Toward modeling a dynamic biological neural network

Mammalian macular endorgans are linear bioaccelerometers located in the vestibular membranous labyrinth of the inner ear. In this paper, the organization of the endorgan is interpreted on physical and engineering principles. This is a necessary prerequisite to mathematical and symbolic modeling of i...

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Veröffentlicht in:Mathematical and computer modelling 1990, Vol.13 (7), p.97-105
Hauptverfasser: Ross, M.D., Dayhoff, J.E., Mugler, D.H.
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container_title Mathematical and computer modelling
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creator Ross, M.D.
Dayhoff, J.E.
Mugler, D.H.
description Mammalian macular endorgans are linear bioaccelerometers located in the vestibular membranous labyrinth of the inner ear. In this paper, the organization of the endorgan is interpreted on physical and engineering principles. This is a necessary prerequisite to mathematical and symbolic modeling of information processing by the macular neural network. Mathematical notations that describe the functioning system were used to produce a novel, symbolic model. The model is six-tiered and is constructed to mimic the neural system. Initial simulations show that the network functions best when some of the detecting elements (type I hair cells) are excitatory and others (type II hair cells) are weakly inhibitory. The simulations also illustrate the importance of disinhibition of receptors located in the third tier in shaping nerve discharge patterns at the sixth tier in the model system.
doi_str_mv 10.1016/0895-7177(90)90132-7
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subjects Acceleration
Acoustic Maculae - anatomy & histology
Acoustic Maculae - physiology
Animals
Computer Simulation
Hair Cells, Vestibular - anatomy & histology
Hair Cells, Vestibular - physiology
Life Sciences (General)
Models, Neurological
Nerve Net - anatomy & histology
Nerve Net - physiology
Neural Networks (Computer)
Otolithic Membrane - anatomy & histology
Otolithic Membrane - physiology
Saccule and Utricle - anatomy & histology
Saccule and Utricle - physiology
Signal Transduction - physiology
Space life sciences
title Toward modeling a dynamic biological neural network
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