Developmental Cognitive Neuroscience (Aug 2016)

Connectome hubs at resting state in children and adolescents: Reproducibility and psychopathological correlation

  • João Ricardo Sato,
  • Claudinei Eduardo Biazoli Jr,
  • Giovanni Abrahão Salum,
  • Ary Gadelha,
  • Nicolas Crossley,
  • Gilson Vieira,
  • André Zugman,
  • Felipe Almeida Picon,
  • Pedro Mario Pan,
  • Marcelo Queiroz Hoexter,
  • Mauricio Anés,
  • Luciana Monteiro Moura,
  • Marco Antonio Gomes Del’Aquilla,
  • Edson Amaro Junior,
  • Philip Mcguire,
  • Luis Augusto Rohde,
  • Euripedes Constantino Miguel,
  • Rodrigo Affonseca Bressan,
  • Andrea Parolin Jackowski

DOI
https://doi.org/10.1016/j.dcn.2016.05.002
Journal volume & issue
Vol. 20, no. C
pp. 2 – 11

Abstract

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Functional brain hubs are key integrative regions in brain networks. Recently, brain hubs identified through resting-state fMRI have emerged as interesting targets to increase understanding of the relationships between large-scale functional networks and psychopathology. However, few studies have directly addressed the replicability and consistency of the hub regions identified and their association with symptoms. Here, we used the eigenvector centrality (EVC) measure obtained from graph analysis of two large, independent population-based samples of children and adolescents (7–15 years old; total N = 652; 341 subjects for site 1 and 311 for site 2) to evaluate the replicability of hub identification. Subsequently, we tested the association between replicable hub regions and psychiatric symptoms. We identified a set of hubs consisting of the anterior medial prefrontal cortex and inferior parietal lobule/intraparietal sulcus (IPL/IPS). Moreover, lower EVC values in the right IPS were associated with psychiatric symptoms in both samples. Thus, low centrality of the IPS was a replicable sign of potential vulnerability to mental disorders in children. The identification of critical and replicable hubs in functional cortical networks in children and adolescents can foster understanding of the mechanisms underlying mental disorders.

Keywords