This study investigates the coupling strength between low-frequency peripheral and cerebral hemodynamics among young, healthy volunteers, with concurrent acquisition of peripheral NIRS, brain fMRI, and EEG across wake and NREM sleep. The results document a strong positive coupling between low-frequency peripheral and cerebral hemodynamics during all stages except deep sleep (NREM3). Collectively, our results demonstrate that systemic physiology remains a dominant source of variability in brain hemodynamics both during resting wakefulness and light NREM sleep. However, deep NREM3 sleep may be an exception to this phenomenon implicative of its noteworthy role in optimal restoration of cerebral vasomotion.
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
The application of functional near-infrared spectroscopy (fNIRS) in the neurosciences has been expanding over the last 40 years. Today, it is addressing a wide range of applications within different populations and utilizes a great variety of experimental paradigms. With the rapid growth and the diversification of research methods, some inconsistencies are appearing in the way in which methods are presented, which can make the interpretation and replication of studies unnecessarily challenging. The Society for Functional Near-Infrared Spectroscopy has thus been motivated to organize a representative (but not exhaustive) group of leaders in the field to build a consensus on the best practices for describing the methods utilized in fNIRS studies.
Our paper has been designed to provide guidelines to help enhance the reliability, repeatability, and traceability of reported fNIRS studies and encourage best practices throughout the community. A checklist is provided to guide authors in the preparation of their manuscripts and to assist reviewers when evaluating fNIRS papers.
Significance: Low-frequency oscillations (LFOs) ranging from 0.01 to 0.15 Hz are common in functional imaging studies. Some of these LFOs are non-neuronal and are correlated with autonomic physiological processes.
Aim: We investigate the relationships between systemic low-frequency oscillations (sLFOs) measured at different peripheral sites during resting states in ischemic stroke patients.
Approach: Twenty-seven ischemic stroke patients (ages 44 to 90; 20 male and 7 female) were recruited for the study. During the experiments, fluctuations in oxyhemoglobin concentration were measured in the left and right toes, fingertips, and earlobes using a multichannel near-infrared spectroscopy instrument. We applied cross-correlation and frequency component analyses on the sLFO data.
Results: The results showed that embolization broke the symmetry of the sLFO transmission and that the damage was not limited to the local area but spread throughout the body. Among six peripheral sites, the power spectrum width of the earlobes was significantly larger than that of the fingers and toes. This indicates that the earlobes may contain more physiological information. Finally, the results of fuzzy clustering verified that sLFOs can serve as perfusion biomarkers to differentiate stroke from healthy subjects.
Conclusions: The high correlation values and corresponding delays in sLFOs support the hypothesis that (1) the correlation characteristics of sLFOs in stroke patients are different from those of healthy subjects. These characteristics can reflect patient condition, to an extent. Embolization in ischemic stroke patients breaks the symmetry of the body’s sLFO transmission, disrupting the balance of blood circulation. (2) sLFOs can be used as perfusion biomarkers to differentiate ischemic stroke patients from healthy subjects. Studying these signals can explicate the overall feedback/influence of pericentral interactions. Finally, peripheral sLFOs have been shown to be an effective and accurate tool for assessing peripheral blood circulation and vascular integrity in ischemic stroke patients.
Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional imaging technique measuring hemodynamic changes including oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin. Low frequency (LF; 0.01 to 0.15 Hz) band is commonly analyzed in fNIRS to represent neuronal activation. However, systemic physiological artifacts (i.e., nonneuronal) likely occur also in overlapping frequency bands. We measured peripheral photoplethysmogram (PPG) signal concurrently with fNIRS (at prefrontal region) to extract the low-frequency oscillations (LFOs) as systemic noise regressors. We investigated three main points in this study: (1) the relationship between prefrontal fNIRS and peripheral PPG signals; (2) the denoising potential using these peripheral LFOs, and (3) the innovative ways to avoid the false-positive result in fNIRS studies. We employed spatial working memory (WM) and control tasks (e.g., resting state) to illustrate these points. Our results showed: (1) correlation between signals from prefrontal fNIRS and peripheral PPG is region-dependent. The high correlation with peripheral ear signal (i.e., O2Hb) occurred mainly in frontopolar regions in both spatial WM and control tasks. This may indicate the finding of task-dependent effect even in peripheral signals. We also found that the PPG recording at the ear has a high correlation with prefrontal fNIRS signal than the finger signals. (2) The systemic noise was reduced by 25% to 34% on average across regions, with a maximum of 39% to 58% in the highly correlated frontopolar region, by using these peripheral LFOs as noise regressors. (3) By performing the control tasks, we confirmed that the statistically significant activation was observed in the spatial WM task, not in the controls. This suggested that systemic (and any other) noises unlikely violated the major statistical inference. (4) Lastly, by denoising using the task-related signals, the significant activation of region-of-interest was still observed suggesting the manifest task-evoked response in the spatial WM task.
