False fMRI activation after motion correction

Hum Brain Mapp. 2017 Sep;38(9):4497-4510. doi: 10.1002/hbm.23677. Epub 2017 Jun 5.

Abstract

Motion correction of echo-planar imaging (EPI) data used in functional MRI (fMRI) is an essential preprocessing step performed prior to statistical analysis. At ultra-high resolution fMRI, current requirements regarding translational and rotational motion may no longer be acceptable. This prompts the need for a systematic investigation of the effects of motion correction procedures with in vivo fMRI data. Here we systematically evaluated the effect of retrospective motion correction with freely available fMRI analysis software packages (FSL, AFNI, and SPM) on activation maps using fMRI data acquired with prospective motion detection, to identify and quantify confounding effects of retrospective motion correction, and to evaluate its dependence on spatial resolution and motion correction algorithms. Brain activation maps were obtained for two different resolutions, an ultrahigh, that is, 0.653 mm3 , and a more widely used 2.03 mm3 isotropic resolutions at 7 T. The EPI data were acquired using simultaneous non-image-based optical moiré phase tracking (MPT) of physical motion. The results showed that image-based motion detection, performed by SPM8 software package, may be erroneous in high-field fMRI data with partial brain coverage and can introduce spurious motion leading to false-positive and false-negative activation. Further analyses demonstrated that limited acquisition field of view has the dominant influence on the effect. Hum Brain Mapp 38:4497-4510, 2017. © 2017 Wiley Periodicals, Inc.

Keywords: EPI; artifacts; fMRI; motion correction; prospective motion correction.

Publication types

  • Evaluation Study

MeSH terms

  • Adult
  • Artifacts*
  • Brain / diagnostic imaging
  • Brain / physiology
  • Brain Mapping / methods
  • Female
  • Head Movements
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Male
  • Motion*
  • Software*
  • Visual Perception / physiology