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Reading: Study reveals why some gamers prefer inverted controls and the cognitive science behind it
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Home » Blog » Study reveals why some gamers prefer inverted controls and the cognitive science behind it
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Study reveals why some gamers prefer inverted controls and the cognitive science behind it

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Last updated: September 22, 2025 11:29 AM
David Graff
Published: September 22, 2025
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Inverted Controls
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A recent study by Dr. Jennifer Corbett and Dr. Jaap Munneke from Brunel University London sheds light on why some gamers prefer inverted controls while others do not.

Why it matters: Understanding the cognitive factors behind control preferences can improve human-computer interactions in various fields, from gaming to surgery.

The details:

  • Participants completed tasks related to spatial awareness, such as mentally rotating shapes and determining object tilt.
  • The most predictive factor was how quickly gamers could mentally rotate objects and overcome the “Simon effect” – the difficulty in responding when a target appears on the opposite side of the screen from the response button.
  • Faster performance in these tasks correlated with a lower likelihood of inverting controls.
  • Inverters were generally more accurate, even if slower, compared to non-inverters.

The study suggests that personal experiences, such as playing flight simulators or using certain consoles, do not significantly influence control preferences. Instead, it is more likely due to how an individual’s brain perceives objects in 3D space.

What they’re saying:

  • “The most surprising finding for non-inverters is that they might perform better with practice using an inverted control scheme. It could dramatically enhance competitive gameplay.” – Dr. Jennifer Corbett
  • “Understanding how an individual performs best with certain settings can improve interactions between humans and machines in various scenarios.” – Dr. Jennifer Corbett

The other side: Some gamers may have a strong preference for their current control scheme due to familiarity and learned behavior.

What’s next: The research has broader applications in optimizing human-machine teaming, from AI-human collaboration in gaming to improving precision in laparoscopic surgery.

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ByDavid Graff
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David is the editor-in-chief of Techpinions.com. Technologist, writer, journalist.
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