Covarying structural alterations in laterality of the temporal lobe in schizophrenia: A case for source-based laterality.

Journal Article (Journal Article)

The human brain is asymmetrically lateralized for certain functions (such as language processing) to regions in one hemisphere relative to the other. Asymmetries are measured with a laterality index (LI). However, traditional LI measures are limited by a lack of consensus on metrics used for its calculation. To address this limitation, source-based laterality (SBL) leverages an independent component analysis for the identification of laterality-specific alterations, identifying covarying components between hemispheres across subjects. SBL is successfully implemented with simulated data with inherent differences in laterality. SBL is then compared with a voxel-wise analysis utilizing structural data from a sample of patients with schizophrenia and controls without schizophrenia. SBL group comparisons identified three distinct temporal regions and one cerebellar region with significantly altered laterality in patients with schizophrenia relative to controls. Previous work highlights reductions in laterality (ie, reduced left gray matter volume) in patients with schizophrenia compared with controls without schizophrenia. Results from this pilot SBL project are the first, to our knowledge, to identify covarying laterality differences within discrete temporal brain regions. The authors argue SBL provides a unique focus to detect covarying laterality differences in patients with schizophrenia, facilitating the discovery of laterality aspects undetected in previous work.

Full Text

Duke Authors

Cited Authors

  • DeRamus, TP; Silva, RF; Iraji, A; Damaraju, E; Belger, A; Ford, JM; McEwen, SC; Mathalon, DH; Mueller, BA; Pearlson, GD; Potkin, SG; Preda, A; Turner, JA; Vaidya, JG; van Erp, TGM; Calhoun, VD

Published Date

  • June 2020

Published In

Volume / Issue

  • 33 / 6

Start / End Page

  • e4294 -

PubMed ID

  • 32207187

Electronic International Standard Serial Number (EISSN)

  • 1099-1492

Digital Object Identifier (DOI)

  • 10.1002/nbm.4294

Language

  • eng

Conference Location

  • England