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This review explores how the brain controls movement by integrating neural population activity, optimal feedback, and body biomechanics. Understanding these interactions is key to advancing models of sensorimotor control.

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Area of Science:

  • Neuroscience
  • Motor Control
  • Computational Neuroscience

Background:

  • Sensorimotor control relies on complex interactions between neural populations, feedback mechanisms, and body biomechanics.
  • Existing models often focus on individual components, necessitating an integrated approach.

Purpose of the Study:

  • To review and synthesize current understanding of sensorimotor control.
  • To highlight the interplay between neural activity, optimal control principles, and biomechanics.
  • To identify future research directions for a comprehensive theory of motor control.

Main Methods:

  • Literature review of anatomical loops, neural population dynamics, optimal control theory, and embodied control.
  • Synthesis of findings from studies on sensorimotor signal processing and motor behavior.
  • Discussion of recent advances in elucidating neural activity via musculoskeletal dynamics.

Main Results:

  • Sensorimotor signals involve distributed loops connecting cortex, subcortical regions, and the spinal cord.
  • Neural population activity during movement planning and execution is characterized by low-dimensional, evolving manifolds.
  • Optimal control theory provides a framework for understanding internal models and feedback in motor control.

Conclusions:

  • An integrative account of neural movement control requires combining insights from neural populations, optimal feedback, and biomechanics.
  • Future research should address multitasking, cognitively rich behaviors, multiregional circuit models, and appropriate levels of anatomical detail.
  • Advances in embodied sensorimotor control are crucial for bridging current theoretical gaps.