EEG-BIDS, an extension to the brain imaging data structure for electroencephalography

By Cyril R. Pernet, S. Appelhoff, Krzysztof J. Gorgolewski, Guillaume Flandin, Christophe L. M. Phillips, Arnaud Delorme, Robert Oostenveld. Scientific Data, 2019

389 citations recorded by the source corpus.

The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and references to a series of public EEG datasets organized using this new standard.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/45ef280a1e43e6f6ff72063346eb76ef6cbb4fc2

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

The OpenNeuro resource for sharing of neuroscience data (2021, positive): “…BIDS is quickly expanding to other modalities that can readily be uploaded to OpenNeuro, and there has been a rapid increase in sharing of other modalities; for example, more than 60 EEG datasets have been deposited since the publication of the BIDS-EEG standard in 2019 ( Pernet et al., 2019 ).”
The BRAIN Initiative data-sharing ecosystem: Characteristics, challenges, benefits, and opportunities (2024, unknown): “…is built into the BRAIN Initiative data-sharing ecosystem, for instance in the ability to store electrophysiology data in DABI, DANDI, or OpenNeuro and the extensions of the BIDS standards to EEG, iEEG, and MEG ( Holdgraf et al., 2019 ; Niso et al., 2018 ; Pernet et al., 2019 ) in 2018 and 2019.”
Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity (2024, unknown): “Fortunately, the Brain Imaging Data Structure (BIDS)(Gorgolewski et al., 2016), a community driven effort to standardize imaging data, already has specifications for iEEG (Holdgraf et al., 2019), EEG (Pernet et al., 2019) and MEG (Niso et al., 2018).”
Hierarchical Event Descriptor library schema for EEG data annotation (2023, unknown): “These annotations are based on terms and definitions provided by the ILAE and IFCN that can be used to characterize normal as well as pathological (ictal) EEG data as encapsulated in the Standardized Computer-based Organized Reporting of EEG (SCORE) 16 .”
Novel Verbal Instructions Recruit Abstract Neural Patterns of Time-Variable Information Dimensionality (2025, methodology): “The EEG signal was recorded at a 1000 Hz sampling rate, and data files were structured following EEG-BIDS (Pernet et al., 2019).”
Maximizing the potential of EEG as a developmental neuroscience tool (2023, methodology): “Moreover, when researchers leverage open-source tools, as opposed to proprietary software, and adopt standardized data formats (e.g., the Brain Imaging Data Structure; BIDS) (Gorgolewski et al., 2016; Meyer et al., 2021; Pernet et al., 2019), this further enhances the likelihood of widespread adopti”
A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment (2022, methodology): “We recommend that future research studies adhere with up to date EEG guidelines for recording, analysis, and reporting (Keil et al., 2014, 2022; Clayson et al., 2019; Pernet et al., 2019; Babiloni et al., 2020; Styles et al., 2021) and leverage open-source data processing pipelines for replication a”