Neural mind reading of multi-dimensional decisions by monkey mid-brain activity

Ryohei P. Hasegawa*, Yukako T. Hasegawa, Mark A. Segraves

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Brain-machine interfaces (BMIs) have the potential to improve the quality of life for individuals with disabilities. We engaged in the development of neural mind-reading techniques for cognitive BMIs to provide a readout of decision processes. We trained 2 monkeys on go/no-go tasks, and monitored the activity of groups of neurons in their mid-brain superior colliculus (SC). We designed a virtual decision function (VDF) reflecting the continuous progress of binary decisions on a single-trial basis, and applied it to the ensemble activity of SC neurons. Post hoc analyses using the VDF predicted the cue location as well as the monkey's motor choice (go or no-go) soon after the presentation of the cue. These results suggest that our neural mind-reading techniques have the potential to provide rapid real-time control of communication support devices.

Original languageEnglish (US)
Pages (from-to)1247-1256
Number of pages10
JournalNeural Networks
Volume22
Issue number9
DOIs
StatePublished - Nov 1 2009

Keywords

  • Brain-machine interface
  • Decision-making
  • Monkey
  • Saccade
  • Superior colliculus

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence

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