NM000409: ieeg dataset, 8 subjects#
ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs)
Access recordings and metadata through EEGDash.
Citation: Hohyun Cho, Gerwin Schalk, Markus Adamek, Ladan Moheimanian, William G. Coon, Sung Chan Jun, Jonathan R. Wolpaw, Peter Brunner (2021). ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs). 10.82901/nemar.nm000409
Modality: ieeg Subjects: 8 Recordings: 24 License: CC-BY-4.0 Source: nemar
Metadata: Complete (100%)
8-participant iEEG dataset — ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs).
Quickstart#
Install
pip install eegdash
Access the data
from eegdash.dataset import NM000409
dataset = NM000409(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)
Filter by subject
dataset = NM000409(cache_dir="./data", subject="01")
Advanced query
dataset = NM000409(
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{nm000409,
title = {ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs)},
author = {Hohyun Cho and Gerwin Schalk and Markus Adamek and Ladan Moheimanian and William G. Coon and Sung Chan Jun and Jonathan R. Wolpaw and Peter Brunner},
doi = {10.82901/nemar.nm000409},
url = {https://doi.org/10.82901/nemar.nm000409},
}
About This Dataset#
Electrocorticography (ECoG) from 8 subjects performing a simple reaction-time task (press a button as fast as possible
after an auditory stimulus), released with the code of:
Cho H, Schalk G, Adamek M, Moheimanian L, Coon WG, Jun SC, Wolpaw JR, Brunner P (2021). Revealing the physiological origin of event-related potentials using electrocorticography in humans. bioRxiv, https://doi.org/10.1101/2021.02.12.430921
ECoG during a simple auditory reaction-time task (derivative)
Source record: Zenodo https://doi.org/10.5281/zenodo.4361654 (CC-BY-4.0), Evoked_Potentials_ECoG_Data.zip
(“ECoG activity from eight human subjects; EEG activity from seven human subjects; recorded during a simple
reaction-time task”).
This is a derivative dataset: the release holds the authors’ downsampled (400 Hz) epochs, not continuous recordings.
Files
View full README
ECoG during a simple auditory reaction-time task (derivative)
Source record: Zenodo https://doi.org/10.5281/zenodo.4361654 (CC-BY-4.0), Evoked_Potentials_ECoG_Data.zip
(“ECoG activity from eight human subjects; EEG activity from seven human subjects; recorded during a simple
reaction-time task”).
This is a derivative dataset: the release holds the authors’ downsampled (400 Hz) epochs, not continuous recordings.
Files
For each subject sub-01 … sub-08 (release files s1 … s8), three BrainVision files (float32 = the release’s
float64 values rounded), epochs written back to back, trial k at the same position in all three:
- desc-stimlocked: -1.0 to +1.5 s around the auditory stimulus (1000 samples per trial);
- desc-responselocked: -1.5 to +1.5 s around the button press (1200 samples per trial);
- desc-rest: a 1-s rest segment per trial (400 samples), used by the authors as baseline.
Epoch windows are those of the authors’ figure scripts (linspace(-1,1.5,srate*2.5), linspace(-1.5,1.5,srate*3)).
*_events.tsv has one row per trial at the alignment point. channels.tsv marks the channels the paper used as
auditory (ach_data_final.mat) and motor (mch_data_final.mat) channels.
Limitations
The release has no channel names (channels are numbered
ch001...in column order), no electrode positions matched to the channels, and no per-subject age or sex.The physical unit is not stated; the channels are labelled µV as an assumption.
The original sampling rate and the anti-alias filter used for downsampling are not stated.
Line frequency 60 Hz is taken from the release’s notch parameters (58-62 Hz, 117-123 Hz).
sourcedata/zenodo-4361654/sub-XX_parameters.jsonholds the analysis parameters stored in each subject file, without the original file paths, subject numbers and brain-model file names (these carry site study codes).The EEG data, figure data, cortical models and code of the release are not copied; they remain in the source record.
Licence
CC-BY-4.0, as the source record. Please cite the preprint and the Zenodo record.
