HED test datasets

The hed-examples repository contains a set of HED-annotated datasets in BIDS-compatible format. These datasets can be useful for:

  1. Writing lightweight software tests.

  2. Serving as examples of how to incorporate HED into BIDS-structured data.

The datasets have empty raw data files. However, some data headers containing the metadata are still intact.

Datasets that are derived from datasets on OpenNeuro are identified by their OpenNeuro accession number plus ‘s’ plus a modifier. Datasets focused on particular a particular modality may have the modality prepended to the name. For example, eeg_ds003645s identifies a reduced dataset derived the EEG data in OpenNeuro dataset ds003645. The suffix modifier indicates what this dataset is designed to test.

Dataset

Description

OpenNeuro

eeg_ds002893s_hed_attention_shift

Shift between auditory and visual modalities.

ds002893

eeg_ds003645s_hed

Short-form tags with definitions.

ds003645

eeg_ds003645s_hed_column

Some events.tsv files contain a HED column.

eeg_ds003645s_hed_inheritance

Multiple sidecars with inheritance.

eeg_ds003645s_hed_library

Multiple HED library schemas.

eeg_ds003645s_hed_longform

Long-form with definitions.

eeg_ds004105s_hed_longform

BCIT auditory cueing

ds004105

eeg_ds004106s_hed_longform

BCIT advanced guard duty

ds004106

eeg_ds004117s_hed_sternberg

Sternberg working memory task

ds004117

fmri_ds002790s_hed_aomic

Annotation with single column.

ds002790

fmri_soccer21_hed

Annotation with single column.

eeg_ds002893s_hed

This dataset includes rapid shifts in instructed attention between visual and auditory modalities. The dataset is mentioned as an example in the OHBM 2022 tutorial Annotating the timeline of neuroimaging time series data using Hierarchical Event Descriptors.

eeg_ds003645s_hed

This dataset was originally released as multi-modal dataset ds000117 by Daniel Wakeman and Richard Henson. The dataset events in ds003645 have been reorganized from the original and additional events added from the experimental logs. The dataset includes MEEG and behavioral data. HED tags have been added.

The dataset is used as a HED case study in:

Robbins, K., Truong, D., Appelhoff, S., Delorme, A., & Makeig, S. (2021).
Capturing the nature of events and event context using Hierarchical Event Descriptors (HED).
Neuroimage 2021 Dec 15;245:118766. doi: 10.1016/j.neuroimage.2021.118766. Epub 2021 Nov 27.
https://www.sciencedirect.com/science/article/pii/S1053811921010387?via%3Dihub.

eeg_ds003645s_hed_column

This is a modification of ds003645s_hed where some events.tsv files contain a HED column.

eeg_ds003645s_hed_inheritance

This is a modification of ds003645s_hed where multiple sidecars containing HED tags are included to test that HED tools correctly handle BIDS inheritance rules.

eeg_ds003645s_hed_library

This dataset is designed to test the HED library schema facility. It uses HED 8.0.0 as a base schema and as the “test” library schema. In addition, this dataset uses the SCORE library version 1.0.0 as a library schema.

The schemas are specified in the dataset_description.json file.

eeg_ds003645s_hed_longform

This is a modification of ds003645s_hed where the HED tags include a mix of tags in long and short forms to test that tools work with either long-form or short-form HED tags.

eeg_ds004105s_hed

Subjects in the Auditory Cueing study performed a long-duration simulated driving task with perturbations and audio stimuli in a visually sparse environment. The dataset is part of a collection of 10 datasets from the BCIT program designed to test EEG mega-analysis.

eeg_ds004106s_hed

BCIT Advanced Guard Duty study was designed to measure sustained vigilance in realistic settings by having subjects verify information on replica ID badges. The dataset is part of a collection of 10 datasets from the BCIT program designed to test EEG mega-analysis.

eeg_ds004117s_hed_sternberg

Sternberg working memory dataset, described in Onton et al. 2005, is used in a number of HED case studies including the OHBM 2022 tutorial Annotating the timeline of neuroimaging time series data using Hierarchical Event Descriptors and the book chapter 2.3 End-to-end processing of M/EEG data with BIDS, HED, and EEGLAB by Thruong et al. in Methods for analyzing large neuroimaging datasets edited by Whelan and Lemaitre.

The study was also selected for replication in the EEGManyLabs initiative.

fmri_ds002790s_hed_aomic

This dataset is part of the Amsterdam OpenMRI Collection (AOMIC).

The dataset is used as a case study for the book chapter 2.4 Actionable event annotation and analysis in fMRI: A practical guide to event handling by Denissen et al. in Methods for analyzing large neuroimaging datasets edited by Whelan and Lemaitre.

fmri_soccer21_hed

This dataset is designed to illustrate a basic FMRI pipeline. The dataset is used as a case study for the book chapter 2.4 Actionable event annotation and analysis in fMRI: A practical guide to event handling by Denissen et al. in Methods for analyzing large neuroimaging datasets edited by Whelan and Lemaitre.

BIDS validation

For general information on the bids-validator, including installation, configuration, and usage, see the bids-validator README file.

Example: The following command validates the eeg_ds003645s_hed dataset:

bids-validator eeg_ds003645s_hed --config.ignore=99

This example assumes that npm and the bids-validator npm package have been installed on the local machine. The command is run from the directory above the dataset root directory. The --config.ignore=99 flag tells the bids-validator to ignore empty data files rather than to report the empty file error.

For additional information on BIDS validation, see the bids-examples.