This repository contains user supporting code and documentation for using the Hierarchical Event Descriptor (HED) system for annotating, summarizing, and analyzing data.
The datasets subdirectory contains HED-annotated datasets in BIDS-compatible format. These datasets can be useful for:
- Writing lightweight software tests.
- 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 a particular modality may have the modality prepended to the name.
For example, eeg_ds003645s identifies a reduced dataset derived from the EEG data
in OpenNeuro dataset ds003645.
The suffix modifier indicates what this dataset is designed to test.
| Dataset | Description |
|---|---|
| eeg_ds002893s_hed_attention_shift | Auditory-visual attention shift data. Illustrates remapping of multiple event columns. |
| eeg_ds003645s_hed | Face Perception data using short form tags and definitions. |
| eeg_ds003645s_hed_column | Face Perception data to test annotations in HED column. |
| eeg_ds003645s_hed_demo | Face Perception data demonstrating full usage of HED in tsv. |
| eeg_ds003645s_hed_library | Face Perception data using HED libraries. |
| eeg_ds003645s_hed_partnered | Face Perception data using HED partnered libraries. |
| eeg_ds003645s_hed_remodel | Face Perception data in remodeling. |
| eeg_ds004105s_hed | BCIT Driving with auditory cueing data. Part of a test data corpus for BIDS-MEGA testing. |
| eeg_ds004106s_hed | BCIT Advanced guard duty data. Part of a test data corpus for BIDS-MEGA testing. |
| eeg_ds004117s_hed_sternberg | Sternberg working memory task. Chosen as a replication study for EEGManyLabs. |
| fmri_ds002790s_hed_aomic | AOMIC data example. |
| fmri_soccer21s_hed | HED tags using a single column. Used for fMRI processing examples. |
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 FMRI datasets you also need to use the --ignoreNiftiHeaders option.
Example: The following command validates the fmri_soccer21s_hed dataset:
bids-validator fmri_soccer21s_hed --config.ignore=99 --ignoreNiftiHeaders
For additional information on BIDS validation, see the bids-examples.
The src subdirectory contains Python Jupyter notebooks demonstrating calls to HedTools. For MATLAB support for HED see the hed-matlab GitHub repository.
HED documentation and tutorials are available at hed-resources. The HED GitHub organization gathers the HED supporting resources, all of which are open source.