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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.
Highlights
From the first identification of intrinsic fluctuations in fMRI signal in the resting brain, these have been consistently described as low-frequency fluctuations in the range of 0.01 to 0.1 Hz [1,2,3]
The main differences in the spatial distribution of the fractional amplitudes of different frequency bands are between cerebrospinal fluid (CSF), white matter and grey matter (see figure 1 (a))
In the frequency range under consideration there was still a moderately high proportion of the fluctuation amplitude in the grey matter, and about the same amount in white matter and CSF as in the lowest frequency range
Summary
From the first identification of intrinsic fluctuations in fMRI signal in the resting brain, these have been consistently described as low-frequency fluctuations in the range of 0.01 to 0.1 Hz [1,2,3]. The physiological reason is the delay and temporal smoothing introduced by the hemodynamic response, which neuronal activation is subject to before being detectable by fMRI This delay is in the range of 3 to 10 seconds [5,6], and it follows that BOLD signal changes due to neuronal events filtered by the hemodynamic response function are to be found in a frequency range below about 0.15 Hz. From a technical point of view, faster scanning has been possible for a long time only under rather restricted circumstances, for example when using a limited brain coverage like a single slice. There were indications that resting-state network fluctuations could be identified in higher frequencies than 0.1 Hz [10,11]
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