Gabriele Lohmann1, Daniel S. Margulies1, Dirk Goldhahn1, Annette Horstmann1, Burkhard Pleger1, Joeran Lepsien1, Arno Villringer1, Robert Turner1
1Max Planck Institute for Human
Cognitive and Brain Sciences,
We introduce a new assumption- and parameter-free method for the analysis of fMRI resting state data based on eigenvector centrality. Eigenvector centrality attributes a value to each voxel in the brain such that a voxel receives a large value if it is strongly correlated with many other nodes that are themselves central within the network. Google's PageRank algorithm is a variant of eigenvector centrality. We tested eigenvector centrality mapping (ECM) on two resting state scans of 35 subjects, and found a network of hubs including precuneus, thalamus and sensorimotor areas of the marginal ramus of the cingulate and mid-cingulate cortex.