Understanding the spatial and depth sensitivity of non-invasive near-infrared spectroscopy (NIRS) measurements to brain tissue-i.e., near-infrared neuromonitoring (NIN) - is essential for designing ...experiments as well as interpreting research findings. However, a thorough characterization of such sensitivity in realistic head models has remained unavailable. In this study, we conducted 3,555 Monte Carlo (MC) simulations to densely cover the scalp of a well-characterized, adult male template brain (Colin27). We sought to evaluate: (i) the spatial sensitivity profile of NIRS to brain tissue as a function of source-detector separation, (ii) the NIRS sensitivity to brain tissue as a function of depth in this realistic and complex head model, and (iii) the effect of NIRS instrument sensitivity on detecting brain activation. We found that increasing the source-detector (SD) separation from 20 to 65 mm provides monotonic increases in sensitivity to brain tissue. For every 10 mm increase in SD separation (up to ~45 mm), sensitivity to gray matter increased an additional 4%. Our analyses also demonstrate that sensitivity in depth (S) decreases exponentially, with a "rule-of-thumb" formula S=0.75*0.85(depth). Thus, while the depth sensitivity of NIRS is not strictly limited, NIN signals in adult humans are strongly biased towards the outermost 10-15 mm of intracranial space. These general results, along with the detailed quantitation of sensitivity estimates around the head, can provide detailed guidance for interpreting the likely sources of NIRS signals, as well as help NIRS investigators design and plan better NIRS experiments, head probes and instruments.
Near-infrared neuromonitoring (NIN) is based on near-infrared spectroscopy (NIRS) measurements performed through the intact scalp and skull. Despite the important effects of overlying tissue layers ...on the measurement of brain hemodynamics, the influence of scalp and skull on NIN sensitivity are not well characterized. Using 3555 Monte Carlo simulations, we estimated the sensitivity of individual continuous-wave NIRS measurements to brain activity over the entire adult human head by introducing a small absorption perturbation to brain gray matter and quantifying the influence of scalp and skull thickness on this sensitivity. After segmenting the Colin27 template into five tissue types (scalp, skull, cerebrospinal fluid, gray matter and white matter), the average scalp thickness was 6.9±3.6mm (range: 3.6–11.2mm), while the average skull thickness was 6.0±1.9mm (range: 2.5–10.5mm). Mean NIN sensitivity – defined as the partial path length through gray matter divided by the total photon path length – ranged from 0.06 (i.e., 6% of total path length) at a 20mm source–detector separation, to over 0.19 at 50mm separations. NIN sensitivity varied substantially around the head, with occipital pole exhibiting the highest NIRS sensitivity to gray matter, whereas inferior frontal regions had the lowest sensitivity. Increased scalp and skull thickness were strongly associated with decreased sensitivity to brain tissue. Scalp thickness always exhibited a slightly larger effect on sensitivity than skull thickness, but the effect of both varied with SD separation. We quantitatively characterize sensitivity around the head as well as the effects of scalp and skull, which can be used to interpret NIN brain activation studies as well as guide the design, development and optimization of NIRS devices and sensors.
•We conducted 3,555 simulations of photon propagation in a realistic head model.•Sensitivity to the brain increased monotonically across 30-75mm separations.•Regional sensitivity around the head spanned an order of magnitude.•Scalp and skull layers were the primary contributors to regional variability.•Quantitative estimates of the influence of scalp and skull are provided.
In previous work we introduced a novel method for reducing global interference, based on adaptive filtering, to improve the contrast to noise ratio (CNR) of evoked hemodynamic responses measured ...non-invasively with near infrared spectroscopy (NIRS). Here, we address the issue of how to generally apply the proposed adaptive filtering method. A total of 156 evoked visual response measurements, collected from 15 individuals, were analyzed. The similarity (correlation) between measurements with far and near source–detector separations collected during the rest period before visual stimulation was used as indicator of global interference dominance. A detailed analysis of CNR improvement in oxy-hemoglobin (O2Hb) and deoxy-hemoglobin (HHb), as a function of the rest period correlation coefficient, is presented. Results show that for O2Hb measurements, 66% exhibited substantial global interference. For this dataset, dominated by global interference, 71% of the measurements revealed CNR improvements after adaptive filtering, with a mean CNR improvement of 60%. No CNR improvement was observed for HHb. This study corroborates our previous finding that adaptive filtering provides an effective method to increase CNR when there is strong global interference, and also provides a practical way for determining when and where to apply this technique.
