Abnormal brain connectivity in first-episode psychosis: A diffusion MRI tractography study of the corpus callosum

Gary Price, Mara Cercignani, Geoffrey J M Parker, Daniel R. Altmann, Thomas R E Barnes, Gareth J. Barker, Eileen M. Joyce, Maria A. Ron

Research output: Contribution to journalArticlepeer-review


A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the clinical manifestations of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail and we present here a study of patients with first-episode psychosis using this technique. We selected the corpus callosum for this study because there is evidence that it is abnormal in schizophrenia. In addition, the topographical organization of its fibers makes it possible to relate focal abnormalities to specific cortical regions. Eighteen patients with first-episode psychosis and 21 healthy subjects took part in the study. A probabilistic tractography algorithm (PICo) was used to study fractional anisotropy (FA). Seed regions were placed in the genu and splenium to track fiber tracts traversing these regions, and a multi-threshold approach to study the probability of connection was used. Multiple linear regressions were used to explore group differences. FA, a measure of tract coherence, was reduced in tracts crossing the genu, and to a lesser degree the splenium, in patients compared with controls. FA was also lower in the genu in females across both groups, but there was no gender-by-group interaction. The FA reduction in patients may be due to aberrant myelination or axonal abnormalities, but the similar tract volumes in the two groups suggest that severe axonal loss is unlikely at this stage of the illness.

Original languageEnglish
Pages (from-to)458-466
Number of pages9
Issue number2
Publication statusPublished - Apr 1 2007


  • Corpus callosum
  • Diffusion tensor imaging
  • First-episode psychosis
  • Tractography

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology


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