Effect of astrocyte on synchronization of thermosensitive neuron-astrocyte minimum system

Abstract

Astrocytes have a regulatory function on the central nervous system (CNS), especially in the temperature sensitive hippocampal region. In order to explore the thermosensitive dynamic mechanism of astrocytes in CNS, we establish a neuron-astrocyte minimum system to analyze the synchronization change characteristics based on Hodgkin-Huxley model, in which a pyramidal cell and an interneuron are connected by an astrocyte. Besides, the temperature range set 0°C-40°C to juggle theoretical calculation and reality of brain environment. It is represented that the synchronization of thermosensitive neurons exhibits nonlinear behavior with change of astrocyte parameters. At temperature range of 0°C-18°C, the effects of astrocyte can provide tremendous influence to neurons in synchronization. We found existence of a value for inositol triphosphate (IP3) production rate and feedback intensities of astrocyte to neurons, which can ensure the weak synchronization of two neurons. In addition, it is revealed that the regulation of astrocyte to pyramidal cell is more sensitive than that to interneuron. Finally, it is shown that the synchronization and phase transition of neurons depend on the change of Ca2+ concentration at the temperature of weak synchronization. The results in this paper would provide some enlightenment in mechanism of cognitive dysfunction and neurological disorders with astrocytes.

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

“…[10][11][12] When a memristor is connected to a neural circuit, the impact of electromagnetic induction on neurons can be estimated. [5,[13][14][15][16] Because the resistance value of a thermistor varies with temperature, [17][18][19][20] neural circuits with thermistors can be used as biophysical thermosensitive neurons. [21][22][23][24] Phototubes can convert optical signals into electrical signals.…”

The lag and module-phase synchronization of complex-valued neural networks with mixed delays

“…The results show that the control method is effective. And many achievements of synchronization, such as global synchronization, local synchronization, exponential synchronization, antisynchronization and so on [14][15][16][17][18][19]. In recent years, the problem of module-phase synchronization was solved [20].…”