Study On Synchronization Of Brain Cognitive Networks And Remote Synchronization Of Local Brain Regions

The human brain contains 86 billion neurons and almost the same number of glial cells,which is one of the most complex systems known.At the same time,the human brain not only needs to ensure the most basic life activities of the human body,but also integrates and processes the information input from the outside to form intelligent behaviors such as cognitive activities,complex emotions and consciousness.Because of the complexity and importance of the brain,the research on it has always been a hot topic.With the progress of neuroscience and technology,we have obtained more and more brain data.Through these data,we can construct brain networks,and then study the brain with complex network methods.So far,great achievements have been made in the application of complex networks in brain research.However,these studies focus on the whole brain network and can not be fully used to reveal the micro-mechanism of brain function.The reason is that,even in the process of cognitive function execution,most of the brain regions are still in a resting state.This requires us to pay attention to the characteristics of different parts of the brain and study the similarities and differences between them.We have made a preliminary discussion on the above problems,and the main research results are as follows:1.Experimental data show that when the brain is in a resting-state,only a few local brain regions are active;while the brain is performing tasks,only some brain regions are activated,and different tasks correspond to different activated brain regions.This reflects the differences between different local brain regions.Through the study of the dynamics of the local brain regions,we find that the synchronization of the local brain regions is essentially different from the global brain network,and there is a phenomenon of amplitude death.We divide a real brain network into63 local brain regions and simulate them numerically.The results show that the dynamic behavior of different brain regions is different,some brain regions have second-order phase transition,while other brain regions have explosive synchronization.In order to find out the mechanisms of different phenomena,we first studied the topological structure of typical brain region networks and found that there are differences in the topological structure of different brain regions.The increase of node degree in the brain region with second-order phase transition is irregular,while the moderate nodes in the brain network with explosive synchronization reflect the characteristics of power law distribution.Then we demonstrate the emergence of explosive synchronization from the point of view of the change of the effective frequency of the oscillator.At the same time,we find that there are multiple hysteresis loops in some brain regions,and the amplitude of the oscillator in these brain regions is dead.We describe this phenomenon of amplitude death by different parameters and compare the similarities and differences of amplitude death in different brain regions.We find that this death phenomenon is also the key factor of explosive synchronization and is closely related to functional behavior and mode switching in local brain areas,which provides a possible explanation for the phenomenon that only part of the brain is activated when the brain is in the task state.Finally,we make a theoretical analysis.By through the solution of the eigenvalues in the system,we find out the cause of the amplitude death phenomenon.2.The cognitive network in the brain is often composed of non-adjacent neurons,and the explanation of this phenomenon usually adopts the remote synchronization framework with star network structure.However,the local brain region with remote synchronization is a network with community structure,and the star network model does not fit the actual situation very well.Therefore,we hope to find the phenomenon of remote synchronization on the scale of network with community structure.For this reason,we extend the study of remote synchronization in the original star network to the multi-layer network.Specifically,every node in the original star network is extended to a subnetwork with community structure,so the multi-layer network has the characteristics of star topology,and the topology of each sub-network is different,corresponding to different community structures.This network structure is more in line with the actual characteristics of the brain cognitive network.We find that remote synchronization does occur in a multi-layer network with one central layer sub-network and two leaf layer sub-networks.Furthermore,we discuss the effects of other parameters,such as coupling strength,oscillator frequency,network scale and so on,on the remote synchronization phenomenon.Then we construct a multi-layer network model of a central layer sub-network and three leaf-layer sub-networks,and find a similar remote synchronization phenomenon,which proves that remote synchronization is also common in multi-layer networks with more leaf layer subnetworks.Then we extract the local brain regions with similar star-shaped structure from the brain network,and carry out the same numerical simulation,and also find the phenomenon of remote synchronization,which provides a possible explanation for the interaction of non-nearest neighbor neurons in the brain functional network.Finally,in order to make a theoretical analysis of these structures,we select the simplest model,that is,a system composed of a central layer network and two leaf layer networks.Through the Laplace transform,we apportion the hub effect of the central layer sub-network on the leaf layer sub-network into two leaf layers,thus revealing the mechanism of remote synchronization.In summary,the work of this paper focuses on the study of the dynamics of the local brain region,and finds the phenomenon of mixed phase transition and the amplitude death of the oscillator in the local brain regions.At the same time,we design a system with multi-layer star network structure to study the remote synchronization phenomenon in different local brain regions,and confirm the universality of remote synchronization in the local community network.These results provide new ideas and methods for the working mechanism of cognitive networks and the formation of cognitive models in the brain.