Identifying topological motif patterns of human brain functional networks

Recent imaging connectome studies demonstrated that the human functional brain network follows an efficient small-world topology with cohesive functional modules and highly connected hubs. However, the functional motif patterns that represent the underlying information flow remain largely unknown. Here, we investigated motif patterns within directed human functional brain networks, which were derived from resting-state functional magnetic resonance imaging data with controlled confounding hemodynamic latencies. We found several significantly recurring motifs within the network, including the two-node reciprocal motif and five classes of three-node motifs. These recurring motifs were distributed in distinct patterns to support intra- and inter-module functional connectivity, which also promoted integration and segregation in network organization. Moreover, the significant participation of several functional hubs in the recurring motifs exhibited their critical role in global integration. Collectively, our findings highlight the basic architecture governing brain network organization and provide insight into the information flow mechanism underlying intrinsic brain activities. Hum Brain Mapp 38:2734–2750, 2017