DocumentCode
1517740
Title
Learning from biological systems: modeling neural control
Author
He, Jiping ; Maltenfort, Mitchell G. ; Wang, Qingjun ; Hamm, Thomas M.
Author_Institution
Dept. of Bioeng., Arizona State Univ., Tempe, AZ, USA
Volume
21
Issue
4
fYear
2001
fDate
8/1/2001 12:00:00 AM
Firstpage
55
Lastpage
69
Abstract
We have been pursuing a modular approach to modeling and investigating the neural control of posture and movement. A modular approach is a practical and natural way of investigating the function and structure of the complex central nervous system (CNS). The modules can include skeletal dynamics, muscle dynamics with recruitment and force-generation characteristics, basic spinal cord neural circuits responsible for the local stretch reflex, interneuronal networks that provide modulation of various reflexes, various structures of brain circuits, and control strategy decision-making centers. The anatomical detail and complexity of each module can vary depending on the specific scientific question or motor task to be investigated and the extent of information available on the hierarchy. To demonstrate the modular approach, we present two examples that illustrate how biological motor control tasks can be investigated in varying degrees of complexity and detail. One example shows that a model with detailed anatomical structure and dynamic properties has to be developed to investigate the detailed interactions among several sensory feedback loops in the spinal cord. The other example shows that when investigating whole-body behavior, a grosser structured model with lumped components is more tractable so issues such as the interaction of spinal cord regulation and upper CNS intelligent control can be investigated
Keywords
biocontrol; biomechanics; feedback; neurophysiology; physiological models; basic spinal cord neural circuits; biological motor control tasks; biological systems; brain circuits; complex central nervous system; control strategy decision-making centers; detailed anatomical structure; dynamic properties; force-generation characteristics; intelligent control; interneuronal networks; local stretch reflex; modular approach; movement control; muscle dynamics; neural control; posture control; sensory feedback loops; skeletal dynamics; spinal cord; whole-body behavior; Biological control systems; Biological system modeling; Biological systems; Central nervous system; Circuits; Control system synthesis; Force control; Muscles; Recruitment; Spinal cord;
fLanguage
English
Journal_Title
Control Systems, IEEE
Publisher
ieee
ISSN
1066-033X
Type
jour
DOI
10.1109/37.939944
Filename
939944
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