Single-distance and dual-slope frequency-domain near-infrared spectroscopy to assess skeletal muscle hemodynamics.

Significance: Non-invasive optical measurements of deep tissue (e.g., muscle) need to take into account confounding contributions from baseline and dynamic optical properties of superficial tissue (adipose tissue). Aim: Discriminate superficial and deep tissue hemodynamics using data collected with frequency-domain (FD) near-infrared spectroscopy (NIRS) in a dual-slope (DS) configuration. Approach: Experimental data were collected in vivo on the forearm of three human subjects during a 3-min arterial occlusion or 1-min venous occlusion. Theoretical data were generated using diffusion theory for two-layered media with varying values of the reduced scattering coefficient (µs') (range: 0.5 to 1.1 mm-1) and absorption coefficient (µa) (range: 0.005-0.015 mm-1) of the two layers, and top layer thickness (range: 2 to 8 mm). Data were analyzed using diffusion theory for a homogeneous semi-infinite medium. Results: Experimental data in vivo were consistent with simulated data for a two-layered medium with a larger µs' in the top layer, comparable absorption changes in the top and bottom layers during venous occlusion, and smaller absorption changes in the top vs. bottom layers during arterial occlusion. Conclusions: The dataset generated by DS FD-NIRS may allow for discrimination of superficial and deep absorption changes in two-layered media, thus lending itself to individual measurements of hemodynamics in adipose and muscle tissue.

Dual-ratio approach for detection of point fluorophores in biological tissue.

Significance: Diffuse in vivo flow cytometry (DiFC) is an emerging fluorescence sensing method to non-invasively detect labeled circulating cells in vivo. However, due to signal-to-noise ratio (SNR) constraints largely attributed to background tissue autofluorescence (AF), DiFC's measurement depth is limited. Aim: The dual ratio (DR)/dual slope is an optical measurement method that aims to suppress noise and enhance SNR to deep tissue regions. We aim to investigate the combination of DR and near-infrared (NIR) DiFC to improve circulating cells' maximum detectable depth and SNR. Approach: Phantom experiments were used to estimate the key parameters in a diffuse fluorescence excitation and emission model. This model and parameters were implemented in Monte Carlo to simulate DR DiFC while varying noise and AF parameters to identify the advantages and limitations of the proposed technique. Results: Two key factors must be true to give DR DiFC an advantage over traditional DiFC: first, the fraction of noise that DR methods cannot cancel cannot be above the order of 10% for acceptable SNR. Second, DR DiFC has an advantage, in terms of SNR, if the distribution of tissue AF contributors is surface-weighted. Conclusions: DR cancelable noise may be designed (e.g., through the use of source multiplexing), and indications point to the AF contributors' distribution being truly surface-weighted in vivo. Successful and worthwhile implementation of DR DiFC depends on these considerations, but results point to DR DiFC having possible advantages over traditional DiFC.

Dual-ratio approach for detection of point fluorophores in biological tissue.

SIGNIFICANCE: Diffuse in-vivo Flow Cytometry (DiFC) is an emerging fluorescence sensing method to non-invasively detect labeled circulating cells in-vivo. However, due to Signal-to-Noise Ratio (SNR) constraints largely attributed to background tissue autofluorescence, DiFC's measurement depth is limited. multiplies Aim: The Dual-Ratio (DR) / dual-slope is a new optical measurement method that aims to suppress noise and enhance SNR to deep tissue regions. We aim to investigate the combination of DR and Near-InfraRed (NIR) DiFC to improve circulating cells' maximum detectable depth and SNR. APPROACH: Phantom experiments were used to estimate the key parameters in a diffuse fluorescence excitation and emission model. This model and parameters were implemented in Monte-Carlo to simulate DR DiFC while varying noise and autofluorescence parameters to identify the advantages and limitations of the proposed technique. RESULTS: Two key factors must be true to give DR DiFC an advantage over traditional DiFC; first, the fraction of noise that DR methods cannot cancel cannot be above the order of 10% for acceptable SNR. Second, DR DiFC has an advantage, in terms of SNR, if the distribution of tissue autofluorescence contributors is surface-weighted. CONCLUSIONS: DR cancelable noise may be designed for (e.g. through the use of source multiplexing), and indications point to the autofluorescence contributors' distribution being truly surface-weighted in-vivo. Successful and worthwhile implementation of DR DiFC depends on these considerations, but results point to DR DiFC having possible advantages over traditional DiFC.

