RESTplus: an improved toolkit for resting-state functional magnetic resonance imaging data processing

Jia, Xize; Wang, Jue; Sun, Hao; Zhang, Han; Liao, Wei; Wang, Ze; Chen, Yan; Song, Xiaowei; Zang, Yu‐Feng

doi:10.1016/j.scib.2019.05.008

Cited by 230 publications

(174 citation statements)

References 11 publications

(14 reference statements)

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“…To facilitate future applications, we implemented PerAF in a new version of REST package [27] named RESTplus [28] which based on Statistical Parametric Mapping (SPM) [29]. From http://www.restfmri.net, the most recent version of RESTplus can be downloaded.…”

Section: Implementation and Usage Of Peraf Calculation Toolkitmentioning

confidence: 99%

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

et al. 2020

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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...

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Section: Implementation and Usage Of Peraf Calculation Toolkitmentioning

confidence: 99%

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

et al. 2020

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“…The rsfMRI data were processed using SPM12 1 and RESTplus (Jia et al, 2019) 2 . The first 10 time points were discarded as adaptation of the participant to the scanner noise.…”

Section: Rsfmri Preprocessingmentioning

confidence: 99%

“…Then, the resulting spatial fALFF maps were then divided with each voxel divided by the wholebrain fALFF mean (mfALFF), providing mfALFF spatial maps (Zou et al, 2008). PerAF designated the percentage amplitude of BOLD fluctuation relative to the mean BOLD signal intensity of a given time series (Jia et al, 2017) with RESTplus (Jia et al, 2019). PerAF is standardized at the single voxel level, the resulting spatial PerAF maps were then normalized with each voxel divided by the global mean PerAF (mPerAF).…”

Section: Static Alff Fractional Alff (Falff) Percent Amplitude Of Fmentioning

confidence: 99%

“…PerAF is standardized at the single voxel level, the resulting spatial PerAF maps were then normalized with each voxel divided by the global mean PerAF (mPerAF). Both PerAF and mPerAF can be used for group-level statistical analysis, here we used mPerAF for further statistical analyses (Jia et al, 2019;Yu et al, 2019). For ReHo, the Kendall's coefficient of concordance (KCC) of the time course of every 27 nearest neighboring voxels was calculated (Zang et al, 2004).…”

Section: Static Alff Fractional Alff (Falff) Percent Amplitude Of Fmentioning

confidence: 99%

“…Blood oxygenation level-dependent (BOLD) resting-state functional MRI (rsfMRI), has attracted enormous research interest in studying the neural mechanisms of cognitive dysfunction in individuals with psychiatric disorders (Biswal, 2012). Various rsfMRI measures such as functional connectivity (FC) (Biswal et al, 1995), amplitude of low-frequency fluctuation (ALFF) (Zang et al, 2007) fractional ALFF (fALFF) (Zou et al, 2008), percent amplitude of fluctuation (PerAF) (Jia et al, 2017(Jia et al, , 2019 regional homogeneity (ReHo) (Zang et al, 2004) and degree centrality (DC) (Zuo et al, 2012) have been used to describe the intrinsic brain activity (IBA). IBA involves dynamic neural and metabolic activities, it is activity and plays a pivotal role in brain function (Dai and He, 2014;Raichle, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Depression Affects Intrinsic Brain Activity in Patients With Mild Cognitive Impairment

Lin

et al. 2019

Front. Neurosci.

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Numerous observational studies have shown that depressive symptoms are common in individuals with mild cognitive impairment (MCI) who have a higher rate of progress to dementia. However, it is still uncertain whether there are any differences between MCI patients with and without depression symptom in their brain function activities. Here we have identified the brain function activity differences in two groups of MCI patients (with depression or without depression) using the resting state MRI (rsfMRI) measurements. 76 right-handed MCI subjects have been recruited in this study, including 27 MCI patients with depression symptom (MCID), 49 MCI patients without depression symptom (MCIND). Analyses based on 7 rsfMRI measurements, including four static measurements (ALFF, fALFF, PerAF, and ReHo) and three dynamic measurements (dALFF, dfALFF, and dReHo) have been used to explore the temporal variability of intrinsic brain activity. No significant differences in ALFF and dALFF between the two group were found. In the MCID group, fALFF decreased in temporal gyrus, frontal gyrus, inferior occipital gyrus, middle frontal gyrus and cerebellum, but increased in cuneus, calcarine, lingual; while PerAF increased in left parahippocampus. The differences of ReHo in the two groups was only found in cerebellum. Compared to MCIND group, dfALFF in MCID decreased in cuneus, occipital gyrus and calcarine, while dReHo in MCID increased in bilateral temporal gyrus, frontal gyrus, superior parietal gyrus, inferior parietal gyrus and precuneus. Our results may provide a better understanding in the relationship between the depressive symptoms and memory deficits.

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Abnormal intrinsic functional hubs and connectivity in patients with post‐stroke depression

Wu,

Xu,

et al. 2024

Ann Clin Transl Neurol

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ObjectiveThe present study aimed to investigate the specific alterations of brain networks in patients with post‐stroke depression (PSD), and further assist in elucidating the brain mechanisms underlying the PSD which would provide supporting evidence for early diagnosis and interventions for the disease.MethodsResting‐state functional magnetic resonace imaging data were acquired from 82 nondepressed stroke patients (Stroke), 39 PSD patients, and 74 healthy controls (HC). Voxel‐wise degree centrality (DC) conjoined with seed‐based functional connectivity (FC) analyses were performed to investigate the PSD‐related connectivity alterations. The relationship between these alterations and depression severity was further examined in PSD patients.ResultsRelative to both Stroke and HC groups, (1) PSD showed increased centrality in regions within the default mode network (DMN), including contralesional angular gyrus (ANG), posterior cingulate cortex (PCC), and hippocampus (HIP). DC values in contralesional ANG positively correlated with the Patient Health Questionnaire‐9 (PHQ‐9) scores in PSD group. (2) PSD exhibited increased connectivity between these three seeds showing altered DC and regions within the DMN: bilateral medial prefrontal cortex and middle temporal gyrus and ipsilesional superior parietal gyrus, and regions outside the DMN: bilateral calcarine, ipsilesional inferior occipital gyrus and contralesional lingual gyrus, while decreased connectivity between contralesional ANG and contralesional supramarginal gyrus. Moreover, these FC alterations could predict PHQ‐9 scores in PSD group.InterpretationThese findings highlight that PSD was related with increased functional connectivity strength in some areas within the DMN, which might be attribute to the specific alterations of connectivity between within DMN and outside DMN regions in PSD.

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RESTplus: an improved toolkit for resting-state functional magnetic resonance imaging data processing

Cited by 230 publications

References 11 publications

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

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

Depression Affects Intrinsic Brain Activity in Patients With Mild Cognitive Impairment

Abnormal intrinsic functional hubs and connectivity in patients with post‐stroke depression

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