A large-scale structural and functional connectome of social mentalizing

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Connectomics

Background:

• Human ability to infer others' minds (mentalizing) involves a distributed brain network.
• The precise connectivity and interaction within this mentalizing network (MTN) remain unclear.

Purpose of the Study:

• To elucidate the brain-wide organization and mechanisms of mentalizing processing using large-scale multimodal neuroimaging data.
• To detail the connectomic features of the mentalizing network (MTN).

Main Methods:

• Leveraged large-scale multimodal neuroimaging data.
• Analyzed structural and functional connectivity.
• Compared the mentalizing network (MTN) with the default mode network (DMN).

Main Results:

• Identified two parallel subsystems and redundant white matter fiber construction in the MTN's structural architecture.
• Revealed a functional architecture synchronized by mentalizing degree and a hierarchy reflecting information integration.
• Found differences between structural and functional connectivity in topology, variance, and specificity.
• Elaborated on distinctions between the MTN and DMN in dynamics, laterality, and homogeneity.

Conclusions:

• Mentalizing processing involves functionally heterogeneous regions with structured fiber tracts and a unique hierarchical functional architecture.
• The mentalizing network (MTN) is distinct from the default mode network (DMN) and related cognitive networks.