ArticleJournal of neurophysiology2013
Temporal changes of neocortical high-frequency oscillations in epilepsy.
Article in Journal of neurophysiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
42 citing papers in PubMed, 2 syntheses or guidelines pooled it, 66 citations in OpenAlex.
- The role of high-frequency oscillations in epilepsy surgery planning.The Cochrane database of systematic reviews · 2017Pooled it
- The role of high-frequency oscillations in epilepsy surgery planning.The Cochrane database of systematic reviews · 2014Pooled it
- Common Data Elements for Preclinical High-Frequency Oscillations in Epilepsy.Epilepsy currents · 2026Review
- Article
- Dysfunction of GABAergic interneurons underlies altered neural network oscillations associated with epileptiform activity in PPT1-deficient mice.Translational psychiatry · 2026Article
- Integrating data across oscillatory power bands predicts the seizure onset zone in focal epilepsies.Brain communications · 2026Article
- AI-based localization of the epileptogenic zone using intracranial EEG.Epilepsia open · 2025Review
- Optimizing automated detection of high frequency oscillations using visual markings does not improve SOZ localization.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2024Article
- Generalisability of epileptiform patterns across time and patients.Scientific reports · 2024Article
- Networks through the lens of high-frequency oscillations.Frontiers in network physiology · 2024Review
- Temporal stability of intracranial electroencephalographic abnormality maps for localizing epileptogenic tissue.Epilepsia · 2023Article
- Mesial-Temporal Epileptic Ripples Correlate With Verbal Memory Impairment.Frontiers in neurology · 2022Article
- Physiological Ripples Associated With Sleep Spindles Can Be Identified in Patients With Refractory Epilepsy Beyond Mesio-Temporal Structures.Frontiers in neurology · 2021Article
- Application of High-Frequency Oscillations on Scalp EEG in Infant Spasm: A Prospective Controlled Study.Frontiers in human neuroscience · 2021Article
- Ictal Occurrence of High-Frequency Oscillations Correlates With Seizure Severity in a Rat Model of Temporal Lobe Epilepsy.Frontiers in human neuroscience · 2021Article
- Article
- Trends in the use of automated algorithms for the detection of high-frequency oscillations associated with human epilepsy.Epilepsia · 2020Review
- Detection of anomalous high-frequency events in human intracranial EEG.Epilepsia open · 2020Article
- Deep Convolutional Neural Network Based Interictal-Preictal Electroencephalography Prediction: Application to Focal Cortical Dysplasia Type-II.Frontiers in neurology · 2020Article
- Viability of Preictal High-Frequency Oscillation Rates as a Biomarker for Seizure Prediction.Frontiers in human neuroscience · 2020Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
High-frequency (100-500 Hz) oscillations (HFOs) recorded from intracranial electrodes are a potential biomarker for epileptogenic brain. HFOs are commonly categorized as ripples (100-250 Hz) or fast ripples (250-500 Hz), and a third class of mixed frequency events has also been identified. We hypothesize that temporal changes in HFOs may identify periods of increased the likelihood of seizure onset. HFOs (86,151) from five patients with neocortical epilepsy implanted with hybrid (micro + macro) intracranial electrodes were detected using a previously validated automated algorithm run over all channels of each patient's entire recording. HFOs were characterized by extracting quantitative morphologic features and divided into four time epochs (interictal, preictal, ictal, and postictal) and three HFO clusters (ripples, fast ripples, and mixed events). We used supervised classification and nonparametric statistical tests to explore quantitative changes in HFO features before, during, and after seizures. We also analyzed temporal changes in the rates and proportions of events from each HFO cluster during these periods. We observed patient-specific changes in HFO morphology linked to fluctuation in the relative rates of ripples, fast ripples, and mixed frequency events. These changes in relative rate occurred in pre- and postictal periods up to thirty min before and after seizures. We also found evidence that the distribution of HFOs during these different time periods varied greatly between individual patients. These results suggest that temporal analysis of HFO features has potential for designing custom seizure prediction algorithms and for exploring the relationship between HFOs and seizure generation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.