Chaos, Solitons and Fractals
The dynamical behavior of the neurons directly depends on the transition from resting to spiking states. These transitions show different types of bifurcations and has different spiking periods. The transitions are also affected by the temperature exposure of the ionic channels. To understand such effects, we investigate the Morris-Lecar (ML) neuron model with temperature affected calcium, potassium and leak current channels. The presented ML model is considered with electromagnetic field coupling considering a simple cubic memristor flux relation. Firstly the basic dynamical properties of the ML model is analyzed considering the current temperature as the control parameter. The temperature affected ionic channels in the ML model leads to various types of oscillations from periodic spiking to chaotic bursting. These bifurcation patterns are well discussed with corresponding Lyapunov exponents. To study the wave propagation in the temperature dependent ML model (TDML), we have constructed two different types of network structure. In the first a simple lattice network is considered with the local nodes of the TDML neurons and the temperature effects on the wave propagation is studied individually for the three channels. In the second type of network, we have considered inter coupled three lattice layers of TDML neurons. This discussion is subdivided in to two cases and in the first case the layers are constructed such that the first, second and third layers having temperature affected calcium, potassium and leaky current channels respectively. In the second case we considered only one channel to have temperature effects and the others have no temperature affected ion channels. The wave propagation phenomenon in both the types of network is analyzed considering the current temperature as the control parameter.
