Multimodal Mapping of the Face Connectome

Face processing supports our ability to recognize friend from foe, form tribes, and understand the emotional implications of changes in facial musculature. This skill relies on a distributed network of brain regions but how these regions interact is poorly understood. Here, we integrate anatomical and functional connectivity measurements with behavioral assays to create a global model of the face connectome. We dissect key features such as the network topology and fiber composition. We propose a neurocognitive model with three core streams, and face processing along these streams occurs in a parallel and reciprocal fashion. While long-range fiber paths are important, face network is dominated by short-range fibers. Last, we provide some evidence that the well-known right lateralization of face processing arises from imbalanced intra/interhemispheric connections. In sum, the face network relies on dynamic communication across highly structured fiber tracts, which enables coherent face processing that underpins behavior and cognition.