Statistical Tests and Inferences

A. L. Shelton, A. S. Greenberg

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Brain imaging techniques have increased in popularity and complexity in recent years. Assessing statistical significance in the face of increasingly large and intricate data sets has become a challenging task. In this article we discuss neuroimaging analysis techniques, with a focus on functional MRI, posed as a problem of massive data reduction. Standard preprocessing steps are outlined in detail along with common methods for modeling data at both the individual subject and group level. Various issues regarding display/communication of neuroimaging data are considered, including choice of statistical threshold, corrections for multiple comparisons, and region-of-interest analyses. Closing remarks briefly highlight other techniques used to make inferences about brain activity.

Original languageEnglish (US)
Title of host publicationEncyclopedia of Neuroscience
PublisherElsevier Ltd
Pages393-400
Number of pages8
ISBN (Print)9780080450469
DOIs
StatePublished - Jan 1 2009

Keywords

  • BOLD
  • Beta weight
  • Bonferroni
  • Coregistration
  • Deconvolution
  • Design matrix
  • Event-related average
  • FMRI
  • Gaussian random field theory
  • General linear model
  • Hemodynamic response function (HRF)
  • Magnetic resonance imagine
  • Multiple regression
  • Neuroimaging
  • Region of interest
  • Regressor
  • Resel
  • Signal-to-noise ratio
  • Smoothing kernel
  • Statistical threshold
  • Time series
  • Voxel

ASJC Scopus subject areas

  • Neuroscience(all)

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  • Cite this

    Shelton, A. L., & Greenberg, A. S. (2009). Statistical Tests and Inferences. In Encyclopedia of Neuroscience (pp. 393-400). Elsevier Ltd. https://doi.org/10.1016/B978-008045046-9.00331-4