Citations

Ultrafast oscillations (UFOs) are brief bursts of high-frequency (2–8 kHz) activity recorded using depth electrodes in epileptic brain tissue. While reliably detected at small scales using microelectrodes, UFOs have thus far likely not been observed at larger scales using macroelectrodes. Here we show that faint echoes of these bursting patterns can be detected in macroelectrode signals using a model of cross-scale propagation. To model this cross-scale effect, we extend the classical damped wave equation to include an explicit scale coordinate governed by the dilation operator. We then use Green's functions to obtain an expression for the spectral echo expected at the macroelectrode scale. This echo takes the form of a carrier envelope modulated by the temporal structure of the original microscale bursting event. We test the predicted signature echo pattern in human intracranial recordings from eleven epilepsy patients implanted with both micro- and macroelectrodes. Statistically significant echoes are confirmed in two out of eleven patients, appearing in 2% of all tested micro-macro pairs.

Abstract Objective The upper frequency limit of human brain activity remains unknown. Using ultrahigh sampling rate (≥20 kHz) intracranial microelectroencephalography, this study aimed to systematically explore and quantitatively characterize brain field oscillations beyond the established high‐frequency oscillation range (>2 kHz), and to determine their relationship to epileptogenic tissue. Methods We analyzed intracranial electroencephalographic recordings from 15 patients with drug‐resistant epilepsy, comprising 466 microcontacts and 434 macrocontacts implanted in mesiotemporal structures across four international epilepsy centers. A custom spectrogram‐based detector optimized for ultrahigh frequencies was developed to identify ultrafast oscillations (UFOs; >2 kHz). UFO rates were assessed in epileptic (successfully resected) and nonepileptic hippocampi and compared with established electrophysiological biomarkers, including interictal epileptiform discharges, ripples, and fast ripples. Statistical comparisons were performed using mixed‐effects models to account for intersubject and interelectrode variability. Results We identified a previously undescribed class of short‐duration oscillatory events spanning 2–8 kHz. UFOs occurred at significantly higher rates in epileptic compared with nonepileptic mesiotemporal regions, with the strongest differentiation observed in the 2–3‐kHz band. Two distinct UFO phenotypes were consistently observed: (1) spindlelike, narrow‐band oscillations and (2) sharp‐onset, rapidly decaying bursts. Both forms were prevalent within epileptic hippocampi but were exceedingly rare in nonepileptic structures. UFOs exhibited pronounced temporal intermittency and spatial focality and frequently arose independently of ripples, fast ripples, and very high‐frequency oscillations, indicating that they represent a distinct electrophysiological phenomenon. Macrocontacts detected UFOs only exceptionally, highlighting the necessity of microelectrode recordings to capture activity in this ultrahigh‐frequency regime. Significance These findings substantially extend the known frequency range of human brain field activity and identify ultrafast oscillations as a novel biomarker of neuronal hyperexcitability. UFOs likely reflect pathological microcircuit dynamics inaccessible to conventional clinical recordings and provide new insights into the organization and pathophysiology of epileptogenic networks.

Abstract Objective Memory impairments are common in neurological disorders, especially drug‐resistant epilepsy, where cognitive deficits such as accelerated long‐term forgetting may occur before surgery due to interictal/ictal discharges, antiseizure medications, and disease progression. Postsurgical memory decline affects 40%–60% of patients. Understanding the neural mechanisms of memory encoding is essential for identifying critical network hubs and guiding surgical interventions that preserve cognitive function. Methods We analyzed intracranial electroencephalographic recordings from epilepsy patients ( n = 15) performing a verbal memory encoding task to identify key structures involved in successful memory formation. Functional connectivity was computed using multiple features across several frequency bands. Temporal dynamics of connectivity were examined to characterize pre‐encoding and encoding phases. Results The middle temporal gyrus (MTG) consistently emerged as a verbal memory hub across features and frequency bands. The inferior frontal gyrus (IFG) was identified as a beta‐band‐specific hub via phase synchrony. Temporal analyses revealed that MTG exhibited stable and widespread connectivity differences across all encoding phases, suggesting a role in pre‐encoding network priming. In contrast, IFG displayed a transient decrease in connectivity and spatial extent during early encoding, indicating a more focal and dynamic contribution. Significance These findings suggest that successful memory encoding relies on widespread, frequency‐specific connectivity patterns centered on MTG, complemented by transient, localized IFG activity. Identifying such hubs may inform surgical planning by highlighting regions critical for cognitive outcomes, ultimately supporting strategies to preserve memory in epilepsy surgery.

