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Sample sizes and population differences in brain template construction.

Guoyuan Yang1, Sizhong Zhou1, Jelena Bozek2

  • 1Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China.

Neuroimage
|November 6, 2019
PubMed
Summary
This summary is machine-generated.

Using population-matched brain templates improves magnetic resonance imaging (MRI) analysis accuracy. This study quantifies how sample size and population differences impact template construction, recommending matched templates for better human brain mapping.

Keywords:
Brain templateMRIPopulationSample sizeVariability

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Image Analysis

Background:

  • Spatial normalization to brain templates is crucial for magnetic resonance imaging (MRI) processing.
  • Current templates often use limited sample sizes and may not represent diverse populations.
  • Brain morphology exhibits significant individual variability, impacting template accuracy.

Purpose of the Study:

  • To quantify the impact of sample size and population differences on brain template construction.
  • To assess the performance of population-matched versus mismatched templates in spatial normalization.
  • To provide population-specific brain templates for enhanced human brain mapping.

Main Methods:

  • Utilized Human Connectome Project (HCP) and Chinese Human Connectome Project (CHCP) datasets.
  • Assessed sample size effects using deformation variability and Jacobian determinants.
  • Constructed Caucasian (US200) and Chinese (CN200) brain atlases.
  • Evaluated segmentation and registration accuracy with matched and mismatched templates.

Main Results:

  • Brain template variability scales with sample size, following a power function.
  • Frontoparietal and dorsal attention networks showed higher deformation variability.
  • Significant differences in deformation variability were observed between Caucasian and Chinese templates, especially in language areas.
  • Population-mismatched templates significantly reduced segmentation and registration accuracy.

Conclusions:

  • Population-matched templates are essential for accurate human brain mapping.
  • Sample size and population diversity are critical factors in brain template construction.
  • The US200 and CN200 templates offer improved resources for neuroimaging research.