Structural and functional network analysis of twins using fMRI data

Xing Yao, Benjamin Klugah-Brown, Hang Yang, Bharat Biswal

Research output: Contribution to journalArticlepeer-review


Similarities between twins have been widely demonstrated, underscoring the remarkable influence of genetics across numerous traits. In this study, we explore the genetic underpinnings of the human brain by examining MRI data from the Queensland Twin Imaging study. Specifically, this study seeks to compare brain structure and function between twins and unrelated subjects, with an emphasis on describing the effects of genetic factors. To achieve these goals, we employed the source-based morphometry method to extract intrinsic components and elucidate recognizable patterns. Our results show that twins exhibit a higher degree of similarity in gray and white matter density compared with unrelated individuals. In addition, four distinct states of brain activity were identified using coactivation patterns analysis. Furthermore, twins demonstrated a greater degree of similarity in the temporal and spatial features of each state compared with unrelated subjects. Taken together, these results support the hypothesis that twins show greater similarity in both brain structure and dynamic functional brain activity. Further exploration of these methods may advance our understanding of the complex interplay between genes, environment, and brain networks.

Original languageEnglish (US)
Pages (from-to)11060-11069
Number of pages10
JournalCerebral Cortex
Issue number22
StatePublished - Nov 15 2023

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience


  • coactivation pattern
  • functional MRI
  • source-based morphometry
  • structural MRI
  • twins


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