Percent amplitude of fluctuation: A simple measure for resting-state fMRI signal at single voxel level

Autoři: Xi-Ze Jia aff001;  Jia-Wei Sun aff003;  Gong-Jun Ji aff001;  Wei Liao aff001;  Ya-Ting Lv aff001;  Jue Wang aff001;  Ze Wang aff001;  Han Zhang aff001;  Dong-Qiang Liu aff001;  Yu-Feng Zang aff001
Působiště autorů: Center for Cognition and Brain Disorders, Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China aff001;  Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China aff002;  School of Information and Electronics Technology, Jiamusi University, Jiamusi, Heilongjiang, China aff003;  Department of Medical Psychology, Chaohu Clinical Medical College, Anhui Medical University, Hefei, China aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0227021


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.

Klíčová slova:

Simulation and modeling – Functional magnetic resonance imaging – Neuroimaging – Central nervous system – Eyes – Research validity – Preprocessing – Auditory cortex


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