Voxel-based lesion symptom mapping (VLSM) techniques have been important in elucidating structure-function relationships in the human brain. Rorden, Karnath & Bonilha (2007b) introduced the nonparametric Brunner-Munzel rank order test as an alternative to parametric tests often used in VLSM analyses. However, the Brunner-Munzel statistic produces inflated z scores when used at any voxel where there are less than ten subjects in either the lesion or no lesion groups. Unfortunately, a number of recently published VLSM studies using this statistic include relatively small patient populations, such that most (if not all) examined voxels do not meet the necessary criteria. We demonstrate the effects of inappropriate usage of the Brunner-Munzel test using a dataset included with MRIcron, and find large Type I errors. To correct for this we suggest that researchers use a permutation-derived correction as implemented in current versions of MRIcron when using the Brunner-Munzel test.
Keywordsvoxel-based lesion symptom mapping; VLSM; brain-lesion mapping; lesion; voxel; structurefunction Much of our understanding of brain function is based on observations of the consequences of brain injury. By examining the consequences of brain disruption, one can identify whether a brain region is required to perform a task, providing a stronger inference than afforded by measures of brain function such as functional imaging that identify regions involved in but not necessarily crucial to a task. Bates and colleagues (2003) introduced voxel-based lesion symptom mapping (VLSM), an update of a method for structure-function mapping that has been widely used for over a century. As its name suggests, the method considers the statistical relationship between behavior and the structural integrity of the brain, on a voxel-by-voxel basis. This technique can extend traditional lesion analysis by identifying novel brain areas (rather than being restricted to predefined regions of interest).The original work of Bates and colleagues was based on the parametric t-test, which makes a number of assumptions regarding the distribution of the behavioral data. Rorden, Karnath & Bonilha (2007b) introduced analyses using non-parametric statistics that do not make such assumptions. As the distribution of behavioral scores from brain-damaged subjects are often Corresponding address: Jared Medina, 3 West Gates, 3400 Spruce Street, University of Pennsylvania, Philadelphia, PA 19104, Phone: 215-614-0274, Fax: 215-349-8260, jared.medina@uphs.upenn.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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