Toward More Versatile and Intuitive Cortical Brain–Machine Interfaces

• Published in: Current biology Vol. 24; no. 18; pp. R885 - R897
• Main Authors: Andersen, Richard A., Kellis, Spencer, Klaes, Christian, Aflalo, Tyson
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 22.09.2014
• Subjects: Algorithms; Brain - physiology; Brain-Computer Interfaces; Evoked Potentials, Somatosensory; Humans; Prostheses and Implants; Robotics
• ISSN: 0960-9822; 1879-0445; 1879-0445
• DOI: 10.1016/j.cub.2014.07.068

Brain–machine interfaces have great potential for the development of neuroprosthetic applications to assist patients suffering from brain injury or neurodegenerative disease. One type of brain–machine interface is a cortical motor prosthetic, which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. These include using: recordings from cortical areas outside motor cortex; local field potentials as a source of recorded signals; somatosensory feedback for more dexterous control of robotics; and new decoding methods that work in concert to form an ecology of decode algorithms. These new advances promise to greatly accelerate the applicability and ease of operation of motor prosthetics. Brain-machine interfaces have great potential for aiding communication between brain and body in brain-damaged patients. Andersen et al. review advances that promise to accelerate the development of cortical motor prosthetics to assist patients paralyzed through brain injury or neurodegenerative disease.