Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI

Yeu Sheng Tyan, Jan Ray Liao, Chao Yu Shen, Yu Chieh Lin, Jun Cheng Weng*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

41 Scopus citations

Abstract

The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

Original languageEnglish
Pages (from-to)376-382
Number of pages7
JournalNeuroImage: Clinical
Volume15
DOIs
StatePublished - 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 The Authors

Keywords

  • Gender difference
  • Generalized q-sampling imaging (GQI)
  • Graph theoretical analysis
  • Network-based statistical (NBS) analysis
  • Structural connectome

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