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

Abstract

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. Significance statement: Although the integration and segregation are major principles of human brain organization, little is known about whether they support the cognitive processes. By correlating the within-network connectivity (WNC) and between-network connectivity (BNC) of the face network with face recognition performance, we found that individuals with stronger WNC in the right fusiform face area or weaker BNC in the right occipital face area were better at recognizing faces. Our study not only demonstrates the behavioral relevance of the integration and segregation but also provides evidence supporting functional division of labor between the occipital face area and fusiform face area in the hierarchically organized face network.

Keywords: between-network connectivity; face recognition; fusiform face area; occipital face area; within-network connectivity.

Figure 1.

Example stimuli and trial types. A, In the old/new recognition task, participants studied a single image (either a face or a flower). They were then shown a series of individual images of the corresponding type and asked to indicate which of the images had been shown in the study segment. B, In the face-inversion task, participants performed a successive same-different matching task on upright and inverted faces.

Figure 2.

Group-level face-selective probabilistic activation map. Fourteen face-selective regions were identified in group analysis. Color bar represents the percentage of participants who showed face-selective activation. SFG, Superior frontal gyrus; MFG, medial frontal gyrus; PCG, right precentral gyrus; L, left; R, right. The visualization was provided by BrainNet Viewer (http://www.nitrc.org/projects/bnv/).

Figure 3.

Global pattern of the WNC/BNC in the FN. The group-level (one sample t test) WNC map (A), group-level (one sample t test) BNC map (B), and the difference (paired two sample t test) between the two connectivity metrics across participants (C) are overlaid on cortical surface. C, A total of 95.4% of the voxels in the FN had significantly larger WNC than BNC (t > 2.6, two-tailed p < 0.01, uncorrected). D, Scatter plots showing the across-voxel correlation between the probability of the face-selective activation in Figure 2 and the t-statistical difference in C (nonparametric Spearman r = 0.40, p < 10⁻⁵).

Figure 4.

WNC/BNC value and their comparison across participants. For display purposes, the average WNC and BNC values of the peak coordinates in Table 1 are shown in the bar plot. The t value indicates the paired t test statistic between WNC and BNC across participants for each peak. Error bars indicate SEM. SFG, Superior frontal gyrus; MFG, medial frontal gyrus; PCG, right precentral gyrus.

Figure 5.

Correlation between WNC/BNC and FRA. Correlations were calculated between each voxel's WNC/BNC in the FN and FRA. A, Of the entire FN, only rFFA's WNC significantly correlated with FRA (p < 0.05, corrected for multiple comparisons, 168 voxels). To better visualize the location of the significant cluster, the boundary of the rFFA in Figure 2 is shown with a green contour. The scatter plot between the WNC in the rFFA region and FRA is shown for illustration purposes only. B, Of the entire FN, only rOFA's BNC significantly correlated with FRA (p < 0.05, corrected for multiple comparisons, 200 voxels). Green contour represents the boundary of the rOFA in Figure 2. The scatter plot between the BNC in the rOFA region and FRA is shown for illustration purposes only. L, Left; R, right; a.u., arbitrary units.