The anticorrelations in fMRI measurements are still not well characterized, but some new evidences point to a possible physiological role. We explored the topology of functional brain networks characterized by negative edgess and their possible alterations in schizophrenia, using functional images of 8 healthy subjects and 8 schizophrenic patients in a resting state condition. In order to minimize the insertion of artifactual negative correlations, the preprocessing of images was carried out by the CompCorr procedure, and the results compared with the Global Signal Regression (GSR) procedure. The degree distribution, the centrality, the efficiency and the rich-club behavior were used to characterize the functional brain network with negative links of healthy controls in comparison with schizophrenic patients. The results show that functional brain networks with both positive and negative values have a truncated power-law degree distribution. Moreover, although functional brain networks characterized by negative values have not small-world topology, they show a specific disassortative configuration: the more connected nodes tend to have fewer connections between them. This feature is lost using the GSR procedure. Finally, the comparison with schizophrenic patients showed a decreased (local and global) efficiency associated to a decreased connectivity among central nodes. As a conclusion, functional brain networks characterized by negative values, despite lacking a well defined topology, show specific features, different from random, and indicate an implication in the alterations associated to schizophrenia.
Keywords: Anticorrelated networks; Functional connectivity; Network analysis; Resting state; Schizophrenia.