physiological or pathological remains challenging. Classification of tissue under individual electrodes was demonstrated to be feasible. The open source data and algorithms provide a resource for future studies.

Kurtosis-Based Detection of Intracranial High-Frequency Oscillations for the Identification of the Seizure Onset Zone

Pathological High-Frequency Oscillations (HFOs) have been recently proposed as potential biomarker of the seizure onset zone (SOZ) and have shown superior accuracy to interictal epileptiform discharges in delineating its anatomical boundaries. Characterization of HFOs is still in its infancy and this is reflected in the heterogeneity of analysis and reporting methods across studies and in clinical practice. The clinical approach to HFOs identification and quantification usually still relies on visual inspection of EEG data. In this study, we developed a pipeline for the detection and analysis of HFOs. This includes preliminary selection of the most informative channels exploiting statistical properties of the pre-ictal and ictal intracranial EEG (iEEG) time series based on spectral kurtosis, followed by wavelet-based characterization of the time-frequency properties of the signal. We performed a preliminary validation analyzing EEG data in the ripple frequency band (80-250 Hz) from six patients with drug-resistant epilepsy who underwent pre-surgical evaluation with stereo-EEG (SEEG) followed by surgical resection of pathologic brain areas, who had at least two-year positive post-surgical outcome. In this series, kurtosis-driven selection and wavelet-based detection of HFOs had average sensitivity of 81.94% and average specificity of 96.03% in identifying the HFO area which overlapped with the SOZ as defined by clinical presurgical workup. Furthermore, the kurtosis-based channel selection resulted in an average reduction in computational time of 66.60%.

Fast oscillation dynamics during hypsarrhythmia as a localization biomarker

Hypsarrhythmia in West syndrome, although hard to define, is characterized by chaotic and disorganized electrical activity of the brain and is often regarded as a generalized EEG pattern without any localization value. Using event-related spectral perturbation (ERSP), we tried to determine the brain dynamics during hypsarrhythmia. Routine 1-h scalp EEGs were retrieved from 31 patients with infantile spasms and 20 age-matched controls. Using the EEGLAB toolbox of MATLAB 2015b, the ERSPs of fast oscillations (FOs; 20-100 Hz) of selected channels were analyzed and compared among groups according to their MRI lesions. FO-ERSP cutoff values for predicting the pathologic foci were estimated. The mean FO-ERSPs across all analyzed electrodes of patients with spasms were significantly higher than those of controls. When the patients were categorized into nonlesional, focal/multifocal, or diffuse lesional groups, the FO-ERSP of patients in the focal/multifocal lesional group was significantly lower than that of those in the nonfocal or diffuse lesional groups. In the focal/multifocal lesional group, seven patients (7/9, 77.8%) showed that the locations of channels with high FO-ERSPs were matched to the pathologic MRI lesions. Thus, the localization of high FO-ERSPs is closely associated with the location of pathologic brain lesions. Further research is required to prove the value of the FO-ERSP as an important quantitative localizing biomarker of West syndrome. NEW & NOTEWORTHY The locations of high fast oscillation-event-related spectral perturbations (FO-ERSPs) are closely associated with brain pathologic lesions, and high FO-ERSPs can be used as a localization biomarker of pathologic brain lesions in patients with hypsarrhythmia. With further validation, FO-ERSP might be useful as a biomarker for the localization of hidden pathologies in conditions with generalized epileptiform activities such as West syndrome.

The role of high-frequency oscillations in epilepsy surgery planning

BACKGROUND

Epilepsy is a serious brain disorder characterized by recurrent unprovoked seizures. Approximately two-thirds of seizures can be controlled with antiepileptic medications (Kwan 2000). For some of the others, surgery can completely eliminate or significantly reduce the occurrence of disabling seizures. Localization of epileptogenic areas for resective surgery is far from perfect, and new tools are being investigated to more accurately localize the epileptogenic zone (the zone of the brain where the seizures begin) and improve the likelihood of freedom from postsurgical seizures. Recordings of pathological high-frequency oscillations (HFOs) may be one such tool.

OBJECTIVES

To assess the ability of HFOs to improve the outcomes of epilepsy surgery by helping to identify more accurately the epileptogenic areas of the brain.

