Spatial and temporal reproducibility-based ranking of the independent components of BOLD fMRI data

Weiming Zeng, Anqi Qiu, Betty Ann Chodkowski, James J. Pekar

Research output: Contribution to journalArticle

Abstract

Independent component analysis (ICA) decomposes fMRI data into spatially independent maps and their corresponding time courses. However, distinguishing the neurobiologically and biophysically reasonable components from those representing noise and artifacts is not trivial. We present a simple method for the ranking of independent components, by assessing the resemblance between components estimated from all the data, and components estimated from only the odd- (or even-) numbered time points. We show that the meaningful independent components of fMRI data resemble independent components estimated from downsampled data, and thus tend to be highly ranked by the method.

Original languageEnglish (US)
Pages (from-to)1041-1054
Number of pages14
JournalNeuroImage
Volume46
Issue number4
DOIs
StatePublished - Jul 15 2009

Keywords

  • Independent component analysis
  • Maximum mean correlation
  • fMRI

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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