Functional connectivity pattern in the core face network reflects different mechanisms of holistic face processing measured by the whole-part effect and composite-face effect.

Holistic 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.

Dissociated neural basis of two behavioral hallmarks of holistic face processing: The whole-part effect and composite-face effect.

It has been long proposed that our extraordinary face recognition ability stems from holistic face processing. Two widely-used behavioral hallmarks of holistic face processing are the whole-part effect (WPE) and composite-face effect (CFE). However, it remains unknown whether these two effects reflect similar or different aspects of holistic face processing. Here we investigated this question by examining whether the WPE and CFE involved shared or distinct neural substrates in a large sample of participants (N=200). We found that the WPE and CFE showed hemispheric dissociation in the fusiform face area (FFA), that is, the WPE was correlated with face selectivity in the left FFA, while the CFE was correlated with face selectivity in the right FFA. Further, the correlation between the WPE and face selectivity was largely driven by the FFA response to faces, whereas the association between the CFE and face selectivity resulted from suppressed response to objects in the right FFA. Finally, we also observed dissociated correlation patterns of the WPE and CFE in other face-selective regions and across the whole brain. These results suggest that the WPE and CFE may reflect different aspects of holistic face processing, which shed new light on the behavioral dissociations of these two effects demonstrated in literature.

Structural and functional neural correlates of spatial navigation: a combined voxel-based morphometry and functional connectivity study.

INTRODUCTION: Navigation is a fundamental and multidimensional cognitive function that individuals rely on to move around the environment. In this study, we investigated the neural basis of human spatial navigation ability. METHODS: A large cohort of participants (N > 200) was examined on their navigation ability behaviorally and structural and functional magnetic resonance imaging (MRI) were then used to explore the corresponding neural basis of spatial navigation. RESULTS: The gray matter volume (GMV) of the bilateral parahippocampus (PHG), retrosplenial complex (RSC), entorhinal cortex (EC), hippocampus (HPC), and thalamus (THAL) was correlated with the participants' self-reported navigational ability in general, and their sense of direction in particular. Further fMRI studies showed that the PHG, RSC, and EC selectively responded to visually presented scenes, whereas the HPC and THAL showed no selectivity, suggesting a functional division of labor among these regions in spatial navigation. The resting-state functional connectivity analysis further revealed a hierarchical neural network for navigation constituted by these regions, which can be further categorized into three relatively independent components (i.e., scene recognition component, cognitive map component, and the component of heading direction for locomotion, respectively). CONCLUSIONS: Our study combined multi-modality imaging data to illustrate that multiple brain regions may work collaboratively to extract, integrate, store, and orientate spatial information to guide navigation behaviors.

Brain regions involved in dispositional mindfulness during resting state and their relation with well-being.

Mindfulness can be viewed as an important dispositional characteristic that reflects the tendency to be mindful in daily life, which is beneficial for improving individuals' both hedonic and eudaimonic well-being. However, no study to date has examined the brain regions involved in individual differences in dispositional mindfulness during the resting state and its relation with hedonic and eudaimonic well-being. To investigate this issue, the present study employed resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate the regional homogeneity (ReHo) that measures the local synchronization of spontaneous brain activity in a large sample. We found that dispositional mindfulness was positively associated with the ReHo in the left orbitofrontal cortex (OFC), left parahippocampal gyrus (PHG), and right insula implicated in emotion processing, body awareness, and self-referential processing, and negatively associated with the ReHo in right inferior frontal gyrus (IFG) implicated in response inhibition and attentional control. Furthermore, we found different neural associations with hedonic (i.e., positive and negative affect) and eudaimonic well-being (i.e., the meaningful and purposeful life). Specifically, the ReHo in the IFG predicted eudaimonic well-being whereas the OFC predicted positive affect, both of which were mediated by dispositional mindfulness. Taken together, our study provides the first evidence for linking individual differences in dispositional mindfulness to spontaneous brain activity and demonstrates that dispositional mindfulness engages multiple brain mechanisms that differentially influence hedonic and eudaimonic well-being.