Natalia Yakunina1,2, Eun Kyoung Kang3, Tae Su Kim4,5, Ji-Hoon Min6, Sam Soo Kim2,7, Eui-Cheol Nam8,9. 1. Institute of Medical Science, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea. 2. Neuroscience Research Institute, Kangwon National University Hospital, Chuncheon, Republic of Korea. 3. Department of Rehabilitation Medicine, Kangwon National University Hospital, Chuncheon, Republic of Korea. 4. Department of Otolaryngology, Kangwon National University Hospital, Chuncheon, Republic of Korea. 5. Department of Otolaryngology, Kangwon National University, School of Medicine, Kangwondaehak-gil 1, Chuncheon, 200-701, Republic of Korea. 6. Department of Biopsychology, Cognition, and Neuroscience, University of Michigan, Ann Arbor, MI, USA. 7. Department of Radiology, Kangwon National University, School of Medicine, Chuncheon, Republic of Korea. 8. Neuroscience Research Institute, Kangwon National University Hospital, Chuncheon, Republic of Korea. birdynec@kangwon.ac.kr. 9. Department of Otolaryngology, Kangwon National University, School of Medicine, Kangwondaehak-gil 1, Chuncheon, 200-701, Republic of Korea. birdynec@kangwon.ac.kr.
Abstract
INTRODUCTION: Although the effects of scanner background noise (SBN) during functional magnetic resonance imaging (fMRI) have been extensively investigated for the brain regions involved in auditory processing, its impact on other types of intrinsic brain activity has largely been neglected. The present study evaluated the influence of SBN on a number of intrinsic connectivity networks (ICNs) during auditory stimulation by comparing the results obtained using sparse temporal acquisition (STA) with those using continuous acquisition (CA). METHODS: Fourteen healthy subjects were presented with classical music pieces in a block paradigm during two sessions of STA and CA. A volume-matched CA dataset (CAm) was generated by subsampling the CA dataset to temporally match it with the STA data. Independent component analysis was performed on the concatenated STA-CAm datasets, and voxel data, time courses, power spectra, and functional connectivity were compared. RESULTS: The ICA revealed 19 ICNs; the auditory, default mode, salience, and frontoparietal networks showed greater activity in the STA. The spectral peaks in 17 networks corresponded to the stimulation cycles in the STA, while only five networks displayed this correspondence in the CA. The dorsal default mode and salience networks exhibited stronger correlations with the stimulus waveform in the STA. CONCLUSIONS: SBN appeared to influence not only the areas of auditory response but also the majority of other ICNs, including attention and sensory networks. Therefore, SBN should be regarded as a serious nuisance factor during fMRI studies investigating intrinsic brain activity under external stimulation or task loads.
INTRODUCTION: Although the effects of scanner background noise (SBN) during functional magnetic resonance imaging (fMRI) have been extensively investigated for the brain regions involved in auditory processing, its impact on other types of intrinsic brain activity has largely been neglected. The present study evaluated the influence of SBN on a number of intrinsic connectivity networks (ICNs) during auditory stimulation by comparing the results obtained using sparse temporal acquisition (STA) with those using continuous acquisition (CA). METHODS: Fourteen healthy subjects were presented with classical music pieces in a block paradigm during two sessions of STA and CA. A volume-matched CA dataset (CAm) was generated by subsampling the CA dataset to temporally match it with the STA data. Independent component analysis was performed on the concatenated STA-CAm datasets, and voxel data, time courses, power spectra, and functional connectivity were compared. RESULTS: The ICA revealed 19 ICNs; the auditory, default mode, salience, and frontoparietal networks showed greater activity in the STA. The spectral peaks in 17 networks corresponded to the stimulation cycles in the STA, while only five networks displayed this correspondence in the CA. The dorsal default mode and salience networks exhibited stronger correlations with the stimulus waveform in the STA. CONCLUSIONS:SBN appeared to influence not only the areas of auditory response but also the majority of other ICNs, including attention and sensory networks. Therefore, SBN should be regarded as a serious nuisance factor during fMRI studies investigating intrinsic brain activity under external stimulation or task loads.
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