Seizures can occur spontaneously and in a recurrent manner, which defines epilepsy; or they can be induced in a normal brain under a variety of conditions in most neuronal networks and species from flies to humans. Such universality raises the possibility that invariant properties exist that characterize seizures under different physiological and pathological conditions. Here, we analysed seizure dynamics mathematically and established a taxonomy of seizures based on first principles. For the predominant seizure class we developed a generic model called Epileptor. As an experimental model system, we used ictal-like discharges induced in vitro in mouse hippocampi. We show that only five state variables linked by integral-differential equations are sufficient to describe the onset, time course and offset of ictal-like discharges as well as their recurrence. Two state variables are responsible for generating rapid discharges (fast time scale), two for spike and wave events (intermediate time scale) and one for the control of time course, including the alternation between 'normal' and ictal periods (slow time scale). We propose that normal and ictal activities coexist: a separatrix acts as a barrier (or seizure threshold) between these states. Seizure onset is reached upon the collision of normal brain trajectories with the separatrix. We show theoretically and experimentally how a system can be pushed toward seizure under a wide variety of conditions. Within our experimental model, the onset and offset of ictal-like discharges are well-defined mathematical events: a saddle-node and homoclinic bifurcation, respectively. These bifurcations necessitate a baseline shift at onset and a logarithmic scaling of interspike intervals at offset. These predictions were not only confirmed in our in vitro experiments, but also for focal seizures recorded in different syndromes, brain regions and species (humans and zebrafish). Finally, we identified several possible biophysical parameters contributing to the five state variables in our model system. We show that these parameters apply to specific experimental conditions and propose that there exists a wide array of possible biophysical mechanisms for seizure genesis, while preserving central invariant properties. Epileptor and the seizure taxonomy will guide future modeling and translational research by identifying universal rules governing the initiation and termination of seizures and predicting the conditions necessary for those transitions.

Preparation of hippocampal slices and perfusionAll experiments were performed in the CA1 or CA3 regions of hippocampal brain slices prepared from Sprague-Dawley rats (175-250 g). Rats were anaesthetized with ethyl ether and decapitated. The experimental protocol was reviewed and approved by the Institution Animal Care and Use Committee. The brain was rapidly removed and one hemisphere glued to the stage of a Vibroslicer (Vibroslice, Campden Instruments Ltd, London, UK) Slicing was carried out in cold (3-4°C), oxygenated sucrose-based artificial cerebrospinal fluid (ACSF) consisting of (mM): sucrose 220, KCl 3, NaH 2 PO 4 1.25, MgSO 4 2, NaHCO 3 26, CaCl 2 2, dextrose 10. The resulting 350 mm thick slices were immediately transferred to a holding chamber with 'normal' ACSF consisting of (mM): NaCl 124, KCl 3.75, KH 2 PO 4 1.25, CaCl 2 2, MgSO 4 2, NaHCO 3 26, dextrose 10, held at room temperature and bubbled with 95 % O 2 -5 % CO 2 .

Sinusoidal high frequency (20‐50 Hz) electric fields induced across rat hippocampal slices were found to suppress zero‐Ca2+, low‐Ca2+, picrotoxin, and high‐K+ epileptiform activity for the duration of the stimulus and for up to several minutes following the stimulus. Suppression of spontaneous activity by high frequency stimulation was found to be frequency (< 500 Hz) but not orientation or waveform dependent. Potassium‐sensitive microelectrodes showed that block of epileptiform activity was always coincident with a stimulus‐induced rise in extracellular potassium concentration during stimulation. Post‐stimulus inhibition was always associated with a decrease in extracellular potassium activity below baseline levels. Intracellular recordings and optical imaging with voltage‐sensitive dyes showed that during suppression neurons were depolarized yet did not fire action potentials. Direct injection of sinusoidal current into individual pyramidal cells did not result in a tonic depolarization. Injection of large direct current (DC) depolarized neurons and suppressed action potential generation. These findings suggest that high frequency stimulation suppresses epileptiform activity by inducing potassium efflux and depolarization block.

