Selective detrending method for reducing task-correlated motion artifact during speech in event-related FMRI

Kaundinya Gopinath, Bruce Crosson, Keith McGregor, Kyung Peck, Yu Ling Chang, Anna Moore, Megan Sherod, Christy Cavanagh, Ashley Wabnitz, Christina Wierenga, Keith White, Sergey Cheshkov, Venkatagiri Krishnamurthy, Richard W. Briggs

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Task-correlated motion artifacts that occur during functional magnetic resonance imaging can be mistaken for brain activity. In this work, a new selective detrending method for reduction of artifacts associated with task-correlated motion (TCM) during speech in event-related functional magnetic resonance imaging is introduced and demonstrated in an overt word generation paradigm. The performance of this new method is compared with that of three existing methods for reducing artifacts because of TCM: (1) motion parameter regression, (2) ignoring images during speech, and (3) detrending time course datasets of signal components related to TCM (deduced from artifact corrupted voxels). The selective detrending method outperforms the other three methods in reducing TCM artifacts and in retaining blood oxygenation level dependent signal.

Original languageEnglish (US)
Pages (from-to)1105-1119
Number of pages15
JournalHuman Brain Mapping
Volume30
Issue number4
DOIs
Publication statusPublished - Apr 2009

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Keywords

  • Artifact reduction
  • FMRI
  • Image processing
  • Speech
  • Task-correlated motion
  • Word-generation

ASJC Scopus subject areas

  • Clinical Neurology
  • Anatomy
  • Neurology
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Gopinath, K., Crosson, B., McGregor, K., Peck, K., Chang, Y. L., Moore, A., ... Briggs, R. W. (2009). Selective detrending method for reducing task-correlated motion artifact during speech in event-related FMRI. Human Brain Mapping, 30(4), 1105-1119. https://doi.org/10.1002/hbm.20572