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The amplitude of low-frequency fluctuation (ALFF) measures resting-state functional magnetic resonance imaging (RS-fMRI) signal of each voxel. However, the unit of blood oxygenation level-dependent (BOLD) signal is arbitrary and hence ALFF is sensitive to the scale of raw signal. A well-accepted standardization procedure is to divide each voxel's ALFF by the global mean ALFF, named mALFF. Although fractional ALFF (fALFF), a ratio of the ALFF to the total amplitude within the full frequency band, offers possible solution of the standardization, it actually mixes with the fluctuation power within the full frequency band and thus cannot reveal the true amplitude characteristics of a given frequency band. The current study borrowed the percent signal change in task fMRI studies and proposed percent amplitude of fluctuation (PerAF) for RS-fMRI. We firstly applied PerAF and mPerAF (i.e., divided by global mean PerAF) to eyes open (EO) vs. eyes closed (EC) RS-fMRI data. PerAF and mPerAF yielded prominently difference between EO and EC, being well consistent with previous studies. We secondly performed test-retest reliability analysis and found that (PerAF � mPerAF � mALFF) > (fALFF � mfALFF). Head motion regression (Friston-24) increased the reliability of PerAF, but decreased all other metrics (e.g. mPerAF, mALFF, fALFF, and mfALFF). The above results suggest that mPerAF is a valid, more reliable, more straightforward, and hence a promising metric for voxel-level RS-fMRI studies. Future study could use both PerAF and mPerAF metrics. For prompting future application of PerAF, we implemented PerAF in a new version of REST package named RESTplus. OPEN ACCESS Citation: Jia X-Z, Sun J-W, Ji G-J, Liao W, Lv Y-T, Wang J, et al. (2020) Percent amplitude of fluctuation: A simple measure for resting-state fMRI signal at single voxel level. PLoS ONE 15(1): e0227021. https://doi.org/10.synchronization of the BOLD signals between any pair of brain regions, FC analysis cannot directly measure the regional spontaneous brain activity of a specific voxel per se. Another widely used RS-fMRI measurement, ALFF [2], can be adopted on this purpose, as it provides direct characterization of the spontaneous brain activity at each voxel. However, since BOLD signal has arbitrary units, ALFF is sensitive to the scale of the raw BOLD signal and cannot be directly applied to subsequent group-level statistical analysis.An approach to deal with such a scaling effect is to normalize the raw amplitude value by the global mean amplitude, i.e., the averaged amplitude value across all voxels in the brain [2][3][4]. However, such manipulation assumes that the BOLD signal of all voxels has the same scaling value. In fact, many factors affect the scaling value, including spatial inhomogeneity, brain tissue composition, and brain lesions. Standardization at single voxel level may be helpful to reduce such effects.Another voxel-level metric, namely fractional ALFF (fALFF), had been proposed to normalize ALFF [5]. The fALFF is a ratio of the ALFF within a spec...

As the multi-center studies with resting-state functional magnetic resonance imaging (RS-fMRI) have been more and more applied to neuropsychiatric studies, both intra- and inter-scanner reliability of RS-fMRI are becoming increasingly important. The amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) are 3 main RS-fMRI metrics in a way of voxel-wise whole-brain (VWWB) analysis. Although the intra-scanner reliability (i.e., test-retest reliability) of these metrics has been widely investigated, few studies has investigated their inter-scanner reliability. In the current study, 21 healthy young subjects were enrolled and scanned with blood oxygenation level dependent (BOLD) RS-fMRI in 3 visits (V1 – V3), with V1 and V2 scanned on a GE MR750 scanner and V3 on a Siemens Prisma. RS-fMRI data were collected under two conditions, eyes open (EO) and eyes closed (EC), each lasting 8 minutes. We firstly evaluated the intra- and inter-scanner reliability of ALFF, ReHo, and DC. Secondly, we measured systematic difference between two scanning visits of the same scanner as well as between two scanners. Thirdly, to account for the potential difference of intra- and inter-scanner local magnetic field inhomogeneity, we measured the difference of relative BOLD signal intensity to the mean BOLD signal intensity of the whole brain between each pair of visits. Last, we used percent amplitude of fluctuation (PerAF) to correct the difference induced by relative BOLD signal intensity. The inter-scanner reliability was much worse than intra-scanner reliability; Among the VWWB metrics, DC showed the worst (both for intra-scanner and inter-scanner comparisons). PerAF showed similar intra-scanner reliability with ALFF and the best reliability among all the 4 metrics. PerAF reduced the influence of BOLD signal intensity and hence increase the inter-scanner reliability of ALFF. For multi-center studies, inter-scanner reliability should be taken into account.

Aims To explore the potential relationships among gut microbiota (GM), local brain spontaneous activity, and neuropsychological characteristics in amnestic mild cognitive impairment (aMCI) patients. Methods Twenty aMCI and 22 healthy control (HC) subjects were recruited. The GM composition was determined by 16S ribosomal RNA gene sequencing. Resting‐state functional magnetic resonance imaging scans were performed, and fractional amplitude of low‐frequency fluctuations (fALFF) was calculated across different frequencies. The Spearman or Pearson correlation analysis was used to analyze the relationship between spontaneous brain activity and cognitive function, and GM composition. Results aMCI patients had altered GM state and local spontaneous brain activity as compared with HC subjects. Correlation analysis showed that aMCI and HC groups had different “GM‐intrinsic brain activity interaction” patterns. In aMCI group, at the typical band (0.01‐0.08 Hz), the relative abundance (RA) of Bacteroides from phylum to genus level was negatively correlated with fALFF value of cerebellar vermis IV‐V, and the Ruminococcaceae RA was negatively correlated with fALFF values of left lenticular nucleus and pallidum. The Clostridiaceae RA and Blautia RA were positively correlated with the left cerebellum lobules IV‐V at the slow‐4 band (0.027‐0.073 Hz). The Veillonellaceae RA was positively correlated with fALFF values of left precentral gyrus at the slow‐5 band (0.073‐0.08 Hz). Correlation analysis showed that Clostridium members (Lachnospiraceae and Blautia) were positively, while Veillonellaceae was negatively, correlated with cognition test. Bacteroides was positively correlated with attention and computation, and negatively correlated with the three‐stage command score. Conclusions aMCI patients have a specific GM‐intrinsic brain activity‐cognitive function interaction pattern.

There is limited amplitude of low-frequency fluctuation (ALFF) of resting-state functional magnetic resonance imaging (fMRI) studies in late-onset depression (LOD) but reported different results. This may be due to the impact of different frequency bands. In this study, we examined the ALFF in five different frequency bands (slow-6: 0–0.01 Hz; slow-5: 0.01–0.027 Hz; slow-4: 0.027–0.073 Hz; slow-3: 0.073–0.167 Hz, and slow-2: 0.167–0.25 Hz) within the whole brain during resting-state fMRI in 16 LOD patients and 16 normal control (NC) subjects. The ALFF of primary effect of disease was widely distributed over left cerebellum anterior lobe, left cerebellum posterior lobe, left middle orbitofrontal gyrus, left superior occipital, and right superior parietal, while the interaction effect of disease and frequency was distributed over right superior frontal gyrus. Further relationship analysis findings suggest these abnormal ALFF may relate to cognitive dysfunction of LOD. Therefore, our data show that LOD patients have widespread abnormalities in intrinsic brain activity, which is dependent on the frequency band, and suggest that future studies should take the frequency bands into account when measuring intrinsic brain activity.