Frontiers in Human Neuroscience (Oct 2023)

Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis

  • Tingting Zhu,
  • Tingting Zhu,
  • Zengxiu Wang,
  • Weifeng Wu,
  • Yuru Ling,
  • Zixu Wang,
  • Chao Zhou,
  • Xinyu Fang,
  • Chengbing Huang,
  • Chengbing Huang,
  • Chunming Xie,
  • Jiu Chen,
  • Xiangrong Zhang,
  • Xiangrong Zhang

DOI
https://doi.org/10.3389/fnhum.2023.1204632
Journal volume & issue
Vol. 17

Abstract

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ObjectiveTo investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients.MethodsWe performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls.ResultsSeventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear.ConclusionThis meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).

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