title: Meta-analysis of gray matter anomalies in schizophrenia: application of anatomic likelihood estimation and network analysis.
abstract: BACKGROUND
  Although structural neuroimaging methods have been widely used to study brain morphology in schizophrenia, synthesizing this literature has been difficult. With the increasing popularity of voxel-based morphometric (VBM) methods in which group differences are reported in standardized coordinates, it is possible to apply powerful meta-analytic techniques initially designed for functional neuroimaging. In this study, we performed a voxelwise, coordinate-based meta-analysis to better conceptualize the neuroanatomic correlates of schizophrenia.
  
  
  METHODS
  Thirty-one peer-reviewed articles, with a total of 1195 patients with schizophrenia contrasted with 1262 healthy volunteers, were included in the meta-analysis. Coordinates from each article were used to create a statistical map that estimated the likelihood of between-group gray matter density differences at every brain voxel. These results were subsequently entered into a network analysis.
  
  
  RESULTS
  Patients had reduced gray matter density relative to control subjects in a distributed network of regions, including bilateral insular cortex, anterior cingulate, left parahippocampal gyrus, left middle frontal gyrus, postcentral gyrus, and thalamus. Network analysis grouped these regions into four distinct networks that potentially represent different pathologic processes. Patients had increased gray matter density in striatal regions.
  
  
  CONCLUSIONS
  This study expands on previous meta-analyses of the neuroanatomy of schizophrenia by elucidating a series of brain networks disrupted by the illness. Because it is possible that these networks are influenced by independent etiologic factors, this work should foster more detailed neural models of the illness and focus research designed to discover the mechanisms of gray matter reduction in schizophrenia.
authors.affiliation: Department of Psychiatry, University of Texas Health Science Center, San Antonio, Texas 78229-3900, USA. glahn@uthscsa.edu
authors.forename: David C
authors.initials: DC
authors.lastname: Glahn
authors.forename: Angela R
authors.initials: AR
authors.lastname: Laird
authors.forename: Ian
authors.initials: I
authors.lastname: Ellison-Wright
authors.forename: Sarah M
authors.initials: SM
authors.lastname: Thelen
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Robinson
authors.forename: Jack L
authors.initials: JL
authors.lastname: Lancaster
authors.forename: Edward
authors.initials: E
authors.lastname: Bullmore
authors.forename: Peter T
authors.initials: PT
authors.lastname: Fox
mesh_terms: D001921:Brain / Q000473:pathology*; D001931:Brain Mapping; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016013:Likelihood Functions; D008279:Magnetic Resonance Imaging; D015201:Meta-Analysis as Topic; D009434:Neural Pathways / Q000473:pathology; D009457:Neuroglia / Q000473:pathology*; D012559:Schizophrenia / Q000453:epidemiology / Q000473:pathology*