期刊
JOURNAL OF NEUROSCIENCE
卷 36, 期 3, 页码 890-900出版社
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.2789-15.2016
关键词
between-network connectivity; face recognition; fusiform face area; occipital face area; within-network connectivity
资金
- National Natural Science Foundation of China [31230031, 31221003, 31470055, 31471067]
- National Basic Research Program of China [2014CB846101, 2014CB846103]
- Changjiang Scholars Programme of China
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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