Early Development of Infant Brain Complex Network

Weixiong Jiang, Han Zhang, Li Ming Hsu, Dan Hu, Guoshi Li, Ye Wu, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The infant brain experiences explosive growth in the first few years of life. The developing topology of the functional network mirrors the emergence of complex cognitive functions. However, early development of brain topological properties in infants is still largely unclear due to the dearth of high-quality longitudinal infant functional MRI (fMRI) data. In this study, we employed advanced methods to investigate the developmental trajectories of various network features on high-resolution, longitudinal fMRI data of infants from birth to 2 years of age. The developmental trajectories of various global and nodal metrics were evaluated with linear mixed-effect modeling. We then investigated the association between these developmental trajectories and the visual reception ability, an important skill that could shape the future development of other cognitive functions. Four global metrics (shortest path length, global efficiency, local efficiency, and sigma (i.e., small-worldness)) showed significant developmental changes to facilitate more efficient information processing. Significant developmental changes were also found in the nodal characters with a prominent spatial specificity, and some brain regions showed increasing importance along the development. Most importantly, different associations between developmental trajectories in both global and nodal network characters and varied visual reception ability were revealed. This is the first longitudinal study on the early development of the brain functional connectome and its potential relationship to the individual variability of the visual abilities. These findings provide valuable knowledge for better understanding of normative and abnormal neurodevelopment in the first few years of life.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings
EditorsDinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou
PublisherSpringer
Pages832-840
Number of pages9
ISBN (Print)9783030322441
DOIs
Publication statusPublished - 2019 Jan 1
Externally publishedYes
Event22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 2019 Oct 132019 Oct 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11765 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
CountryChina
CityShenzhen
Period19/10/1319/10/17

Keywords

  • Complex network
  • Development
  • Graph theory
  • Infant
  • Longitudinal
  • Resting-state fMRI
  • Visual reception

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Jiang, W., Zhang, H., Hsu, L. M., Hu, D., Li, G., Wu, Y., & Shen, D. (2019). Early Development of Infant Brain Complex Network. In D. Shen, P-T. Yap, T. Liu, T. M. Peters, A. Khan, L. H. Staib, C. Essert, & S. Zhou (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings (pp. 832-840). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11765 LNCS). Springer. https://doi.org/10.1007/978-3-030-32245-8_92