Neural adaptation of epidural electrocorticographic (EECoG) signals during closed-loop brain computer interface (BCI) tasks

Annu Int Conf IEEE Eng Med Biol Soc. 2009:2009:5514-7. doi: 10.1109/IEMBS.2009.5333180.

Abstract

Invasive BCI studies have classically relied on actual or imagined movements to train their neural decoding algorithms. In this study, non-human primates were required to perform a 2D BCI task using epidural microECoG recordings. The decoding weights and cortical locations of the electrodes used for control were randomly chosen and fixed for a series of daily recording sessions for five days. Over a period of one week, the subjects learned to accurately control a 2D computer cursor through neural adaptation of microECoG signals over "cortical control columns" having diameters on a the order of a few mm. These results suggest that the spatial resolution of microECoG recordings can be increased via neural plasticity.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adaptation, Physiological / physiology
  • Animals
  • Biofeedback, Psychology / methods
  • Biofeedback, Psychology / physiology*
  • Dura Mater / physiopathology
  • Electroencephalography / methods*
  • Haplorhini
  • Motor Cortex / physiology*
  • Movement / physiology*
  • Nerve Net / physiology*
  • Neuronal Plasticity / physiology*
  • Task Performance and Analysis*
  • User-Computer Interface