2016
DOI: 10.3389/fnhum.2016.00187
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The Brain Is Faster than the Hand in Split-Second Intentions to Respond to an Impending Hazard: A Simulation of Neuroadaptive Automation to Speed Recovery to Perturbation in Flight Attitude

Abstract: The goal of this research is to test the potential for neuroadaptive automation to improve response speed to a hazardous event by using a brain-computer interface (BCI) to decode perceptual-motor intention. Seven participants underwent four experimental sessions while measuring brain activity with magnetoencephalograpy. The first three sessions were of a simple constrained task in which the participant was to pull back on the control stick to recover from a perturbation in attitude in one condition and to pass… Show more

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Cited by 12 publications
(11 citation statements)
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“…These results contribute to a growing number of neuroergonomic‐based studies that maintain that the brain can better be understood by investigating it in real world like settings rather than simplified isolated conditions that only occur in the laboratory (Adamson et al, ; Callan et al, ; Callan, Falcone, Wada, & Parasuraman, ; Callan, Terzibas, Cassel, Sato, & Parasuraman, ; Durantin, Scannella, Gateau, Delorme, & Dehais, ; Durantin et al, ; Gateau, Durantin, Lancelot, Scannella, & Dehais, ; Scholl et al, ). This is specifically important when the critical situations under study cannot be easily simulated in the laboratory.…”
Section: Resultsmentioning
confidence: 88%
“…These results contribute to a growing number of neuroergonomic‐based studies that maintain that the brain can better be understood by investigating it in real world like settings rather than simplified isolated conditions that only occur in the laboratory (Adamson et al, ; Callan et al, ; Callan, Falcone, Wada, & Parasuraman, ; Callan, Terzibas, Cassel, Sato, & Parasuraman, ; Durantin, Scannella, Gateau, Delorme, & Dehais, ; Durantin et al, ; Gateau, Durantin, Lancelot, Scannella, & Dehais, ; Scholl et al, ). This is specifically important when the critical situations under study cannot be easily simulated in the laboratory.…”
Section: Resultsmentioning
confidence: 88%
“…Gateau et al (2016) implemented an online attentional state estimator coupled with a stochastic decision framework to dynamically adapt authority sharing between human and robots in a search and rescue scenario to prevent effort withdrawal on the part of the human. In a more extreme fashion, Callan et al (2016) revealed that it is possible to decode user motor intention so automation can perform on behalf of the user to drastically reduce the response time in emergency situations (e.g., collision with terrain). In the future, it is assumed that aircraft designers will implement adaptive automation technology that takes over from the pilots by either inhibiting their inputs on the flight deck or performing automated evasive actions (e.g., automatic pullup) to prevent from perseveration.…”
Section: Task and Automation Adaptationmentioning
confidence: 99%
“…These mental state-inference systems offer a unique insight into the development of the human-system interactions to overcome cognitive limitations (Zander and Kothe, 2011 ; Brouwer et al, 2013 ). While several pBCIs have been successfully implemented in driving (Dijksterhuis et al, 2013 ) and flight simulator (Gateau et al, 2015 ; Aricò et al, 2016 ; Çakır et al, 2016 ; Callan et al, 2016 ; Verdière et al, 2018 ), few have attempted to test these systems under more realistic settings. However, very few studies have attempted to test these adaptive systems under realistic settings (Callan et al, 2015 ).…”
Section: Introductionmentioning
confidence: 99%