An important preprocessing step in fNIRS data analysis is the signal quality check of the raw signal for each channel. The noise in fNIRS signal may originate either from the measurement system (e.g., due to light source instability, electronic noise, and shot noise), which we call merely “noise,” or of physiological origin or head/body motion which we call “confounding signals” throughout the paper.
The fNIRS signal quality check on noise can be tested either by a simple SNR check or by obtaining cardiac power at each channel using spectral analysis. When the sampling rate is reasonably high (e.g., 10 Hz), the heartbeat is a good indicator of optode-scalp coupling and thus a good quality control metric for the fNIRS signal. The Methods section may thus include an indication of the SNR threshold (e.g., ) and cardiac power threshold56 utilized to reject data channels from further analysis. As it is likely that different measurement channels will fail the criteria for different participants, one should also report the number of participants remaining for each channel to avoid any misinterpretation of the results.
Especially in fNIRS, due to the various types of confounding signals and noise, it is important to be aware of the conceptual differences between the metrics SNR, CNR, and contrast-to-background ratio (CBR) and to use these terms unambiguously. The term SNR should be used to quantify the signal quality of an instrument’s fNIRS channel. It is calculated from the measured raw light intensity within a fixed time window and is expressed as , where corresponds to the signal’s intensity offset (dc component) and corresponds to the signal’s variance (ac component). Contrast metrics (CBR/CNR) are used when the strength of an extracted hemodynamic response is to be related to background confounding signals or measurement noise and thus depend on the specific preprocessing of the signal. For more details on these metrics, refer to Ref. 57.
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