Adaptive conductance control. (2022)

• Record Type: Journal Article
• Authors: Schmetterling, Raphael; Burghi, Thiago B.; Sepulchre, Rodolphe
• Is Part Of: Annual reviews in control. Volume 54(2022)
• Page Start: 352
• Page End: 362
• Publication Date: 2022
• Subjects: Adaptive control -- Conductance-based models -- Biophysical models -- Bursting -- Neuromorphics -- Neuromodulation; Automatic control -- Periodicals; Periodicals; 629.805
• DOI: 10.1016/j.arcontrol.2022.07.005
• Languages: English
• ISSNs: 1367-5788

Abstract

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.