Synchronization and complex dynamics in locally active threshold memristive neurons with chemical synapses

Memristor has been extensively employed to emulate neuron/synapse-inspired behaviors and to characterize the electromagnetic induction generated by ionic flowing. A link between memristive features and neural electrical activities is significantly necessary to be investigated. Thus, we propose a new neuron model with a locally active threshold flux-controlled (LTF) memristor, which depicts the electromagnetic induction. The LTF memristive neuron model can exhibit a regular evolution and transition of various firing patterns dependent upon the negative different conductance of the memristor, through performing the corresponding numerical simulations. It is demonstrated that due to the locally active threshold effect, the obtained model has complex firing behaviors. The memristive neural network is connected via chemical synapses. The memristive neural network under the modulation of excitatory and inhibitory chemical synapses shows different synchronous patterns. The captured results reveal that the locally active threshold effect is crucial for the generation of complex firing modes and the emergence of synchronization behaviors.