SEARCH METHODS

For the latest update, we searched the Cochrane Epilepsy Group Specialized Register (25 July 2016), the Cochrane Central Register of Controlled Trials (CENTRAL) via the Cochrane Register of Studies Online (CRSO, 25 July 2016), MEDLINE (Ovid, 1946 to 25 July 2016), CINAHL Plus (EBSCOhost, 25 July 2016), Web of Science (Thomson Reuters, 25 July 2016), ClinicalTrials.gov (25 July 2016), and the World Health Organization International Clinical Trials Registry Platform ICTRP (25 July 2016).

SELECTION CRITERIA

We included studies that provided information on the outcomes of epilepsy surgery for at least six months and which used high-frequency oscillations in making decisions about epilepsy surgery.

DATA COLLECTION AND ANALYSIS

The primary outcome of the review was the Engel Class Outcome System (class I = no disabling seizures, II = rare disabling seizures, III = worthwhile improvement, IV = no worthwhile improvement). Secondary outcomes were responder rate, International League Against Epilepsy (ILAE) epilepsy surgery outcome, frequency of adverse events from any source and quality of life outcomes. We intended to analyse outcomes via an aggregated data fixed-effect model meta-analysis.

MAIN RESULTS

Two studies representing 11 participants met the inclusion criteria. Both studies were small non-randomised trials, with no control group and no blinding. The quality of evidence for all outcomes was very low. The combination of these two studies resulted in 11 participants who prospectively used ictal HFOs for epilepsy surgery decision making. Results of the postsurgical seizure freedom Engel class I to IV outcome were determined over a period of 12 to 38 months (average 23.4 months) and indicated that six participants had an Engel class I outcome (seizure freedom), two had class II (rare disabling seizures), three had class III (worthwhile improvement). No adverse effects were reported. Neither study compared surgical results guided by HFOs versus surgical results guided without HFOs.

AUTHORS' CONCLUSIONS

No reliable conclusions can be drawn regarding the efficacy of using HFOs in epilepsy surgery decision making at present.

Interictal high-frequency oscillations in focal human epilepsy

PURPOSE OF REVIEW

Localization of focal epileptic brain is critical for successful epilepsy surgery and focal brain stimulation. Despite significant progress, roughly half of all patients undergoing focal surgical resection, and most patients receiving focal electrical stimulation, are not seizure free. There is intense interest in high-frequency oscillations (HFOs) recorded with intracranial electroencephalography as potential biomarkers to improve epileptogenic brain localization, resective surgery, and focal electrical stimulation. The present review examines the evidence that HFOs are clinically useful biomarkers.

RECENT FINDINGS

Performing the PubMed search 'High-Frequency Oscillations and Epilepsy' for 2013-2015 identifies 308 articles exploring HFO characteristics, physiological significance, and potential clinical applications.

SUMMARY

There is strong evidence that HFOs are spatially associated with epileptic brain. There remain, however, significant challenges for clinical translation of HFOs as epileptogenic brain biomarkers: Differentiating true HFO from the high-frequency power changes associated with increased neuronal firing and bandpass filtering sharp transients. Distinguishing pathological HFO from normal physiological HFO. Classifying tissue under individual electrodes as normal or pathological. Sharing data and algorithms so research results can be reproduced across laboratories. Multicenter prospective trials to provide definitive evidence of clinical utility.

Correlation of FDG-PET hypometabolism and SEEG epileptogenicity mapping in patients with drug-resistant focal epilepsy

OBJECTIVE

Interictal [18F]fluorodeoxyglucose-positron emission tomography (FDG-PET) is used in the presurgical evaluation of patients with drug-resistant focal epilepsy. We aimed at clarifying its relationships with ictal high-frequency oscillations (iHFOs) shown to be a relevant marker of the seizure-onset zone.

METHODS

We studied the correlation between FDG-PET and epileptogenicity maps in an unselected series of 37 successive patients having been explored with stereo-electroencephalography (SEEG).

RESULTS

At the group level, we found a significant correlation between iHFOs and FDG-PET interictal hypometabolism only in cases of temporal lobe epilepsy. This correlation was found with HFOs, and the same comparison between FDG-PET and ictal SEEG power of lower frequencies during the same epochs did not show the same significance.

SIGNIFICANCE

This finding suggests that interictal FDG-PET and ictal HFOs may share common underlying pathophysiologic mechanisms of ictogenesis in temporal lobe epilepsy, and combining both features may help to identify the seizure-onset zone.

