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The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
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The indirect motor or extrapyramidal pathways originate in the brainstem, the lower portion of the brain that connects it to the spinal cord. They consist of several distinct tracts, each with specialized functions. The four main tracts of the indirect motor pathways are the vestibulospinal tract, the reticulospinal tract, the tectospinal tract, and the rubrospinal tract.
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Updated: Oct 21, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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Motor planning under uncertainty.

Laith Alhussein1, Maurice A Smith1,2

  • 1John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States.

Elife
|September 6, 2021
PubMed
Summary
This summary is machine-generated.

When facing uncertain goals, the brain optimizes actions for peak performance, not by averaging potential movements. This research offers new insights into how the nervous system makes decisions for motor planning.

Keywords:
decision makingforce-fieldhumanmovement planningneurosciencereachingsafety marginuncertainty

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Area of Science:

  • Neuroscience
  • Motor Control
  • Cognitive Psychology

Background:

  • Goal-directed actions often involve choosing among multiple possibilities.
  • Previous theories proposed the brain averages motor plans during goal uncertainty.

Purpose of the Study:

  • To investigate whether the brain averages motor plans or optimizes for performance under goal uncertainty.
  • To dissociate between averaging and optimization theories of motor planning.

Main Methods:

  • Novel experimental manipulations to create goal uncertainty.
  • Analysis of population-averaged motor output.
  • Development of a computational model based on performance-optimization theory.

Main Results:

  • Humans generate motor plans that optimize task performance when faced with uncertainty.
  • The performance-optimization theory accurately predicted population-averaged motor output changes.
  • The computational model explained significant individual differences in motor planning.

Conclusions:

  • The brain optimizes motor plans for performance rather than averaging possibilities during goal uncertainty.
  • Findings provide fundamental insights into the neural mechanisms of motor planning.
  • Resolves a long-standing question in neuroscience regarding action selection under uncertainty.