title: The spectral diversity of resting-state fluctuations in the human brain.
abstract: In order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms) and compared to 20 resting-state datasets from standard, high-TR (1800 ms) EPI scans. The spatial distribution of fluctuations in various frequency ranges are analyzed along with the spectra of the time-series in voxels from different regions of interest. Functional connectivity specific to different frequency ranges (<0.1 Hz; 0.1-0.25 Hz; 0.25-0.75 Hz; 0.75-1.4 Hz) was computed for both the low-TR and (for the two lower-frequency ranges) the high-TR datasets using bandpass filters. In the low-TR data, cortical regions exhibited highest contribution of low-frequency fluctuations and the most marked low-frequency peak in the spectrum, while the time courses in subcortical grey matter regions as well as the insula were strongly contaminated by high-frequency signals. White matter and CSF regions had highest contribution of high-frequency fluctuations and a mostly flat power spectrum. In the high-TR data, the basic patterns of the low-TR data can be recognized, but the high-frequency proportions of the signal fluctuations are folded into the low frequency range, thus obfuscating the low-frequency dynamics. Regions with higher proportion of high-frequency oscillations in the low-TR data showed flatter power spectra in the high-TR data due to aliasing of the high-frequency signal components, leading to loss of specificity in the signal from these regions in high-TR data. Functional connectivity analyses showed that there are correlations between resting-state signal fluctuations of distant brain regions even at high frequencies, which can be measured using low-TR fMRI. On the other hand, in the high-TR data, loss of specificity of measured fluctuations leads to lower sensitivity in detecting functional connectivity. This underlines the advantages of low-TR EPI sequences for resting-state and potentially also task-related fMRI experiments.
authors.affiliation: Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Department of Statistics and Probability Theory, Vienna University of Technology, Vienna, Austria.
authors.forename: Klaudius
authors.initials: K
authors.lastname: Kalcher
authors.affiliation: Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Department of Statistics and Probability Theory, Vienna University of Technology, Vienna, Austria.
authors.forename: Roland N
authors.initials: RN
authors.lastname: Boubela
authors.affiliation: Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Department of Statistics and Probability Theory, Vienna University of Technology, Vienna, Austria.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Huf
authors.affiliation: Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
authors.forename: Lucie
authors.initials: L
authors.lastname: Bartova
authors.affiliation: MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Department of Radiodiagnostics and Nuclear Medicine, Medical University of Vienna, Vienna, Austria.
authors.forename: Claudia
authors.initials: C
authors.lastname: Kronnerwetter
authors.affiliation: Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.
authors.forename: Birgit
authors.initials: B
authors.lastname: Derntl
authors.affiliation: Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
authors.forename: Lukas
authors.initials: L
authors.lastname: Pezawas
authors.affiliation: Department of Statistics and Probability Theory, Vienna University of Technology, Vienna, Austria.
authors.forename: Peter
authors.initials: P
authors.lastname: Filzmoser
authors.affiliation: Department of Radiology, Tulln Hospital, Tulln, Austria.
authors.forename: Christian
authors.initials: C
authors.lastname: Nasel
authors.affiliation: Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Brain Behaviour Laboratory, Department of Psychiatry, University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, United States of America.
authors.forename: Ewald
authors.initials: E
authors.lastname: Moser
mesh_terms: D001921:Brain / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D012146:Rest / Q000502:physiology*
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