Control of a brain-computer interface without spike sorting.
Two rhesus monkeys were trained to move a cursor using neural activity recorded with silicon arrays of 96 microelectrodes implanted in the primary motor cortex. We have developed a method to extract movement information from the recorded single and multi-unit activity in the absence of spike sorting. By setting a single threshold across all channels and fitting the resultant events with a spline tuning function, a control signal was extracted from this population using a Bayesian particle-filter extraction algorithm. The animals achieved high-quality control comparable to the performance of decoding schemes based on sorted spikes. Our results suggest that even the simplest signal processing is sufficient for high-quality neuroprosthetic control.
Fraser
George W
GW
Department of Neurobiology, University of Pittsburgh, PA 15213, USA. gwf2@pitt.edu
Chase
Steven M
SM
Whitford
Andrew
A
Schwartz
Andrew B
AB
D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D005246:Feedback / Q000502:physiology*; D008253:Macaca mulatta; D008297:Male; D009068:Movement / Q000502:physiology*; D014584:User-Computer Interface