ArticleeNeuro
HFOApp: A MATLAB Graphical User Interface for High-Frequency Oscillation Marking.
Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Time-frequency characteristics of scalp high-frequency oscillations provide complementary biomarkers in infantile epileptic spasms syndrome.Experimental physiology · 2026Article
- Phenotypic Classification of Scalp High-Frequency Oscillations in Absence Epilepsy Based on Multiple Characteristics Using K-Means Clustering.Bioengineering (Basel, Switzerland) · 2026Article
- Opposing interictal dynamics in Alzheimer's disease and epilepsy.Progress in neurobiology · 2026Article
- High-frequency oscillations >250 Hz in people with Down syndrome and associated Alzheimer's disease dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Predicting seizure onset zones from interictal intracranial EEG using functional connectivity and machine learning.Scientific reports · 2025Article
- Association Between Scalp High-Frequency Oscillations and Burden of Amplitudes and Epileptiform Discharges (BASED) Scores in Infantile Epileptic Spasms Syndrome.Biomolecules · 2025Article
- Mesoscale insights in Epileptic Networks: A Multimodal Intracranial Dataset.Scientific data · 2025Article
- The role of electroencephalography in epilepsy research-From seizures to interictal activity and comorbidities.Epilepsia · 2025Review
- The appearance of scalp high-frequency oscillations is associated with poor seizure control in pediatric epilepsy patients.Epilepsia open · 2025Article
- Timing differences between HFOs and interictal epileptiform discharges generated in vitro by different mechanisms in rat hippocampal slices: A novel approach.Epilepsia open · 2022Article
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Authors and funding
9 authors.
Funding
Abstract
Epilepsy affects 3.4 million people in the United States, and, despite the availability of numerous antiepileptic drugs, 36% of patients have uncontrollable seizures, which severely impact quality of life. High-frequency oscillations (HFOs) are a potential biomarker of epileptogenic tissue that could be useful in surgical planning. As a result, research into the efficacy of HFOs as a clinical tool has increased over the last 2 decades. However, detection and identification of these transient rhythms in intracranial electroencephalographic recordings remain time-consuming and challenging. Although automated detection algorithms have been developed, their results are widely inconsistent, reducing reliability. Thus, manual marking of HFOs remains the gold standard, and manual review of automated results is required. However, manual marking and review are time consuming and can still produce variable results because of their subjective nature and the limitations in functionality of existing open-source software. Our goal was to develop a new software with broad application that improves on existing open-source HFO detection applications in usability, speed, and accuracy. Here, we present HFOApp: a free, open-source, easy-to-use MATLAB-based graphical user interface for HFO marking. This toolbox offers a high degree of intuitive and ergonomic usability and integrates interactive automation-assist options with manual marking, significantly reducing the time needed for review and manual marking of recordings, while increasing inter-rater reliability. The toolbox also features simultaneous multichannel detection and marking. HFOApp was designed as an easy-to-use toolbox for clinicians and researchers to quickly and accurately mark, quantify, and characterize HFOs within electrophysiological datasets.
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Registered trials
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