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Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
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NetBat: A network-driven harmonization method for structural connectivity.

Gustav R Sjobeck1, Mahbaneh Eshaghzadeh Torbati1, Davneet S Minhas1

  • 1University of Pittsburgh, Department of Psychiatry, United States of America.

Neuroimage
|June 25, 2025
PubMed
Summary
This summary is machine-generated.

Neuroimaging data harmonization is crucial for removing scanner effects. A new method, NetBat, improves accuracy and preserves brain network structure better than existing techniques.

Keywords:
Multi-scan studiesNetwork harmonizationStructural connectivity

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Network Science

Background:

  • Multi-site neuroimaging data aggregation is increasing.
  • Harmonization, the removal of scanner effects, is vital for data consistency.
  • Existing methods like ComBat and CovBat do not fully account for brain network structure.

Purpose of the Study:

  • To introduce NetBat, a novel harmonization method for neuroimaging data.
  • To integrate network parameters from the weighted stochastic block model (WSBM) into ComBat.
  • To improve the modeling of true underlying brain networks in structural connectivity studies.

Main Methods:

  • Developed NetBat by incorporating WSBM network parameters as covariates into the ComBat harmonization method.
  • Applied NetBat to analyze structural connectivity data from eighteen neurotypical individuals.
  • Each individual underwent MRI scanning on four different scanners to assess harmonization effects.

Main Results:

  • NetBat demonstrated more accurate overall harmonization compared to existing methods.
  • The proposed method showed superior retention of brain network structure.
  • Results indicate NetBat's effectiveness under the tested experimental conditions.

Conclusions:

  • NetBat offers an improved approach to neuroimaging data harmonization.
  • The method effectively preserves crucial brain network properties.
  • NetBat is a promising tool for researchers studying structural connectivity across multiple sites.