Neural mechanisms underlying catastrophic failure in human-machine interaction during aerial navigation

Objective. We investigated the neural correlates of workload buildup in a fine visuomotor task called the boundary avoidance task (BAT). The BAT has been known to induce naturally occurring failures of human-machine coupling in high performance aircraft that can potentially lead to a crash-these fai...

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Vydané v:Journal of neural engineering Ročník 13; číslo 6; s. 066005 - 66015
Hlavní autori: Saproo, Sameer, Shih, Victor, Jangraw, David C, Sajda, Paul
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England IOP Publishing 01.12.2016
Predmet:
Adult
Aircraft
Algorithms
Aviation
boundary avoidance task
Decision Making - physiology
EEG
Electroencephalography
Female
flight
Gyrus Cinguli - physiology
Humans
Locus Coeruleus - physiology
Male
Man-Machine Systems
motor control
Nerve Net - physiology
pilot induced oscillations
Pilots
Psychomotor Performance - physiology
pupillometry
rapid decision making
Reflex, Pupillary - physiology
Somatosensory Cortex - physiology
Virtual Reality
Workload
Young Adult
ISSN:1741-2560, 1741-2552, 1741-2552
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Shrnutí:Objective. We investigated the neural correlates of workload buildup in a fine visuomotor task called the boundary avoidance task (BAT). The BAT has been known to induce naturally occurring failures of human-machine coupling in high performance aircraft that can potentially lead to a crash-these failures are termed pilot induced oscillations (PIOs). Approach. We recorded EEG and pupillometry data from human subjects engaged in a flight BAT simulated within a virtual 3D environment. Main results. We find that workload buildup in a BAT can be successfully decoded from oscillatory features in the electroencephalogram (EEG). Information in delta, theta, alpha, beta, and gamma spectral bands of the EEG all contribute to successful decoding, however gamma band activity with a lateralized somatosensory topography has the highest contribution, while theta band activity with a fronto-central topography has the most robust contribution in terms of real-world usability. We show that the output of the spectral decoder can be used to predict PIO susceptibility. We also find that workload buildup in the task induces pupil dilation, the magnitude of which is significantly correlated with the magnitude of the decoded EEG signals. These results suggest that PIOs may result from the dysregulation of cortical networks such as the locus coeruleus (LC)-anterior cingulate cortex (ACC) circuit. Significance. Our findings may generalize to similar control failures in other cases of tight man-machine coupling where gains and latencies in the control system must be inferred and compensated for by the human operators. A closed-loop intervention using neurophysiological decoding of workload buildup that targets the LC-ACC circuit may positively impact operator performance in such situations.
Bibliografia:JNE-101247.R3
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ISSN:1741-2560
1741-2552
1741-2552
DOI:10.1088/1741-2560/13/6/066005