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Related Concept Videos

Hierarchy of Motor Control01:18

Hierarchy of Motor Control

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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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The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.
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A reflex activity is an automatic, involuntary response to specific stimuli. It is a part of our survival mechanism, designed to protect us from potential harm. For example, when a bright light suddenly shines into our eyes, we instinctively close them or look away. This is a simple reflex activity orchestrated by the nervous system without conscious thought or effort.
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Sensory impulses related to touch, pressure, vibration, and proprioception from various body parts, such as the limbs, trunk, neck, and posterior head, travel to the cerebral cortex through the posterior column-medial lemniscus pathway. The pathway’s name derives from the two white-matter tracts that convey the impulses: the spinal cord's posterior column and the brainstem's medial lemniscus. First-order sensory neurons extend their axons into the spinal cord, forming the...
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Related Experiment Video

Updated: Feb 17, 2026

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
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Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping.

Christian Schumacher1, André Seyfarth1

  • 1Lauflabor Locomotion Laboratory, Centre for Cognitive Science, Institute of Sport Science, Technische Universität Darmstadt, Darmstadt, Germany.

Frontiers in Computational Neuroscience
|December 13, 2017
PubMed
Summary

This study models hopping to show how sensory feedback pathways (length, velocity, force) influence movement. Different pathway combinations optimize hopping performance and efficiency, demonstrating robust sensor-motor maps adaptable to body variations.

Keywords:
feedback pathwaysfunctional decompositionhoppingmotor controlmultisensory integrationmuscle-tendon functionneuromechanicssensor-motor map

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Area of Science:

  • Biomechanics and Motor Control
  • Neuroscience
  • Robotics

Background:

  • Locomotion relies on sensory feedback for modulation.
  • Understanding reflex pathways is crucial for motor control research.
  • Existing models often lack adaptability to morphological variations.

Purpose of the Study:

  • To investigate the individual and combined roles of proprioceptive feedback pathways in hopping.
  • To develop and analyze a neuromuscular model of hopping.
  • To visualize and assess the robustness of sensory-motor maps.

Main Methods:

  • Developed a neuromuscular model simulating hopping movements.
  • Incorporated proprioceptive length (LFB), velocity (VFB), and force feedback (FFB) pathways.
  • Explored reflex parameter space to create 'sensor-motor maps'.
  • Evaluated map robustness against changes in physical and environmental parameters.

Main Results:

  • Different feedback pathway compositions selectively optimize hopping characteristics.
  • Force feedback (FFB) and length feedback (LFB) enable hopping; FFB maximizes height, LFB improves efficiency.
  • Velocity feedback (VFB) can disable hopping.
  • Sensor-motor map topology and optimal compositions were invariant to system design and environmental changes.

Conclusions:

  • Distinct feedback pathway compositions serve specific functional roles in motor control.
  • The robustness of sensor-motor maps suggests adaptability to diverse body mechanics.
  • This finding is highly relevant for understanding human motor control variability and designing adaptable robotic systems.