Longitudinal development of cortical thickness, folding, and fiber density networks in the first 2 years of life

Jingxin Nie, Gang Li, Li Wang, Feng Shi, Weili Lin, John H. Gilmore, Dinggang Shen

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)


Quantitatively characterizing the development of cortical anatomical networks during the early stage of life plays an important role in revealing the relationship between cortical structural connection and high-level functional development. The development of correlation networks of cortical-thickness, cortical folding, and fiber-density is systematically analyzed in this article to study the relationship between different anatomical properties during the first 2 years of life. Specifically, longitudinal MR images of 73 healthy subjects from birth to 2 year old are used. For each subject at each time point, its measures of cortical thickness, cortical folding, and fiber density are projected to its cortical surface that has been partitioned into 78 cortical regions. Then, the correlation matrices for cortical thickness, cortical folding, and fiber density at each time point can be constructed, respectively, by computing the inter-regional Pearson correlation coefficient (of any pair of ROIs) across all 73 subjects. Finally, the presence/absence pattern (i.e., binary pattern) of the connection network is constructed from each inter-regional correlation matrix, and its statistical and anatomical properties are adopted to analyze the longitudinal development of anatomical networks. The results show that the development of anatomical network could be characterized differently by using different anatomical properties (i.e., using cortical thickness, cortical folding, or fiber density).

Original languageEnglish
Pages (from-to)3726-3737
Number of pages12
JournalHuman Brain Mapping
Issue number8
Publication statusPublished - 2014 Aug


  • Anatomical network
  • Cortical development
  • Cortical folding
  • Early brain development

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology


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