Editorial Special Section on Biomedical Diffuse Optics for the Brain.

This special section collects four articles on the application of diffuse optics to measure cerebral hemodynamics and oxygenation. The possibility of using near-infrared light to collect cerebral hemodynamic and metabolic information through the intact scalp and skull was first proposed in the 1970s [1]. Commercial cerebral oximeters were developed in the 1990s, and functional measurements of brain activation, which signaled the birth of functional near-infrared spectroscopy (fNIRS), were first reported in 1993 [2], [3], [4], [5]. Oscillatory cerebral hemodynamics were also investigated in relation to functional and diagnostic applications [6], [7], [8], [9]. Journal special issues were published to celebrate the 20th [10] and 30th [11] anniversaries of fNIRS, and numerous review articles have provided overviews of the field of noninvasive optical measurements of the brain [12], [13], [14], [15].

Estimating Systemic Cognitive States from a Mixture of Physiological and Brain Signals.

As human-machine teams are being considered for a variety of mixed-initiative tasks, detecting and being responsive to human cognitive states, in particular systematic cognitive states, is among the most critical capabilities for artificial systems to ensure smooth interactions with humans and high overall team performance. Various human physiological parameters, such as heart rate, respiration rate, blood pressure, and skin conductance, as well as brain activity inferred from functional near-infrared spectroscopy or electroencephalogram, have been linked to different systemic cognitive states, such as workload, distraction, or mind-wandering among others. Whether these multimodal signals are indeed sufficient to isolate such cognitive states across individuals performing tasks or whether additional contextual information (e.g., about the task state or the task environment) is required for making appropriate inferences remains an important open problem. In this paper, we introduce an experimental and machine learning framework for investigating these questions and focus specifically on using physiological and neurophysiological measurements to learn classifiers associated with systemic cognitive states like cognitive load, distraction, sense of urgency, mind wandering, and interference. Specifically, we describe a multitasking interactive experimental setting used to obtain a comprehensive multimodal data set which provided the foundation for a first evaluation of various standard state-of-the-art machine learning techniques with respect to their effectiveness in inferring systemic cognitive states. While the classification success of these standard methods based on just the physiological and neurophysiological signals across subjects was modest, which is to be expected given the complexity of the classification problem and the possibility that higher accuracy rates might not in general be achievable, the results nevertheless can serve as a baseline for evaluating future efforts to improve classification, especially methods that take contextual aspects such as task and environmental states into account.

Novel data types for frequency-domain diffuse optical spectroscopy and imaging of tissues: characterization of sensitivity and contrast-to-noise ratio for absorption perturbations.

