The Study Of Neuronal Signal Propagation In Complex Networks

The brain is one of the most important parts of humans,and it is also a very complex system.Thanks to the development of science and technology,the brain network can be measured using methods such as diffusion tensor imaging or functional magnetic resonance imaging,so that people can promote the study of brain function on this basis.Many studies shows that brain functions such as cognition and memory are inseparable from the synchronization of neurons,while brain diseases such as epilepsy show abnormal synchronization of neurons.In recent years,many special synchronized behaviors have been discovered and attracted extensive attention.These synchronized behaviors are also reflected in the EEG signals.For example,the behavior during epileptic seizures is similar to explosive synchronization.Some mammals have half-brain sleep similar to singularity.The distributed processing of brain information is related to remote synchronization.But how do these synchronization occur? Is it closely related to the propagation of neural signals in the brain? How do nerve signals in the brain spread? Little is known about such issues.In view of this,this paper will do some preliminary discussions on some of these problems,mainly the signal propagation in the brain,and hope that our research results will trigger everyone's follow-up research boom.We have mainly completed two aspects of work,as follows:1.In order to study the abnormal synchronization of epilepsy from the perspective of signal propagation,we constructed a network structure similar to the brain,and considered the abnormal synchronization caused by small changes in the brain structure from the perspective of neural signal propagation.First,we study the propagation of the neuron model under different network structures,and find that the network structure under different clustering coefficients differs greatly,and the propagation behavior of the firing is also essentially different.We found a network with a structure and function similar to the brain,and used it as a model network of the brain for further research.We randomly reconnect the edges of the model network to simulate the brain damage caused by physical shock or huge stimuli.We found that reconnecting a small number of edges will also cause the global propagation of the firing signal and the explosive synchronization of the system,indicating that the local propagation behavior of the firing is fragile,which puts a new perspective on the cause of epilepsy.In addition,we also reanalyzed the EEG data of epileptic seizures in the previous literature,and obtained the explosive synchronous behavior consistent with the numerical simulation.Finally,we made a qualitative theoretical analysis of these propagation behaviors and found that the propagation of firing between two neurons is affected by both the source neuron and the target neuron.The smaller the degree,the easier it is to propagate.In addition,due to the time accumulation effect and space accumulation effect,the increase in the triangular structure due to the large network clustering coefficient,promotes the propagation.2.Signal propagation has been extensively studied on different network structures,but few are specific to the specific structure of brain networks.The efficiency of the brain's processing of information is very efficient.To explore the impact of brain structure on signal propagation,we used a bistable model and the brain's real structural network to simulate the propagation of signals in the brain.We found that the propagation effect does not increase monotonically with the increasing coupling strength,but a resonance curve with an optimal value.Changing the brain network structure will reduce the optimal value of the resonance curve.Then we also found the effect of remote propagation when studying the propagation path: the signal did not reach the next layer,but reached the lower layer.This discovery may do a greater help in understanding the emergence of various brain functions,especially distributed processing in the brain.In order to explain this effect,we propose a heterogeneous chain structure and found that the signal of the central node causes weak oscillations of multiple leaf nodes.The combined effect of the weak oscillation of multiple channelsmakes the signal be reproduced at the hub node of the next layer.At the same time,we found that there is global propagation in the heterogeneous chain structure which dose not occur on the the real brain network.Considering that there are same loops in the real brain network,we added backward coupling to the structure,and found that backward coupling will inhibit the global propagation in the original network.It means that this kind of structure of the real brain network can suppress the occurrence of epilepsy.Finally,we theoretically analyzed the remote propagation behavior on a heterogeneous chain structure,and the theoretical analysis is in good agreement with the numerical simulation results.Our results have initially explored the propagation of neural signals from brainlike networks and brain networks from two aspects of numerical simulation and theoretical analysis,and revealed the conditions for the successful propagation of signals and the influence of specific structures of brain networks on signal propagation.These results have a strong impetus for the understanding of the microscopic mechanism of epileptic seizures and the dynamics of remote propagation in brain function.