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Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

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Published on: May 8, 2021

Optimal motor control may mask sensory dynamics.

Sean G Carver¹, Tim Kiemel, Noah J Cowan

¹Department of Psychological and Brain Sciences, The Johns Hopkins University, Baltimore, MD 21218, USA. sean.carver@jhu.edu

Biological Cybernetics

|May 2, 2009

Summary

Standard system identification methods may miss key neural controller properties in sensorimotor behavior. New closed-loop system identification techniques are needed to uncover hidden controller features by perturbing the system between sensor and control.

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Area of Science:

Neuroscience
Control Theory
System Identification

Background:

Neural controllers govern sensorimotor behavior.
System identification infers controller properties from input-output relationships.
Standard methods analyze closed-loop systems by perturbing the input and measuring the output.

Purpose of the Study:

To investigate limitations of standard system identification for neural controllers.
To identify methods for uncovering hidden controller features.
To explore the impact of optimal control assumptions on system identification.

Main Methods:

Analysis of closed-loop sensorimotor systems under optimal control assumptions.
Comparison of standard system identification with novel closed-loop methods.
Exploration of perturbing the system between sensor and controller.

Main Results:

Standard system identification can miss crucial neural controller properties, specifically the masking of sensor modes by controller zeros.
These hidden features can be revealed by perturbing or measuring the system between the sensor and the controller.
Noninvasive techniques like galvanic vestibular stimulation offer a means to achieve this targeted perturbation.

Conclusions:

Current system identification paradigms may provide incomplete insights into neural control.
Advanced closed-loop system identification methods are essential for a comprehensive understanding of sensorimotor control.
Targeted perturbations between sensory and control elements are key to unlocking hidden neural controller dynamics.