This study investigated the relationships of systemic low-frequency oscillations (sLFOs) measured at different peripheral sites in resting state, during passive leg raising (PLR), and during a paced breathing (PB) test. Twenty-five healthy subjects (21 to 57 years old; males: 13 and females: 12) were recruited for these experiments. During the experiments, the fluctuations of oxyhemoglobin concentration were measured at six peripheral sites (left and right toes, fingertips, and earlobes) using a multichannel near-infrared spectroscopy instrument developed by our group. We applied cross-correlation and frequency component analyses on the data. The results showed that the sLFO signals in the symmetric peripheral sites were highly correlated, with time delays close to zero, whereas the correlation coefficients decreased between the sLFO signals of asymmetric sites, with delays up to several seconds. Furthermore, in PLR/PB tests, we found that PB caused wider and more robust changes in hemoglobin concentrations at peripheral sites compared to PLR. Among six peripheral sites, earlobes were the most sensitive to these perturbations, followed by fingertips, and then toes. Lastly, we showed that the perturbation signals may have different coupling mechanisms than the sLFO signals. The study deepened our understanding of the sLFO signals and establishes baseline measures for developing perfusion biomarkers to assess peripheral vascular integrity.
Monitoring the changes of cerebral hemodynamics and the state of consciousness during general anesthesia (GA) is clinically important. There is a great need for developing advanced detectors to investigate the physiological processes of the brain during GA. We developed a multichanneled, functional near-infrared spectroscopy (fNIRS) system device and applied it to GA operation monitoring. The cerebral hemodynamic data from the forehead of 11 patients undergoing propofol and sevoflurane anesthesia were analyzed. The concentration changes of oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin, and cerebral tissue heart rate were determined from the raw optical information based on the discrete stationary wavelet transform. This custom-made device provides an easy-to-build solution for continuous wave-fNIRS system, with customized specifications. The developed device has a potential value in cerebral monitoring in clinical settings.
KEYWORDS: Functional magnetic resonance imaging, Sensors, Signal to noise ratio, Head, Magnetic resonance imaging, Near infrared spectroscopy, Spatial resolution, Temporal resolution, Data acquisition, 3D printing
Functional near-infrared spectroscopy (fNIRS) is an increasingly important noninvasive method in neuroscience due to its high temporal resolution and ability to independently measure oxy- and deoxy-hemoglobin. However, the relatively low spatial resolution of fNIRS makes it difficult to relate this signal to underlying anatomy. Simultaneous functional magnetic resonance imaging (fMRI) can complement fNIRS with superior spatial resolution and the ability to image the entire brain, providing additional information to improve fNIRS localization. However, current simultaneous fMRI/fNIRS acquisition methods are not optimal, due to the poor physical compatibility of existing MR coils and fNIRS optodes. Here, we present a technique to manufacture a true multimodal fMRI/fNIRS probe in which both modalities can be used with maximal sensitivity. To achieve this, we designed custom MR coils with integral fNIRS optodes using three-dimensional printing. This multimodal probe can be used to optimize spatial (1.2×1.2×1.8 mm) and temporal resolution (2.5 Hz) of fMRI, and it provides maximal MRI sensitivity, while allowing for high flexibility in the location and density of fNIRS optodes within the area of interest. Phantom and human data are shown to confirm the improvement in sensitivity in both modalities. This probe shows promise for addressing fundamental questions of the relation of fNIRS to physiology.
Low-frequency oscillations (LFOs) in the range of 0.01-0.15 Hz are commonly observed in functional imaging studies, such as blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) and functional near-infrared spectroscopy (fNIRS). Some of these LFOs are nonneuronal and are closely related to autonomic physiological processes. In the current study, we conducted a concurrent resting-state fMRI and NIRS experiment with healthy volunteers. LFO data was collected simultaneously at peripheral sites (middle fingertip and big toes) by NIRS, and centrally in the brain by BOLD fMRI. The cross-correlations of the LFOs collected from the finger, toes, and brain were calculated. Our data show that the LFOs measured in the periphery (NIRS signals) and in the brain (BOLD fMRI) were strongly correlated with varying time delays. This demonstrates that some portion of the LFOs actually reflect systemic physiological circulatory effects. Furthermore, we demonstrated that NIRS is effective for measuring the peripheral LFOs, and that these LFOs and the temporal shifts between them are consistent in healthy participants and may serve as useful biomarkers for detecting and monitoring circulatory dysfunction.
