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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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Predictability of trajectory modulates manual tracking: from real-time feedback to internal-model-based control.

Yuqi You1, Pin Yang2, Zhongting Chen3

  • 1Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine and School of Psychology, Shanghai, China.

Cognitive Psychology
|April 14, 2026
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Summary

Humans adapt sensorimotor control for predictable tasks, reducing reliance on real-time vision. This study reveals internal mechanisms enhance visuomotor processes, even without performance gains.

Keywords:
Bayesian integrationInternal modelManual trackingTrajectory predictabilityVisuomotor control

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Area of Science:

  • Human sensorimotor control
  • Visuomotor adaptation
  • Internal representations in motor control

Background:

  • Humans exhibit remarkable environmental adaptation.
  • Fundamental questions remain regarding internal representations for efficient feedforward control in sensorimotor tasks.

Purpose of the Study:

  • To investigate whether and how internal representations facilitate feedforward control.
  • To examine the modulation of manual tracking by trajectory predictability in humans.

Main Methods:

  • Manual tracking tasks with varying trajectory predictability.
  • Kalman filter modeling to analyze visuomotor processes.
  • Assessment of human participants' tracking performance and adaptation strategies.

Main Results:

  • No significant improvement in tracking performance was observed due to trajectory predictability, even when participants were aware of it.
  • Kalman filter analysis revealed participants reduced reliance on real-time visual input for more predictable trajectories.
  • Adaptation in visuomotor processes occurred despite unchanged overall tracking performance.

Conclusions:

  • Humans adapt sensorimotor control by adjusting reliance on internal mechanisms versus real-time feedback based on trajectory predictability.
  • The study highlights adaptive use of environmental information redundancy.
  • Findings provide insights into the balance between feedforward and feedback control mechanisms in human motor behavior.