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Control of a brain–computer interface without spike sorting

George W Fraser1,2,5, Steven M Chase1,2,3, Andrew Whitford2,4 and Andrew B Schwartz1,2,4

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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.


PACS

87.85.Ng Biological signal processing

07.05.Wr Computer interfaces

87.19.L- Neuroscience

87.19.R- Mechanical and electrical properties of tissues and organs

Subjects

Instrumentation and measurement

Medical physics

Biological physics

Dates

Issue 5 (October 2009)

Received 16 January 2009, accepted for publication 15 July 2009

Published 1 September 2009



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