Distributed cortical adaptation during learning of a brain-computer interface task

  • ,
  • Timothy Blakely ,
  • Kai J. Miller ,
  • Kurt E. Weaver ,
  • Lise A. Johnson ,
  • Jared D. Olson ,
  • Eberhard E. Fetz ,
  • Rajesh P. N. Rao ,
  • Jeffrey G. Ojemann

Proceedings of the National Academy of Sciences |

Published by National Academy of Sciences

Publication

The majority of subjects who attempt to learn control of a brain–computer interface (BCI) can do so with adequate training. Much like when one learns to type or ride a bicycle, BCI users report transitioning from a deliberate, cognitively focused mindset to near automatic control as training progresses. What are the neural correlates of this process of BCI skill acquisition? Seven subjects were implanted with electrocorticography (ECoG) electrodes and had multiple opportunities to practice a 1D BCI task. As subjects became proficient, strong initial task-related activation was followed by lessening of activation in prefrontal cortex, premotor cortex, and posterior parietal cortex, areas that have previously been implicated in the cognitive phase of motor sequence learning and abstract task learning. These results demonstrate that, although the use of a BCI only requires modulation of a local population of neurons, a distributed network of cortical areas is involved in the acquisition of BCI proficiency.