Abstract
It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level-dependent signals was analyzed. A three-way analysis of variance ([Formula: see text]) indicated that the main effect of fNIRS signal depth on the correlation is significant [[Formula: see text], [Formula: see text]]. This result indicates that the MD-ICA method successfully separates fNIRS signals into spatially deep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method.
Highlights
The correlation coefficients of original, deep, and shallow signals versus the laser-Doppler flowmetry (LDF) signal were calculated by the way used in some literature,[38,39,64] whereas Takahashi et al.[29] calculated the temporally integrated LDF signal to compare it with Functional near-infrared spectroscopy (fNIRS) signal because, in principle, the integrated LDF signal may relate more to the fNIRS signal than the direct LDF signal does
While the total-Hb signal is more related to the blood flow signal than oxy- and deoxy-Hb signals in general, oxy- and deoxy-Hb signals were used for the correlation analysis with LDF signals because the present study focused on deep and shallow separation and the contribution ratio depends on Hb types.[38]
The representative positions of each fNIRS channel were determined from the closest point on the brain surface to the midpoint of the source and detector positions
Summary
One of the limitations of fNIRS is the potential effect of the extracerebral tissue on the signal. It was reported that an fNIRS signal can be contaminated by extracerebral signals.[25,26,27,28,29] It has been reported that the regional cerebral oxygen saturation is affected by extracranial contamination.[30,31]. Another issue concerning extracerebral effects is the interference of systemic hemodynamics on fNIRS signals.[32,33] This is
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
