Hierarchical Event Descriptor library schema for EEG data annotation
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arXiv
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| Autores principales: | , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866916456390721536 |
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| author | Hermes, Dora Attia, Tal Pal Beniczky, Sándor Bosch-Bayard, Jorge Delorme, Arnaud Lundstrom, Brian Nils Rogers, Christine Rampp, Stefan Shirazi, Seyed Yahya Truong, Dung Valdes-Sosa, Pedro Worrell, Greg Makeig, Scott Robbins, Kay |
| author_facet | Hermes, Dora Attia, Tal Pal Beniczky, Sándor Bosch-Bayard, Jorge Delorme, Arnaud Lundstrom, Brian Nils Rogers, Christine Rampp, Stefan Shirazi, Seyed Yahya Truong, Dung Valdes-Sosa, Pedro Worrell, Greg Makeig, Scott Robbins, Kay |
| contents | Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Sharing data enriched with standard terms can facilitate data exploration, from case studies to mega-analyses. The machine readability of such electrophysiological event annotations is essential for performing analyses efficiently across software tools and packages. Hierarchical Event Descriptors (HED) provide a framework for describing events in neuroscience experiments. HED library schemas extend the standard HED schema vocabulary to include specialized vocabularies, such as standardized clinical terms for electrophysiological events. The Standardized Computer-based Organized Reporting of EEG (SCORE) defines terms for annotating EEG events, including artifacts. This study developed a HED library schema for SCORE, making the terms machine-readable. 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 now use the HED-SCORE library schema to annotate and compute on electrophysiological data obtained from the human brain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_15173 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Hierarchical Event Descriptor library schema for EEG data annotation Hermes, Dora Attia, Tal Pal Beniczky, Sándor Bosch-Bayard, Jorge Delorme, Arnaud Lundstrom, Brian Nils Rogers, Christine Rampp, Stefan Shirazi, Seyed Yahya Truong, Dung Valdes-Sosa, Pedro Worrell, Greg Makeig, Scott Robbins, Kay Neurons and Cognition E.1 Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Sharing data enriched with standard terms can facilitate data exploration, from case studies to mega-analyses. The machine readability of such electrophysiological event annotations is essential for performing analyses efficiently across software tools and packages. Hierarchical Event Descriptors (HED) provide a framework for describing events in neuroscience experiments. HED library schemas extend the standard HED schema vocabulary to include specialized vocabularies, such as standardized clinical terms for electrophysiological events. The Standardized Computer-based Organized Reporting of EEG (SCORE) defines terms for annotating EEG events, including artifacts. This study developed a HED library schema for SCORE, making the terms machine-readable. 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 now use the HED-SCORE library schema to annotate and compute on electrophysiological data obtained from the human brain. |
| title | Hierarchical Event Descriptor library schema for EEG data annotation |
| topic | Neurons and Cognition E.1 |
| url | https://arxiv.org/abs/2310.15173 |