The invention discloses a space-time modeling method for improving a
human brain communication process by activating a network. The space-time modeling method comprises the following steps: S1, integrating data; s2, data preprocessing; s3, activity and background of function connection; s4, function connection calculation activity; s5, constructing a high-low activation network; s6, performing
graph theory analysis and classification; s7, performing statistical test; and S8, obtaining a result. Experimental results show that the AFC shows high correlation with potential dynamics, in addition, the activation network shows more multi-region interaction in space and has high sensitivity to
mental state change, more information of large-scale
brain network communication is temporarily revealed with a stable communication effect and low cost, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. According to the method,
verification is carried out through an application program,
disease classification is achieved, the network activation is an important framework for understanding the
brain network, new insights are provided for
brain network construction through research, and the potential of using the network activation in network
neuroscience research is emphasized.