title: A 12-step user guide for analyzing voxel-wise gray matter asymmetries in statistical parametric mapping (SPM).
abstract: Voxel-based morphometry (VBM) has been proven capable of capturing cerebral gray matter asymmetries with a high (voxel-wise) regional specificity. However, a standardized reference on how to conduct voxel-wise asymmetry analyses is missing. This protocol provides the scientific community with a carefully developed guide describing, in 12 distinct steps, how to take structural images from data pre-processing, via statistical analysis, to the final interpretation of the significance maps. Key adaptations compared with the standard VBM workflow involve establishing a voxel-wise hemispheric correspondence, capturing the direction and degree of asymmetry and preventing a blurring of information across hemispheres. The workflow incorporates the most recent methodological developments, including high-dimensional spatial normalization and partial volume estimations. Although the protocol is primarily designed to enable relatively inexperienced users to conduct a voxel-based asymmetry analysis on their own, it may also be useful to experienced users who wish to efficiently adapt their existing scripts or pipelines.
authors.affiliation: Department of Neurology, University of California, Los Angeles (UCLA) School of Medicine, Los Angeles, California, USA.
authors.forename: Florian
authors.initials: F
authors.lastname: Kurth
authors.affiliation: 1] Department of Psychiatry, Jena University Hospital, Jena, Germany. [2] Department of Neurology, Jena University Hospital, Jena, Germany.
authors.forename: Christian
authors.initials: C
authors.lastname: Gaser
authors.affiliation: Department of Neurology, University of California, Los Angeles (UCLA) School of Medicine, Los Angeles, California, USA.
authors.forename: Eileen
authors.initials: E
authors.lastname: Luders
mesh_terms: D001931:Brain Mapping / Q000379:methods*; D066128:Gray Matter / Q000033:anatomy & histology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008432:Mathematical Computing; D057188:Workflow