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High-frequency oscillations (HFOs) are associated with normal brain function, but are also increasingly recognized as potential biomarkers of epileptogenic tissue. Considering the important role of interneuron activity in physiological HFO generation, we studied their modulation by midazolam (MDZ), an agonist of γ-aminobutyric acid type A (GABA A )-benzodiazepine receptors. Here, we analyzed 80 intracranial electrode contacts in amygdala and hippocampus of 13 patients with drug-refractory focal epilepsy who had received MDZ for seizure termination during presurgical monitoring. Ripples (80-250 Hz) and fast ripples (FRs; 250-400 Hz) were compared before and after seizures with MDZ application, and according to their origin either within or outside the individual seizure onset zone (SOZ). We found that MDZ distinctly suppressed all HFOs (ripples and FRs), whereas the reduction of ripples was significantly less pronounced inside the SOZ compared to non-SOZ contacts. The rate of FRs inside the SOZ was less affected, especially in hippocampal contacts. In a few cases, even a marked increase of FRs following MDZ administration was seen. Our results demonstrate, for the first time, a significant HFO modulation in amygdala and hippocampus by MDZ, thus giving insights into the malfunction of GABA-mediated inhibition within epileptogenic areas and its role in HFO generation., (© 2024 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Objective: Technology for localizing epileptogenic brain regions plays a central role in surgical planning. Recent improvements in acquisition and electrode technology have revealed that high-frequency oscillations (HFOs) within the 80-500 Hz frequency range provide the neurophysiologist with new information about the extent of the epileptogenic tissue in addition to ictal and interictal lower frequency events. Nevertheless, two decades after their discovery there remain questions about HFOs as biomarkers of epileptogenic brain and there use in clinical practice., Methods: In this review, we provide practical, technical guidance for epileptologists and clinical researchers on recording, evaluation, and interpretation of ripples, fast ripples, and very high-frequency oscillations., Results: We emphasize the importance of low noise recording to minimize artifacts. HFO analysis, either visual or with automatic detection methods, of high fidelity recordings can still be challenging because of various artifacts including muscle, movement, and filtering. Magnetoencephalography and intracranial electroencephalography (iEEG) recordings are subject to the same artifacts., Significance: High-frequency oscillations are promising new biomarkers in epilepsy. This review provides interested researchers and clinicians with a review of current state of the art of recording and identification and potential challenges to clinical translation., (Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.)

From the very beginning the seizure prediction community faced problems concerning evaluation, standardization, and reproducibility of its studies. One of the main reasons for these shortcomings was the lack of access to high-quality long-term electroencephalography (EEG) data. In this article we present the EPILEPSIAE database, which was made publicly available in 2012. We illustrate its content and scope. The EPILEPSIAE database provides long-term EEG recordings of 275 patients as well as extensive metadata and standardized annotation of the data sets. It will adhere to the current standards in the field of prediction and facilitate reproducibility and comparison of those studies. Beyond seizure prediction, it may also be of considerable benefit for studies focusing on seizure detection, basic neurophysiology, and other fields., (Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.)

Purpose: Analysis of the EEG signal has recently shown evidence of dynamic changes preceding ictal onset in seizures selected from patients with clear epileptogenic foci. Most of the studies were conducted in highly selected EEG epochs and patients. In addition, these studies relied mostly on mathematical approaches and neglected clinical and visual EEG parameters. We therefore performed a systematic comparison of a nonlinear method (the similarity measure) with classic visual inspection of the EEG and the patient's clinical state., Methods: We analyzed the dynamics of long epochs of intracranial EEG containing 129 electroclinical and 45 electrographic seizures in 13 successive unselected patients undergoing presurgical evaluation., Results: (a) The similarity measure detected preictal dynamical changes of the EEG signal in two thirds of the seizures whether or not a clear focus was identified, and whether seizures were electroclinical or purely electrographic. The mean duration of preictal changes was 12 min. (b) The preictal changes were correlated with various visually detectable EEG changes in 78.9% of electroclinical seizures. (c) 81.5% of the preictal dynamic changes were correlated with changes of vigilance or behavior. (d) Fluctuations of the dynamics were not necessarily followed by seizures., Conclusions: Our results indicate that EEG dynamics frequently change before seizures. These preictal changes are most often associated with the EEG changes accompanying transitions between states of vigilance. The preictal dynamic changes may represent physiologic changes acting as facilitating factors or pathologic changes reflecting a network dysfunction.

Although considerable information on cellular and network mechanisms of epilepsy exists, it is still not understood why, how, and when the transition from interictal to ictal state takes place. The authors review their work on nonlinear EEG analysis and provide consistent evidences that dynamical changes in the neural activity allows the characterization of a preictal state several minutes before seizure onset. This new neurodynamical approach of ictogenesis opens new perspectives for studying the basic mechanisms in epilepsy as well as for possible therapeutic interventions.