Study On The Self-organization Collective Dynamics Of Neurons Under Mixed Coupling Mode

Brain is a complex network consisting of several ten billion neurons that are connected to each other.Neurons are coupled with different ways to transmit information and produce rich collective dynamic behaviors,which is necessary for the regulation of processing,transferring and integrating neural information.Chemical synapses,that are pathways for neural information transmission,are interacted with neurons and self-organize to form an economical neuronal network.This self-organized structure is the foundation for learning and memory in the nervous system.Using the nonlinear dynamics theory,we studied the structures and dynamic behaviors of self-organized neuronal networks with hybrid coupling modes.The research results would be helpful for further understanding the functional mechanism of the brain at the neuron scale.Firstly,we investigated the effects of electromagnetic radiation on topological properties and dynamics of self-organized neuronal networks.In the self-organized neuronal networks,we coupled the neurons and the electromagnetic field.We explored the effects of radiation intensity on synaptic connection characteristics,topological properties and synchronization of self-organized neuronal networks.It was found that electromagnetic radiation has a complex effect on the formation of self-organized neuronal networks,but appropriate radiation intensity induces the self-organized neuronal networks to have stronger information transmission in the structure and a higher synchronization in dynamic behaviors.Secondly,we studied the effects of memristive synapses on the structures and dynamics of self-organized neuronal networks.In self-organized neuronal networks,we coupled the heterogeneous neurons and the memristive synapses.We investigated how the strength and closing rate of memristive synapses modulate the excitatory-excitatory,high excitatoryinhibitory and low excitatory-inhibitory neuronal networks.The modulation of memristive synapses on the structure and dynamics of self-organized neuronal networks is greatly dependent on model selection.It was found that in the excitatory-excitatory and high excitatory-inhibitory neuronal networks,stronger memristive synaptic coupling produces a stable network structure and enhanced network synchronization,but increasing the closing rate of memristive synapses has little effects.In the low excitatory-inhibitory neuronal network,stronger memristive synaptic coupling produces complex modulation effects,but increasing the closing rate of the memristive synapse speeds up the self-organization process,enhances network synchronization,and produces complex firing patterns.Finally,we investigated how astrocytes modulate the self-organization collective dynamics of neuronal networks.By linearizing the relationship between the calcium ion concentration in astrocytes and the neuronal firing frequency,we constructed a simplified dynamic model that couples the neurons and astrocytes,and we use this model to study the effects of astrocytic feedback intensity on dynamics of single neuron and neuronal networks.It was found that as astrocytic feedback intensity increases,neuronal firing patterns are transferred from normal to epileptic-like firing,and periodic oscillation modes to chaotic firing modes.