Characterizing reproducibility of cerebral hemodynamic responses when applying short-channel regression in functional near-infrared spectroscopy

Abstract

. Significance: Functional near-infrared spectroscopy (fNIRS) enables the measurement of brain activity noninvasively. Optical neuroimaging with fNIRS has been shown to be reproducible on the group level and hence is an excellent research tool, but the reproducibility on the single-subject level is still insufficient, challenging the use for clinical applications. Aim: We investigated the effect of short-channel regression (SCR) as an approach to obtain fNIRS measurements with higher reproducibility on a single-subject level. SCR simultaneously considers contributions from long- and short-separation channels and removes confounding physiological changes through the regression of the short-separation channel information. Approach: We performed a test-retest study with a hand grasping task in 15 healthy subjects using a wearable fNIRS device, optoHIVE. Relevant brain regions were localized with transcranial magnetic stimulation to ensure correct placement of the optodes. Reproducibility was assessed by intraclass correlation, correlation analysis, mixed effects modeling, and classification accuracy of the hand grasping task. Further, we characterized the influence of SCR on reproducibility. Results: We found a high reproducibility of fNIRS measurements on a single-subject level ( and correlation ). SCR increased the reproducibility from 0.64 to 0.81 ( ) but did not affect classification (85% overall accuracy). Significant intersubject variability in the reproducibility was observed and was explained by Mayer wave oscillations and low raw signal strength. The raw signal-to-noise ratio (threshold at 40 dB) allowed for distinguishing between persons with weak and strong activations. Conclusions: We report, for the first time, that fNIRS measurements are reproducible on a single-subject level using our optoHIVE fNIRS system and that SCR improves reproducibility. In addition, we give a benchmark to easily assess the ability of a subject to elicit sufficiently strong hemodynamic responses. With these insights, we pave the way for the reliable use of fNIRS neuroimaging in single subjects for neuroscientific research and clinical applications.

Neural Activity During Audiovisual Speech Processing: Protocol For a Functional Neuroimaging Study

“…All study participants must (1) be at least 18 years old, (2) be native German speakers, and (3) have preferably light and thin hair [ 29 , 30 ]. Participants with a severe cardiac, psychiatric, or neurological disease (eg, epilepsy) or brain injury will be excluded from the study (refer to Multimedia Appendix 1 for details).…”

Systemic physiology augmented functional near-infrared spectroscopy: a powerful approach to study the embodied human brain

“…The methods improve the ability to measure changes related to NVC 98 , 118 , 126 – 129 and increase the reproducibility of fNIRS measurements on the single-subject level. 130 …”

“…The methods improve the ability to measure changes related to NVC 98,118,[126][127][128][129] and increase the reproducibility of fNIRS measurements on the single-subject level. 130 A comparison between short-channel regression, and SPA-fNIRS-based regression has been recently published by Abdalmalak et al 99 investigating the impact of both methods on the detection and quantification of functional resting-state brain networks. The authors concluded that both approaches are useful and necessary to detect the functional networks and that short-channels and systemic physiological signals "provided complementary information that could not be obtained by either regressor separately."…”

Using preregistration as a tool for transparent fNIRS study design

“…So far, the most accurate way of removing the extracerebral part of such artifacts is by using the hardware-based solution: shortdistance channels (SDCs). SDCs are generated by placing the source and detector at a distance of < 1 cm, and ideally at ~0.8 cm for adults 72 , to capture the hemodynamic activity from extracerebral tissue only 33,100,[114][115][116][117][118] . SDC signals can be used for correcting the regular distance channels, for instance, by applying a regression-based approach.…”