Behavioral Heterogeneity in Relation with Brain Functional Networks in Young Children. (9th August 2017)

• Record Type: Journal Article
• Authors: Wee, Chong-Yaw; Poh, Joann S; Wang, Qiang; Broekman, Birit FP; Chong, Yap-Seng; Kwek, Kenneth; Shek, Lynette P; Saw, Seang-Mei; Gluckman, Peter D; Fortier, Marielle V; Meaney, Michael J; Qiu, Anqi
• Is Part Of: Cerebral cortex. Volume 28:Number 9(2018)
• Page Start: 3322
• Page End: 3331
• Publication Date: 2017-08-09
• Subjects: attention network -- child behavior checklist -- classification -- frontal network -- resting-state fMRI; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhx205
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: This study aimed to identify distinct behavioral profiles in a population-based sample of 654 4-year-old children and characterize their relationships with brain functional networks using resting-state functional magnetic resonance imaging data. Young children showed 7 behavioral profiles, including a super healthy behavioral profile with the lowest scores across all Child Behavior CheckList (CBCL) subscales (G1) and other 6 behavioral profiles, respectively with pronounced withdrawal (G2), somatic complaints (G3), anxiety and withdrawal (G4), somatic complaints and withdrawal (G5), the mixture of emotion, withdrawal, and aggression (G6), and attention (G7) problems. Compared with children in G1, children with withdrawal shared abnormal functional connectivities among the sensorimotor networks. Children in emotionally relevant problems shared the common pattern among the attentional and frontal networks. Nevertheless, children in sole withdrawal problems showed a unique pattern of connectivity alterations among the sensorimotor, cerebellar, and salience networks. Children with somatic complaints showed abnormal functional connectivities between the attentional and subcortical networks, and between the language and posterior default mode networks. This study provides novel evidence on the existence of behavioral heterogeneity in early childhood and its associations with specific functional networks that are clinically relevant phenotypes for mental illness and are apparent from early childhood.