The functional organization of human epileptic hippocampus

The function and connectivity of human brain is disrupted in epilepsy. We previously reported that the region of epileptic brain generating focal seizures, i.e., the seizure onset zone (SOZ), is functionally isolated from surrounding brain regions in focal neocortical epilepsy. The modulatory effect of behavioral state on the spatial and spectral scales over which the reduced functional connectivity occurs, however, is unclear. Here we use simultaneous sleep staging from scalp EEG with intracranial EEG recordings from medial temporal lobe to investigate how behavioral state modulates the spatial and spectral scales of local field potential synchrony in focal epileptic hippocampus. The local field spectral power and linear correlation between adjacent electrodes provide measures of neuronal population synchrony at different spatial scales, ∼1 and 10 mm, respectively. Our results show increased connectivity inside the SOZ and low connectivity between electrodes in SOZ and outside the SOZ. During slow-wave sleep, we observed decreased connectivity for ripple and fast ripple frequency bands within the SOZ at the 10 mm spatial scale, while the local synchrony remained high at the 1 mm spatial scale. Further study of these phenomena may prove useful for SOZ localization and help understand seizure generation, and the functional deficits seen in epileptic eloquent cortex.

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.

Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning

Sharp wave ripples (SPW-Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW-Rs occur during "off-line" states of the brain, associated with consummatory behaviors and non-REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW-induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW-Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW-Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW-Rs interferes with memory. Recently acquired and pre-existing information are combined during SPW-R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW-Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW-Rs leads to their pathological conversion, "p-ripples," which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW-R genesis and function are discussed in this review.

Genetic Programming and Frequent Itemset Mining to Identify Feature Selection Patterns of iEEG and fMRI Epilepsy Data

Pattern classification for intracranial electroencephalogram (iEEG) and functional magnetic resonance imaging (fMRI) signals has furthered epilepsy research toward understanding the origin of epileptic seizures and localizing dysfunctional brain tissue for treatment. Prior research has demonstrated that implicitly selecting features with a genetic programming (GP) algorithm more effectively determined the proper features to discern biomarker and non-biomarker interictal iEEG and fMRI activity than conventional feature selection approaches. However for each the iEEG and fMRI modalities, it is still uncertain whether the stochastic properties of indirect feature selection with a GP yield (a) consistent results within a patient data set and (b) features that are specific or universal across multiple patient data sets. We examined the reproducibility of implicitly selecting features to classify interictal activity using a GP algorithm by performing several selection trials and subsequent frequent itemset mining (FIM) for separate iEEG and fMRI epilepsy patient data. We observed within-subject consistency and across-subject variability with some small similarity for selected features, indicating a clear need for patient-specific features and possible need for patient-specific feature selection or/and classification. For the fMRI, using nearest-neighbor classification and 30 GP generations, we obtained over 60% median sensitivity and over 60% median selectivity. For the iEEG, using nearest-neighbor classification and 30 GP generations, we obtained over 65% median sensitivity and over 65% median selectivity except one patient.

Neuronal ensemble synchrony during human focal seizures

Seizures are classically characterized as the expression of hypersynchronous neural activity, yet the true degree of synchrony in neuronal spiking (action potentials) during human seizures remains a fundamental question. We quantified the temporal precision of spike synchrony in ensembles of neocortical neurons during seizures in people with pharmacologically intractable epilepsy. Two seizure types were analyzed: those characterized by sustained gamma (∼40-60 Hz) local field potential (LFP) oscillations or by spike-wave complexes (SWCs; ∼3 Hz). Fine (<10 ms) temporal synchrony was rarely present during gamma-band seizures, where neuronal spiking remained highly irregular and asynchronous. In SWC seizures, phase locking of neuronal spiking to the SWC spike phase induced synchrony at a coarse 50-100 ms level. In addition, transient fine synchrony occurred primarily during the initial ∼20 ms period of the SWC spike phase and varied across subjects and seizures. Sporadic coherence events between neuronal population spike counts and LFPs were observed during SWC seizures in high (∼80 Hz) gamma-band and during high-frequency oscillations (∼130 Hz). Maximum entropy models of the joint neuronal spiking probability, constrained only on single neurons' nonstationary coarse spiking rates and local network activation, explained most of the fine synchrony in both seizure types. Our findings indicate that fine neuronal ensemble synchrony occurs mostly during SWC, not gamma-band, seizures, and primarily during the initial phase of SWC spikes. Furthermore, these fine synchrony events result mostly from transient increases in overall neuronal network spiking rates, rather than changes in precise spiking correlations between specific pairs of neurons.

