Selective detrending method for reducing task-correlated motion artifact during speech in event-related FMRI
✍ Scribed by Kaundinya Gopinath; Bruce Crosson; Keith McGregor; Kyung K. Peck; Yu-Ling Chang; Anna Moore; Megan Sherod; Christy Cavanagh; Ashley Wabnitz; Christina Wierenga; Keith White; Sergey Cheshkov; Venkatagiri Krishnamurthy; Richard W. Briggs
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 488 KB
- Volume
- 30
- Category
- Article
- ISSN
- 1065-9471
No coin nor oath required. For personal study only.
✦ Synopsis
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. Hum Brain Mapp 2009. © 2008 Wiley‐Liss, Inc.