Impact of the combined effect of synaptic weight and electromagnetic radiation on the dynamical behaviors of a Rulkov neuron: Theoretical investigations and microcontroller-based experiment

The neural network of a biological brain is made up of billions of neurons interconnected to each other through their dendrites and synapses. Using their synapses, these neurons communicate or transmit information by emitting electrical impulses. This makes it very necessary for us to consider both the complex electromagnetic environments present in the brain, and the synaptic behavior of the biological neurons while simulating and studying brain functions. With the aim of studying the combined effects of these two phenomena on an improved Rulkov neuron, this work makes use of non-polynomial memristor to simulate and investigate the synaptic behavior of an improved Rulkov neuron under electromagnetic radiation. The investigations carried out shows that the studied model undergoes both stable and unstable dynamics depending on the system parameters. This is further consolidated by numerical analyses from which the synaptic weight Rulkov neuron exposed to electromagnetic radiation shows rich and interesting dynamics such as self-excited and hidden attractors, which evolve from periodic to irregular motions, bubble-like bifurcation and offset boosting features. Finally, physical findings obtained with the help of breadboard microcontroller-based experiment confirm the validity of the numerical simulations results.