Decoding movement-related cortical potentials from electrocorticography

Chandan G. Reddy*, Goutam G. Reddy, Hiroto Kawasaki, Hiroyuki Oya, Lee E. Miller, Matthew A. Howard

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Object Control signals for brain-machine interfaces may be obtained from a variety of sources, each with their own relative merits. Electrocorticography (ECoG) provides better spatial and spectral resolution than scalp electroencephalography and does not include the risks attendant upon penetration of the brain parenchyma associated with single and multiunit recordings. For these reasons, subdural electrode recordings have been proposed as useful primary or adjunctive control signals for brain-machine interfaces. The goal of the present study was to determine if 2D control signals could be decoded from ECoG. Methods Six patients undergoing invasive monitoring for medically intractable epilepsy using subdural grid electrodes were asked to perform a motor task involving moving a joystick in 1 of 4 cardinal directions (up, down, left, or right) and a fifth condition (" trigger"). Evoked activity was synchronized to joystick movement and analyzed in the theta, alpha, beta, gamma, and high-gamma frequency bands. Results Movement-related cortical potentials could be accurately differentiated from rest with very high accuracy (83-96%). Further distinguishing the movement direction (up, down, left, or right) could also be resolved with high accuracy (58-86%) using information only from the high-gamma range, whereas distinguishing the trigger condition from the remaining directions provided better accuracy. Conclusions Two-dimensional control signals can be derived from ECoG. Local field potentials as measured by ECoG from subdural grids will be useful as control signals for a brain-machine interface.

Original languageEnglish (US)
JournalNeurosurgical focus
Volume27
Issue number1
DOIs
StatePublished - 2009

Keywords

  • Brain-machine interface
  • Electrocorticography
  • Epilepsy
  • Local field potentials
  • Motor control

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology

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