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals

Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2–3 days and used 1–2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory.

Approaches to refractory epilepsy

Epilepsy is one of the most common serious neurological conditions, and 30 to 40% of people with epilepsy have seizures that are not controlled by medication. Patients are considered to have refractory epilepsy if disabling seizures continue despite appropriate trials of two antiseizure drugs, either alone or in combination. At this point, patients should be referred to multidisciplinary epilepsy centers that perform specialized diagnostic testing to first determine whether they are, in fact, pharmacoresistant, and then, if so, offer alternative treatments. Apparent pharmacoresistance can result from a variety of situations, including noncompliance, seizures that are not epileptic, misdiagnosis of the seizure type or epilepsy syndrome, inappropriate use of medication, and lifestyle issues. For patients who are pharmacoresistant, surgical treatment offers the best opportunity for complete freedom from seizures. Surgically remediable epilepsy syndromes have been identified, but patients with more complicated epilepsy can also benefit from surgical treatment and require more specialized evaluation, including intracranial EEG monitoring. For patients who are not surgical candidates, or who are unwilling to consider surgery, a variety of other alternative treatments can be considered, including peripheral or central neurostimulation, ketogenic diet, and complementary and alternative approaches. When such alternative treatments are not appropriate or effective, quality of life can still be greatly improved by the psychological and social support services offered by multidisciplinary epilepsy centers. A major obstacle remains the fact that only a small proportion of patients with refractory epilepsy are referred for expert evaluation and treatment.

Electrophysiological biomarkers of epilepsy

In patients being evaluated for epilepsy and in animal models of epilepsy, electrophysiological recordings are carried to capture seizures to determine the existence of epilepsy. Electroencephalography recordings from the scalp, or sometimes directly from the brain, are also used to locate brain areas where seizure begins, and in surgical treatment help plan the area for resection. As seizures are unpredictable and can occur infrequently, ictal recordings are not ideal in terms of time, cost, or risk when, for example, determining the efficacy of existing or new anti-seizure drugs, evaluating potential anti-epileptogenic interventions, or for prolonged intracerebral electrode studies. Thus, there is a need to identify and validate other electrophysiological biomarkers of epilepsy that could be used to diagnose, treat, cure, and prevent epilepsy. Electroencephalography recordings in the epileptic brain contain other interictal electrophysiological disturbances that can occur more frequently than seizures, such as interictal spikes (IIS) and sharp waves, and from invasive studies using wide bandwidth recording and small diameter electrodes, the discovery of pathological high-frequency oscillations (HFOs) and microseizures. Of IIS, HFOs, and microseizures, a significant amount of recent research has focused on HFOs in the pathophysiology of epilepsy. Results from studies in animals with epilepsy and presurgical patients have consistently found a strong association between HFOs and epileptogenic brain tissue that suggest HFOs could be a potential biomarker of epileptogenicity and epileptogenesis. Here, we discuss several aspects of HFOs, as well as IIS and microseizures, and the evidence that supports their role as biomarkers of epilepsy.

The role of high-frequency oscillations in epilepsy surgery planning

BACKGROUND

Epilepsy is a serious brain disorder characterized by recurrent unprovoked seizures. Approximately two-thirds of seizures can be controlled with antiepileptic medications (Kwan 2000). For some of the others, surgery can completely eliminate or significantly reduce the occurrence of disabling seizures. Localization of epileptogenic areas for resective surgery is far from perfect, and new tools are being investigated to more accurately localize the epileptogenic zone (the zone of the brain where the seizures begin) and improve the likelihood of freedom from postsurgical seizures. Recordings of pathological high-frequency oscillations (HFOs) may be one such tool.

OBJECTIVES

To assess the ability of HFOs to improve the outcomes of epilepsy surgery by helping to identify more accurately the epileptogenic areas of the brain.

SEARCH METHODS

We searched the Cochrane Epilepsy Group Specialized Register (15 April 2013), the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (2013, Issue 3), MEDLINE (Ovid) (1946 to 15 April 2013), CINAHL (EBSCOhost) (15 April 2013), Web of Knowledge (Thomson Reuters) (15 April 2013), www.clinicaltrials.gov (15 April 2013), and the World Health Organization International Clinical Trials Registry Platform (15 April 2013).