Additional metadata and localisation (added 2026-10-08)
Compiled after the upload from the article, its supplement and the source deposit (each statement names its source). Text and sidecar metadata only; no data file was changed. Recording system. BCI2000 with eight 16-channel g.USBamp amplifiers or one 256-channel g.HIamp (g.tec), sampling rate 1,200 Hz; a connector split the cables between the clinical system and the research amplifiers (doi:10.1101/2021.02.12.430921, Methods ‘Data collection’). The deposited s<N>_auditory_ds.mat are downsampled (‘_ds’): the preprint downsampled 1200 -> 400 Hz after 0.05 Hz high-pass and common median reference (doi:10.1101/2021.02.12.430921, ‘Data pre-processing’); each file holds ecog.rest_data, ecog.stim_data, ecog.button_data (samples x channels), ecog.srate, ecog.n_trials, ecog.parameters (Voyager Job ieeg-b3enr-c-cho-erp-1007221214). Reference scheme. Offline common median reference, excluding channels with excessive 60 Hz noise (doi:10.1101/2021.02.12.430921). Hardware reference not stated (n/a). Electrode types. Subdural grids (Ad-Tech Medical, Racine WI; PMT, Chanhassen MN), platinum-iridium, 4 mm diameter (2.3 mm exposed), 10 mm centre-to-centre (doi:10.1101/2021.02.12.430921, Methods ‘Subjects’). Localisation method. Postoperative radiographs and CT, with MRI, were used to build subject-specific 3D cortical models and derive electrode locations (Coon et al. 2016) (doi:10.1101/2021.02.12.430921). The deposit contains, per subject, the brain model with electrode coordinates (data/s<N>_brain.mat and talairach_alignment/s<N>/orig_brain_model.mat) and the same electrodes aligned to the activeBrain Talairach template (talairach_alignment/s<N>/talairach_tal_brain_model.mat); These positions are not assigned to channels in this dataset: the release has no channel names and each subject’s data have 0-5 more columns than the brain model has electrodes (see coordsystem.json), so the electrode-to-channel mapping cannot be verified.
Correction (2026-10-09)
The hemisphere column of participants.tsv listed all eight subjects as left. It had been copied from the release analysis parameter IsRightHemisphere, which is no in every subject file. The preprint (doi:10.1101/2021.02.12.430921, Methods ‘Subjects’) places the grids in the left hemisphere for S1, S3, S6 and S7 and in the right hemisphere for S2, S4, S5 and S8, and the electrode coordinates in the deposit agree (positive x for s2, s4, s5 and s8). sub-02, sub-04, sub-05 and sub-08 are now right. No data file or coordinate was changed.
NEMAR Metadata#
[](https://doi.org/10.82901/nemar.nm000409) # ECoG during a simple auditory reaction-time task (derivative) Electrocorticography (ECoG) from 8 subjects performing a simple reaction-time task (press a button as fast as possible after an auditory stimulus), released with the code of: > Cho H, Schalk G, Adamek M, Moheimanian L, Coon WG, Jun SC, Wolpaw JR, Brunner P (2021). Revealing the physiological > origin of event-related potentials using electrocorticography in humans. bioRxiv, https://doi.org/10.1101/2021.02.12.430921 Source record: Zenodo https://doi.org/10.5281/zenodo.4361654 (CC-BY-4.0), Evoked_Potentials_ECoG_Data.zip (“ECoG activity from eight human subjects; EEG activity from seven human subjects; recorded during a simple reaction-time task”). This is a derivative dataset: the release holds the authors’ downsampled (400 Hz) epochs, not continuous recordings. ## Files For each subject sub-01 … sub-08 (release files s1 … s8), three BrainVision files (float32 = the release’s float64 values rounded), epochs written back to back, trial k at the same position in all three: - desc-stimlocked: -1.0 to +1.5 s around the auditory stimulus (1000 samples per trial); - desc-responselocked: -1.5 to +1.5 s around the button press (1200 samples per trial); - desc-rest: a 1-s rest segment per trial (400 samples), used by the authors as baseline. Epoch windows are those of the authors’ figure scripts (linspace(-1,1.5,srate*2.5), linspace(-1.5,1.5,srate*3)). *_events.tsv has one row per trial at the alignment point. channels.tsv marks the channels the paper used as auditory (ach_data_final.mat) and motor (mch_data_final.mat) channels. ## Limitations - The release has no channel names (channels are numbered ch001… in column order), no electrode positions matched to
the channels, and no per-subject age or sex.
