TY - JOUR T1 - Using the electrocorticographic speech network to control a brain-computer interface in humans. JF - J Neural Eng Y1 - 2011 A1 - Leuthardt, E C A1 - Charles M Gaona A1 - Sharma, Mohit A1 - Szrama, Nicholas A1 - Roland, Jarod A1 - Zachary V. Freudenberg A1 - Solisb, Jamie A1 - Breshears, Jonathan A1 - Gerwin Schalk KW - Adult KW - Brain KW - Brain Mapping KW - Computer Peripherals KW - Electroencephalography KW - Evoked Potentials KW - Feedback, Physiological KW - Female KW - Humans KW - Imagination KW - Male KW - Middle Aged KW - Nerve Net KW - Speech Production Measurement KW - User-Computer Interface AB -

Electrocorticography (ECoG) has emerged as a new signal platform for brain-computer interface (BCI) systems. Classically, the cortical physiology that has been commonly investigated and utilized for device control in humans has been brain signals from the sensorimotor cortex. Hence, it was unknown whether other neurophysiological substrates, such as the speech network, could be used to further improve on or complement existing motor-based control paradigms. We demonstrate here for the first time that ECoG signals associated with different overt and imagined phoneme articulation can enable invasively monitored human patients to control a one-dimensional computer cursor rapidly and accurately. This phonetic content was distinguishable within higher gamma frequency oscillations and enabled users to achieve final target accuracies between 68% and 91% within 15 min. Additionally, one of the patients achieved robust control using recordings from a microarray consisting of 1 mm spaced microwires. These findings suggest that the cortical network associated with speech could provide an additional cognitive and physiologic substrate for BCI operation and that these signals can be acquired from a cortical array that is small and minimally invasive.

VL - 8 UR - http://www.ncbi.nlm.nih.gov/pubmed/21471638 IS - 3 ER - TY - JOUR T1 - Evolution of brain-computer interfaces: going beyond classic motor physiology. JF - Neurosurg Focus Y1 - 2009 A1 - Leuthardt, E C A1 - Gerwin Schalk A1 - Roland, Jarod A1 - Rouse, Adam A1 - Moran, D KW - Brain KW - Cerebral Cortex KW - Humans KW - Man-Machine Systems KW - Motor Cortex KW - Movement KW - Movement Disorders KW - Neuronal Plasticity KW - Prostheses and Implants KW - Research KW - Signal Processing, Computer-Assisted KW - User-Computer Interface AB -

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.

VL - 27 UR - http://www.ncbi.nlm.nih.gov/pubmed/19569892 IS - 1 ER -