Physiological fluctuations at low frequency (<0.1 Hz) are prominent in functional near-infrared spectroscopy (fNIRS) measurements in both resting state and functional task studies. In this study, we used the high spatial resolution and full brain coverage of functional magnetic resonance imaging (fMRI) to understand the origins and commonalities of these fluctuations. Specifically, we applied a newly developed method, regressor interpolation at progressive time delays, to analyze concurrently recorded fNIRS and fMRI data acquired both in a resting state study and in a finger tapping study. The method calculates the voxelwise correlations between blood oxygen level dependent (BOLD) fMRI and fNIRS signals with different time shifts and localizes the areas in the brain that highly correlate with the fNIRS signal recorded at the surface of the head. The results show the wide spatial distribution of this physiological fluctuation in BOLD data, both in task and resting states. The brain areas that are highly correlated with global physiological fluctuations observed by fNIRS have a pattern that resembles the venous system of the brain, indicating the blood fluctuation from veins on the brain surface might strongly contribute to the overall fNIRS signal.
Cerebrovascular reactivity (CVR) reflects the compensatory dilatory capacity of cerebral vasculature to a dilatory
stimulus and is an important indicator of brain vascular reserve. fMRI has been proven to be an effective imaging
technique to obtain the CVR map when the subjects perform CO2 inhalation or the breath holding task (BH). However,
the traditional data analysis inaccurately models the BOLD using a boxcar function with fixed time delay. We propose a
novel way to process the fMRI data obtained during a blocked BH by using the simultaneously collected near infrared
spectroscopy (NIRS) data as regressor1. In this concurrent NIRS and fMRI study, 6 healthy subjects performed a blocked
BH (5 breath holds with 20s durations intermitted by 40s of regular breathing). A NIRS probe of two sources and two
detectors separated by 3 cm was placed on the right side of prefrontal area of the subjects. The time course of changes in
oxy-hemoglobin (Δ[HbO]) was calculated from NIRS data and shifted in time by various amounts, and resampled to the
fMRI acquisition rate. Each shifted time course was used as regressor in FEAT (the analysis tool in FSL). The resulting
z-statistic maps were concatenated in time and the maximal value was taken along the time for all the voxels to generate
a 3-D CVR map. The new method produces more accurate and thorough CVR maps; moreover, it enables us to produce
a comparable baseline cerebral vascular map if applied to resting state (RS) data.
We show some limitations of the standard t test when used together with typical data processing methods in functional Near Infrared Spectroscopy of the brain to assess the significance of multiple correlated points. We studied the occurrence of errors type I (that is the occurrence of false positive points) when typical processing methods are applied to time series of normal random numbers and to time series of simulated baseline systemic fluctuations. Since the results of the two studies are very similar we concluded that normal random numbers can be used to assess the occurrence of error type I due to certain algorithms of data processing. In order to decrease the occurrence of false positive points we propose to use some modified stepwise Bonferroni procedures, among which we studied the performance of Dubey/Armitage-Parmar algorithm. The results of the algorithm are shown for both simulated and experimental data.
We propose a new method for BOLD signal calculation that is more meaningful for comparison with NIRS data. We
provide evidence that BOLD signal can be highly localized within the region of activation not only in terms of the
amplitude of activation but also for the nuances of the temporal trend. Therefore, in order to take into account of the
spatial dependence of BOLD signal we propose to introduce a weighting function given by a photon hitting density
function calculated for a given optical source-detector pair. In one case study, after we define this new method of BOLD
calculation and extract a BOLD trend for each optical source-detector pairs we show that there is an high correlation
between this BOLD signal and the changes of oxy and deoxy hemoglobin calculated at the same source-detector pair;
however the correlation becomes poorer when the newly defined BOLD signal is compared with the changes of oxy and
deoxy hemoglobin occurring in different channels. This results is consistent with the fact that for this experiment (which
used a 3T MRI machine) the BOLD and NIRS signals were sensitive to changes occurring in the same locations and in
similar vascular compartments.
Complex neuronal structures and interactions make studying fast optical signals associated with brain activation
difficult, especially in non-invasive measurements that are further complicated by the filtering effect of the scalp and
skull. We have chosen to study fast optical signals in the peripheral nervous system to look at a more simplified
biological neuronal structure and a system that is more accessible to non-invasive optical studies. In this study, we
recorded spatially resolved electrical and optical responses of the human sural nerve to electrical stimulation. A 0.1 ms
electrical stimulation was used to activate the sural nerve. Electrical signals were collected by an electromyogram
machine and results showed an electrical response spanning a distance of 8 mm across the nerve. Optical signals were
collected by a two-wavelength (690 and 830 nm) near-infrared spectrometer and displayed a characteristic decrease in
intensity at both wavelengths. Data were taken at multiple positions and then reproduced five times. The average optical
data over the five trials showed an optical signal that was spatially consistent with the electrical response to sural nerve
stimulation.
