Datasets

A dataset handle and abstract low level access to the data. the dataset will takes data stored locally, in the format in which they have been downloaded, and will convert them into a MNE raw object. There are options to pool all the different recording sessions per subject or to evaluate them separately.

See NeuroTechX/moabb for detail on datasets (electrodes, number of trials, sessions, etc.)

Motor Imagery Datasets

AlexMI()	Alex Motor Imagery dataset.
BNCI2014_001()	BNCI 2014-001 Motor Imagery dataset.
BNCI2014_002()	BNCI 2014-002 Motor Imagery dataset.
BNCI2014_004()	BNCI 2014-004 Motor Imagery dataset.
BNCI2015_001()	BNCI 2015-001 Motor Imagery dataset.
BNCI2015_004()	BNCI 2015-004 Motor Imagery dataset.
Cho2017()	Motor Imagery dataset from Cho et al 2017.
Lee2019_MI([train_run, test_run, ...])	BMI/OpenBMI dataset for MI.
GrosseWentrup2009()	Munich Motor Imagery dataset.
Ofner2017([imagined, executed])	Motor Imagery ataset from Ofner et al 2017.
PhysionetMI([imagined, executed])	Physionet Motor Imagery dataset.
Schirrmeister2017()	High-gamma dataset described in Schirrmeister et al. 2017.
Shin2017A([accept])	Motor Imagey Dataset from Shin et al 2017.
Shin2017B([accept])	Mental Arithmetic Dataset from Shin et al 2017.
Weibo2014()	Motor Imagery dataset from Weibo et al 2014.
Zhou2016()	Motor Imagery dataset from Zhou et al 2016.
Stieger2021([interval, sessions])	Motor Imagery dataset from Stieger et al. 2021.
Liu2024([break_events, instr_events])

ERP Datasets

BI2012([Training, Online])	P300 dataset BI2012 from a "Brain Invaders" experiment.
BI2013a([NonAdaptive, Adaptive, Training, ...])	P300 dataset BI2013a from a "Brain Invaders" experiment.
BI2014a()	P300 dataset BI2014a from a "Brain Invaders" experiment.
BI2014b()	P300 dataset BI2014b from a "Brain Invaders" experiment.
BI2015a()	P300 dataset BI2015a from a "Brain Invaders" experiment.
BI2015b()	P300 dataset BI2015b from a "Brain Invaders" experiment.
Cattan2019_VR([virtual_reality, screen_display])	Dataset of an EEG-based BCI experiment in Virtual Reality using P300.
BNCI2014_008()	BNCI 2014-008 P300 dataset.
BNCI2014_009()	BNCI 2014-009 P300 dataset.
BNCI2015_003()	BNCI 2015-003 P300 dataset.
DemonsP300()	Visual P300 dataset recorded in Virtual Reality (VR) game Raccoons versus Demons.
EPFLP300()	P300 dataset from Hoffmann et al 2008.
Huebner2017([interval, raw_slice_offset, ...])	Learning from label proportions for a visual matrix speller (ERP) dataset from Hübner et al 2017 [R0a211c89d39d-1].
Huebner2018([interval, raw_slice_offset, ...])	Mixture of LLP and EM for a visual matrix speller (ERP) dataset from Hübner et al 2018 [R8f30fc0d0ace-1].
Lee2019_ERP([train_run, test_run, ...])	BMI/OpenBMI dataset for P300.
Sosulski2019([use_soas_as_sessions, ...])	P300 dataset from initial spot study.

SSVEP Datasets

Kalunga2016()	SSVEP Exo dataset.
Nakanishi2015()	SSVEP Nakanishi 2015 dataset.
Wang2016()	SSVEP Wang 2016 dataset.
MAMEM1()	SSVEP MAMEM 1 dataset.
MAMEM2()	SSVEP MAMEM 2 dataset.
MAMEM3()	SSVEP MAMEM 3 dataset.
Lee2019_SSVEP([train_run, test_run, ...])	BMI/OpenBMI dataset for SSVEP.

c-VEP Datasets

Thielen2015()	c-VEP dataset from Thielen et al. (2015).
Thielen2021()	c-VEP dataset from Thielen et al. (2021).
CastillosBurstVEP40()	c-VEP and Burst-VEP dataset from Castillos et al. (2023).
CastillosBurstVEP100()	c-VEP and Burst-VEP dataset from Castillos et al. (2023).
CastillosCVEP40()	c-VEP and Burst-VEP dataset from Castillos et al. (2023).
CastillosCVEP100()	c-VEP and Burst-VEP dataset from Castillos et al. (2023).

Resting State Datasets

Cattan2019_PHMD()	Passive Head Mounted Display with Music Listening dataset.
Hinss2021()	Neuroergonomic 2021 dataset.
Rodrigues2017()	Alphawaves dataset

Base & Utils

base.BaseDataset(subjects, ...[, doi, ...])	Abstract Moabb BaseDataset.
base.CacheConfig([save_raw, save_epochs, ...])	Configuration for caching of datasets.
fake.FakeDataset([event_list, n_sessions, ...])	Fake Dataset for test purpose.
fake.FakeVirtualRealityDataset([seed])	Fake Cattan2019_VR dataset for test purpose.

download.data_path(url, sign[, path, ...])	Get path to local copy of given dataset URL.
download.data_dl(url, sign[, path, ...])	Download file from url to specified path.
download.fs_issue_request(method, url, headers)	Wrapper for HTTP request.
download.fs_get_file_list(article_id[, version])	List all the files associated with a given article.
download.fs_get_file_hash(filelist)	Returns a dict associating figshare file id to MD5 hash.
download.fs_get_file_id(filelist)	Returns a dict associating filename to figshare file id.
download.fs_get_file_name(filelist)	Returns a dict associating figshare file id to filename.
utils.dataset_search([paradigm, ...])	Returns a list of datasets that match a given criteria.
utils.find_intersecting_channels(datasets[, ...])	Given a list of dataset instances return a list of channels shared by all datasets.

Compound Datasets

ERP Datasets

BI2014a_Il()	A selection of subject from BI2014a with AUC < 0.7 with pipeline: ERPCovariances(estimator="lwf"), MDM(metric="riemann")
BI2014b_Il()	A selection of subject from BI2014b with AUC < 0.7 with pipeline: ERPCovariances(estimator="lwf"), MDM(metric="riemann")
BI2015a_Il()	A selection of subject from BI2015a with AUC < 0.7 with pipeline: ERPCovariances(estimator="lwf"), MDM(metric="riemann")
BI2015b_Il()	A selection of subject from BI2015b with AUC < 0.7 with pipeline: ERPCovariances(estimator="lwf"), MDM(metric="riemann")
Cattan2019_VR_Il()	A selection of subject from Cattan2019_VR with AUC < 0.7 with pipeline: ERPCovariances(estimator="lwf"), MDM(metric="riemann")
BI_Il()	Subjects from braininvaders datasets with AUC < 0.7 with pipeline: ERPCovariances(estimator="lwf"), MDM(metric="riemann")