In frequency-domain (FD) diffuse optics it is known that the phase of photon-density waves (ϕ) has a stronger deep-to-superficial sensitivity ratio to absorption perturbations than the alternate current (AC) amplitude, or the direct current intensity (DC). This work is an attempt to find FD data types that feature similar or even better sensitivity and/or contrast-to-noise for deeper absorption perturbations than phase. One way is to start from the definition of characteristic function (Xt(ω)) of the photon's arrival time (t) and combining the real (ℜ(Xt(ω))=ACDCcos(ϕ)) and imaginary parts (ℑ[Xt(ω)]=ACDCsin(ϕ)) with phase to yield new data types. These new data types enhance the role of higher order moments of the probability distribution of the photon's arrival time t. We study the contrast-to-noise and sensitivity features of these new data types not only in the single-distance arrangement (traditionally used in diffuse optics), but we also consider the spatial gradients, which we named dual-slope arrangements. We have identified six data types that for typical values of the optical properties of tissues and depths of interest, have better sensitivity or contrast-to-noise features than phase data and that can be used to enhance the limits of imaging of tissue in FD near infrared spectroscopy (NIRS). For example, one promising data type is ϕ-ℑ[Xt(ω)] which shows, in the single-distance source-detector arrangement, an increase of deep-to-superficial sensitivity ratio with respect to phase by 41% and 27% at a source-detector separation of 25 and 35 mm, respectively. The same data type also shows an increase of contrast-to noise up to 35% with respect to phase when the spatial gradients of the data are considered.

Shrub Cover and Soil Moisture Affect Taxus baccata L. Regeneration at Its Southern Range.

The effect of key ecological and anthropic factors on the recruitment of the common yew (Taxus baccata L.) in Sardinia (Italy) has been analyzed. After bibliographic and cartographic research, followed by field surveys, we found 232 sites where yew grows in Sardinia (as opposed to 69 previously reported in the literature). Among them, we selected 40 sites, located in 14 different mountain chains, characterized by a number of individuals ranging from 11 to 836 adult yews with an average diameter at breast height (DBH) from 13 to 130 cm. By means of generalized linear modeling, we investigated and weighted the effect of ecological, structural, and anthropic factors on the amount of T. baccata recruitment. Our analyses showed that stand recruitment was positively correlated to shrub cover and soil moisture. In particular, shrub cover had a stronger effect, clearly showing that a thicker shrub layer, both bushy and/or spiny, corresponded to a higher number of yew seedlings and saplings. Secondarily, moister sites had a higher number of seedlings and saplings, showing that habitat suitability improved with higher humidity. On the contrary, recruitment was negatively correlated to browsing (both from livestock and wild animals). Our data confirm that the presence of a protective layer of shrubs is a crucial factor for seedling and sapling survival, mostly in relation to protection from summer drought and the browsing of large herbivores. Finally, guidelines for the conservation and restoration of T. baccata communities, referred to as the EU priority habitat 9580* (Mediterranean Taxus baccata woods), have been outlined.

Dual-slope imaging of cerebral hemodynamics with frequency-domain near-infrared spectroscopy.

Significance: This work targets the contamination of optical signals by superficial hemodynamics, which is one of the chief hurdles in non-invasive optical measurements of the human brain. Aim: To identify optimal source-detector distances for dual-slope (DS) measurements in frequency-domain (FD) near-infrared spectroscopy (NIRS) and demonstrate preferential sensitivity of DS imaging to deeper tissue (brain) versus superficial tissue (scalp). Approach: Theoretical studies (in-silico) based on diffusion theory in two-layered and in homogeneous scattering media. In-vivo demonstrations of DS imaging of the human brain during visual stimulation and during systemic blood pressure oscillations. Results: The mean distance (between the two source-detector distances needed for DS) is the key factor for depth sensitivity. In-vivo imaging of the human occipital lobe with FD NIRS and a mean distance of 31 mm indicated: (1) greater hemodynamic response to visual stimulation from FD phase versus intensity, and from DS versus single-distance (SD); (2) hemodynamics from FD phase and DS mainly driven by blood flow, and hemodynamics from SD intensity mainly driven by blood volume. Conclusions: DS imaging with FD NIRS may suppress confounding contributions from superficial hemodynamics without relying on data at short source-detector distances. This capability can have significant implications for non-invasive optical measurements of the human brain.

Optical imaging and spectroscopy for the study of the human brain: status report.

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.

Broadband diffuse optical spectroscopy of two-layered scattering media containing oxyhemoglobin, deoxyhemoglobin, water, and lipids.