We present a study of the near-infrared optical response to electrical stimulation of peripheral nerves. The sural nerve of six healthy subjects between the ages of 22 and 41 was stimulated with transcutaneous electrical pulses in a region located approximately 10 cm above the ankle. A two-wavelength (690 and 830 nm) tissue spectrometer was used to probe the same sural nerve below the ankle. We measured optical changes that peaked 60 to 160 ms after the electrical stimulus. On the basis of the strong wavelength dependence of these fast optical signals, we argue that their origin is mostly from absorption rather than scattering. From these absorption changes, we obtain oxy- and deoxy-hemoglobin concentration changes that describe a rapid hemodynamic response to electrical nerve activation. In five out of six subjects, this hemodynamic response is an increase in total (oxy+deoxy) hemoglobin concentration, consistent with a fast vasodilation. Our findings support the hypothesis that the peripheral nervous system undergoes neurovascular coupling, even though more data is needed to prove such hypothesis.
We present a new method for the calculation of a blood oxygen level dependent (BOLD) signal which is meaningful for
a quantitative comparison with near infrared spectroscopy (NIRS) data. Since optical tomography of the human brain
still poses several difficulties, in this study we propose a way to project the BOLD signal on a two-dimensional (2D)
map for comparison with NIRS data. The underlying assumption is that fMRI and NIRS are sensitive to similar aspects
of the hemodynamic changes occurring during a functional task, and therefore they should have similar spatial and
temporal features. We present a case study of functional activation during a finger-tapping test where we used the new
method for the calculation of BOLD signal. For every optical source-detector pair we calculated a weighted BOLD
signal by using a photon hitting-density weight function, and by using a simple back-projection algorithm we were able
to generate BOLD 2D maps. We found that the weighted BOLD signals calculated from different source-detector pairs
scale in a similar way to the corresponding oxy and deoxy-hemeoglobin concentration changes calculated from NIRS
data, for most of the time range of the task. Therefore the BOLD 2D maps were quantitatively similar to the optical maps
calculated at different times during the protocol.
Near-infrared spectroscopy (NIRS) has been used for functional brain imaging by employing properly designed source-detector matrices. We demonstrate that by embedding a NIRS source-detector matrix within an electroencephalography (EEG) standard multi-channel cap, we can perform functional brain mapping of hemodynamic response and neuronal response simultaneously. In this study, the P300 endogenous evoked response was generated in human subjects using an auditory odd-ball paradigm while concurrently monitoring the hemodynamic response both spatially and temporally with NIRS. The electrical measurements showed the localization of evoked potential P300, which appeared around 320 ms after the odd-ball stimulus. The NIRS measurements demonstrate a hemodynamic change in the fronto-temporal cortex a few seconds after the appearance of P300.
We present concurrent NIRS-fMRI measurements on a human subject during a finger tapping test. The optical data were collected with a frequency domain experimental apparatus (ISS, Inc., Champaign IL) comprising sixteen laser sources at 690 nm, sixteen laser sources at 830 nm and four photomultiplier tube detectors. The lasers were coupled to optical fibers that led the light onto the subject's head. A special optical helmet (fMRI-compatible) with a retractable and resilient set of optical fibers was devised to improve the coupling between the fibers and the scalp. The fMRI data were collected with a 3 Tesla Siemens Trio magnetic resonance scanner and a quadrature birdcage radiofrequency coil. The spatial and temporal comparison of the fMRI and NIRS signals associated with brain activation showed a very good agreement, confirming the role of NIRS as a reliable brain monitor for functional studies.
Comparison of the spatial and temporal information retrieved from near-infrared phase and average intensity (DC) data reveals that these data types can play a complementary role in the study of the temporal and spatial features of the optical response associated with brain activation during a finger-tapping test. The optical data have been collected with a frequency-domain tissue imager at two wavelengths (690 and 830 nm) and have been analyzed using standard filtering and folding-average procedures. DC and phase data show different temporal and spatial features. A plausible explanation of the different behavior of DC and phase data has been attempted by using Monte Carlo simulations.
We present a new method of fluorescence imaging, which yields nm-scale axial height determination and ~15 nm axial resolution. The method uses the unique spectral signature of the fluorescent emission intensity well above a reflecting surface to determine vertical position unambiguously. We have demonstrated axial height determination with nm sensitivity by resolving the height difference of fluorescein directly on the surface or on top of streptavidin. While different positions of fluorophores of different color are determined independently with nm precision, resolving the position of two fluorophores of the same color is a more convoluted problem due to the finite spectral emission widow of the fluorophores. Hence, for physically close (<λ/2) fluorophores, it is necessary to collect multiple spectra by independently scanning an excitation standing wave in order to deconvolute the contribution to the spectral pattern from different heights. Moving the excitation standing wave successively enhances or suppresses excitation from different parts of the height distribution, changing the spectral content. This way two fluorophores of the same color can be resolved to better than 20 nm. Design aspects of the dielectric stack for independent excitation wave scanning and limits of deconvolution for an arbitrary height distribution will be discussed.
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