A Concurrent Brain-Machine Interface for Enhanced Sequential Motor Function

  • Maryam M. Shanechi
  • Rollin C. Hu
  • Marissa Powers
  • Gregory W. Wornell
  • Emery N. Brown
  • Ziv M. Williams
Chapter
First Online:
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

Brain-machine interfaces (BMIs) have largely been designed for performing single-targeted movements. However, many tasks involve planning a sequence of such targeted movements before execution. Hence a BMI that can concurrently decode the complete planned sequence before its execution can enable subjects to also perform these sequential movements. Moreover, such concurrent decoding may allow the BMI to consider the higher-level goal of the task to reformulate the motor plan and perform it more effectively. Here, we demonstrate that concurrent BMI decoding is possible. Using population-wide modeling, we discovered two distinct subpopulations of neurons in the rhesus monkey premotor cortex that allowed two planned targets of a sequential movement to be simultaneously held in working memory without degradation. Interestingly, this simultaneous representation occurred because each subpopulation encoded either only currently held or only newly added target information regardless of the exact sequence. Capitalizing on this stable representation, we developed a BMI that concurrently decodes a full motor sequence in advance of movement and can then accurately execute it as desired.

Keywords

Brain-machine interface Neuroprosthetics Working memory Sequential motor function Premotor cortex 
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Copyright information

© The Author(s) 2014

Authors and Affiliations

  • Maryam M. Shanechi
    • 1
  • Rollin C. Hu
    • 2
    • 3
  • Marissa Powers
    • 2
  • Gregory W. Wornell
    • 4
  • Emery N. Brown
    • 2
    • 3
    • 5
  • Ziv M. Williams
    • 2
    • 3
  1. 1.Ming Hsieh Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Massachusetts General HospitalBostonUSA
  3. 3.Harvard Medical SchoolBostonUSA
  4. 4.Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyCambridgeUSA
  5. 5.Department of Brain and Cognitive SciencesMassachusetts Institute of TechnologyCambridgeUSA

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