SELECTION CRITERIA

We included studies that provided information on the outcomes of epilepsy surgery at at least six months and which used high-frequency oscillations in making decisions about epilepsy surgery.

DATA COLLECTION AND ANALYSIS

The primary outcome of the review was the Engel Class Outcome System. Secondary outcomes were responder rate, International League Against Epilepsy (ILAE) epilepsy surgery outcome, frequency of adverse events from any source and quality of life outcomes. We intended to analyse outcomes via an aggregated data fixed-effect model meta-analysis.

MAIN RESULTS

Two studies met the inclusion criteria. Both studies were small non-randomised trials, with no control group and no blinding. The quality of evidence for all outcomes was very low. The combination of these two studies resulted in 11 participants who prospectively used ictal HFOs for epilepsy surgery decision making. Results of the postsurgical seizure freedom Engel class I to IV outcome were determined over a period of 12 to 38 months (average 23.4 months) and indicated that six participants had an Engel class I outcome (seizure freedom), two had class II (rare disabling seizures), three had class III (worthwhile improvement). No adverse effects were reported. Neither study compared surgical results guided by HFOs versus surgical results guided without HFOs.

AUTHORS' CONCLUSIONS

No reliable conclusions can be drawn regarding the efficacy of using HFOs in epilepsy surgery decision making at present.

Novel frontiers in epilepsy treatments: preventing epileptogenesis by targeting inflammation

Currently available epilepsy drugs only affect the symptoms (seizures), and there is a need for innovative treatments that target the underlying disease. Increasing evidence points to inflammation as a potentially important mechanism in epileptogenesis. In the last decade, a new generation of etiologically realistic syndrome-specific experimental models have been developed, which are expected to capture the epileptogenic mechanisms operating in corresponding patient populations, and to exhibit similar treatment responsiveness. Recently, an intervention known to have broad-ranging anti-inflammatory effects (selective brain cooling) has been found to prevent the development of spontaneously occurring seizures in an etiologically realistic rat model of post-traumatic epilepsy. Several drugs used clinically for other indications also have the potential for inhibiting inflammation, and should be investigated for antiepileptogenic activity in these models. If results of such studies are positive, these compounds could rapidly enter Phase III trials in patients at high risk of developing epilepsy.

Epilepsy biomarkers

A biomarker is defined as an objectively measured characteristic of a normal or pathologic biologic process. Identification and proper validation of biomarkers of epileptogenesis (the development of epilepsy) and ictogenesis (the propensity to generate spontaneous seizures) might predict the development of an epilepsy condition; identify the presence and severity of tissue capable of generating spontaneous seizures; measure progression after the condition is established; and determine pharmacoresistance. Such biomarkers could be used to create animal models for more cost-effective screening of potential antiepileptogenic and antiseizure drugs and devices, and to reduce the cost of clinical trials by enriching the trial population, and acting as surrogate markers to shorten trial duration. The objectives of the biomarker subgroup for the London Workshop were to define approaches for identifying possible biomarkers for these purposes. Research to identify reliable biomarkers may also reveal underlying mechanisms that could serve as therapeutic targets for the development of new antiepileptogenic and antiseizure compounds.

Localizing epileptic seizure onsets with Granger causality

Accurate localization of the epileptic seizure onset zones (SOZs) is crucial for successful surgery, which usually depends on the information obtained from intracranial electroencephalography (IEEG) recordings. The visual criteria and univariate methods of analyzing IEEG recordings have not always produced clarity on the SOZs for resection and ultimate seizure freedom for patients. Here, to contribute to improving the localization of the SOZs and to understanding the mechanism of seizure propagation over the brain, we applied spectral interdependency methods to IEEG time series recorded from patients during seizures. We found that the high-frequency (>80 Hz) Granger causality (GC) occurs before the onset of any visible ictal activity and causal relationships involve the recording electrodes where clinically identifiable seizures later develop. These results suggest that high-frequency oscillatory network activities precede and underlie epileptic seizures, and that GC spectral measures derived from IEEG can assist in precise delineation of seizure onset times and SOZs.

Why is there still doubt to cut it out?

