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 |
|
Title |
EEG: First Episode Psychosis vs. Control Resting Task 1 |
Year |
2021 |
Authors |
Dean Salisbury, Dylan Seebold, Brian Coffman |
License |
CC0 |
Citation / DOI |
|
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!
Technical Details#
Subjects: 82
Recordings: 351
Tasks: 1
Channels: 61 (82), 64 (82)
Sampling rate (Hz): 1000.0 (162), 3000.00030000003 (2)
Duration (hours): 0.0
Pathology: Not specified
Modality: —
Type: —
Size on disk: 6.2 GB
File count: 351
Format: BIDS
License: CC0
DOI: doi:10.18112/openneuro.ds003944.v1.0.1
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:
EEGDashDatasetOpenNeuro 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.querysupports MongoDB-style filters on fields inALLOWED_QUERY_FIELDSand 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()
See Also#
eegdash.dataset.EEGDashDataseteegdash.dataset