NM000114: eeg dataset, 64 subjects#

MDD Patients and Healthy Controls EEG Data

Access recordings and metadata through EEGDash.

Citation: Wajid Mumtaz, Likun Xia, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin, Mazhar Hussain, Aamir Saeed Malik (2017). MDD Patients and Healthy Controls EEG Data. 10.82901/nemar.nm000114

Modality: eeg Subjects: 64 Recordings: 181 License: CC-BY-4.0 Source: nemar

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import NM000114

dataset = NM000114(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = NM000114(cache_dir="./data", subject="01")

Advanced query

dataset = NM000114(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Iterate recordings

for rec in dataset:
    print(rec.subject, rec.raw.info['sfreq'])

If you use this dataset in your research, please cite the original authors.

BibTeX

@dataset{nm000114,
  title = {MDD Patients and Healthy Controls EEG Data},
  author = {Wajid Mumtaz and Likun Xia and Syed Saad Azhar Ali and Mohd Azhar Mohd Yasin and Mazhar Hussain and Aamir Saeed Malik},
  doi = {10.82901/nemar.nm000114},
  url = {https://doi.org/10.82901/nemar.nm000114},
}

About This Dataset#

DOI

MDD Patients and Healthy Controls EEG Data

Introduction

This dataset contains resting-state and task-based EEG recordings from patients diagnosed with Major Depressive Disorder (MDD) and healthy control participants (H). The data was collected to investigate differences in brain electrical activity between MDD patients and healthy individuals across different mental states. The dataset includes 34 participants (19 healthy controls and 15 MDD patients) with recordings during eyes-closed rest, eyes-open rest, and an auditory oddball P300 task. This dataset enables research on neurophysiological biomarkers of depression, comparative studies of brain activity patterns between clinical and healthy populations, and investigation of attentional processing differences in MDD.

Overview of the experiment

View full README

DOI

MDD Patients and Healthy Controls EEG Data

Introduction

This dataset contains resting-state and task-based EEG recordings from patients diagnosed with Major Depressive Disorder (MDD) and healthy control participants (H). The data was collected to investigate differences in brain electrical activity between MDD patients and healthy individuals across different mental states. The dataset includes 34 participants (19 healthy controls and 15 MDD patients) with recordings during eyes-closed rest, eyes-open rest, and an auditory oddball P300 task. This dataset enables research on neurophysiological biomarkers of depression, comparative studies of brain activity patterns between clinical and healthy populations, and investigation of attentional processing differences in MDD.

Overview of the experiment

Participants underwent three recording conditions: (1) eyes-closed resting state, (2) eyes-open resting state, and (3) an auditory oddball P300 task. During the resting-state conditions, participants were instructed to sit quietly with either their eyes closed (EC) or eyes open (EO) for the duration of the recording. In the P300 task, participants were presented with auditory stimuli consisting of frequent standard tones (80% probability) and infrequent target tones (20% probability), and were required to mentally count the target tones. EEG was recorded using a 19-channel monopolar EEG system with electrodes positioned according to the International 10-20 system, referenced to linked ears (A1+A2). The sampling rate was 256 Hz. Hardware filters included a high-pass filter at 0.5 Hz and a low-pass filter at 70 Hz, with a 50 Hz notch filter to remove power line noise. All electrode impedances were maintained below 5 kΩ. The recordings were conducted in a controlled environment to minimize external artifacts. One participant (MDD S15) had two separate recording sessions, resulting in duplicate recordings for this subject.

Description of the preprocessing if any

The original EDF files have been converted to BIDS format. Channel names have been standardized by extracting the electrode names from the original “EEG <electrode>-<reference>” format. Channels originally referenced to the left ear (LE) are now labeled with just the electrode name, while other bipolar derivations (e.g., A2-A1, 23A-23R, 24A-24R) retain their bipolar notation in the format “<electrode1>-<electrode2>”. The dataset includes 19 standard EEG channels plus three additional bipolar channels. Subject IDs have been prefixed with their diagnostic group (“H” for healthy controls, “MDD” for Major Depressive Disorder patients) to facilitate group comparisons. All recordings were artifact-free segments selected from longer recording sessions, with epochs containing excessive oculographic or myographic artifacts excluded during initial data collection.

Description of the event values if any

No events.tsv files are provided as the recordings represent continuous resting-state or task conditions without discrete trial markers. The experimental condition for each recording is indicated by the “task” field in the BIDS filename: - “eyesClosed”: eyes-closed resting state - “eyesOpen”: eyes-open resting state - “P300”: auditory oddball task (continuous recording during the entire task block)

For the P300 task recordings, while individual stimulus onsets are not marked in events.tsv files, the entire recording represents the period during which participants performed the auditory oddball counting task.

