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Spatially heterogeneous structure-function coupling in haemodynamic and electromagnetic brain networks.

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  • 1McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.

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Brain connectivity research reveals that the link between brain structure and function varies by region and frequency. Neurophysiological recordings show stronger structure-function coupling than fMRI, especially in slower frequencies.

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Area of Science:

  • Neuroscience
  • Connectomics
  • Brain Imaging

Background:

  • Understanding the relationship between structural and functional brain connectivity is crucial in connectomics.
  • Quantifying how structural connections influence brain activity patterns is a key challenge.

Purpose of the Study:

  • To quantify structure-function coupling across the neocortex.
  • To compare coupling using diffusion MRI, MEG, and fMRI data.
  • To investigate factors influencing structure-function coupling, including frequency bands and cortical hierarchies.

Main Methods:

  • Compared structural connectivity (diffusion MRI) with functional connectivity (MEG and fMRI).
  • Analyzed structure-function coupling across different brain regions and frequency bands.
  • Investigated coupling patterns along the sensorimotor-association hierarchy and laminar differentiation.

Main Results:

  • Structure-function coupling is heterogeneous across the neocortex and frequency bands.
  • Neurophysiological (MEG) coupling is generally stronger than haemodynamic (fMRI) coupling.
  • Coupling is stronger in slower/intermediate frequencies and follows cortical hierarchies, peaking in layer IV.
  • Structure-informed communication metrics better explain coupling than structural connectivity alone.

Conclusions:

  • Established a common frame of reference for neurophysiological and haemodynamic structure-function relationships.
  • Demonstrated that structure-function coupling varies systematically with cortical organization.
  • Highlighted the importance of communication metrics for understanding brain connectivity.