Dimensional reduction in sensorimotor systems: a framework for understanding muscle coordination of posture

Area of Science:

• Neuroscience
• Biomechanics
• Motor Control

Background:

• Standing balance is a complex motor behavior requiring integration of sensory information and muscle coordination.
• Redundant sensory inputs are processed to estimate key postural variables like body center of mass (CoM).
• Muscle synergies are employed to control task-variables, such as CoM position, during postural adjustments.

Purpose of the Study:

• To propose a hierarchical feedback control system for sensorimotor transformations in balance.
• To investigate how the nervous system simplifies goal-directed computations in task-variable space.
• To explore the transformations between low-dimensional task-space and high-dimensional sensor/muscle spaces.

Main Methods:

• Conceptual framework development.
• Analysis of sensorimotor transformations.
• Neuromechanical modeling.

Main Results:

• Postural actions are modulated in task-variable space.
• Transformations between low- and high-dimensional spaces are key to balance control.
• A hierarchical model offers robustness and computational simplicity.

Conclusions:

• Hierarchical feedback control simplifies sensorimotor computations for balance.
• Understanding these transformations is crucial for explaining motor control and its alterations after injury.
• Neuromechanical models can reveal organizational principles of sensorimotor transformations.