Unknown

Dataset Information

Brain mechanisms of automated conflict avoidance simulator supervision.


ABSTRACT: Supervision of automated systems is an ubiquitous aspect of most of our everyday life activities which is even more necessary in high risk industries (aeronautics, power plants, etc.). Performance monitoring related to our own error making has been widely studied. Here we propose to assess the neurofunctional correlates of system error detection. We used an aviation-based conflict avoidance simulator with a 40% error-rate and recorded the electroencephalographic activity of participants while they were supervising it. Neural dynamics related to the supervision of system's correct and erroneous responses were assessed in the time and time-frequency domains to address the dynamics of the error detection process in this environment. Two levels of perceptual difficulty were introduced to asses

SUBMITTER: Somon B 

PROVIDER: S-EPMC10078105 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature