Social communication and brain network properties: cognitive predictors and modulation by autistic traits

Area of Science:

• Neuroscience
• Cognitive Science
• Psychology

Background:

• Social communication (SC) integrates language, pragmatic inference, and theory of mind (ToM), but its neural basis is unclear.
• Understanding the neural architecture of SC is crucial for characterizing social-cognitive functioning.

Purpose of the Study:

• To propose and test a unified social communication network model.
• To investigate the roles of language, executive functions, and perceptual reasoning in neural network efficiency.
• To examine how autistic traits moderate brain-behavior relationships in social communication.

Main Methods:

• Utilized information neural graph theory metrics and multi-domain cognitive modeling.
• Assessed language, executive functions, social cognition, and perceptual reasoning in neurotypical adults.
• Computed global and local network efficiency and clustering coefficients, alongside autism spectrum quotient (AQ).
• Performed a replication analysis with an independent sample including autistic individuals.

Main Results:

• Language abilities were the primary predictors of network efficiency, especially in temporal-parietal regions.
• Executive functions predicted efficiency in frontal control regions; perceptual reasoning linked to precuneus efficiency.
• Autistic traits significantly moderated brain-behavior relationships, highlighting individual differences in neural organization.

Conclusions:

• Communicative competence arises from dynamic interactions within linguistic, executive, and inferential systems.
• Neural organization of SC networks is shaped by individual cognitive profiles and autistic traits.
• This dimensional framework aids understanding of social-cognitive variability and personalized communication models.