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Efficiency of structural connectivity networks relates to intrinsic motivation in children born extremely preterm

  • Leona Pascoe
  • Deanne Thompson
  • Megan Spencer-Smith
  • Richard Beare
  • Chris Adamson
  • Katherine J. Lee
  • Claire Kelly
  • Nellie Georgiou-Karistianis
  • Chiara Nosarti
  • Elisha Josev
  • Gehan Roberts
  • Lex W. Doyle
  • Marc L. Seal
  • Peter J. Anderson
Original Research
  • 154 Downloads

Abstract

Intrinsic motivation is essential for academic success and cognitive growth, but limited work has examined the neuroanatomical underpinnings of intrinsic motivation from a network perspective, particularly in early childhood. Using graph theoretical analysis, this study investigated global and local properties of structural connectivity networks in relation to intrinsic motivation within a vulnerable group of children at early school age. Fifty-three 7 year-old children born extremely preterm (<28 weeks’ gestational age)/extremely low birth weight (<1000 g) underwent T1 and diffusion weighted imaging. Structural connectivity networks were generated using 162 cortical and subcortical nodes, and edges were created using constrained spherical deconvolution-based tractography. Global and node-specific network measures were analyzed in association with self-reported aspects of intrinsic motivation for school learning (Mastery, Challenge and Curiosity) using linear regression. Results indicated that increased information transfer across the network was associated with greater Mastery, while increased clustering and small-world topology related to greater Challenge. Increased efficiency and connection strength of the striatum in particular, related to greater intrinsic motivation. These findings suggest that both integrated and segregated network communication support aspects of intrinsic motivation in childhood, and shed new light on structural network properties important for intrinsic motivation orientations in extremely preterm children at early school age.

Keywords

Intrinsic motivation Diffusion weighted imaging Graph theory Preterm birth 

Notes

Acknowledgements

This research was supported by the National Health and Medical Research Council, Monash University and the Murdoch Children’s Research Institute. The Murdoch Children’s Research Institute is supported by the Royal Children’s Hospital, The Royal Children’s Hospital Foundation, Department of Paediatrics, The University of Melbourne and the Victorian Government’s Operational Infrastructure Support Program.

Funding

This research was funded by the National Health and Medical Research Council (NHMRC: Project Grant 1028422, Centre of Research Excellence in Newborn Medicine (1060733), Program Grant 606789, Senior Research Fellowship 1081288, Career Development Fellowship 1085754), Monash University and the Murdoch Children’s Research Institute.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Authors and Affiliations

  • Leona Pascoe
    • 1
    • 2
  • Deanne Thompson
    • 2
    • 3
  • Megan Spencer-Smith
    • 1
    • 2
  • Richard Beare
    • 2
    • 4
  • Chris Adamson
    • 2
  • Katherine J. Lee
    • 2
    • 5
  • Claire Kelly
    • 2
  • Nellie Georgiou-Karistianis
    • 1
  • Chiara Nosarti
    • 6
  • Elisha Josev
    • 2
    • 5
  • Gehan Roberts
    • 2
    • 5
  • Lex W. Doyle
    • 2
    • 5
    • 7
    • 8
  • Marc L. Seal
    • 2
    • 5
  • Peter J. Anderson
    • 1
    • 2
  1. 1.Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological SciencesMonash UniversityClaytonAustralia
  2. 2.Murdoch Children’s Research InstituteMelbourneAustralia
  3. 3.Florey Institute of Neuroscience and Mental HealthMelbourneAustralia
  4. 4.Department of MedicineMonash UniversityClaytonAustralia
  5. 5.Department of PaediatricsThe University of MelbourneMelbourneAustralia
  6. 6.King’s College LondonLondonUK
  7. 7.Neonatal ServicesThe Royal Women’s HospitalMelbourneAustralia
  8. 8.Department of Obstetrics and GynaecologyThe University of MelbourneMelbourneAustralia

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