Emergent mechanisms in multiple pattern generation of the lobster pyloric network
By using a hard-wired oscillator network, multiple pattern generation of the lobster pyloric network is simulated. The network model is constructed using a relaxation oscillator representing an oscillatory or quiescent (i.e. steady-state) neuron. Modulatory inputs to the network are hypothesized to...
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| Published in | Biological cybernetics Vol. 82; no. 6; pp. 443 - 454 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Germany
Springer Nature B.V
01.06.2000
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| Subjects | |
| Online Access | Get full text |
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| Abstract | By using a hard-wired oscillator network, multiple pattern generation of the lobster pyloric network is simulated. The network model is constructed using a relaxation oscillator representing an oscillatory or quiescent (i.e. steady-state) neuron. Modulatory inputs to the network are hypothesized to cause changes in the dynamical properties of each pyloric neuron: the oscillatory frequency, the postinhibitory rebound property, and the resting membrane potential. Changes in each of these properties are induced by changing appropriate parameters of the oscillator. By changing seven parameters of the network as a whole, modulatory input-dependent patterns are successfully simulated. |
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| AbstractList | By using a hard-wired oscillator network, multiple pattern generation of the lobster pyloric network is simulated. The network model is constructed using a relaxation oscillator representing an oscillatory or quiescent (i.e. steady-state) neuron. Modulatory inputs to the network are hypothesized to cause changes in the dynamical properties of each pyloric neuron: the oscillatory frequency, the postinhibitory rebound property, and the resting membrane potential. Changes in each of these properties are induced by changing appropriate parameters of the oscillator. By changing seven parameters of the network as a whole, modulatory input-dependent patterns are successfully simulated. By using a hard-wired oscillator network, multiple pattern generation of the lobster pyloric network is simulated. The network model is constructed using a relaxation oscillator representing an oscillatory or quiescent (i.e. steady-state) neuron. Modulatory inputs to the network are hypothesized to cause changes in the dynamical properties of each pyloric neuron: the oscillatory frequency, the postinhibitory rebound property, and the resting membrane potential. Changes in each of these properties are induced by changing appropriate parameters of the oscillator. By changing seven parameters of the network as a whole, modulatory input-dependent patterns are successfully simulated.[PUBLICATION ABSTRACT] |
| Author | Yano, M Makino, Y Akiyama, M |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/10879428$$D View this record in MEDLINE/PubMed |
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| DOI | 10.1007/s004220050597 |
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| Snippet | By using a hard-wired oscillator network, multiple pattern generation of the lobster pyloric network is simulated. The network model is constructed using a... |
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| SubjectTerms | Animals Crustaceans Cybernetics Lobsters Marine Mathematical models Membrane Potentials Models, Biological Nephropidae - physiology Nerve Net Networks Neurons Oscillators Pattern generation Pylorus - physiology Simulation |
| Title | Emergent mechanisms in multiple pattern generation of the lobster pyloric network |
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