We investigated the relationship between chromophore concentrations in two-layered scattering media and the apparent chromophore concentrations measured with broadband optical spectroscopy in conjunction with commonly used homogeneous medium inverse models. We used diffusion theory togenerate optical data from a two-layered distribution of relevant tissue absorbers, namely, oxyhemoglobin, deoxyhemoglobin, water, and lipids, with a top-layer thickness in the range 1-15 mm. The generated data consisted of broadband continuous-wave (CW) diffuse reflectance in the wavelength range 650-1024 nm, and frequency-domain (FD) diffuse reflectance at 690 and 830 nm; two source-detector distances of 25 and 35 mm were used to simulate a dual-slope technique. The data were inverted using diffusion theory for a semi-infinite homogeneous medium to generate reduced scattering coefficients at 690 and 830 nm (from FD data) and effective absorption spectra in the range 650-1024 nm (from CW data). The absorption spectra were then converted into effective total concentration and oxygen saturation of hemoglobin, as well as water and lipid concentrations. For absolute values, it was found that the effective hemoglobin parameters are typically representative of the bottom layer, whereas water and lipid represent some average of the respective concentrations in the two layers. For concentration changes, lipid showed a significant cross-talk with other absorber concentrations, thus indicating that lipid dynamics obtained in these conditions may not be reliable. These systematic simulations of broadband spectroscopy of two-layered media provide guidance on how to interpret effective optical properties measured with similar instrumental setups under the assumption of medium homogeneity.

Method for Measuring Absolute Optical Properties of Turbid Samples in a Standard Cuvette.

Many applications seek to measure a sample's absorption coefficient spectrum to retrieve the chemical makeup. Many real-world samples are optically turbid, causing scattering confounds which many commercial spectrometers cannot address. Using diffusion theory and considering absorption and reduced scattering coefficients on the order of 0.01 mm-1 and 1 mm-1, respectively, we develop a method which utilizes frequency-domain to measure absolute optical properties of turbid samples in a standard cuvette (45 mm × 10 mm × 10 mm). Inspired by the self-calibrating method, which removes instrumental confounds, the method uses measurements of the diffuse complex transmittance at two sets of two different source-detector distances. We find: this works best for highly scattering samples (reduced scattering coefficient above 1 mm-1); higher relative error in the absorption coefficient compared to the reduced scattering coefficient; accuracy is tied to knowledge of the sample's index of refraction. Noise simulations with 0.1 % amplitude and 0.1° = 1.7 mrad phase uncertainty find errors in absorption and reduced scattering coefficients of 4 % and 1 %, respectively. We expect that higher error in the absorption coefficient can be alleviated with highly scattering samples and that boundary condition confounds may be suppressed by designing a cuvette with high index of refraction. Further work will investigate implementation and reproducibility.

Noninvasive Optical Measurements of Dynamic Cerebral Autoregulation by Inducing Oscillatory Cerebral Hemodynamics.

Objective: Cerebral autoregulation limits the variability of cerebral blood flow (CBF) in the presence of systemic arterial blood pressure (ABP) changes. Monitoring cerebral autoregulation is important in the Neurocritical Care Unit (NCCU) to assess cerebral health. Here, our goal is to identify optimal frequency-domain near-infrared spectroscopy (FD-NIRS) parameters and apply a hemodynamic model of coherent hemodynamics spectroscopy (CHS) to assess cerebral autoregulation in healthy adult subjects and NCCU patients. Methods: In five healthy subjects and three NCCU patients, ABP oscillations at a frequency around 0.065 Hz were induced by cyclic inflation-deflation of pneumatic thigh cuffs. Transfer function analysis based on wavelet transform was performed to measure dynamic relationships between ABP and oscillations in oxy- (O), deoxy- (D), and total- (T) hemoglobin concentrations measured with different FD-NIRS methods. In healthy subjects, we also obtained the dynamic CBF-ABP relationship by using FD-NIRS measurements and the CHS model. In healthy subjects, an interval of hypercapnia was performed to induce cerebral autoregulation impairment. In NCCU patients, the optical measurements of autoregulation were linked to individual clinical diagnoses. Results: In healthy subjects, hypercapnia leads to a more negative phase difference of both O and D oscillations vs. ABP oscillations, which are consistent across different FD-NIRS methods and are highly correlated with a more negative phase difference CBF vs. ABP. In the NCCU, a less negative phase difference of D vs. ABP was observed in one patient as compared to two others, indicating a better autoregulation in that patient. Conclusions: Non-invasive optical measurements of induced phase difference between D and ABP show the strongest sensitivity to cerebral autoregulation. The results from healthy subjects also show that the CHS model, in combination with FD-NIRS, can be applied to measure the CBF-ABP dynamics for a better direct measurement of cerebral autoregulation.

