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Neuromorphic meets neuromechanics, part I: the methodology and implementation
Chuanxin M Niu1,2, Kian Jalaleddini3, Won Joon Sohn3
1Department of Rehabilitation Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
Journal of Neural Engineering
|January 14, 2017
Summary
Researchers created a neuromechanical system using spiking neurons to mimic muscle afferentation. This system realistically reproduced stretch reflexes in cadaveric fingers, advancing neuromorphic engineering for robotic applications.
Area of Science:
- Neuromorphic Engineering
- Robotics
- Biophysics
Background:
- Neuromorphic engineering aims to create realistic robotic systems by mimicking biological principles.
- Implementing spinal circuitry for muscle afferentation is crucial for robotic behavior.
- Muscle afferentation involves complex interactions between neurons, muscle fibers, and sensory receptors.
Purpose of the Study:
- To develop a neuromechanical system that emulates biological muscle afferentation.
- To create a platform for studying sensorimotor function in robotic systems.
- To investigate the mechanisms of healthy and pathological sensorimotor control.
Main Methods:
- Utilized programmable very-large-scale-circuit (VLSI) hardware to model spiking neurons and muscle systems.
- Implemented models of muscle spindle proprioceptors, alpha- and gamma-motoneurons, and their circuitry.
- Created a multi-scale system emulating antagonistic mammalian muscles acting on a joint via tendons.
Main Results:
- The system successfully maintained joint angles and reproduced stretch reflex responses in cadaveric fingers.
- Explored various gamma-gain values, replicating some human pathological conditions.
- Investigated muscle force production models, finding sensitivity to tendon elasticity.
Conclusions:
- Developed the first autonomous, multi-scale, neuromorphic, neuromechanical system for realistic reflex behavior.
- The research platform enables first-principles exploration of sensorimotor function.
- This work is a precursor to advanced neuromorphic robotic systems.
