Structural and functional network analysis of twins using fMRI data

Author:

Yao Xing12,Klugah-Brown Benjamin12ORCID,Yang Hang12,Biswal Bharat123

Affiliation:

1. The Clinical Hospital of Chengdu Brain Science Institute , MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, , Chengdu 611731 , China

2. University of Electronic Science and Technology of China , MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, , Chengdu 611731 , China

3. Department of Biomedical Engineering, New Jersey Institute of Technology , Newark, NJ, 07102 , USA

Abstract

Abstract 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.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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