HFOApp

HFOApp detects and annotates high-frequency oscillations (HFOs) in intracranial electroencephalographic (iEEG) recordings to identify and characterize epileptogenic tissue for epilepsy research and surgical planning.

Key Features:

• MATLAB implementation: Implemented in MATLAB for computational processing of iEEG data.
• Interactive automation-assist: Combines automated detection with manual marking to support reviewer-guided annotation.
• Manual marking capabilities: Enables manual annotation and refinement of detected HFO events.
• Simultaneous multichannel detection and marking: Performs detection and marking across multiple channels concurrently for multichannel electrophysiological datasets.
• Time and reliability improvement: Aims to reduce review and manual annotation time and to improve inter-rater reliability.
• HFO biomarker targeting: Specifically targets high-frequency oscillations as biomarkers of epileptogenic tissue in iEEG recordings.

Scientific Applications:

• Epileptogenic zone localization: Identification and characterization of HFOs in iEEG recordings to inform surgical planning and localize epileptogenic tissue.
• Treatment efficacy assessment: Quantification of HFOs to assess treatment effects and surgical outcomes.
• Electrophysiological research: Streamlining marking and quantification of HFOs to facilitate analysis of electrophysiological datasets and study of epileptogenic mechanisms.

Methodology:

Implemented in MATLAB; integrates automated detection with manual marking and supports simultaneous multichannel detection and marking of HFOs in iEEG recordings.