Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data

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Twenty years of functional near-infrared spectroscopy: introduction for the special issue (2014, background): “Brigadoi et al. (2014) explore the utility of variousmotion correction algorithms for facilitating the analysis of data otherwise lost to motion artifacts.”
Temporal Derivative Distribution Repair (TDDR): A motion correction method for fNIRS (2018, unknown): “This interpretation is supported by previous studies generally finding CBSI performance similar to or less than other methods in real data (Brigadoi et al., 2014; Hu et al., 2015; Jahani et al., 2018).”
Current Status and Issues Regarding Pre-processing of fNIRS Neuroimaging Data: An Investigation of Diverse Signal Filtering Methods Within a General Linear Model Framework (2019, methodology): “Several techniques have been proposed so far and have been reviewed elsewhere (Brigadoi et al., 2014).”