School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada.
J Neurosci Methods. 2020 Jan 15;330:108519. doi: 10.1016/j.jneumeth.2019.108519. Epub 2019 Nov 13.
It has been suggested that the use of window functions, other than the rectangular, in the sliding window method, may be beneficial for reducing the effects of motion-related outliers in the time-series, when assessing dynamic functional connectivity (dFC) in resting-state fMRI (rs-fMRI).
Ten window functions for a wide range of window lengths (20-150 s) combined with Pearson and Kendall correlation metrics, were investigated. One hundred high quality rs-fMRI datasets from healthy controls, were used to systematically assess the effect of varying the window function and length on dFC assessment. To this end, two approaches were implemented: a) simulated outliers were added to the experimental data and b) the experimental data were divided into low and high motion subgroups.
The presence of experimental motion-noise tended to inflate the number of dynamic connections for longer (≥100 s) wide-shaped windows, while shorter (20-30 s) narrow-shaped windows exhibited increased sensitivity in the presence of simulated outliers. Moreover, window sizes from 60 s to 90 s were mildly affected by motion-related effects. In most cases, the number of dynamic connections increased, and gradually lower frequencies were captured, with an increasing window size.
Subject motion considerably affects the obtained dFC patterns; thus, it is preferable to perform motion artefact removal in the pre-processing stage rather than using alternative window functions to mitigate their effects. Provided that motion-noise is not excessive, the choice of a rectangular window is adequate. Finally, low frequency oscillations in functional connectivity seem to play an important role in the context of dFC assessment.
在滑动窗口方法中，使用矩形以外的窗口函数可能有助于减少时间序列中与运动相关的离群值对动态功能连接(dFC)评估的影响，这一点已经得到了证实。
研究了十种窗口函数，涵盖了广泛的窗口长度（20-150 秒），并结合了 Pearson 和 Kendall 相关系数。使用一百个高质量的健康对照者的 rs-fMRI 数据集，系统地评估了改变窗口函数和长度对 dFC 评估的影响。为此，实施了两种方法：a）向实验数据中添加模拟离群值，b）将实验数据分为低运动和高运动子组。
实验性运动噪声的存在往往会增加较长（≥100 秒）宽窗的动态连接数量，而较短（20-30 秒）窄窗在存在模拟离群值时表现出更高的敏感性。此外，60-90 秒的窗口大小受与运动相关的影响较小。在大多数情况下，随着窗口大小的增加，动态连接的数量增加，并且逐渐捕获到更低的频率。
受试者运动对获得的 dFC 模式有很大影响；因此，最好在预处理阶段进行运动伪影去除，而不是使用替代窗口函数来减轻其影响。如果运动噪声不过量，则选择矩形窗口就足够了。最后，功能连接中的低频振荡在 dFC 评估中似乎起着重要作用。
