Abstract
The paper presents mathematical model of spike activity of a neuronal culture which exhibits bursting behavior—synchronized spontaneous packs of population activity. Neuron in the developed neural network model is a modification of Leaky Integrate-and-Fire neuron. The neuron model acquires a new quality due to the introduction of two new neuron state variables—“resource” and “strength”. The new learning mechanism for synaptic weights is proposed. It assumes dependence of weight corrections from the intensity of spike activity of presynaptic neurons for a previous time interval. The model experiment shows the ability of the neural network based on the proposed model of neurons, to produce bursting activity. Setting of neuron model parameters makes it possible to obtain bursts with various characteristics. The results of model simulation are presented. The prospects for applying the model to study the mechanisms of learning in neuronal cultures in vitro are discussed.
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References
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Acknowledgments
This work was supported by the Russian Science Foundation, Grant No 15-11-30014.
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Volkov, D., Mishulina, O. (2016). The Approach to Modeling of Synchronized Bursting in Neuronal Culture Using a Mathematical Model of a Neuron with Autoregulation Mechanism. In: Samsonovich, A., Klimov, V., Rybina, G. (eds) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists . Advances in Intelligent Systems and Computing, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-319-32554-5_33
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DOI: https://doi.org/10.1007/978-3-319-32554-5_33
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