Brain-Computer Interfaces

Brain-Computer Interfaces (BCIs) are systems that employ machine learning methods to decode subjects’ intentions from brain imaging data. They hold the promise of enabling severely paralyzed patients to communicate and interact with their environment. In this seminar, we will take a look at the history of BCIs, introduce the design of invasive and non-invasive BCIs, study machine learning methods for decoding mental states from brain imaging data, and discuss the open problems that need to be solved to move BCIs from the lab into the real world.