In recent years, several inverse solutions of magnetoencephalography (MEG) have been proposed. Among them, the multiple signal classification (MUSIC) method utilizes spatio-temporal information obtained from magnetic fields. The conventional MUSIC method is, however, sensitive to Gaussian noise and a sufficiently large signal-to-noise ratio (SNR) is required to estimate the number of sources and to specify the precise locations of electrical neural activities. In this paper, a new algorithm for solving the inverse problem using the fourth order MUSIC (FO-MUSIC) method is proposed. We apply it to the MEG source estimation problem. Numerical simulations demonstrate that the proposed FO-MUSIC algorithm is more robust against Gaussian noise than the conventional MUSIC algorithm.