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Modeling the Functional Network for Spatial Navigation in the Human Brain
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Parcellation-based anatomic modeling of the default mode network.

Zainab Sandhu1, Onur Tanglay2, Isabella M Young3

  • 1Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.

Brain and Behavior
|December 18, 2020
PubMed
Summary
This summary is machine-generated.

This study maps the default mode network (DMN) using advanced imaging techniques. The findings reveal specific structural connections within the DMN, laying groundwork for future clinical applications.

Keywords:
ALEanatomydefault mode networkparcellationtractographywhite matter

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Area of Science:

  • Neuroscience
  • Neuroimaging
  • Connectomics

Background:

  • The default mode network (DMN) is crucial for passive cognitive states.
  • Previous research identified cortical regions within the DMN but lacked detailed connectivity information.
  • Tractographic specificity of DMN connectivity was limited.

Purpose of the Study:

  • To create a detailed tractographical model of the default mode network.
  • To identify structural connections between cortical regions within the DMN.
  • To provide a foundation for potential clinical applications of DMN research.

Main Methods:

  • Resting-state fMRI data and activation likelihood estimation (ALE) were utilized.
  • A tractographical model was constructed based on the Human Connectome Project's cortical parcellation.
  • Diffusion spectrum imaging (DSI)-based fiber tractography was performed to map structural connections.

Main Results:

  • Seventeen cortical regions were identified as integral components of the DMN.
  • Consistent interconnections were observed between adjacent cortical parcellations.
  • The cingulum bundle was identified as a key structure connecting anterior and posterior cingulate regions within the DMN.

Conclusions:

  • A preliminary anatomical model of the default mode network has been established.
  • This model provides a more specific understanding of DMN structural connectivity.
  • Further research aims to refine this model for clinical relevance.