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Structural and functional network analysis of twins using fMRI data.

Xing Yao1, Benjamin Klugah-Brown1, Hang Yang1

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

Cerebral Cortex (New York, N.Y. : 1991)
|September 29, 2023
PubMed
Summary
This summary is machine-generated.

Genetic factors significantly influence brain structure and function. Twins show greater similarity in brain gray/white matter density and dynamic brain activity patterns compared to unrelated individuals, highlighting genetics

Keywords:
coactivation patternfunctional MRIsource-based morphometrystructural MRItwins

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Area of Science:

  • Neuroscience
  • Behavioral Genetics
  • Human Brain Imaging

Background:

  • Genetics profoundly impacts human traits, as evidenced by twin studies.
  • Understanding genetic influences on the brain is crucial for neuroscience.
  • Previous research highlights genetic contributions to various biological systems.

Purpose of the Study:

  • To investigate the genetic basis of human brain structure and function.
  • To compare brain imaging data between twins and unrelated individuals.
  • To quantify the effects of genetic factors on brain morphology and activity.

Main Methods:

  • Utilized Magnetic Resonance Imaging (MRI) data from the Queensland Twin Imaging study.
  • Applied source-based morphometry (SBM) to identify intrinsic brain components.
  • Employed coactivation patterns analysis to characterize dynamic functional brain states.

Main Results:

  • Twins displayed significantly higher similarity in gray and white matter density than unrelated subjects.
  • Identified four distinct states of brain activity through coactivation patterns analysis.
  • Twins exhibited greater temporal and spatial similarity in these brain activity states.

Conclusions:

  • Results support the strong influence of genetics on both brain structure and dynamic functional activity.
  • Demonstrated that twin similarity extends to complex patterns of brain network engagement.
  • Suggests potential for advanced neuroimaging methods to explore gene-environment interactions in brain networks.