title: Evolution of brain-computer interfaces: going beyond classic motor physiology.
abstract: The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future.
authors: Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri 63110, USA. leuthardte@nsurg.wustl.edu
authors: Eric C
authors: EC
authors: Leuthardt
authors: Gerwin
authors: G
authors: Schalk
authors: Jarod
authors: J
authors: Roland
authors: Adam
authors: A
authors: Rouse
authors: Daniel W
authors: DW
authors: Moran
mesh_terms: D001921:Brain / Q000502:physiology*; D002540:Cerebral Cortex / Q000502:physiology; D006801:Humans; D008328:Man-Machine Systems; D009044:Motor Cortex / Q000502:physiology*; D009068:Movement / Q000502:physiology; D009069:Movement Disorders / Q000534:rehabilitation; D009473:Neuronal Plasticity / Q000502:physiology; D019736:Prostheses and Implants; D012106:Research / Q000639:trends; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface