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. 2020 Mar;10(3):e01524.
doi: 10.1002/brb3.1524. Epub 2020 Jan 23.

Exploring the social cognition network in young adults with autism spectrum disorder using graph analysis

Roberto Vagnetti  1 , Maria Chiara Pino  1   2 , Francesco Masedu  1 , Sara Peretti  1 , Ilenia Le Donne  1 , Rodolfo Rossi  3 , Marco Valenti  1   2 , Monica Mazza  1   2
Affiliations

Exploring the social cognition network in young adults with autism spectrum disorder using graph analysis

Roberto Vagnetti et al. Brain Behav. 2020 Mar.

Abstract

Background: Autism spectrum disorder (ASD) is characterized by an impairment in social cognition (SC). SC is a cognitive construct that refers to the capacity to process information about social situations. It is a complex network that includes distinct components. Exploring how SC components work together leads to a better understanding of how their interactions promote adequate social functioning. Our main goal was to use a novel statistical method, graph theory, to analyze SC relationships in ASD and Typically Developing (TD) individuals.

Methods: We applied graph theory to SC measures to verify how the SC components interact and to establish which of them are important within the interacting SC network for TD and ASD groups.

Results: The results showed that, in the TD group, the SC nodes are connected; their network showed increased betweenness among nodes, especially for the Theory of Mind. By contrast, in the SC network in the ASD group the nodes are highly disconnected, and the efficient connection among the components is absent.

Conclusion: ASD adults do not show SC competencies and functional communication among these skills. Under this regard, specific components are crucial, suggesting they could represent critical domains for ASD SC.

Keywords: autism spectrum disorder; graph theory; network analysis; social cognition; social functioning.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Graphs of ASD and TD populations. Each node represents a SC domain. Strength is represented by the edge's thickness and closeness by the nodes’ distance. Blue and red links represent positive and negative partial correlation coefficients, respectively. AES‐BES, Affective Empathy subscale of BES; A‐ToM, Advanced Theory of Mind task; CEQ‐EQ, Cognitive empathy; CES‐BES, Cognitive Empathy subscale of BES; EEQ‐EQ, Emotional empathy; ET, Eyes Task; SSQ‐EQ, Social Skills
Figure 2
Figure 2
Sample (red line), bootstrap mean (blue line), and SEM (gray area) of centrality indices for each node and group
See this image and copyright information in PMC

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