Abstract Precise localization of the epileptogenic zone is pivotal for planning minimally invasive surgeries in drug-resistant epilepsy. Here, we present a graph neural network (GNN) framework that integrates interictal intracranial EEG features, electrode topology, and MRI features to automate epilepsy surgery planning. We retrospectively evaluated the model using leave-one-patient-out cross-validation on a dataset of 80 drug-resistant epilepsy patients treated at St. Anne's University Hospital (Brno, Czech Republic), comprising 31 patients with good postsurgical outcomes (Engel I) and 49 with poor outcomes (Engel II–IV). The GNN predictions demonstrated a significantly better (P < 0.05, Mann–Whitney-U test) area under the precision-recall curve in patients with good outcomes (area under the precision-recall curve: 0.69) compared with those with poor outcomes (area under the precision-recall curve: 0.33), indicating that the model captures clinically relevant targets in successful cases. In patients with poor outcomes, the graph neural network proposed alternative intervention sites that diverged from the original clinical plans, highlighting its potential to identify alternative therapeutic targets. We show that topology-aware GNNs significantly outperformed (P < 0.05, Wilcoxon signed-rank test) traditional neural networks while using the same intracranial EEG features, emphasizing the importance of incorporating implantation topology into predictive models. These findings uncover the potential of GNNs to automatically suggest targets for epilepsy surgery, which can assist the clinical team during the planning process.

Abstract Oscillations in the high gamma and ripple frequency ranges are known to coordinate local hippocampal and neocortical neuronal assemblies during memory encoding and recall. Here, we explored spatiotemporal dynamics and the role of global coordination of these fast oscillatory discharges across the sensory and associational cortical areas in distinct phases of memory processing. Individual bursts of high frequency oscillations were detected in intracranial recordings from epilepsy patients remembering word lists for immediate free recall. We found constant coincident bursting across visual and higher order processing areas, peaking before recall and elevated during encoding of words. This global co-bursting was modulated by memory processing, engaged approximately half of the recorded electrode sites, and clustered into a sequence of multiple consecutive bursting discharges. Our results suggest a general role of global coincident high frequency oscillations in organizing large-scale information processing across the brain necessary especially, but not exclusively, for memory functions.

Abstract Despite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected in the human mesial temporal lobe and neocortical intracranial recordings spanning gamma/epsilon (60–150 Hz), ripple (80–250 Hz) and higher frequency ranges. Separate from other non-oscillatory activities, these brief electrophysiological oscillations of distinct duration, frequency and amplitude are thought to be generated by coordinated spiking of neuronal ensembles within volumes as small as a single cortical column. Although the exact origins, mechanisms and physiological roles in health and disease remain elusive, they have been associated with human memory consolidation and cognitive processing. Recent studies suggest their involvement in encoding and recall of episodic memory with a possible role in the formation and reactivation of memory traces. High frequency oscillations are detected during encoding, throughout maintenance, and right before recall of remembered items, meeting a basic definition for an engram activity. The temporal coordination of high frequency oscillations reactivated across cortical and subcortical neural networks is ideally suited for integrating multimodal memory representations, which can be replayed and consolidated during states of wakefulness and sleep. High frequency oscillations have been shown to reflect coordinated bursts of neuronal assembly firing and offer a promising substrate for tracking and modulation of the hypothetical electrophysiological engram.