Surgical treatment for epilepsy has made tremendous strides in the past few decades as a result of advances in neurodiagnostics-particularly structural and functional neuroimaging-and improved surgical techniques. This has not only resulted in better outcomes with respect to epileptic seizures and quality of life, and reduced surgical morbidity and mortality, but it has also increased the population of patients now considered as surgical candidates, particularly in the pediatric age range, and enhanced cost-effectiveness sufficient to make surgical treatment available to countries with limited resources. Yet surgical treatment for epilepsy remains arguably the most underutilized of all accepted medical interventions. In the United States, less than 1% of patients with pharmacoresistant epilepsy are referred to epilepsy centers. Although the number of epilepsy surgery centers has increased appreciably over the past two decades, the number of therapeutic surgical procedures performed for epilepsy has not increased at all. For patients who are referred, the average delay from onset of epilepsy to surgery is more than 20 years-too late for many to avoid a lifetime of disability or premature death. Not only has there been no consistent message to convince neurologists and primary care physicians to refer patients for surgery, but the increase in epilepsy surgery centers in the United States has appeared to result in a divergence of approaches to surgical treatment. Efforts are still needed to further improve the safety and efficacy of surgical treatment, including the identification of biomarkers that can reliably determine the extent of the epileptogenic region; however, the greatest benefits would derive from increasing access for potential surgical candidates to epilepsy surgery facilities. Information is needed to determine why appropriate surgical referrals are not being made. Consensus conferences are necessary to resolve controversies that still exist regarding presurgical evaluation and surgical approaches. Standards should be established for certifying epilepsy centers as recommended by the Institute of Medicine's report on epilepsy. Finally, the epilepsy community should not be promoting epilepsy surgery per se but instead emphasize that epilepsy centers do more than epilepsy surgery, promoting the message: All patients with disabling pharmacoresistant seizures deserve evaluation by specialists at epilepsy centers who can provide a variety of advanced diagnostic and therapeutic services.

An algorithm for on-line detection of high frequency oscillations related to epilepsy

Recent studies suggest that the appearance of signals with high frequency oscillations components in specific regions of the brain is related to the incidence of epilepsy. These oscillations are in general small in amplitude and short in duration, making them difficult to identify. The analysis of these oscillations are particularly important in epilepsy and their study could lead to the development of better medical treatments. Therefore, the development of algorithms for detection of these high frequency oscillations is of great importance. In this work, a new algorithm for automatic detection of high frequency oscillations is presented. This algorithm uses approximate entropy and artificial neural networks to extract features in order to detect and classify high frequency components in electrophysiological signals. In contrast to the existing algorithms, the one proposed here is fast and accurate, and can be implemented on-line, thus reducing the time employed to analyze the experimental electrophysiological signals.

High-frequency oscillations - where we are and where we need to go

High-frequency oscillations (HFOs) are EEG field potentials with frequencies higher than 30 Hz; commonly the frequency band between 30 and 70 Hz is denominated the gamma band, but with the discovery of activities at frequencies higher than 70 Hz a variety of terms have been proposed to describe the latter (Gotman and Crone, 2011). In general we may consider that the term HFO encompasses activities from 30 to 600 Hz. The best practice is to indicate always explicitly the frequency range of the HFOs in any specific study. There are numerous types of HFOs: those in normal brain appear to facilitate synchronization and information transfer necessary for cognitive processes and memory, while a particular class of HFOs in the brain of animals and people with epilepsy appears to reflect fundamental mechanisms of epileptic phenomena and could serve as biomarkers of epileptogenesis and epileptogenicity in abnormal conditions such as epilepsy. A better understanding of the significance of HFOs depends on a deeper analysis of the mechanisms of generation of different kinds of HFOs, that typically are at the crossroads between intrinsic membrane properties and neuronal interactions, both chemical and electrical. There is still a lack of understanding of how specific information is carried by HFOs and can be operational in normal cognitive processes such as in working and long-term memory and abnormal conditions such as epilepsy. The complexity of these processes makes the development of relevant computational models of dynamical neuronal networks most compelling.

In search of epilepsy biomarkers in the immature brain: goals, challenges and strategies

Epilepsy and seizures are very common in the early years of life and are often associated with significant morbidity and mortality. Identification of biomarkers for the early detection of epileptogenicity, epileptogenesis, comorbidities, disease progression and treatment implementation will be very important in implementing more effective therapies. This article summarizes the current needs in the search for new early life epilepsy-related biomarkers and discusses the candidate biomarkers that are under investigation, as well as the challenges associated with the identification and validation of these biomarkers.