Abstract
Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05–0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.
Highlights
Functional near-infrared spectroscopy is a noninvasive functional neuroimaging technique that can monitor concentration changes in oxygenated and deoxygenated hemoglobin (HbO and HbR) in the cerebral cortex. functional near-infrared spectroscopy (fNIRS) measurement is based on the absorption of light in near-infrared spectrum from 700 to 1000 nm by biological tissues
While Experiment 1 focused on the stationary properties of fNIRS and EEG, we further evaluated whether the epochby-epoch fluctuations in fNIRS global signal and EEG vigilance are associated in Experiment 2
Considering that individuals exhibited different levels of vigilance fluctuations, we examined whether the standard derivation of EEG vigilance modulated the association between EEG vigilance measures and fNIRS global signal; yet the analysis showed that the scale of vigilance fluctuation levels was not relevant (p > 0.1)
Summary
Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional neuroimaging technique that can monitor concentration changes in oxygenated and deoxygenated hemoglobin (HbO and HbR) in the cerebral cortex. fNIRS measurement is based on the absorption of light in near-infrared spectrum from 700 to 1000 nm by biological tissues. FNIRS measurement is based on the absorption of light in near-infrared spectrum from 700 to 1000 nm by biological tissues. Different chromophores, such as hemoglobin, myoglobin, and cytochrome aa, have different absorptivity (Sood et al, 2015). With the advantage of low-cost, portability, and ease to co-register with other neural recording modalities, such as an EEG and fNIRS has become an attractive means for imaging and monitoring hemodynamic signals in the human brain, which complements the use of fMRI in versatile environment. Imaging of resting-state functional connectivity (RSFC) in the human brain has been a recent focus for neuroimaging studies, including fNIRS (Mohammadi-Nejad et al, 2018; Pinti et al, 2018). Evidences show that a neural component (Scholvinck et al, 2010; Wong et al, 2013, 2016) and even diagnostic information (Hahamy et al, 2014; Murphy and Fox, 2017; Yang et al, 2017) exist in the global signal, which challenges the assumption of removing it in the first place
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