OBJECT: Control signals for brain-machine interfaces may be obtained from a variety of sources, each with their own relative merits. Electrocorticography (ECoG) provides better spatial and spectral resolution than scalp electroencephalography and does not include the risks attendant upon penetration of the brain parenchyma associated with single and multiunit recordings. For these reasons, subdural electrode recordings have been proposed as useful primary or adjunctive control signals for brain-machine interfaces. The goal of the present study was to determine if 2D control signals could be decoded from ECoG. METHODS: Six patients undergoing invasive monitoring for medically intractable epilepsy using subdural grid electrodes were asked to perform a motor task involving moving a joystick in 1 of 4 cardinal directions (up, down, left, or right) and a fifth condition ("trigger"). Evoked activity was synchronized to joystick movement and analyzed in the theta, alpha, beta, gamma, and high-gamma frequency bands. RESULTS: Movement-related cortical potentials could be accurately differentiated from rest with very high accuracy (83-96%). Further distinguishing the movement direction (up, down, left, or right) could also be resolved with high accuracy (58-86%) using information only from the high-gamma range, whereas distinguishing the trigger condition from the remaining directions provided better accuracy. CONCLUSIONS: Two-dimensional control signals can be derived from ECoG. Local field potentials as measured by ECoG from subdural grids will be useful as control signals for a brain-machine interface.
OBJECT: Control signals for brain-machine interfaces may be obtained from a variety of sources, each with their own relative merits. Electrocorticography (ECoG) provides better spatial and spectral resolution than scalp electroencephalography and does not include the risks attendant upon penetration of the brain parenchyma associated with single and multiunit recordings. For these reasons, subdural electrode recordings have been proposed as useful primary or adjunctive control signals for brain-machine interfaces. The goal of the present study was to determine if 2D control signals could be decoded from ECoG. METHODS: Six patients undergoing invasive monitoring for medically intractable epilepsy using subdural grid electrodes were asked to perform a motor task involving moving a joystick in 1 of 4 cardinal directions (up, down, left, or right) and a fifth condition ("trigger"). Evoked activity was synchronized to joystick movement and analyzed in the theta, alpha, beta, gamma, and high-gamma frequency bands. RESULTS: Movement-related cortical potentials could be accurately differentiated from rest with very high accuracy (83-96%). Further distinguishing the movement direction (up, down, left, or right) could also be resolved with high accuracy (58-86%) using information only from the high-gamma range, whereas distinguishing the trigger condition from the remaining directions provided better accuracy. CONCLUSIONS: Two-dimensional control signals can be derived from ECoG. Local field potentials as measured by ECoG from subdural grids will be useful as control signals for a brain-machine interface.
Authors: Jonathan R Wolpaw; Niels Birbaumer; Dennis J McFarland; Gert Pfurtscheller; Theresa M Vaughan Journal: Clin Neurophysiol Date: 2002-06 Impact factor: 3.708
Authors: Jose M Carmena; Mikhail A Lebedev; Roy E Crist; Joseph E O'Doherty; David M Santucci; Dragan F Dimitrov; Parag G Patil; Craig S Henriquez; Miguel A L Nicolelis Journal: PLoS Biol Date: 2003-10-13 Impact factor: 8.029
Authors: Omid Talakoub; Milos R Popovic; Jessie Navaro; Clement Hamani; Erich T Fonoff; Willy Wong Journal: Front Neurosci Date: 2015-01-13 Impact factor: 4.677