Control of a brain-computer interface without spike sorting

J Neural Eng. 2009 Oct;6(5):055004. doi: 10.1088/1741-2560/6/5/055004. Epub 2009 Sep 1.

Abstract

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.

MeSH terms

  • Action Potentials / physiology*
  • Algorithms*
  • Animals
  • Brain / physiology*
  • Electroencephalography / methods*
  • Evoked Potentials, Motor / physiology*
  • Feedback / physiology*
  • Macaca mulatta
  • Male
  • Movement / physiology*
  • User-Computer Interface*