Performance on the Robotics On-Board Trainer (ROBoT-r) Spaceflight Simulation During Acute Sleep Deprivation

• Published in: Frontiers in neuroscience Vol. 14; p. 697
• Main Authors: Wong, Lily, Pradhan, Sean, Karasinski, John, Hu, Cindy, Strangman, Gary, Ivkovic, Vladimir, Arsintescu, Lucia, Flynn-Evans, Erin
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 21.07.2020; Frontiers Media S.A
• Subjects: Anxiety; Astronauts; circadian phase; Circadian rhythms; complex tasks; Decision making; Fatigue; Laboratories; Mental depression; Neuroscience; Robotics; Robotics On-Board Trainer; Robots; Simulation; Sleep and wakefulness; Sleep deprivation; sleep loss; Space flight; Space stations; Training; Vigilance
• ISSN: 1662-453X; 1662-4548; 1662-453X
• DOI: 10.3389/fnins.2020.00697

Exploration of deep space poses many challenges. Mission support personnel will not be immediately available to assist crewmembers performing complex operations on future long-duration exploration operations. Consequently, it is imperative that crewmembers have objective, reliable, and non-invasive metrics available to aid them in determining their fitness for duty prior to engaging in potentially dangerous tasks. The Robotics On-­Board Trainer (ROBoT) task is NASA’s platform for training astronauts to perform docking and grappling maneuvers. It is regularly used by crewmembers during spaceflight for refresher training. The operational ROBoT system, however, does not record data. Thus, a research version of ROBoT, called ROBoT-r, was developed so that operationally-relevant data could be mined to provide feedback to crewmembers. We investigated whether ROBoT-r metrics would change according to sleep loss and circadian phase in a 28-hour laboratory-based sleep deprivation study. Overall, participants showed improvement over time despite sleep loss, indicating continued learning. Performance on the psychomotor vigilance task (PVT) followed an expected profile, with reduced performance across the night. These findings suggest that individuals may be able to temporarily compensate for sleep loss to maintain performance on complex, novel tasks. It is possible that some ROBoT-r metrics may be sensitive to sleep loss after longer bouts of wakefulness or after individuals have habituated to the task. Studies with additional participants and extended pre-training on the ROBoT-r task should be conducted to disentangle how brain activity may change as individuals learn and habituate to complex tasks during sleep loss.