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Dissecting whole-brain conduction delays through MRI microstructural measures.

Brain structure & function | 2021

Network models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associated conduction delays becomes important. The goal of this study is to estimate and characterize these delays directly from the brain structure. To achieve this, we leveraged microstructural measures from a combination of advanced magnetic resonance imaging acquisitions and computed the main determinants of conduction velocity, namely axonal diameter and myelin content. Using the model proposed by Rushton, we used these measures to calculate the conduction velocity and estimated the associated delays using tractography. We observed that both the axonal diameter and conduction velocity distributions presented a rather constant trend across different connection lengths, with resulting delays that scale linearly with the connection length. Relying on insights from graph theory and Kuramoto simulations, our results support the approximation of constant conduction velocity but also show path- and region-specific differences.

Pubmed ID: 34390416 RIS Download

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Associated grants

  • Agency: NIH HHS, United States
    Id: P41-EB015896
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS118187
  • Agency: Wellcome Trust, United Kingdom
    Id: 213722/Z/18/Z
  • Agency: NIH HHS, United States
    Id: K23-NS096056
  • Agency: NINDS NIH HHS, United States
    Id: K23 NS096056
  • Agency: NIBIB NIH HHS, United States
    Id: P41 EB015896
  • Agency: NIH HHS, United States
    Id: U01-EB026996
  • Agency: NIH HHS, United States
    Id: P41-EB030006
  • Agency: NIBIB NIH HHS, United States
    Id: U01 EB026996
  • Agency: NIH HHS, United States
    Id: R01-NS118187
  • Agency: NIBIB NIH HHS, United States
    Id: P41 EB030006
  • Agency: Wellcome Trust, United Kingdom

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FreeSurfer (tool)

RRID:SCR_001847

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

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