2016/05/05 by Sameer Saproo, Saproo, Sameer, Victor Shih +5 · 1 citation
Medicine · Neuroscience · Psychology · #EEG and Brain-Computer Interfaces #FOS: Biological sciences #Heart Rate Variability and Autonomic Control #Human-Automation Interaction and Safety #Neurons and Cognition (q-bio.NC)
paper · pdf · doi:10.48550/arxiv.1605.01784
openalex publication_date 2016/05/05 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
Objective. We investigated the neural correlates of workload buildup in a\nfine visuomotor task called the boundary avoidance task (BAT). The BAT has been\nknown to induce naturally occurring failures of human-machine coupling in high\nperformance aircraft that can potentially lead to a crash; these failures are\ntermed pilot induced oscillations (PIOs). Approach. We recorded EEG and\npupillometry data from human subjects engaged in a flight BAT simulated within\na virtual 3D environment. Main results. We find that workload buildup in a BAT\ncan be successfully decoded from oscillatory features in the\nelectroencephalogram (EEG). Information in delta, theta, alpha, beta, and gamma\nspectral bands of the EEG all contribute to successful decoding, however gamma\nband activity with a lateralized somatosensory topography has the highest\ncontribution, while theta band activity with a frontocentral topography has the\nmost robust contribution in terms of real world usability. We show that the\noutput of the spectral decoder can be used to predict PIO susceptibility. We\nalso find that workload buildup in the task induces pupil dilation, the\nmagnitude of which is significantly correlated with the magnitude of the\ndecoded EEG signals. These results suggest that PIOs may result from the\ndysregulation of cortical networks such as the locus coeruleus (LC) anterior\ncingulate cortex (ACC) circuit. Significance. Our findings may generalize to\nsimilar control failures in other cases of tight man machine coupling where\ngains and latencies in the control system must be inferred and compensated for\nby the human operators. A closed-loop intervention using neurophysiological\ndecoding of workload buildup that targets the LC ACC circuit may positively\nimpact operator performance in such situations.\n