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Structural connectivity within neural ganglia: A default small-world network.

Abdol Aziz O Ould Ismail1, Ghoncheh Amouzandeh2, Samuel C Grant1

  • 1The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA; Department of Chemical and Biomedical Engineering, Florida State University, FAMU-FSU College of Engineering, Tallahassee, FL, USA.

Neuroscience
|September 24, 2016
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Summary

Diffusion tensor imaging reveals the small-world network properties of Aplysia abdominal ganglia. This study quantifies neural tissue connectivity using network theory and DTI tractography for macroscopic insights.

Keywords:
diffusion tensor imaginggraph theorysmall-world networksstructural connectivity

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Area of Science:

  • Neuroscience
  • Biophysics
  • Network Science

Background:

  • Diffusion tensor imaging (DTI) offers unique contrast for water diffusion in anisotropic environments.
  • DTI-based tractography is crucial for characterizing structural connectivity in neural tissue.
  • Network theory provides a framework for analyzing complex systems, including neural networks.

Purpose of the Study:

  • To analyze the structural connectivity within the isolated abdominal ganglia (ABG) of Aplysia californica using DTI and network theory.
  • To quantify regional physical properties and inner-community connections within the ABG.
  • To categorize the properties of neural structural networks and derive mean-field information for macroscopic connectivity.

Main Methods:

  • Diffusion tensor imaging (DTI) and DTI-based tractography were employed on Aplysia abdominal ganglia.
  • Network theory metrics including fractional anisotropy, apparent diffusion coefficient, local/global efficiency, characteristic path lengths, and clustering analysis were applied.
  • Weighted clustering coefficients and small-worldness metrics were used to analyze network communication and properties.

Main Results:

  • DTI tractography yielded unweighted, undirected graphs representing community structures within the ABG.
  • Analysis revealed specific small-world properties in the ABG's default structural network.
  • These properties were compared against simulated lattice and random networks of equivalent order and degree.

Conclusions:

  • The Aplysia abdominal ganglia exhibit inherent small-world network properties.
  • DTI and network theory can quantitatively describe macroscopic connectivity in model neural tissues.
  • Findings provide a foundation for understanding neural network organization and deriving mean-field information.