Studies On The Regulation Of Synaptic Coupling On Self-Sustained Activity Of Neuronal Network

Self-sustained activity of neuronal ensembles has been widely observed in the brain.It's not only closely related to the fundamental function like transition between sleep states,biological rhythm,but also may be involved in a variety of advanced functions such as memory,cognition,and learning.Substantial evidence suggested that dynamics of synaptic coupling have a significant impact on the activity of neuronal population.So far,it is still unclear how synaptic coupling regulates self-sustained activity in neural system.Therefore,carrying out study on corresponding problems will be helpful to further understand the functional role of self-sustained activity in the neural system.In this thesis,based on a random neuronal network model,we systematically explored how network structure and synaptic transmission dynamics modulate the generation and maintenance of self-sustained activity in neuronal network.The main results are summarized as follows:Firstly,we investigated the effect of network structure on neuronal network selfsustained activity.We found that self-sustained activity only generated in the network with certain connectivity density,and the self-sustained time increasing first and then decreasing as connectivity probability increased.In the condition of the same connectivity probability,the duration of self-sustained activity became longer as the network scale increased.Secondly,we systematically investigated how synaptic coupling modulates the selfsustained activity of neuronal populations.We found that the distribution of synaptic coupling intensity and synaptic transmission delay mainly contributes to the regulation of self-sustained activity.The self-sustained time increases with an increase in either the mean value or standard deviation of the coupling intensity distribution.Meanwhile,excitatory and inhibitory synaptic transmission delay plays the opposite role in regulating self-sustained activity.The increase of excitatory transmission delay is conducive to the maintenance of self-sustained activity while excessively long inhibitory synaptic delay is conducive to the persistent population firing.In addition,our findings confirmed that increasing the refractory period of neurons can significantly inhibit self-sustained activity of neuronal network.Thirdly,we further investigated the relationship among firing irregularity,synchrony and population self-sustained activity.By statistically analyzing the data of population spikes,we found that the more irregular neuronal network firing is the longer selfsustained time will be.However,we have not reached a consistent conclusion about the relationship between synchronization and self-sustained activity in the neuronal network model.In summary,we found that network structure,synaptic coupling strength,and network firing patterns play an important role in the generation and maintenance of selfsustained activity,by constructing a neuronal network model in which the synaptic coupling strength conforms to the lognormal distribution.These results might deepen the understanding of information processing mechanism of neural system,and provide theoretical guidance or verification for physiological experiments.