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Making Sense of Connectivity.

Andreas Hahn1, Rupert Lanzenberger1, Siegfried Kasper1

  • 1Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria.

The International Journal of Neuropsychopharmacology
|December 14, 2018
PubMed
Summary

Brain connectivity analysis using neuroimaging reveals network alterations in neurological and psychiatric disorders. Future research focuses on multimodal imaging and biomarkers for improved clinical interpretation.

Keywords:
connectivitydiffusion tensor imaginggraph theorynetworkpositron emission tomographyresting-state fMRI

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Systems Biology

Background:

  • Investigating brain networks complements local region analysis in neuroimaging.
  • Connectivity analysis examines interactions and information transfer between brain regions.
  • Approaches include structural, functional, and molecular connectivity.

Purpose of the Study:

  • To provide an overview of brain connectivity analysis techniques.
  • To discuss interpretations, limitations, and applications in pharmacological imaging and clinical settings.
  • To highlight advancements in understanding brain networks in disease.

Main Methods:

  • Diffusion MRI for structural connectivity (neuronal fiber tracts).
  • Analysis of signal time course correlations for functional connectivity.
  • Positron Emission Tomography (PET) for molecular connectivity (metabolic demands, neurotransmitter systems).

Main Results:

  • Connectivity analysis reveals novel network-level alterations in neurological and psychiatric disorders.
  • Structural, functional, and molecular connectivity provide complementary insights into brain interactions.
  • Neuroimaging techniques enable assessment across different granularities, from specific regions to the whole brain.

Conclusions:

  • Connectivity analysis offers valuable insights into brain function and dysfunction in disease.
  • Combined assessment of multiple imaging modalities and development of robust biomarkers are crucial for clinical application.
  • Future advancements will enhance the biological interpretation of human brain connectivity metrics and networks.