AbstractObjectiveHigh‐frequency oscillations are considered among the most promising interictal biomarkers of the epileptogenic zone in patients suffering from pharmacoresistant focal epilepsy. However, there is no clear definition of pathological high‐frequency oscillations, and the existing detectors vary in methodology, performance, and computational costs. This study proposes relative entropy as an easy‐to‐use novel interictal biomarker of the epileptic tissue.MethodsWe evaluated relative entropy and high‐frequency oscillation biomarkers on intracranial electroencephalographic data from 39 patients with seizure‐free postoperative outcome (Engel Ia) from three institutions. We tested their capability to localize the epileptogenic zone, defined as resected contacts located in the seizure onset zone. The performance was compared using areas under the receiver operating curves (AUROCs) and precision‐recall curves. Then we tested whether a universal threshold can be used to delineate the epileptogenic zone across patients from different institutions.ResultsRelative entropy in the ripple band (80–250 Hz) achieved an average AUROC of .85. The normalized high‐frequency oscillation rate in the ripple band showed an identical AUROC of .85. In contrast to high‐frequency oscillations, relative entropy did not require any patient‐level normalization and was easy and fast to calculate due to its clear and straightforward definition. One threshold could be set across different patients and institutions, because relative entropy is independent of signal amplitude and sampling frequency.SignificanceAlthough both relative entropy and high‐frequency oscillations have a similar performance, relative entropy has significant advantages such as straightforward definition, computational speed, and universal interpatient threshold, making it an easy‐to‐use promising biomarker of the epileptogenic zone.

Abstract The objective of this clinical practice guideline (CPG) is to provide recommendations for healthcare personnel working with patients with epilepsy on the use of wearable devices for automated seizure detection in patients with epilepsy, in outpatient, ambulatory settings. The Working Group of the International League Against Epilepsy (ILAE) and the International Federation of Clinical Neurophysiology (IFCN) developed the CPG according to the methodology proposed by the ILAE Epilepsy Guidelines Working Group. We reviewed the published evidence using The Preferred Reporting Items for Systematic Review and Meta‐Analysis (PRISMA) statement and evaluated the evidence and formulated the recommendations following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We found high level of evidence for the accuracy of automated detection of generalized tonic‐clonic seizures (GTCS) and focal‐to‐bilateral tonic‐clonic seizures (FBTCS) and recommend the use of wearable automated seizure detection devices for selected patients when accurate detection of GTCS and FBTCS is recommended as a clinical adjunct. We also found a moderate level of evidence for seizure types without GTCS or FBTCS. However, it was uncertain whether the detected alarms resulted in meaningful clinical outcomes for the patients. We recommend using clinically validated devices for automated detection of GTCS and FBTCS, especially in unsupervised patients, where alarms can result in rapid intervention (weak/conditional recommendation). At present, we do not recommend clinical use of the currently available devices for other seizure types (weak/conditional recommendation). Further research and development are needed to improve the performance of automated seizure detection and to document their accuracy and clinical utility.

ObjectiveIn the present study, we aimed to investigate depth electroencephalographic (EEG) recordings in a large cohort of patients with drug‐resistant epilepsy and to focus on interictal very high‐frequency oscillations (VHFOs) between 500Hz and 2kHz. We hypothesized that interictal VHFOs are more specific biomarkers for epileptogenic zone compared to traditional HFOs.MethodsForty patients with focal epilepsy who underwent presurgical stereo‐EEG (SEEG) were included in the study. SEEG data were recorded with a sampling rate of 25kHz, and a 30‐minute resting period was analyzed for each patient. Ten patients met selected criteria for analyses of correlations with surgical outcome: detection of interictal ripples (Rs), fast ripples (FRs), and VHFOs; resective surgery; and at least 1 year of postoperative follow‐up. Using power envelope computation and visual inspection of power distribution matrixes, electrode contacts with HFOs and VHFOs were detected and analyzed.ResultsInterictal very fast ripples (VFRs; 500–1,000Hz) were detected in 23 of 40 patients and ultrafast ripples (UFRs; 1,000–2,000Hz) in almost half of investigated subjects (n = 19). VFRs and UFRs were observed only in patients with temporal lobe epilepsy and were recorded exclusively from mesiotemporal structures. The UFRs were more spatially restricted in the brain than lower‐frequency HFOs. When compared to R oscillations, significantly better outcomes were observed in patients with a higher percentage of removed contacts containing FRs, VFRs, and UFRs.InterpretationInterictal VHFOs are relatively frequent abnormal phenomena in patients with epilepsy, and appear to be more specific biomarkers for epileptogenic zone when compared to traditional HFOs. Ann Neurol 2017;82:299–310