Ambulatory diffuse optical tomography (aDOT) is based on near-infrared spectroscopy (NIRS) and enables three-dimensional imaging of regional hemodynamics and oxygen consumption during a person's ...normal activities. Although NIRS has been previously used for muscle assessment, it has been notably limited in terms of the number of channels measured, the extent to which subjects can be ambulatory, and/or the ability to simultaneously acquire synchronized auxiliary data such as electromyography (EMG) or electrocardiography (ECG). We describe the development of a prototype aDOT system, called NINscan-M, capable of ambulatory tomographic imaging as well as simultaneous auxiliary multimodal physiological monitoring. Powered by four AA size batteries and weighing 577 g, the NINscan-M prototype can synchronously record 64-channel NIRS imaging data, eight channels of EMG, ECG, or other analog signals, plus force, acceleration, rotation, and temperature for 24+ h at up to 250 Hz. We describe the system's design, characterization, and performance characteristics. We also describe examples of isometric, cycle ergometer, and free-running ambulatory exercise to demonstrate tomographic imaging at 25 Hz. NINscan-M represents a multiuse tool for muscle physiology studies as well as clinical muscle assessment.
The sensitivity of near-infrared spectroscopy (NIRS) to evoked brain activity is reduced by physiological interference in at least two locations: 1. the superficial scalp and skull layers, and 2. in ...brain tissue itself. These interferences are generally termed as "global interferences" or "systemic interferences," and arise from cardiac activity, respiration, and other homeostatic processes. We present a novel method for global interference reduction and real-time recovery of evoked brain activity, based on the combination of a multiseparation probe configuration and adaptive filtering. Monte Carlo simulations demonstrate that this method can be effective in reducing the global interference and recovering otherwise obscured evoked brain activity. We also demonstrate that the physiological interference in the superficial layers is the major component of global interference. Thus, a measurement of superficial layer hemodynamics (e.g., using a short source-detector separation) makes a good reference in adaptive interference cancellation. The adaptive-filtering-based algorithm is shown to be resistant to errors in source-detector position information as well as to errors in the differential pathlength factor (DPF). The technique can be performed in real time, an important feature required for applications such as brain activity localization, biofeedback, and potential neuroprosthetic devices.
The grueling psychological demands of a journey into deep space coupled with ever-increasing distances away from home pose a unique problem: how can we best take advantage of the benefits of fresh ...foods in a place that has none? Here, we consider the biggest challenges associated with our current spaceflight food system, highlight the importance of supporting optimal brain health on missions into deep space, and discuss evidence about food components that impact brain health. We propose a future food system that leverages the gut microbiota that can be individually tailored to best support the brain and mental health of crews on deep space long-duration missions. Working toward this goal, we will also be making investments in sustainable means to nourish the crew that remains here on spaceship Earth.
Aerospace research has a long history of developing technologies with industry-changing applications and recent history is no exception. The expansion of commercial spaceflight and the upcoming ...exploration-class missions to the Moon and Mars are expected to accelerate this process even more. The resulting portable, wearable, contactless, and regenerable medical technologies are not only the future of healthcare in deep space but also the future of healthcare here on Earth. These multi-dimensional and integrative technologies are non-invasive, easily-deployable, low-footprint devices that have the ability to facilitate rapid detection, diagnosis, monitoring, and treatment of a variety of conditions, and to provide decision-making and performance support. Therefore, they are primed for applications in low-resource and remote environments, facilitating the extension of quality care delivery to all patients in all communities and empowering non-specialists to intervene early and safely in order to optimize patient-centered outcomes. Additionally, these technologies have the potential to advance care delivery in tertiary care centers by improving transitions of care, providing holistic patient data, and supporting clinician wellness and performance. The requirements of space exploration have created a number of paradigm-altering medical technologies that are primed to revitalize and elevate our standard of care here on Earth.
Near-infrared spectroscopy (NIRS) can be used to noninvasively measure changes in the concentrations of oxy- and deoxyhemoglobin in tissue. We have previously shown that while global changes can be ...reliably measured, focal changes can produce erroneous estimates of concentration changes (NeuroImage 13 (2001), 76). Here, we describe four separate sources for systematic error in the calculation of focal hemoglobin changes from NIRS data and use experimental methods and Monte Carlo simulations to examine the importance and mitigation methods of each. The sources of error are: (1) the absolute magnitudes and relative differences in pathlength factors as a function of wavelength, (2) the location and spatial extent of the absorption change with respect to the optical probe, (3) possible differences in the spatial distribution of hemoglobin species, and (4) the potential for simultaneous monitoring of multiple regions of activation. We found wavelength selection and optode placement to be important variables in minimizing such errors, and our findings indicate that appropriate experimental procedures could reduce each of these errors to a small fraction (<10%) of the observed concentration changes.
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