Eyes Closed Elevates Brain Intrinsic Activity of Sensory Dominance Networks: A Classifier Discrimination Analysis

Brain neocortex is usually dominated by visual input (with eyes open [EO]), whereas this visual predominance could be reduced by closing eyes. Cutting off visual input from the eyes (with eyes closed [EC]) would also benefit other sensory performance; however, the neural basis underlying the state-switching remains unclear. In this study, we investigated the brain intrinsic activity of either the EO or EC states by using the resting-state functional magnetic resonance imaging data from 22 healthy participants. The 10 resting-state networks (RSNs) of these participants were explored by the independent component analysis method. Within each RSN, various network parameters (i.e., the amplitude of low-frequency fluctuation, the voxel-wise weighted degree centrality, and the RSN-wise functional connectivity) were measured to depict the brain intrinsic activity properties underlying the EO and EC states. Taking these brain intrinsic activity properties as discriminative features in a linear classifier, we found that the EO and EC states could be effectively classified using the intrinsic properties of the sensory dominance networks and the salience network (SN). Further analysis showed that the brain intrinsic activity within the sensory dominance networks was constantly overwhelmed during the EC state relative to that in the EO state. The SN might play a key role as a switcher between state-switching. Therefore, this study indicated that the brain intrinsic activity in the sensory dominance networks would be enhanced with EC, which might improve other sensory-relative task performance.