Broadband absorption spectroscopy of heterogeneous biological tissue.

Absorption spectra (∼600 to 1064 nm) of six tissues in three healthy volunteers were measured by combining dual-slope continuous-wave broadband spectroscopy with self-calibrated frequency-domain measurements of scattering at two wavelengths (690 and 830 nm). The spectral fit with a linear combination of oxy- and deoxyhemoglobin, water, and lipids extinction spectra is improved by a wavelength-independent absorption background. The need to introduce this background is assigned to the inhomogeneous distribution of absorbers in tissue. By using a two-layer model, the relationship between recovered concentrations and their two-layer values was investigated, and the implications for non-invasive tissue spectroscopy are discussed.

Sensitivity of frequency-domain optical measurements to brain hemodynamics: simulations and human study of cerebral blood flow during hypercapnia.

This study characterizes the sensitivity of noninvasive measurements of cerebral blood flow (CBF) by using frequency-domain near-infrared spectroscopy (FD-NIRS) and coherent hemodynamics spectroscopy (CHS). We considered six FD-NIRS methods: single-distance intensity and phase (SDI and SDϕ), single-slope intensity and phase (SSI and SSϕ), and dual-slope intensity and phase (DSI and DSϕ). Cerebrovascular reactivity (CVR) was obtained from the relative change in measured CBF during a step hypercapnic challenge. Greater measured values of CVR are assigned to a greater sensitivity to cerebral hemodynamics. In a first experiment with eight subjects, CVRSDϕ was greater than CVRSDI (p < 0.01), whereas CVRDSI and CVRDSϕ showed no significant difference (p > 0.5). In a second experiment with four subjects, a 5 mm scattering layer was added between the optical probe and the scalp tissue to increase the extracerebral layer thickness (L ec ), which caused CVRDSϕ to become significantly greater than CVRDSI (p < 0.05). CVRSS measurements yielded similar results as CVRDS measurements but with a greater variability, possibly resulting from instrumental artifacts in SS measurements. Theoretical simulations with two-layered media confirmed that, if the top (extracerebral) layer is more scattering than the bottom (brain) layer, the relative values of CVRDSI and CVRDSϕ depend on L ec . Specifically, the sensitivity to the brain is greater for DSI than DSϕ for a thin extracerebral layer (L ec < 13 mm), whereas it is greater for DSϕ than DSI for a thicker extracerebral layer.

Tracking Brain Development From Neonates to the Elderly by Hemoglobin Phase Measurement Using Functional Near-Infrared Spectroscopy.

