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Simple capacitor-switch model of excitatory and inhibitory neuron with all parts biologically explained allows input fire pattern dependent chaotic oscillations
P. Cejnar, O. Vyšata, J. Kukal, M. Beránek, M. Vališ, A. Procházka,
Language English Country Great Britain
Document type Journal Article, Research Support, Non-U.S. Gov't
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- MeSH
- Action Potentials physiology MeSH
- Models, Neurological MeSH
- Brain metabolism MeSH
- Neurons metabolism MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Due to known information processing capabilities of the brain, neurons are modeled at many different levels. Circuit theory is also often used to describe the function of neurons, especially in complex multi-compartment models, but when used for simple models, there is no subsequent biological justification of used parts. We propose a new single-compartment model of excitatory and inhibitory neuron, the capacitor-switch model of excitatory and inhibitory neuron, as an extension of the existing integrate-and-fire model, preserving the signal properties of more complex multi-compartment models. The correspondence to existing structures in the neuronal cell is then discussed for each part of the model. We demonstrate that a few such inter-connected model units are capable of acting as a chaotic oscillator dependent on fire patterns of the input signal providing a complex deterministic and specific response through the output signal. The well-known necessary conditions for constructing a chaotic oscillator are met for our presented model. The capacitor-switch model provides a biologically-plausible concept of chaotic oscillator based on neuronal cells.
References provided by Crossref.org
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- $a Cejnar, Pavel $u Department of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic. pavel.cejnar@vscht.cz.
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- $a Simple capacitor-switch model of excitatory and inhibitory neuron with all parts biologically explained allows input fire pattern dependent chaotic oscillations / $c P. Cejnar, O. Vyšata, J. Kukal, M. Beránek, M. Vališ, A. Procházka,
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- $a Due to known information processing capabilities of the brain, neurons are modeled at many different levels. Circuit theory is also often used to describe the function of neurons, especially in complex multi-compartment models, but when used for simple models, there is no subsequent biological justification of used parts. We propose a new single-compartment model of excitatory and inhibitory neuron, the capacitor-switch model of excitatory and inhibitory neuron, as an extension of the existing integrate-and-fire model, preserving the signal properties of more complex multi-compartment models. The correspondence to existing structures in the neuronal cell is then discussed for each part of the model. We demonstrate that a few such inter-connected model units are capable of acting as a chaotic oscillator dependent on fire patterns of the input signal providing a complex deterministic and specific response through the output signal. The well-known necessary conditions for constructing a chaotic oscillator are met for our presented model. The capacitor-switch model provides a biologically-plausible concept of chaotic oscillator based on neuronal cells.
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- $a Vyšata, Oldřich $u Department of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic. Department of Neurology, Faculty of Medicine in Hradec Králové, Charles University, Hradec Králové, Czech Republic.
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- $a Kukal, Jaromír $u Department of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic.
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- $a Procházka, Aleš $u Department of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic. ales.prochazka@vscht.cz. Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic. ales.prochazka@vscht.cz.
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