Forward prediction in the posterior parietal cortex and dynamic brain-machine interface

He Cui

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

While remarkable progress has been made in brain-machine interfaces (BMIs) over the past two decades, it is still difficult to utilize neural signals to drive artificial actuators to produce predictive movements in response to dynamic stimuli. In contrast to naturalistic limb movements largely based on forward planning, brain-controlled neuroprosthetics mainly rely on feedback without prior trajectory formation. As an important sensorimotor interface integrating multisensory inputs and efference copy, the posterior parietal cortex (PPC) might play a proactive role in predictive motor control. Here it is proposed that predictive neural activity in PPC could be decoded to provide prosthetic control signals for guiding BMI systems in dynamic environments.

Original languageEnglish (US)
Article number35
JournalFrontiers in Integrative Neuroscience
Volume10
Issue numberOCT2016
DOIs
StatePublished - Oct 26 2016

Keywords

  • Decoding
  • Internal model
  • Motor control
  • Neuroengineering
  • Neuroprosthetics
  • Paralysis

ASJC Scopus subject areas

  • Sensory Systems
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

Fingerprint Dive into the research topics of 'Forward prediction in the posterior parietal cortex and dynamic brain-machine interface'. Together they form a unique fingerprint.

  • Cite this