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.

Motor Imagery Datasets

AlexMI()	Alex Motor Imagery dataset.
BNCI2014001()	BNCI 2014-001 Motor Imagery dataset.
BNCI2014002()	BNCI 2014-002 Motor Imagery dataset.
BNCI2014004()	BNCI 2014-004 Motor Imagery dataset.
BNCI2015001()	BNCI 2015-001 Motor Imagery dataset.
BNCI2015004()	BNCI 2015-004 Motor Imagery dataset.
Cho2017()	Motor Imagery dataset from Cho et al 2017.
Lee2019_MI([train_run, test_run, …])	Methods
MunichMI()	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 discribed 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.

ERP Datasets

bi2013a([NonAdaptive, Adaptive, Training, …])	P300 dataset bi2013a from a “Brain Invaders” experiment
BNCI2014008()	BNCI 2014-008 P300 dataset
BNCI2014009()	BNCI 2014-009 P300 dataset.
BNCI2015003()	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.
Lee2019_ERP([train_run, test_run, …])	Methods

SSVEP Datasets

SSVEPExo()	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, …])	Methods

Base & Utils

base.BaseDataset(subjects, …[, doi, …])

Parameters required for all datasets

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.