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Negative functional brain networks.

Fabrizio Parente1, Marianna Frascarelli2, Alessia Mirigliani2

  • 1Department of Anatomy, Histology, Forensic Medicine and Orthopaedics, Sapienza University of Rome, Via A. Borelli 50, 00161, Rome, Italy. fabrizio.parente@uniroma1.it.

Brain Imaging and Behavior
|March 30, 2017
PubMed
Summary
This summary is machine-generated.

Functional brain networks with negative connections exhibit unique topological features, differing from random networks. These negative networks show altered connectivity patterns in schizophrenia, suggesting a role in the disorder.

Keywords:
Anticorrelated networksFunctional connectivityNetwork analysisResting stateSchizophrenia

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Area of Science:

  • Neuroimaging
  • Network Neuroscience
  • Psychiatry

Background:

  • Anticorrelations in functional magnetic resonance imaging (fMRI) are not fully understood but may have physiological significance.
  • Exploring negative functional brain networks offers insights into brain organization and potential alterations in neurological disorders.

Purpose of the Study:

  • To investigate the topology of functional brain networks characterized by negative edges.
  • To compare these networks in healthy subjects and individuals with schizophrenia.
  • To assess the impact of preprocessing methods (CompCorr vs. Global Signal Regression) on network analysis.

Main Methods:

  • Analysis of resting-state fMRI data from 8 healthy controls and 8 schizophrenic patients.
  • Characterization of functional brain networks using degree distribution, centrality, efficiency, and rich-club analysis.
  • Comparison of network properties between preprocessing methods and diagnostic groups.

Main Results:

  • Functional brain networks, including those with negative edges, display a truncated power-law degree distribution.
  • Negative edge networks exhibit disassortative properties (highly connected nodes link to fewer nodes), which are lost with Global Signal Regression.
  • Schizophrenia patients show decreased local and global efficiency and reduced connectivity among central nodes in negative networks.

Conclusions:

  • Functional brain networks with negative values possess distinct, non-random topological features.
  • These negative networks are implicated in the neurobiological alterations observed in schizophrenia.
  • Preprocessing choices significantly influence the characterization of negative functional brain networks.