This document presents a proposal devoted to improve the detection of the default mode network (DMN) in resting state functional magnetic resonance imaging in noisy conditions caused by head movement. The proposed approach is inspired by the hierarchical treatment of information, in particular at the level of the brain basal ganglia. Essentially, the fact that information must be selected and reduced suggests propagation of information in the Central Nervous System (CNS) is anisotropic. Under this hypothesis, the reconstruction of information of activation should follow an anisotropic pattern. In this work, an anisotropic filter is used to recover the DMN that is perturbed by simulated motion artifacts. Results obtained show this approach outperforms the state-of-the-art methods by 5.93% PSNR.