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Exploring the functional connectome in white matter.

Jiao Li1,2, Bharat B Biswal1,2,3, Pan Wang1,2

  • 1The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.

Human Brain Mapping
|July 6, 2019
PubMed
Summary
This summary is machine-generated.

Researchers explored brain connectivity using white matter (WM) signals, typically ignored in fMRI studies. They found WM functional connectomes show reliable structure and correlate with intelligence, opening new avenues for neuroscience research.

Keywords:
functional connectomenetwork topologyresting-statetopological reliabilitywhite matter

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Area of Science:

  • Neuroscience
  • Brain Imaging
  • Connectomics

Background:

  • Understanding brain function relies on mapping neural connections (connectome).
  • Functional connectomes are typically derived from gray matter (GM) signals in fMRI.
  • White matter (WM) signals in fMRI are often disregarded as noise.

Purpose of the Study:

  • To derive and characterize a functional connectome from WM signals.
  • To assess the reliability and topological properties of the WM functional connectome.
  • To explore the relationship between WM functional connectome properties and individual intelligence.

Main Methods:

  • Utilized resting-state blood-oxygen-level-dependent (BOLD)-fMRI signals from a cohort of 488 individuals.
  • Derived functional connectomes from WM signals.
  • Analyzed topological properties (small-worldness, modularity) and long-term reliability.

Main Results:

  • The WM functional connectome demonstrated weak small-world topology and nonrandom modularity.
  • High topological reliability was observed over 10 months across various analysis strategies.
  • WM small-worldness positively correlated with individual intelligence scores (r=0.17, p<0.001).

Conclusions:

  • This study provides initial evidence for the utility of WM functional connectomes.
  • WM signals contain valuable functional information beyond GM.
  • These findings offer new metrics for studying WM function in health and disease.