The mentalizing network and theory of mind mediate adjustment after childhood traumatic brain injury. Issue 12 (28th January 2020)

• Record Type: Journal Article
• Authors: Hoskinson, Kristen R; Bigler, Erin D; Abildskov, Tracy J; Dennis, Maureen; Taylor, H Gerry; Rubin, Kenneth; Gerhardt, Cynthia A; Vannatta, Kathryn; Stancin, Terry; Yeates, Keith Owen
• Is Part Of: Social cognitive and affective neuroscience. Volume 14:Issue 12(2019)
• Page Start: 1285
• Page End: 1295
• Publication Date: 2020-01-28
• Subjects: acquired brain injury -- MRI -- social cognition -- social adjustment -- sequelae; Neurosciences -- Periodicals; Cognitive neuroscience -- Periodicals; Neuropsychology -- Periodicals; 612.8205
• DOI: 10.1093/scan/nsaa006
• Languages: English
• ISSNs: 1749-5016

Abstract

Abstract: Childhood traumatic brain injury (TBI) affects over 600 000 children per year in the United States. Following TBI, children are vulnerable to deficits in psychosocial adjustment and neurocognition, including social cognition, which persist long-term. They are also susceptible to direct and secondary damage to related brain networks. In this study, we examine whether brain morphometry of the mentalizing network (MN) and theory of mind (ToM; one component of social cognition) mediates the effects of TBI on adjustment. Children with severe TBI ( n = 15, Mage = 10.32), complicated mild/moderate TBI ( n = 30, Mage = 10.81) and orthopedic injury (OI; n = 42, Mage = 10.65) completed measures of ToM and executive function and underwent MRI; parents rated children's psychosocial adjustment. Children with severe TBI demonstrated reduced right-hemisphere MN volume, and poorer ToM, vs children with OI. Ordinary least-squares path analysis indicated that right-hemisphere MN volume and ToM mediated the association between severe TBI and adjustment. Parallel analyses substituting the central executive network and executive function were not significant, suggesting some model specificity. Children at greatest risk of poor adjustment after TBI could be identified based in part on neuroimaging of social brain networks and assessment of social cognition and thereby more effectively allocate limited intervention resources.