Using computer simulation of electrical processes in a GABA-ergic interneuronal network, we found that synchronization of electrical discharges of the neurons is critically dependent on the geometrical size of the virtual network. If the size, under our simulation conditions, was either less than 2.1 mm or greater than 4.2 mm, the network was not able to generate synchronous discharges. Our findings may explain the geometrical size-dependent gamma rhythm generated by neurons of the hippocampal networks.
The influence of a tonic GABA-ergic current on the processes of network synchronization was examined using a computer model of the neural network with shunting GABA-ergic synapses and tonic excitation that initiated spiking. The tonic inhibitory current was characterized by two parameters, the reversal potential and the conductance introduced. We found that tonic current with a reversal potential more negative than the threshold for spike generation reduces the network spiking frequency and synchronization. A monotonic decrease in the network synchronization with augmentation of the tonic current conductance was shown. We also found that a particular range of tonic current conductance leads to a bistable character of the network dynamics. Depending on the initial conditions of the network examined, spontaneous synchronous oscillations similar to epileptiform activity could appear.
Рассмотрены особенности расчета коэффициента синхронизации колебаний в моделях нейронных сетей мозга. Метод расчета синхронизации основан на кросс-корреляции времен потенциалов действия любых пар нейронов. Недостатком этого метода явл яется способ выбора длительности временного интервала, с помощью которого происходит перевод последовательности генерации потенциалов действия в нейронах сети в бинарный цифровой формат с последующим расчетом величины кросс-корреляции. С использованием принципа оптимизации, позволяющего наиболее точно различать степень синхронизации колебаний в сети, разработан метод определения «оптимальной» величины данного временного интервала.
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