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[0] Santhanam G, Ryu SI, Yu BM, Afshar A, Shenoy KV, A high-performance brain-computer interface.Nature 442:7099, 195-8 (2006 Jul 13)[1] Shenoy KV, Meeker D, Cao S, Kureshi SA, Pesaran B, Buneo CA, Batista AP, Mitra PP, Burdick JW, Andersen RA, Neural prosthetic control signals from plan activity.Neuroreport 14:4, 591-6 (2003 Mar 24)

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ref: Santhanam-2006.07 tags: Shenoy BMI BCI trials date: 01-08-2012 23:37 gmt revision:4 [3] [2] [1] [0] [head]

PMID-16838020[0] A high-performance brain-computer interface

  • the speed and accuracy with which keys can be selected using BCIs is still far lower than for systems relying on eye movements.
    • What is the eye-movement rate?
  • implanted in PMD. 96 electrodes (utah array).
  • used an instructed-delay task. figure 1
    • monkey had to move to target when center target disappeared. peripheral target appeared several seconds prior.
  • actually had the monkey reach to targets; if correct, monkey was immediately rewarded.
    • real movement trials were interspersed to keep the monkey engaged.
  • decoding model: assume that the spike counts come from a poisson or gaussian distribution. Apply ML decoding.
    • poisson better than gaussian.
  • up to 6.5 bits per second, or approximately 15 words per minute, with 96 electrodes.
    • Peak of continuous control = 1.6 bits per second.
  • ITRC = information transfer rate capacity. this metric is proportional to the single trial accuracy / trial length (sorta, see ref 23 - Blahut-Arimoto algorithm)
  • most of their neurons seem to be responsive to actual movements (que supressa!)
  • maximum bandwidth with a trial length of 250ms.
    • lots of other good information-theoretic analysis.
  • PMID-12657892[1] Neural prosthetic control signals from plan activity. -- the preceding Neuroreport simulation study.
    • performance to exceed 90% with as few as 40 neurons.
    • maximum likelihood decoders controlling a FSM.