The Intrinsic Properties of Brain Based on the Network Structure

TL;DR

This paper explores how the intrinsic properties of brain networks, modeled mathematically, relate to brain functions such as stability, decision making, and memory formation.

Contribution

It introduces a mathematical framework to analyze brain network properties and their relation to key brain functions, providing new insights into neural dynamics.

Findings

Network stability depends on excitatory/inhibitory synapse ratio

Network activity can spontaneously evolve into specific distributions

Coupling of network assemblies can form short-term memory

Abstract

Objective: Brain is a fantastic organ that helps creature adapting to the environment. Network is the most essential structure of brain, but the capability of a simple network is still not very clear. In this study, we try to expound some brain functions only by the network property. Methods: Every network can be equivalent to a simplified network, which is expressed by an equation set. The dynamic of the equation set can be described by some basic equations, which is based on the mathematical derivation. Results (1) In a closed network, the stability is based on the excitatory/inhibitory synapse proportion. Spike probabilities in the assembly can meet the solution of a nonlinear equation set. (2) Network activity can spontaneously evolve into a certain distribution under different stimulation, which is closely related to decision making. (3) Short memory can be formed by coupling of network assemblies. Conclusion: The essential property of a network may contribute to some important brain functions.