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Alexander Christoph Stahn1,2, Martin Riemer3, Thomas Wolbers3

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Frontiers in Neural Circuits
|June 26, 2020
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Summary
This summary is machine-generated.

Altered gravity conditions during parabolic flights impaired spatial updating performance for complex tasks. This highlights challenges for navigation in spaceflight and other environments with unreliable sensory cues.

Keywords:
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Area of Science:

  • Human physiology
  • Neuroscience
  • Space biology

Background:

  • Spatial updating is crucial for orientation, integrating visual, proprioceptive, kinesthetic, and vestibular information.
  • Weightlessness disrupts normal sensory integration, as gravity is a key reference.
  • Understanding how altered gravity affects spatial updating is vital for astronaut performance.

Purpose of the Study:

  • To investigate the impact of microgravity (0 g) and hypergravity (1.8 g) on spatial updating performance.
  • To assess how different task complexities (static, short, long virtual movements) influence performance under altered gravity.

Main Methods:

  • Ten healthy participants completed a visual-spatial updating task during parabolic flights.
  • The task involved virtual forward movements of varying lengths and a static condition.
  • Performance was measured during 1 g, 1.8 g, and 0 g phases of parabolic maneuvers.

Main Results:

  • Pointing performance was impaired during 0 g and 1.8 g for long virtual movement trials, showing increased error variability compared to 1 g.
  • No significant changes in performance were observed for short updating or static conditions.
  • Task complexity appears necessary to elicit performance decrements under altered gravity.

Conclusions:

  • Spatial updating performance is sensitive to altered gravity, particularly for more demanding tasks.
  • These findings have implications for navigation and operational safety during space missions, especially during extravehicular activities.
  • Further research should explore seated versus free-floating conditions and identify specific g-thresholds for performance changes.