The physical unit is not stated; the channels are labelled µV as an assumption.
The original sampling rate and the anti-alias filter used for downsampling are not stated.
Line frequency 60 Hz is taken from the release’s notch parameters (58-62 Hz, 117-123 Hz).
sourcedata/zenodo-4361654/sub-XX_parameters.json holds the analysis parameters stored in each subject file, without the original file paths, subject numbers and brain-model file names (these carry site study codes).
The EEG data, figure data, cortical models and code of the release are not copied; they remain in the source record.
## Licence CC-BY-4.0, as the source record. Please cite the preprint and the Zenodo record. ## Additional metadata and localisation (added 2026-10-08) Compiled after the upload from the article, its supplement and the source deposit (each statement names its source). Text and sidecar metadata only; no data file was changed. Recording system. BCI2000 with eight 16-channel g.USBamp amplifiers or one 256-channel g.HIamp (g.tec), sampling rate 1,200 Hz; a connector split the cables between the clinical system and the research amplifiers (doi:10.1101/2021.02.12.430921, Methods ‘Data collection’). The deposited s<N>_auditory_ds.mat are downsampled (‘_ds’): the preprint downsampled 1200 -> 400 Hz after 0.05 Hz high-pass and common median reference (doi:10.1101/2021.02.12.430921, ‘Data pre-processing’); each file holds ecog.rest_data, ecog.stim_data, ecog.button_data (samples x channels), ecog.srate, ecog.n_trials, ecog.parameters (Voyager Job ieeg-b3enr-c-cho-erp-1007221214). Reference scheme. Offline common median reference, excluding channels with excessive 60 Hz noise (doi:10.1101/2021.02.12.430921). Hardware reference not stated (n/a). Electrode types. Subdural grids (Ad-Tech Medical, Racine WI; PMT, Chanhassen MN), platinum-iridium, 4 mm diameter (2.3 mm exposed), 10 mm centre-to-centre (doi:10.1101/2021.02.12.430921, Methods ‘Subjects’). Localisation method. Postoperative radiographs and CT, with MRI, were used to build subject-specific 3D cortical models and derive electrode locations (Coon et al. 2016) (doi:10.1101/2021.02.12.430921). The deposit contains, per subject, the brain model with electrode coordinates (data/s<N>_brain.mat and talairach_alignment/s<N>/orig_brain_model.mat) and the same electrodes aligned to the activeBrain Talairach template (talairach_alignment/s<N>/talairach_tal_brain_model.mat); These positions are not assigned to channels in this dataset: the release has no channel names and each subject’s data have 0-5 more columns than the brain model has electrodes (see coordsystem.json), so the electrode-to-channel mapping cannot be verified. ## Correction (2026-10-09) The hemisphere column of participants.tsv listed all eight subjects as left. It had been copied from the release analysis parameter IsRightHemisphere, which is no in every subject file. The preprint (doi:10.1101/2021.02.12.430921, Methods ‘Subjects’) places the grids in the left hemisphere for S1, S3, S6 and S7 and in the right hemisphere for S2, S4, S5 and S8, and the electrode coordinates in the deposit agree (positive x for s2, s4, s5 and s8). sub-02, sub-04, sub-05 and sub-08 are now right. No data file or coordinate was changed.
License: CC-BY-4.0
Authors:
Hohyun Cho
Gerwin Schalk
Markus Adamek
Ladan Moheimanian
William G. Coon
… and 3 more
Versions:
Version |
DOI |
Released |
|---|---|---|
|
Cohort#
Dataset Statistics#
Channel counts (ch)
Sampling frequencies: 400.0 Hz (n=24 recordings)
Total recording duration: 4 h 16 min
Signal · Electrodes & live trace#
Live trace viewer — sub-01 · task-reactiontime
Showing one representative recording out of
8 subjects and 24 recordings in this dataset.
Browse the full set on OpenNeuro;
drop any other _ieeg.{set,edf,bdf,vhdr} file onto the
viewer (or pass ?ieeg=<url>) to inspect it.
No scalp electrode layout is currently indexed for this dataset. Once the eegdash montage registry ingests it, the interactive viewer will appear here automatically.
