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The Hierarchical Structure of the Face Network Revealed by Its Functional Connectivity Pattern

Wang, X., Zhen, Z., Song, Y., Kong, X., & Liu, J. (2016). The Hierarchical Structure of the Face Network Revealed by Its Functional Connectivity Pattern. The Journal of Neuroscience, 36(3), 890-900. doi:10.1523/JNEUROSCI.2789-15.2016.
A major principle of human brain organization is “integrating” some regions into networks while “segregating” other sets of regions into separate networks. However, little is known about the cognitive function of the integration and segregation of brain networks. Here, we examined the well-studied brain network for face processing, and asked whether the integration and segregation of the face network (FN) are related to face recognition performance. To do so, we used a voxel-based global brain connectivity method based on resting-state fMRI to characterize the within-network connectivity (WNC) and the between-network connectivity (BNC) of the FN. We found that 95.4% of voxels in the FN had a significantly stronger WNC than BNC, suggesting that the FN is a relatively encapsulated network. Importantly, individuals with a stronger WNC (i.e., integration) in the right fusiform face area were better at recognizing faces, whereas individuals with a weaker BNC (i.e., segregation) in the right occipital face area performed better in the face recognition tasks. In short, our study not only demonstrates the behavioral relevance of integration and segregation of the FN but also provides evidence supporting functional division of labor between the occipital face area and fusiform face area in the hierarchically organized FN.
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The Max Planck Institute for Psycholinguistics is an institute of the German Max Planck Society. Our mission is to undertake basic research into the psychological,social and biological foundations of language. The goal is to understand how our minds and brains process language, how language interacts with other aspects of mind, and how we can learn languages of quite different types.

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