About this Research Topic
Brain-computer interfaces (BCIs) are exciting technologies that provide channels of communication between the brain and a computer system. They can be used as communication devices, rehabilitation systems, entertainment devices, and for a whole host of other applications.
Research in BCI is developing rapidly and is a highly multidisciplinary field, involving neuroscientists, engineers, psychologists, computer scientists, clinicians etc. However, reliability and reproducibility of BCI research is held back by a dearth of high quality, publicly available, datasets with which new systems, tools, and technologies, can be evaluated and compared. Indeed the small number of high-quality datasets that are publicly available date back up to 10 years and are now at risk of being over-fit due to frequent use.
This Research Topic seeks to provide a place to collate descriptions, reviews, surveys, and evaluations of publicly available physiological datasets recorded during training and evaluation of BCI systems from leading BCI research labs around the world. This will allow further use of these datasets in development of future BCI systems and encourage high quality and rapid continual development of BCI systems by providing multiple datasets upon which new methods may be rigorously evaluated and compared.
This collection of articles also seeks to provide a platform for new scientific publications, literature reviews, and any other article types related to the availability and use of public datasets in BCI research.
Additionally, all authors are encouraged to upload their data sets on
the BNCI Horizon 2020 web repository to make them available for the
community. Thus, our Research Topic will provide a collated collection of BCI datasets and their descriptions as a resource for future BCI developers.
Keywords: Brain-computer interfaces, Brain-machine interfaces, Open access data, EEG, EMG, fMRI, ECoG, MEG, fNIRS, Spike train recordings
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