Collective behaviors in a multiple functional network with hybrid synapses

Because of functional differentiation of biological neurons, more functional regions have been developed and formed in the brain and the neurons with the same biophysical function are connected in a specific region. Many neural circuits can be improved to exit specific functions by incorporating special electric components into the branch circuits, and they can be connected to simulate the cooperation of neurons with different biophysical properties. In this paper, three kinds of functional neural circuits are connected to develop a functional network for detecting external illumination, temperature changes and acoustic wave synchronously. The synchronous stability between neurons are much dependent on the intrinsic properties of the synaptic connection along the coupling channels. Electric synapse connection, capacitor-connection and induction coil connection are applied to trigger voltage, electric field and magnetic field couplings along the links in the neural network, respectively. Indeed, the field coupling induced by capacitive and inductive coupling can be controllable under external field by injecting energy continuously. The results indicate that the phase lock of the neural network can be stabilized by taming the coupling intensity carefully, and it can be further enhanced and switched by involving the noise. The Hamilton energy is estimated and in line with the phase synchronization. These results are helpful to know potential biophysical mechanism of synchronous firing and mode selection in the functional network.