Objective Interictal high frequency oscillations (HFOs) in intracranial EEG are a potential biomarker of epilepsy, but current automated HFO detectors require human review to remove artifacts. Our objective is to automatically redact false HFO detections, facilitating clinical use of interictal HFOs. Methods Intracranial EEG data from 23 patients were processed with automated detectors of HFOs and artifacts. HFOs not concurrent with artifacts were labeled quality HFOs (qHFOs). Methods were validated by human review on a subset of 2,000 events. The correlation of qHFO rates with the seizure onset zone (SOZ) was assessed via 1) a retrospective asymmetry measure and 2) a novel quasi-prospective algorithm to identify SOZ. Results Human review estimated that less than 12% of qHFOs are artifacts, whereas 78.5% of redacted HFOs are artifacts. The qHFO rate was more correlated with SOZ (p=0.020, Wilcoxon signed rank test) and resected volume (p=0.0037) than baseline detections. Using qHFOs, our algorithm was able to determine SOZ in 60% of the ILAE Class I patients, with all algorithmically-determined SOZs fully within the resected volumes. Conclusions The algorithm reduced false-positive HFO detections, improving the precision of the HFO-biomarker. Significance These methods provide a feasible strategy for HFO detection in real-time, continuous EEG with minimal human monitoring of data quality.

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

Despite substantial innovations in antiepileptic drug therapy over the past 15 years, the proportion of patients with uncontrolled epilepsy has not changed, highlighting the need for new treatment strategies. New implantable antiepileptic devices, which are currently under development and in pivotal clinical trials, hold great promise for improving the quality of life of millions of people with epileptic seizures worldwide. A broad range of strategies to stop seizures is currently being investigated, with various modes of control and intervention. The success of novel antiepileptic devices rests upon collaboration between neuroengineers, physicians and industry to adapt new technologies for clinical use. The initial results with these technologies are exciting, but considerable development and controlled clinical trials will be required before these treatments earn a place in our standard of clinical care.

Transient high-frequency (100-500 Hz) oscillations of the local field potential have been studied extensively in human mesial temporal lobe. Previous studies report that both ripple (100-250 Hz) and fast ripple (250-500 Hz) oscillations are increased in the seizure-onset zone of patients with mesial temporal lobe epilepsy. Comparatively little is known, however, about their spatial distribution with respect to seizure-onset zone in neocortical epilepsy, or their prevalence in normal brain. We present a quantitative analysis of high-frequency oscillations and their rates of occurrence in a group of nine patients with neocortical epilepsy and two control patients with no history of seizures. Oscillations were automatically detected and classified using an unsupervised approach in a data set of unprecedented volume in epilepsy research, over 12 terabytes of continuous long-term micro- and macro-electrode intracranial recordings, without human preprocessing, enabling selection-bias-free estimates of oscillation rates. There are three main results: (i) a cluster of ripple frequency oscillations with median spectral centroid = 137 Hz is increased in the seizure-onset zone more frequently than a cluster of fast ripple frequency oscillations (median spectral centroid = 305 Hz); (ii) we found no difference in the rates of high frequency oscillations in control neocortex and the non-seizure-onset zone neocortex of patients with epilepsy, despite the possibility of different underlying mechanisms of generation; and (iii) while previous studies have demonstrated that oscillations recorded by parenchyma-penetrating micro-electrodes have higher peak 100-500 Hz frequencies than penetrating macro-electrodes, this was not found for the epipial electrodes used here to record from the neocortical surface. We conclude that the relative rate of ripple frequency oscillations is a potential biomarker for epileptic neocortex, but that larger prospective studies correlating high-frequency oscillations rates with seizure-onset zone, resected tissue and surgical outcome are required to determine the true predictive value.

The rate of interictal high frequency oscillations (HFOs) is a promising biomarker of the seizure onset zone, though little is known about its consistency over hours to days. Here we test whether the highest HFO-rate channels are consistent across different 10-min segments of EEG during sleep. An automated HFO detector and blind source separation are applied to nearly 3000 total hours of data from 121 subjects, including 12 control subjects without epilepsy. Although interictal HFOs are significantly correlated with the seizure onset zone, the precise localization is consistent in only 22% of patients. The remaining patients either have one intermittent source (16%), different sources varying over time (45%), or insufficient HFOs (17%). Multiple HFO networks are found in patients with both one and multiple seizure foci. These results indicate that robust HFO interpretation requires prolonged analysis in context with other clinical data, rather than isolated review of short data segments.