The construction of brain functional network based on resting-statefunctional magnetic resonance imaging (fMRI) is an effective method to reveal the mechanism of humanbrain operation, but the common brain functional network generally contains a lot of noise, which leads to wrong analysis results. In this paper, the least absolute shrinkage and selection operator (LASSO) model in compressed sensing is used to reconstruct the brain functional network. This model uses the sparsity of