Abstract
In this paper we present a neuron model based on the description of biophysical mechanisms combined with a regulatory mechanism from control theory. The aim of this work is to provide a neuron model that is capable of describing the main features of biological neurons such as maintaining an equilibrium potential using the NaK-ATPase and the generation of action potentials as well as to provide an estimation of the energy consumption of a single cell in a) quiescent mode (or equilibrium state) and b) firing state, when excited by other neurons. The same mechanism has also been used to model the synaptic excitation used in the simulated system.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Koch, C., Segev, I.: Methods in Neuronal Modeling (1998)
Laughlin, S.B., de Ruyter van Steveninck, R.R., Anderson, J.C.: The metabolic cost of neural information. Nature Neuroscience 1, 36–41 (1998)
MacGregor, R., Lewis, E.: Neural Modeling (1977)
Daut, J.: The living cell as an energy-transducing machine. A minimal model of myocardial metabolism. Biochimica et Biophysica Acta (BBA) - Reviews on Bioenergetics 895, 41–62 (1987)
Destexhe, A., Mainen, Z.F., Sejnowski, T.J.: An efficient Method for Computing Synaptic Conductances Based on a Kinetic Model of Receptor Binding. Neural Computation 6, 14–18 (1994)
Föllinger, O.: Regelungstechnik (1994)
Hodgkin, A., Huxley, A.: A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Phys. 117, 500–544 (1952)
Destexhe, A.: Conductance-based integrate-and-fire models. Neural Computation 9, 503–514 (1997)
Chapeau-Blondeau, F., Chambet, N.: Synapse Models for Neural Networks: From Ion Channel Kinetics to Multiplicative Coefficient w ij . Neural Computation 7, 713–734 (1995)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kaulmann, T., Löffler, A., Rückert, U. (2007). A Control Approach to a Biophysical Neuron Model. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74690-4_54
Download citation
DOI: https://doi.org/10.1007/978-3-540-74690-4_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74689-8
Online ISBN: 978-3-540-74690-4
eBook Packages: Computer ScienceComputer Science (R0)