It has been reported that resting state fluctuation amplitude (RSFA) exhibits extremely large inter-site variability, which limits its application in multisite studies. Although global normalization (GN) based approaches are efficient in reducing the site effects, they may cause spurious results. In this study, our purpose was to find alternative strategies to minimize the substantial site effects for RSFA, without the risk of introducing artificial findings. We firstly modified the ALFF algorithm so that it is conceptually validated and insensitive to data length, then found that (a) global mean amplitude of low-frequency fluctuation (ALFF) covaried only with BOLD signal intensity, while global mean fractional ALFF (fALFF) was significantly correlated with TRs across different sites; (b) The inter-site variations in raw RSFA values were significant across the entire brain and exhibited similar trends between gray matter and white matter; (c) For ALFF, signal intensity rescaling could dramatically reduce inter-site variability by several orders, but could not fully removed the globally distributed inter-site variability. For fALFF, the global site effects could be completely removed by TR controlling; (d) Meanwhile, the magnitude of the inter-site variability of fALFF could also be reduced to an acceptable level, as indicated by the detection power of fALFF in multisite data quite close to that in monosite data. Thus our findings suggest GN based harmonization methods could be replaced with only controlling for confounding factors including signal scaling, TR and full-band power.

据报道，静止状态波动幅度（RSFA）表现出极大的站点间变异性，这限制了其在多站点研究中的应用。尽管基于全局归一化（GN）的方法可有效减少站点影响，但它们可能会导致虚假结果。在这项研究中，我们的目的是找到替代策略，以最大程度地减少RSFA的实质性站点影响，而不会引入人为发现的风险。我们首先修改了ALFF算法，使其在概念上经过验证并且对数据长度不敏感，然后发现（a）低频波动（ALFF）的全局平均幅度仅与BOLD信号强度协变量，而全局平均分数ALFF（fALFF）与不同站点的TR显着相关；（b）在整个大脑中，原始RSFA值的站点间差异很大，并且在灰质和白质之间表现出相似的趋势；（c）对于ALFF，信号强度的缩放可以将站点间的可变性大幅度降低几个数量级，但不能完全消除全局分布的站点间的可变性。对于fALFF，可以通过TR控制完全消除全局站点影响；（d）同时，如多站点数据中fALFF的检测能力非常接近单站点数据中的fALFF的检测能力所表明的那样，fALFF的站点间变异性的幅度也可以降低到可接受的水平。因此，我们的发现表明，仅通过控制包括信号缩放，TR和全频带功率在内的混杂因素，就可以取代基于GN的协调方法。