NEMAR Processing Statistics#
The plots below are generated by NEMAR’s automated EEG pipeline. The histogram shows pipeline success for data cleaning and ICA decomposition, the percentage of data frames and EEG channels retained after artefact removal, line noise per channel (RMS, dB), and the age/gender distribution of participants.
HED event descriptors word cloud
Manifest#
File Explorer#
Browse the BIDS file structure of this dataset. Records are fetched on demand from the EEGDash catalog the first time you open the explorer.
Full dataset metadata table
Dataset ID |
|
Title |
ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs) |
Author (year) |
— |
Canonical |
— |
Importable as |
|
Year |
2021 |
Authors |
Hohyun Cho, Gerwin Schalk, Markus Adamek, Ladan Moheimanian, William G. Coon, Sung Chan Jun, Jonathan R. Wolpaw, Peter Brunner |
License |
CC-BY-4.0 |
Citation / DOI |
|
Source links |
OpenNeuro | NeMAR | Source URL |
Copy-paste BibTeX
@dataset{nm000409,
title = {ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs)},
author = {Hohyun Cho and Gerwin Schalk and Markus Adamek and Ladan Moheimanian and William G. Coon and Sung Chan Jun and Jonathan R. Wolpaw and Peter Brunner},
doi = {10.82901/nemar.nm000409},
url = {https://doi.org/10.82901/nemar.nm000409},
}
API Reference#
eegdash.datasetEEGDashDataset- class eegdash.dataset.NM000409(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#
ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs)
- Study:
nm000409(NeMAR)- Author (year):
—
- Canonical:
—
Also importable as:
NM000409.Modality:
ieeg; Subject type:Unknown. Subjects: 8; recordings: 24; 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
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/nm000409 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=nm000409 DOI: https://doi.org/10.82901/nemar.nm000409
Examples
>>> from eegdash.dataset import NM000409 >>> dataset = NM000409(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: str, overwrite: bool = False, offset: int = 0)[source]#
Save datasets to files by creating one subdirectory for each dataset:
path/ 0/ 0-raw.fif | 0-epo.fif description.json raw_preproc_kwargs.json (if raws were preprocessed) window_kwargs.json (if this is a windowed dataset) window_preproc_kwargs.json (if windows were preprocessed) target_name.json (if target_name is not None and dataset is raw) 1/ 1-raw.fif | 1-epo.fif description.json raw_preproc_kwargs.json (if raws were preprocessed) window_kwargs.json (if this is a windowed dataset) window_preproc_kwargs.json (if windows were preprocessed) target_name.json (if target_name is not None and dataset is raw)
- Parameters:
path (str) –
- Directory in which subdirectories are created to store
-raw.fif | -epo.fif and .json files to.
overwrite (bool) – Whether to delete old subdirectories that will be saved to in this call.
offset (int) – If provided, the integer is added to the id of the dataset in the concat. This is useful in the setting of very large datasets, where one dataset has to be processed and saved at a time to account for its original position.
BaseDataset from braindecode — windowed via create_windows_from_events.braindecodeDataLoader; supports parallel workers and on-the-fly augmentations.pytorch
Find datasets with the EEGDash APIQuery the catalogue, filter by task or modality, list candidates.
Load one EEG recordingResolve a single record to an MNE Raw with channels and events.
EEG recording to PyTorch DataLoaderWrap braindecode windows in a DataLoader for model training.
Preprocess EEG and create windowsFilter, resample, epoch — and persist the windowed dataset.
Save and reload prepared dataCache a windowed dataset to disk and reattach it without recompute.
Download a dataset locallyPrefetch BIDS files to a local cache and validate the layout.Swap any load_dataset(...) call for nm000409 to reproduce the tutorial on this dataset.
Citation
Hohyun Cho, Gerwin Schalk, Markus Adamek, Ladan Moheimanian, William G. Coon, … (2021). ECoG during a simple auditory reaction-time task, 8 subjects: stimulus-locked, response-locked and rest epochs at 400 Hz (Cho et al., physiological origin of ERPs). 10.82901/nemar.nm000409
Provenance
¹Contributed to nemar in BIDS format.
²Curated & ingested by the EEGDash catalog; see CITATION.cff for canonical reference.
³Persistent identifier: 10.82901/nemar.nm000409.
See Also#
eegdash.dataset.EEGDashDataseteegdash.dataset