# Dynamic Pathway Selection Mechanisms of Brain Networks
## 1 Introduction  
The intelligent information age is quietly changing people's way of life and the development mode of the world. It has become an important development trend to study the information transmission and representation of brain network in order to realize brain-like intelligence. Taking the simulation of brain connection mechanism as the starting point for the study of brain-like networks, in-depth study of the close relationship between information representation and loop selection is a hot topic in the study of brain-like intelligence. Recent studies have shown that the information representation of brain-like intelligent networks is mainly reflected by a variety of connection modes of the network; memory storage, extraction and forgetting in the brain network are all related to the link state between neurons [1; 2]. Understanding the neural basis and working principle of brain networks by constructing bionic models and exploring the potential mechanism of loop selection and information representation in brain networks are of great significance to the development of brain-like intelligence. In recent years, the study of the synapse has mainly focused on the perspective around the synapse. Ref. [3] investigates the release of synaptic vesicles as a random transfer model. The authors proposed a statistical model which focuses on the number of neurotransmitters released, and analyzes the plasticity of the complex signal transmission process of the chemical synapse. Ref. [4] states that the orientation of electrical synapses and dendritic positions and the synchronous activity between two neurons depend on electrical synapsesat different locations, and that this asymmetry affects information transmission at synapses and information processing by dendrites. Ref. [5] examines synapses that exhibit auto-adaptive properties when both chemical and electrical synapses are activated together, which can induce a transition from synchrony to desynchrony between neural circuits. In addition, Ref. [6] shows that the extracellular matrix (\(ECM\)) is an important composite protein to regulate brain development, brain connectivity and plasticity, and that \(ECM\) concentration is one of the important mechanisms in regulating the number of synapses so as to avoid excessive excitation of brain network changes. Ref. [7] explains that the dynamic changes in acetylcholine transmitter concentration can affect synaptic efficacy. This shows that synapse study by \(ECM\) concentration is being taken a new direction, which will be important in the understanding of information transmission in the brain. Moreover, related studies have shown that the organization of brain networks is constantly optimized to achieve different tasks with a dynamic reorganization, and one of the mechanisms of dynamic reorganization present in the network is the presence of different neural rhythms (resonance, synchronization) in the processing of signals, while the dynamic reorganization induced by phase synchronization can be achieved by regulating the effective connectivity between nodes [8]. The results of [9; 10] show that the basic functions of receiving, processing and transmitting information in the brain and the higher functions such as memory and association are directly related to the complex loops formed by synaptic coupling, and it can be said that the neural loop modulation mechanisms allow the brain to show different functional properties. Refs. [8; 11] indicate that brain networks can exhibit complex loop connections regardless of whether the brain is in a resting or task state; thus, they choose different network paths to achieve functional tasks, such as memory, association and decision making. In this paper, both dynamic synapses and correlations assessment are mainly considered in terms of how dynamic reorganization of the network can flexibly adapt to changes in functional coupling to external stimuli.