Fuzzy neuronal model of motor control inspired by cerebellar pathways to online and gradually learn inverse biomechanical functions in the presence of delay

DOI10.1007/s00422-017-0735-9zbMath1400.92116OpenAlexW2761841973WikidataQ47585689 ScholiaQ47585689MaRDI QIDQ1990671

Armin Salimi-Badr, Mohammad Mehdi Ebadzadeh, Christian Darlot

Publication date: 25 October 2018

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00422-017-0735-9

zbMATH Keywords

forward modelcerebellumapproximate inverse functiondeep cerebellar nuclei (DCN)fast movementsLTD/LTPonline gradual learningreflex pathways

Mathematics Subject Classification ID

Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20)

Cites Work

• Cerebellum-inspired neural network solution of the inverse kinematics problem
• A hierarchical neural-network model for control and learning of voluntary movement
• Adaptive filter model of the cerebellum
• A model of the cerebellar pathways applied to the control of a single-joint robot arm actuated by McKibben artificial muscles
• Computation of inverse dynamics for the control of movements
• Forward models for physiological motor control
• Data Storage in the Cerebellar Model Articulation Controller (CMAC)
• A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)
• Fuzzy systems as universal approximators