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Summary
This summary is machine-generated.

Human motor control performance improves when considering computational costs. Bounded rational decision theory accurately models sensorimotor performance under time constraints, suggesting it

Keywords:
bounded rationalitycomputational costinformation-processing resourcesmotor controlmovement planningoptimality modelreaction time

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Decision Theory

Background:

  • Expected utility models are standard for motor task baselines but neglect computational costs.
  • Bounded rational decision theory accounts for limited information-processing capacity in strategy adaptation.

Purpose of the Study:

  • To investigate human sensorimotor performance under restricted reaction and movement times.
  • To evaluate bounded rational decision theory as a normative framework for motor control.

Main Methods:

  • A pointing task was designed with manipulated reaction times to limit computational planning.
  • Target location distributions were varied to influence prior strategy and information-processing demands.

Main Results:

  • Movement endpoint precision decreased significantly with reduced planning time.
  • Non-uniform target probabilities improved precision for high-probability targets.
  • Human performance closely approximated bounded optimal strategies.

Conclusions:

  • Bounded rational decision theory offers a promising framework for analyzing human sensorimotor control.
  • Computational costs and prior knowledge significantly impact motor task performance.