| Literature DB >> 18465746 |
Kaundinya Gopinath1, 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.
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. 2008 Wiley-Liss, Inc.Mesh:
Substances:
Year: 2009 PMID: 18465746 PMCID: PMC3010868 DOI: 10.1002/hbm.20572
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.038