Hierarchical Event Descriptor library schema for EEG data annotation

Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Enriching data with standard terms facilitates data exploration, from case studies to mega-analyses. The machine readability of such electrophysiological event annotations is essential for performing automated analyses. The Hierarchical Event Descriptor (HED) framework provides a standard for describing events in neuroscience experiments but does not yet include terms for electrophysiological data features. The Standardized Computer-based Organized Reporting of EEG (SCORE) defines terms for EEG features but is not yet openly available in machine-readable format. This study therefore developed a HED library schema for SCORE: the HED-SCORE library schema. This library schema makes the SCORE terms machine-readable and searchable and extents the standard HED schema with a controlled hierarchical vocabulary to annotate electrophysiological events. We demonstrate that the HED-SCORE library schema can be used to annotate events in EEG data stored in the Brain Imaging Data Structure (BIDS). Clinicians and researchers worldwide can use the HED-SCORE library schema to annotate and compute on human electrophysiological data.

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Publication Details

Journal
Scientific Data
Published
2025-08-19
DOI
https://doi.org/10.1038/s41597-025-05791-2
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.43

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article

Hierarchical Event Descriptor library schema for EEG data annotation

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article

Hierarchical Event Descriptor library schema for EEG data annotation

Pedro A. Valdés‐Sosa, Stefan Rampp, Dung Truong, Jorge Bosch‐Bayard, Sándor Beniczky, Dora Hermes, Scott Makeig, Seyed Yahya Shirazi, Kay A. Robbins, Gregory A. Worrell, Brian N. Lundstrom, Tal Pal Attia, Arnaud Delorme, Christine Rogers
article en
1 citations

Abstract

Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Enriching data with standard terms facilitates data exploration, from case studies to mega-analyses. The machine readability of such electrophysiological event annotations is essential for performing automated analyses. The Hierarchical Event Descriptor (HED) framework provides a standard for describing events in neuroscience experiments but does not yet include terms for electrophysiological data features. The Standardized Computer-based Organized Reporting of EEG (SCORE) defines terms for EEG features but is not yet openly available in machine-readable format. This study therefore developed a HED library schema for SCORE: the HED-SCORE library schema. This library schema makes the SCORE terms machine-readable and searchable and extents the standard HED schema with a controlled hierarchical vocabulary to annotate electrophysiological events. We demonstrate that the HED-SCORE library schema can be used to annotate events in EEG data stored in the Brain Imaging Data Structure (BIDS). Clinicians and researchers worldwide can use the HED-SCORE library schema to annotate and compute on human electrophysiological data.

Scientific DataVol. 12(1)
Montreal Neurological Institute and Hospital (CA), Carl von Ossietzky Universität Oldenburg (DE), Mayo Clinic (US), Aarhus University Hospital (DK), University of California San Diego (US), Universitätsklinikum Erlangen (DE), Mayo Clinic in Arizona (US), Filadelfia (DK), Mayo Clinic in Florida (US), University Hospital in Halle (DE), BioElectronics (United States) (US), The University of Texas at San Antonio (US)
University of Electronic Science and Technology of China, National Institutes of Health, National Institute of Mental Health
Openalex Percentile: Top 16%
EEG and Brain-Computer Interfaces
1.43
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