The bids/ Folder

Each pipeline run outputs results in BIDS (Brain Imaging Data Structure) format, a widely adopted standard for EEG and neuroimaging data. This ensures your cleaned data are interoperable with other tools (e.g., EEGLAB-BIDS, MNE-BIDS, BIDS Validator). The bids/ subfolder contains:
  • Cleaned continuous and epoched EEG data in BIDS layout
  • Standard metadata files describing participants, dataset structure, and channels
  • Events and derivatives for reproducibility
Because BIDS enforces strict formatting rules, the subject identifier (sub-XXXX) inside the bids/ folder will not necessarily match the original filename.
To see how subjects are linked to original recordings, check the participants.tsv file, which maps subject IDs to participant metadata.
└── RestingStateTutorial/ 
    └── bids/ 
        ├── dataset_description.json 
        ├── sub-451559/ 
        ├── participants.tsv 
        ├── participants.json 
        ├── README 
        ├── derivatives/ 
        └── final_files/ 

File and Folder Overview

File / FolderPurpose
dataset_description.jsonRequired by BIDS. Records dataset name, pipeline version, and references.
participants.tsvTable listing subjects and basic attributes (age, sex, etc.).
participants.jsonSidecar describing the meaning, format, and units of each column in participants.tsv.
READMEFree-text description of the dataset, study, or preprocessing notes.
sub-<ID>/Per-subject folder (e.g., sub-451559) containing the actual EEG data and metadata.
derivatives/Preprocessed outputs from the pipeline (e.g., ICA-cleaned signals, epoched data, QC reports).
final_files/Convenience folder with cleaned, ready-to-use outputs (e.g., epoched datasets).

What to Expect

  • Raw-like cleaned EEG lives under each subject folder (sub-<ID>).
  • Metadata (dataset_description.json, participants.tsv/json, README) ensures the dataset is machine-readable and human-readable.
  • Processed derivatives contain artifacts-removed signals and QC artifacts.
  • Final files provide shortcuts for quick analysis, without digging into the full BIDS tree.