Adaptive Conductance Control

TL;DR

This paper introduces an adaptive control method for conductance parameters in neuronal models, aligning neuromodulation principles with impedance control, enhancing robustness and adaptability in neural systems.

Contribution

It presents a novel adaptive control framework for conductance-based neuronal models, bridging neuroscience and robotics concepts.

Findings

Adaptive control effectively modulates conductance parameters.

Method aligns with physiological neuromodulation.

Provides a robust approach for neuronal model regulation.

Abstract

Neuromodulation is central to the adaptation and robustness of animal nervous systems. This paper explores the classical paradigm of indirect adaptive control to design neuromodulatory controllers in conductance-based neuronal models. The adaptive control of maximal conductance parameters is shown to provide a methodology aligned with the central concepts of neuromodulation in physiology and of impedance control in robotics.