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用于脑电图(EEG)数据标注的分层事件描述符库模式。

Hierarchical Event Descriptor library schema for EEG data annotation.

作者信息

Hermes Dora, Pal Attia Tal, 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

机构信息

Multimodal Neuroimaging Laboratory, Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA.

The Danish Epilepsy Centre, Filadelfia, Denmark.

出版信息

Sci Data. 2025 Aug 19;12(1):1448. doi: 10.1038/s41597-025-05791-2.

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.

摘要

标准化用于注释电生理事件的术语可以改善计算研究和临床护理。使用标准术语丰富数据有助于从案例研究到大型分析的数据探索。这种电生理事件注释的机器可读性对于执行自动化分析至关重要。分层事件描述符(HED)框架为描述神经科学实验中的事件提供了一个标准,但尚未包括电生理数据特征的术语。基于计算机的标准化脑电图有组织报告(SCORE)定义了脑电图特征的术语,但尚未以机器可读格式公开提供。因此,本研究为SCORE开发了一个HED库模式:HED-SCORE库模式。这个库模式使SCORE术语具有机器可读性和可搜索性,并用一个受控的分层词汇扩展了标准HED模式,以注释电生理事件。我们证明,HED-SCORE库模式可用于注释存储在脑成像数据结构(BIDS)中的脑电图数据中的事件。全球的临床医生和研究人员可以使用HED-SCORE库模式对人类电生理数据进行注释和计算。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0a/12365201/233f83006f69/41597_2025_5791_Fig1_HTML.jpg

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