The biological and neurological processes during the lifespan are dynamic with significant alterations associated with different stages of life. The phase and coupling of oxy-hemoglobin (Δ[HbO]) and deoxy-hemoglobin concentration changes (Δ[Hb]) measured by functional near-infrared spectroscopy (fNIRS) are shown to characterize the neurovascular and metabolic development of infants. However, the changes in phase and coupling across the human lifespan remain mostly unknown. Here, fNIRS measurements of Δ[HbO] and Δ[Hb] conducted at two sites on different age populations (from newborns to elderly) were combined. Firstly, we assessed the influence of random noise on the calculation of the phase difference and phase-locking index (PLI) in fNIRS measurement. The results showed that the phase difference is close to π as the noise intensity approaches -8 dB, and the coupling strength (i.e., PLI) presents a u-shape curve as the noise increase. Secondly, phase difference and PLI in the frequency range 0.01-0.10 Hz were calculated after denoising. It showed that the phase difference increases from newborns to 3-4-month-olds babies. This phase difference persists throughout adulthood until finally being disrupted in the old age. The children's PLI is the highest, followed by that of adults. These two groups' PLI are significantly higher than those of infants and the elderly (p < 0.001). Lastly, a hemodynamic model was used to explain the observations and found close associations with cerebral autoregulation and speed of blood flow. These results demonstrate that the phase-related parameters measured by fNIRS can be used to study the brain and assess brain health throughout the lifespan.

Domain adaptation for robust workload level alignment between sessions and subjects using fNIRS.

SIGNIFICANCE: We demonstrated the potential of using domain adaptation on functional near-infrared spectroscopy (fNIRS) data to classify different levels of n-back tasks that involve working memory. AIM: Domain shift in fNIRS data is a challenge in the workload level alignment across different experiment sessions and subjects. To address this problem, two domain adaptation approaches-Gromov-Wasserstein (G-W) and fused Gromov-Wasserstein (FG-W) were used. APPROACH: Specifically, we used labeled data from one session or one subject to classify trials in another session (within the same subject) or another subject. We applied G-W for session-by-session alignment and FG-W for subject-by-subject alignment to fNIRS data acquired during different n-back task levels. We compared these approaches with three supervised methods: multiclass support vector machine (SVM), convolutional neural network (CNN), and recurrent neural network (RNN). RESULTS: In a sample of six subjects, G-W resulted in an alignment accuracy of 68 % ± 4 % (weighted mean ± standard error) for session-by-session alignment, FG-W resulted in an alignment accuracy of 55 % ± 2 % for subject-by-subject alignment. In each of these cases, 25% accuracy represents chance. Alignment accuracy results from both G-W and FG-W are significantly greater than those from SVM, CNN, and RNN. We also showed that removal of motion artifacts from the fNIRS data plays an important role in improving alignment performance. CONCLUSIONS: Domain adaptation has potential for session-by-session and subject-by-subject alignment of mental workload by using fNIRS data.

Dual-Slope Diffuse Reflectance Instrument for Calibration-Free Broadband Spectroscopy.

This work presents the design and validation of an instrument for dual-slope broadband diffuse reflectance spectroscopy. This instrument affords calibration-free, continuous-wave measurements of broadband absorbance of optically diffusive media, which may be translated into absolute absorption spectra by adding frequency-domain measurements of scattering at two wavelengths. An experiment on a strongly scattering liquid phantom (milk, water, dyes) confirms the instrument's ability to correctly identify spectral features and measure absolute absorption. This is done by sequentially adding three dyes, each featuring a distinct spectral absorption, to the milk/water phantom. After each dye addition, the absorption spectrum is measured, and it is found to reproduce the spectral features of the added dye. Additionally, the absorption spectrum is compared to the absorption values measured with a commercial frequency-domain instrument at two wavelengths. The measured absorption of the milk/water phantom quantitatively agrees with the known water absorption spectrum (R 2 = 0.98), and the measured absorption of the milk/water/dyes phantom quantitatively agrees with the absorption measured with the frequency-domain instrument in six of eight cases. Additionally, the measured absorption spectrum correctly recovers the concentration of one dye, black India ink, for which we could accurately determine the extinction spectrum (i.e., the specific absorption per unit concentration). The instrumental methods presented in this work can find applications in quantitative spectroscopy of optically diffusive media, and particularly in near-infrared spectroscopy of biological tissue.

Design of a source-detector array for dual-slope diffuse optical imaging.

