DS003944#

EEG: First Episode Psychosis vs. Control Resting Task 1

Access recordings and metadata through EEGDash.

Citation: Dean Salisbury, Dylan Seebold, Brian Coffman (2021). EEG: First Episode Psychosis vs. Control Resting Task 1. 10.18112/openneuro.ds003944.v1.0.1

Modality: eeg Subjects: 82 Recordings: 351 License: CC0 Source: openneuro Citations: 7.0

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS003944

dataset = DS003944(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS003944(cache_dir="./data", subject="01")

Advanced query

dataset = DS003944(
    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{ds003944,
  title = {EEG: First Episode Psychosis vs. Control Resting Task 1},
  author = {Dean Salisbury and Dylan Seebold and Brian Coffman},
  doi = {10.18112/openneuro.ds003944.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds003944.v1.0.1},
}

About This Dataset#

Resting EEG and MEG data was gathered for two independently collected samples of healthy and First Episode Psychosis (FEP) individuals. To obtain resting data, EEG channels were recorded for 5 minutes using an Elekta Neuromag Vectorview system. EEG was recorded using a low-impedance 10-10 system 60-channel cap. The first collected sample of EEG data is provided here. This sample includes a portion of subjects from the second acquisition (EEG: First Episode Psychosis vs. Control Resting Task 2), since they were collected using the same montage. The subjects from Task 2 that have been included here are: sub-2140A, sub-2170A, sub-2174A, sub-2176A, sub-2177A, sub-2184A, sub-2193A, sub-2214A, sub-2217A, sub-2221A.

The phenotype directory contains clinical assessment results and data divided by type for all subjects. The assessment results were categorized as follows: BPRS - Brief Psychiatric Rating Scale, SANS - Scale for Assessment of Negative Symptoms, SAPS - Scale for Assessment of Positive Symptoms, GAFGAS - Global Assessment of Functioning, SFS - Social Functioning Scale, MATRICS - MATRICS Consensus Cognitive Battery, WASI - Wechsler Abbreviated Scale of Intelligence, Hollingshead - Hollingshead Four-Factor Index of Socioeconomic Status, Medications - Chlorpromazine equivalency of prescribed medication at time of EEG scan. Values/scores that were not collected and questions without given responses are denoted by n/a.

Dataset Information#

Dataset ID

DS003944

Title

EEG: First Episode Psychosis vs. Control Resting Task 1

Year

2021

Authors

Dean Salisbury, Dylan Seebold, Brian Coffman

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds003944.v1.0.1

Source links

OpenNeuro | NeMAR | Source URL

Copy-paste BibTeX
@dataset{ds003944,
  title = {EEG: First Episode Psychosis vs. Control Resting Task 1},
  author = {Dean Salisbury and Dylan Seebold and Brian Coffman},
  doi = {10.18112/openneuro.ds003944.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds003944.v1.0.1},
}

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: 82

  • Recordings: 351

  • Tasks: 1

Channels & sampling rate
  • Channels: 61 (82), 64 (82)

  • Sampling rate (Hz): 1000.0 (162), 3000.00030000003 (2)

  • Duration (hours): 0.0

Tags
  • Pathology: Not specified

  • Modality: —

  • Type: —

Files & format
  • Size on disk: 6.2 GB

  • File count: 351

  • Format: BIDS

License & citation
  • License: CC0

  • DOI: doi:10.18112/openneuro.ds003944.v1.0.1

Provenance

API Reference#

Use the DS003944 class to access this dataset programmatically.

class eegdash.dataset.DS003944(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds003944. Modality: eeg; Experiment type: Clinical/Intervention; Subject type: Schizophrenia/Psychosis. Subjects: 82; recordings: 82; tasks: 1.

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/ds003944 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds003944

Examples

>>> from eegdash.dataset import DS003944
>>> dataset = DS003944(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#