Effect of scanner acoustic background noise on strict resting-state fMRI

Effect of scanner acoustic background noise on strict resting-state fMRI

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Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a ‘resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise...

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Bibliographic Details
Main Authors: C. Rondinoni, E. Amaro Jr, F. Cendes, A.C.dos Santos, C.E.G. Salmon
Format: Article
Language:English
Published: Associação Brasileira de Divulgação Científica 2013-12-01
Series:Brazilian Journal of Medical and Biological Research
Subjects:
Resting-state fMRI
Acoustic noise
Default-mode network
Independent component analysis
Granger causality mapping
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2013000400359
Description
Summary:Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a ‘resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced “silent” pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.
ISSN:0100-879X
1414-431X

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