We recently proposed a dual-slope technique for diffuse optical spectroscopy and imaging of scattering media. This technique requires a special configuration of light sources and optical detectors to create dual-slope sets. Here, we present methods for designing, optimizing, and building an optical imaging array that features m dual-slope sets to image n voxels. After defining the m × n matrix (S) that describes the sensitivity of the m dual-slope measurements to absorption perturbations in each of the n voxels, we formulate the inverse imaging problem in terms of the Moore-Penrose pseudoinverse matrix of S (S+). This approach allows us to introduce several measures of imaging performance: reconstruction accuracy (correct spatial mapping), crosstalk (incorrect spatial mapping), resolution (point spread function), and localization (offset between actual and reconstructed point perturbations). Furthermore, by considering the singular value decomposition formulation, we show the significance of visualizing the first m right singular vectors of S, whose linear combination generates the reconstructed map. We also describe methods to build a physical array using a three-layer mesh structure (two polyethylene films and polypropylene hook-and-loop fabric) embedded in silicone (PDMS). Finally, we apply these methods to design two arrays and choose one to construct. The chosen array consists of 16 illumination fibers, 10 detection fibers, and 27 dual-slope sets for dual-slope imaging optimized for the size of field of view and localization of absorption perturbations. This particular array is aimed at functional near-infrared spectroscopy of the human brain, but the methods presented here are of general applicability to a variety of devices and imaging scenarios.

Dual-slope imaging in highly scattering media with frequency-domain near-infrared spectroscopy.

We present theoretical and experimental demonstrations of a novel, to the best of our knowledge, diffuse optical imaging method that is based on the concept of dual slopes (DS) in frequency-domain near-infrared spectroscopy. We consider a special array of sources and detectors that collects intensity (I) and phase (ϕ) data with multiple DS sets. We have recently shown that DSϕ reflectance data features a deeper sensitivity with respect to DSI reflectance data. Here, for the first time, we describe a DS imaging approach based on the Moore-Penrose inverse of the sensitivity matrix for multiple DS data sets. Using a circular 8-source/9-detector array that generates 16 DS data sets at source-detector distances in the range 20-40 mm, we show that DSI images are more sensitive to superficial (<5mm) perturbations, whereas DSϕ images are more sensitive to deeper (>10mm) perturbations in highly scattering media.

Frequency-Domain Techniques for Cerebral and Functional Near-Infrared Spectroscopy.

This article reviews the basic principles of frequency-domain near-infrared spectroscopy (FD-NIRS), which relies on intensity-modulated light sources and phase-sensitive optical detection, and its non-invasive applications to the brain. The simpler instrumentation and more straightforward data analysis of continuous-wave NIRS (CW-NIRS) accounts for the fact that almost all the current commercial instruments for cerebral NIRS have embraced the CW technique. However, FD-NIRS provides data with richer information content, which complements or exceeds the capabilities of CW-NIRS. One example is the ability of FD-NIRS to measure the absolute optical properties (absorption and reduced scattering coefficients) of tissue, and thus the absolute concentrations of oxyhemoglobin and deoxyhemoglobin in brain tissue. This article reviews the measured values of such optical properties and hemoglobin concentrations reported in the literature for animal models and for the human brain in newborns, infants, children, and adults. We also review the application of FD-NIRS to functional brain studies that focused on slower hemodynamic responses to brain activity (time scale of seconds) and faster optical signals that have been linked to neuronal activation (time scale of 100 ms). Another example of the power of FD-NIRS data is related to the different regions of sensitivity featured by intensity and phase data. We report recent developments that take advantage of this feature to maximize the sensitivity of non-invasive optical signals to brain tissue relative to more superficial extracerebral tissue (scalp, skull, etc.). We contend that this latter capability is a highly appealing quality of FD-NIRS, which complements absolute optical measurements and may result in significant advances in the field of non-invasive optical sensing of the brain.