Brain Imaging and Behavior

, Volume 9, Issue 1, pp 115–127 | Cite as

One dataset, many conclusions: BOLD variability’s complicated relationships with age and motion artifacts

  • Benjamin O. Turner
  • Brian Lopez
  • Tyler Santander
  • Michael B. Miller
SI: Developing Brain

Abstract

In recent years, the variability of the blood-oxygen level dependent (BOLD) signal has received attention as an informative measure in its own right. At the same time, there has been growing concern regarding the impact of motion in fMRI, particularly in the domain of resting state studies. Here, we demonstrate that, not only does motion (among other confounds) exert an influence on the results of a BOLD variability analysis of task-related fMRI data—but, that the exact method used to deal with this influence has at least as large an effect as the motion itself. This sensitivity to relatively minor methodological changes is particularly concerning as studies begin to take on a more applied bent, and the risk of mischaracterizing the relationship between BOLD variability and various individual difference variables (for instance, disease progression) acquires real-world relevance.

Keywords

Individual differences Correlation analysis FMRI analysis methods Confound correction 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Benjamin O. Turner
    • 1
  • Brian Lopez
    • 1
  • Tyler Santander
    • 1
  • Michael B. Miller
    • 1
  1. 1.Department of Psychological and Brain SciencesUniversity of California Santa BarbaraSanta BarbaraUSA

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