Abstract
In facial expression perception, a distributed network is activated according to stimulus context. We proposed that an interaction between brain activation and stimulus context in response to facial expressions could signify a pattern of interactivity across the whole brain network beyond the face processing network. Functional magnetic resonance imaging data were acquired for 19 young healthy subjects who were exposed to either emotionally neutral or negative facial expressions. We constructed group-wise functional brain networks for 12 face processing areas [bilateral inferior occipital gyri (IOG), fusiform gyri (FG), superior temporal sulci (STS), amygdalae (AMG), inferior frontal gyri (IFG), and orbitofrontal cortices (OFC)] and for 73 whole brain areas, based on partial correlation of mean activation across subjects. We compared the topological properties of the networks with respect to functional distance-based measures, global and local efficiency, between the two types of face stimulus. In both face processing and whole brain networks, global efficiency was lower and local efficiency was higher for negative faces relative to neutral faces, indicating that network topology differed according to stimulus context. Particularly in the face processing network, emotion-induced changes in network topology were attributable to interactions between core (bilateral IOG, FG, and STS) and extended (bilateral AMG, IFG, and OFC) systems. These results suggest that changes in brain activation patterns in response to emotional face stimuli could be revealed as changes in the topological properties of functional brain networks for the whole brain as well as for face processing areas.
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This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A2044932).
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Supplementary material 1 (TIFF 259 kb) Computation of (A) interregonal and (B) epiregonal efficiency for an example network N with 12 nodes. The interregional efficiency, e ab , between a pair of nodes a and b is 0.2500 as the reciprocal of the shortest path length, d ab , between them (along the path indicated in red in (A)). The global efficiency, E g(N), of the network N is computed as the average of interregional efficiency for 12 × (12-1)/2 pairs of nodes in the network. The epiregional efficiency, E(N c), of a local subnetwork N c that consists of the 5 nearest neighbours of a node c is 0.2000 as the average of interregional efficiency measured for the 5 nodes (indicated in yellow in (B)) in the local subnetwork. The local efficiency, E l(N), of the network N is computed as the average of epiregional efficiency for 12 local subnetworks in the network
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Supplementary material 2 (TIFF 200 kb) Changes in thresholds for correlation matrices, which determine the sparsity of (A) the face selective network and (B) whole brain network, for emotionally negative faces and emotionally neutral faces
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Supplementary material 3 (TIFF 1747 kb) Edges of the face processing network for which interregional efficiency differed between emotionally negative faces and emotionally neutral faces at each connection density. No difference in interregional efficiency was shown at a connection density of 0.30. Red and blue lines indicate higher and lower interregional efficiency, respectively, for emotionally negative faces relative to emotionally neutral faces
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Park, Ch., Lee, HK., Kweon, YS. et al. Emotion-Induced Topological Changes in Functional Brain Networks. Brain Topogr 29, 108–117 (2016). https://doi.org/10.1007/s10548-015-0449-z
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DOI: https://doi.org/10.1007/s10548-015-0449-z