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This study introduces a new computational framework to infer the directionality of brain connections using diffusion MRI (dMRI) and gene expression. The method reveals a directional brain network architecture and a novel measure of directed functional connectivity called angular flow (AF).

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Biophysics

Background:

  • Diffusion MRI (dMRI) tractography estimates structural connectivity (SC) but lacks directional information in white matter pathways.
  • Understanding the directionality of neural connections is crucial for comprehending brain function and dysfunction.
  • Existing methods for inferring connection directionality are limited, especially at a large scale in humans.

Purpose of the Study:

  • To develop and validate a computational framework for inferring directional structural connectivity (dSC) from dMRI data.
  • To investigate the brain's network architecture and functional connectivity using the inferred dSC.
  • To introduce and characterize a novel measure of directed functional connectivity, termed angular flow (AF).

Main Methods:

  • Combined dMRI-derived SC with gene co-expression gradients.
  • Fitted a structure-function model using the Lyapunov equation to infer directionality.
  • Validated the model against ground-truth synaptic connectivity in *C. elegans* and tracer data in rodents and primates.
  • Applied the framework to Human Connectome Project (HCP) data from 770 healthy adults.
  • Developed and analyzed the angular flow (AF) measure based on dSC.

Main Results:

  • The computational framework successfully predicted ground-truth directional connectivity in model organisms and animal studies.
  • Inferred dSC in humans revealed an interdigitated sink/source network architecture and plausible feedback/feedforward pathways in sensory areas.
  • The novel AF measure correlated with causal functional connectivity metrics.
  • AF explained the principal gradient of undirected functional connectivity as net flow from sensory to multimodal areas.

Conclusions:

  • The developed framework provides a robust method for inferring directional structural connectivity in the human brain.
  • The findings reveal a directional brain network architecture and highlight the significance of directed pathways in brain function.
  • Angular flow (AF) offers a new perspective on directed functional connectivity, linking structural directionality to functional organization.