An exact statistical method for comparing topographic maps, with any number of subjects and electrodes
 Walt Karniski M.D.,
 R. Clifford Blair,
 Arthur David Snider
 … show all 3 hide
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Statistical methods for testing differences between neural images (e.g., PET, MRI or EEG maps) are problematic because they require (1) an untenable assumption of data sphericity and (2) a high subject to electrode ratio. We propose and demonstrate an exact and distributionfree method of significance testing which avoids the sphericity assumption and may be computed for any combination of electrode and subject numbers. While this procedure is rigorously rooted in permutation test theory, it is intuitively comprehensible. The sensitivity of the permutation test to graded changes in dipole location for systematically varying levels of signal/noise ratio, intersubject variability and number of subjects was demonstrated through a simulation of 70 different conditions, generating 5,000 different data sets for each condition. Data sets were simulated from a homogenous singleshell dipole model. For noise levels commonly encountered in evoked potential studies and for situations where the number of subjects was less than the number of electrodes, the permutation test was very sensitive to a change in dipole location of less than 0.75 cm. This method is especially sensitive to localized changes that would be “washedout‘ by more traditional methods of analysis. It is superior to all previous methods of statistical analysis for comparing topographical maps, because the test is exact, there is no assumption of a multivariate normal distribution or of the correlation structure of the data requiring correction, the test can be tailored to the specific experimental hypotheses rather than allowing the statistical tests to limit the experimental design, and there is no limitation on the number of electrodes that can be simultaneously analyzed.
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 Title
 An exact statistical method for comparing topographic maps, with any number of subjects and electrodes
 Journal

Brain Topography
Volume 6, Issue 3 , pp 203210
 Cover Date
 19940301
 DOI
 10.1007/BF01187710
 Print ISSN
 08960267
 Online ISSN
 15736792
 Publisher
 Kluwer Academic PublishersHuman Sciences Press
 Additional Links
 Topics
 Keywords

 Brain Topography
 Statistics
 Evoked Potentials
 Electroencephalography (EEG)
 Positron Emission Tomography (PET)
 Magnetic Resonance Imaging (MRI)
 Industry Sectors
 Authors

 Walt Karniski M.D. ^{(1)}
 R. Clifford Blair ^{(1)}
 Arthur David Snider ^{(3)}
 Author Affiliations

 1. College of Medicine, University of South Florida, Tampa, Florida, USA
 3. College of Engineering, University of South Florida, Tampa, Florida, USA