Citation

When using this dataset, please cite: 1. Mumtaz, W., Xia, L., Ali, S. S. A., Yasin, M. A. M., Hussain, M., & Malik, A. S. (2017). Electroencephalogram (EEG)-based computer-aided technique to diagnose major depressive disorder (MDD). Biomedical Signal Processing and Control, 31, 108-115. https://doi.org/10.1016/j.bspc.2016.07.006 2. Mumtaz, Wajid (2016). MDD Patients and Healthy Controls EEG Data (New). figshare. Dataset. https://doi.org/10.6084/m9.figshare.4244171.v2

Data curators: Pierre Guetschel (BIDS conversion) Original data collection team: - Wajid Mumtaz (Universiti Teknologi PETRONAS) - Likun Xia (Universiti Teknologi PETRONAS) - Syed Saad Azhar Ali (Universiti Teknologi PETRONAS) - Mohd Azhar Mohd Yasin (Universiti Teknologi PETRONAS) - Mazhar Hussain (Universiti Teknologi PETRONAS)

- Aamir Saeed Malik (Universiti Teknologi PETRONAS)

Automatic report

Report automatically generated by ``mne_bids.make_report()``.

The MDD Patients and Healthy Controls EEG Data dataset was created by Wajid

Mumtaz, Likun Xia, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin, Mazhar Hussain, and Aamir Saeed Malik and conforms to BIDS version 1.7.0. This report was generated with MNE-BIDS (https://doi.org/10.21105/joss.01896). The dataset consists of 64 participants (sex were all unknown; handedness were all unknown; ages all unknown) . Data was recorded using an EEG system sampled at 256.0 Hz with line noise at n/a Hz. There were 181 scans in total. Recording durations ranged from 180.0 to 686.0 seconds (mean = 408.84, std = 155.23), for a total of 74000.29 seconds of data recorded over all scans. For each dataset, there were on average 21.24 (std = 0.97) recording channels per scan, out of which 21.24 (std = 0.97) were used in analysis (0.0 +/- 0.0 were removed from analysis).

Dataset Information#

Dataset ID

NM000114

Title

MDD Patients and Healthy Controls EEG Data

Author (year)

Mumtaz2017

Canonical

—

Importable as

NM000114, Mumtaz2017

Year

2017

Authors

Wajid Mumtaz, Likun Xia, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin, Mazhar Hussain, Aamir Saeed Malik

License

CC-BY-4.0

Citation / DOI

10.82901/nemar.nm000114

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{nm000114,
  title = {MDD Patients and Healthy Controls EEG Data},
  author = {Wajid Mumtaz and Likun Xia and Syed Saad Azhar Ali and Mohd Azhar Mohd Yasin and Mazhar Hussain and Aamir Saeed Malik},
  doi = {10.82901/nemar.nm000114},
  url = {https://doi.org/10.82901/nemar.nm000114},
}

Found an issue with this dataset?

If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!

Report an Issue on GitHub

Technical Details#

Subjects & recordings

  • Subjects: 64

  • Recordings: 181

  • Tasks: 3

Channels & sampling rate

  • Channels: 22 (112), 20 (69)

  • Sampling rate (Hz): 256

  • Duration (hours): 20.55563693576389

Tags

  • Pathology: Not specified

  • Modality: —

  • Type: —

Files & format

  • Size on disk: 812.8 MB

  • File count: 181

  • Format: BIDS

License & citation

  • License: CC-BY-4.0

  • DOI: 10.82901/nemar.nm000114

Provenance

API Reference#

Use the NM000114 class to access this dataset programmatically.

class eegdash.dataset.NM000114(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

MDD Patients and Healthy Controls EEG Data

Study:

nm000114 (NeMAR)

Author (year):

Mumtaz2017

Canonical:

—

Also importable as: NM000114, Mumtaz2017.

Modality: eeg. Subjects: 64; recordings: 181; tasks: 3.

Parameters:

  • cache_dir (str | Path) – Directory where data are cached locally.

  • query (dict | None) – Additional MongoDB-style filters to AND with the dataset selection. Must not contain the key dataset.

  • s3_bucket (str | None) – Base S3 bucket used to locate the data.

  • **kwargs (dict) – Additional keyword arguments forwarded to EEGDashDataset.

data_dir#

Local dataset cache directory (cache_dir / dataset_id).

Type:

Path

query#

Merged query with the dataset filter applied.

Type:

dict

records#

Metadata records used to build the dataset, if pre-fetched.

Type:

list[dict] | None

Notes

Each item is a recording; recording-level metadata are available via dataset.description. query supports MongoDB-style filters on fields in ALLOWED_QUERY_FIELDS and is combined with the dataset filter. Dataset-specific caveats are not provided in the summary metadata.

References

OpenNeuro dataset: https://openneuro.org/datasets/nm000114 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=nm000114 DOI: https://doi.org/10.82901/nemar.nm000114

Examples

>>> from eegdash.dataset import NM000114
>>> dataset = NM000114(cache_dir="./data")
>>> recording = dataset[0]
>>> raw = recording.load()
__init__(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#
save(path, overwrite=False)[source]#

Save the dataset to disk.

Parameters:

  • path (str or Path) – Destination file path.

  • overwrite (bool, default False) – If True, overwrite existing file.

Return type:

None

See Also#