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Lookup NU author(s): Dr Simon Baumann
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In the functional imaging of auditory cortical functions, long silent periods between the data acquisitions prevent interferences between scanner noise and the auditory stimulus processing. Recent fMRI studies have shown that sparse temporal acquisition designs are advantageous over continuous scanning protocols on physiological, perceptual, and cognitive levels. Sparse temporal acquisition schemes (STA) which use a single volume acquisition after each trial imply the advantage of auditory stimulation devoid of ambient scanner noise but have the drawback of a reduced statistical power. To alleviate this effect, STA schemes have been extended to clustered-sparse temporal acquisition (CTA) designs which record several subsequent BOLD contrast images in rapid succession. In the present study, we collected data from 13 healthy volunteers performing a speech and a tonal discrimination task using both a CTA and STA scheme to carry out a systematic evaluation of these acquisition protocols. By statistical modeling of the fMRI data sets, we revealed stronger effect sizes for the STA protocol regardless of the task, reflecting the better signal-to-noise-ratio of MR images acquired with this scheme. In contrast, we demonstrate higher statistical power for the use of a CTA protocol. Accordingly, in the context of standard fMRI analysis, the CTA protocol clearly outperformed the STA scheme at the level of single-subject analysis and fixed-effects group analysis. Our results clearly suggest that it is advantageous to acquire several sample points per trial if one wants to use the benefit of "silent" fMRI. Furthermore, our data demonstrate the feasibility of the clustered acquisition of subsequent imaging volumes along the T1-decay. © 2007 Elsevier Inc. All rights reserved.
Author(s): Zaehle T, Schmidt CF, Meyer M, Baumann S, Baltes C, Boesiger P, Jancke L
Publication type: Article
Publication status: Published
Journal: NeuroImage
Year: 2007
Volume: 37
Issue: 4
Pages: 1195-1204
ISSN (print): 1053-8119
ISSN (electronic): 1095-9572
Publisher: Academic Press
URL: http://dx.doi.org/10.1016/j.neuroimage.2007.04.073
DOI: 10.1016/j.neuroimage.2007.04.073
PubMed id: 17644001
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