• Jin Li, Yiying Song, and Jia Liu.
• State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
• Neuroscience. 2019 Jun 1; 408: 248-258.

AbstractHolistic face processing is a critical component of face recognition. There are two classical measures of holistic face processing: the whole-part effect (WPE) and composite-face effect (CFE). However, the two effects have demonstrated inconsistent pattern of results in behavioral literature. Here, to address whether the WPE and CFE tap different mechanisms of holistic face processing, we examined the neural basis of the two effects at network level in a large sample of participants. With a voxel-wise global brain connectivity approach based on resting-state fMRI, we calculated the within network connectivity (WNC) of each voxel in the core face network (CFN). We found that a cluster in the right occipital face area (rOFA) showed positive correlation between its WNC and the WPE, while a cluster in the right fusiform face area (rFFA) showed negative correlation between its WNC and the CFE. These results suggested that the WPE was related to integration of the rOFA within the CFN, while the CFE was associated with separation of the rFFA from other CFN regions. Further analyses showed that higher WPE was related to stronger connection between the rOFA and bilateral posterior superior temporal sulcus (pSTS), while larger CFE was associated with weaker connection between the rFFA and bilateral pSTS. In short, our study reveals distinct neural correlates of the two hallmarks of holistic face processing at network level and sheds new light on the different mechanisms of holistic face processing reflected by the two effects.Copyright © 2019 IBRO. Published by Elsevier Ltd. All rights reserved.

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