Physiological properties of brain-machine interface input signals

Marc W. Slutzky*, Robert D. Flint

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

21 Scopus citations

Abstract

Brain-machine interfaces (BMIs), also called brain-computer interfaces (BCIs), decode neural signals and use them to control some type of external device. Despite many experimental successes and terrific demonstrations in animals and humans, a high-performance, clinically viable device has not yet been developed for widespread usage. There are many factors that impact clinical viability and BMI performance. Arguably, the first of these is the selection of brain signals used to control BMIs. In this review, we summarize the physiological characteristics and performance—including movement-related information, longevity, and stability—of multiple types of input signals that have been used in invasive BMIs to date. These include intracortical spikes as well as field potentials obtained inside the cortex, at the surface of the cortex (electrocorticography), and at the surface of the dura mater (epidural signals). We also discuss the potential for future enhancements in input signal performance, both by improving hardware and by leveraging the knowledge of the physiological characteristics of these signals to improve decoding and stability.

Original languageEnglish (US)
Pages (from-to)1329-1343
Number of pages15
JournalJournal of neurophysiology
Volume118
Issue number2
DOIs
StatePublished - Aug 14 2017

Keywords

  • Brain-machine interface
  • ECoG
  • Epidural signals
  • LFP
  • Longevity
  • Spikes
  • Stability

ASJC Scopus subject areas

  • Neuroscience(all)
  • Physiology

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