iEEG data conversion#

Here, we briefly describe the first steps in creating an iEEG dataset in BIDS format. The process can be summarized by the following main steps:

  1. structure your files in the proper folder hierarchy

  2. rename files such that they adhere to the BIDS naming specification,

  3. extract the necessary metadata from your raw data and experimental notes

  4. add electrode-specific information needed for localization

Step 1: Folder structure#

At the highest level, BIDS is a specification for how to structure your files in folders, and how to name files such that one can easily infer their contents. Thus, the first step is to create the proper folder/file hierarchies, which looks like this:

└── subject
    └── session
        └── acquisition

The top level (project) of a BIDS folder must contain a dataset_description.json file, a README, and a CHANGES file. In addition, there are a set of sub-folders, one per subject, that contain all data from a given subject. These must be named according to the convention sub-<label>. Within these folders there is an optional “session” folder (called ses-<label>) and finally a collection of “acquisition folders” that correspond to datasets from different modalities (such as functional imaging, EEG, and iEEG data) that corresponds to this dataset. In our example, there is a folder called ieeg that stores all iEEG data for the subject, for example:

├── dataset_description.json
├── participants.tsv
├── sub-01
│   ├── anat
│   │   └── sub-01_T1w.nii.gz
│   └── ieeg
│       ├── sub-01_task-visualtask_run-01_ieeg.edf
│       ├── sub-01_task-visualtask_run-01_ieeg.json
│       ├── sub-01_task-visualtask_run-01_channels.tsv
│       ├── sub-01_task-visualtask_run-01_events.tsv
│       ├── sub-01_electrodes.tsv
│       └── sub-01_coordsystem.tsv
├── sub-02
│   ├── anat
│   │   └── sub-02_T1w.nii.gz
│   └── ieeg
│       ├── sub-02_task-visualtask_run-01_ieeg.edf
│       ├── sub-02_task-visualtask_run-01_ieeg.json
│       ├── sub-02_task-visualtask_run-01_channels.tsv
│       ├── sub-02_task-visualtask_run-01_events.tsv
│       ├── sub-02_electrodes.tsv
│       └── sub-02_cooordsystem.tsv
└── visualtask_ieeg.json

Step 2. Add raw iEEG data#

Once a folder hierarchy is defined, the folders can be populated with the correct files. Here we focus on the files relevant for iEEG data. Within the ieeg folder, we first copy the raw iEEG data and renamed such that they adhere to the BIDS file naming scheme. For example:


These data are unprocessed and can have one of several file formats (for example: BrainVision and EDF formats are supported, NWB, EEGLab and MEF3 formats are allowed).

Step 3. Add iEEG amplifier metadata#

BIDS datasets should specify all of the metadata needed to analyze and understand a dataset, and these are all contained within text-based JavaScript Object Notation (JSON, field-value) and Tab Separated Value (TSV) metadata files. The iEEG amplifier metadata are stored for each run in a JSON file with the same name structure as the raw data (<raw-data-filename>_ieeg.json) and a TSV file with amplifier metadata (<raw-data-filename>_channels.tsv).

  • <raw-data-filename>_ieeg.json: contains the metadata that are the same for all the data in this run, such as the task name and description, the amplifier brand, and where the experiments were performed. Download a template in the bids-starter-kit here or find the Matlab script to more automatically populate the required fields here.

  • <raw-data-filename>_channels.tsv: The TSV file contains all the settings that differ between iEEG channels such as the units and type of channel (ECOG, SEEG, ECG, EMG, EOG and so on). Download a template in the bids-starter-kit here or find the Matlab script to more automatically populate the required fields here.

Step 4. Add electrode-specific metadata#

In iEEG recordings, each channel in the amplifier is sampled from a specific electrode implanted in the brain. The metadata on the type of electrodes and their coordinates is stored in a TSV file with a row for each metallic electrode contact (_electrodes.tsv). The names of each electrode are used in the amplifier metadata to specify the recorded channel and reference to link these two files. In order to interpret the position of each electrode, the coordinate system is defined in a JSON file (_coordsystem.json). The _coordsystem.json file specifies a reference image file, which can be an MRI, surface rendering, standard space (for example: MNI) or operative photo, such that electrode positions can be displayed. In addition, any raw data collected for the purpose of localizing electrodes is stored in a corresponding anatomy folder (called anat) that lives at the same folder level as the ieeg folder. This can contain files like structural volume data or electrode placement photos.

  • _electrodes.tsv: Download a template in the bids-starter-kit here or find the Matlab script to more automatically populate the required fields here.

  • _coordsystem.json: Download a template in the bids-starter-kit here or find the Matlab script to more automatically populate the required fields here.

Step 5. Add optional metadata#

There are several optional data types that can be stored in BIDS. The way in which events, stimuli, continuous physiology data, and participant information are stored is the same as for BIDS MRI data. These optional metadata are stored within TSV and JSON files as well as any task-specific stimulation files (for example: photos or sounds that were presented to the subject during the task, or videos of the subject and experimental setup). Some examples are shown here:

├── dataset_description.json
├── participants.tsv
├── sub-01
│   ├── stimuli
│   │   └── PresentedPhoto1.png
│   │   └── PresentedSound1.wav
│   └── ieeg
│       ├── sub-01_photo.jpg
│       ├── sub-01_task-visualtask_run-01_physio.tsv.gz
│       ├── sub-01_task-visualtask_run-01_physio.json
│       ├── sub-01_task-visualtask_run-01_stim.tsv.gz
│       ├── sub-01_task-visualtask_run-01_stim.json

Step 6. Validate the iEEG-BIDS data#

In order to verify that a dataset adheres to the BIDS specification, we need to validate the structure, naming conventions, and information inside the dataset. The BIDS validator is a web- and command line-based tool that can validate whether a dataset is BIDS compliant. As a part of the iEEG extension to the BIDS specification, this validator has been updated to check for new conventions related to iEEG data.