title: Association between resting-state coactivation in the parieto-frontal network and intelligence during late childhood and adolescence.
abstract: OBJECTIVE
  A number of studies have associated the adult intelligence quotient with the structure and function of the bilateral parieto-frontal networks, whereas the relationship between intelligence quotient and parieto-frontal network function has been found to be relatively weak in early childhood. Because both human intelligence and brain function undergo protracted development into adulthood, the purpose of the present study was to provide a better understanding of the development of the parieto-frontal network-intelligence quotient relationship.
  
  
  METHODS
  We performed independent component analysis of resting-state fMRI data of 84 children and 50 adolescents separately and then correlated full-scale intelligence quotient with the spatial maps of the bilateral parieto-frontal networks of each group.
  
  
  RESULTS
  In children, significant positive spatial-map versus intelligence quotient correlations were detected in the right angular gyrus and inferior frontal gyrus in the right parieto-frontal network, and no significant correlation was observed in the left parieto-frontal network. In adolescents, significant positive correlation was detected in the left inferior frontal gyrus in the left parieto-frontal network, and the correlations in the frontal pole in the 2 parieto-frontal networks were only marginally significant.
  
  
  CONCLUSIONS
  The present findings not only support the critical role of the parieto-frontal networks for intelligence but indicate that the relationship between intelligence quotient and the parieto-frontal network in the right hemisphere has been well established in late childhood, and that the relationship in the left hemisphere was also established in adolescence.
authors.affiliation: From the Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China.
authors.forename: C
authors.initials: C
authors.lastname: Li
authors.affiliation: From the Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China. lxtian@bjtu.edu.cn tian.bme@gmail.com.
authors.forename: L
authors.initials: L
authors.lastname: Tian
mesh_terms: D000293:Adolescent / Q000502:physiology*; D002648:Child; D002681:China; D003071:Cognition / Q000502:physiology*; D063132:Connectome / Q000379:methods; D005625:Frontal Lobe / Q000254:growth & development* / Q000502:physiology; D006801:Humans; D007360:Intelligence / Q000502:physiology*; D007361:Intelligence Tests; D008297:Male; D009415:Nerve Net / Q000254:growth & development* / Q000502:physiology; D010296:Parietal Lobe / Q000254:growth & development* / Q000502:physiology; D012146:Rest / Q000502:physiology*