title: Examining similarity structure: multidimensional scaling and related approaches in neuroimaging.
abstract: This paper covers similarity analyses, a subset of multivariate pattern analysis techniques that are based on similarity spaces defined by multivariate patterns. These techniques offer several advantages and complement other methods for brain data analyses, as they allow for comparison of representational structure across individuals, brain regions, and data acquisition methods. Particular attention is paid to multidimensional scaling and related approaches that yield spatial representations or provide methods for characterizing individual differences. We highlight unique contributions of these methods by reviewing recent applications to functional magnetic resonance imaging data and emphasize areas of caution in applying and interpreting similarity analysis methods.
authors: Department of Psychology, University of South Carolina, Columbia, SC 29208, USA. shinkareva@sc.edu
authors: Svetlana V
authors: SV
authors: Shinkareva
authors: Jing
authors: J
authors: Wang
authors: Douglas H
authors: DH
authors: Wedell
mesh_terms: D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D001931:Brain Mapping / Q000706:statistics & numerical data; D016000:Cluster Analysis; D019295:Computational Biology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D059906:Neuroimaging / Q000706:statistics & numerical data*; D010363:Pattern Recognition, Automated / Q000706:statistics & numerical data
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