Deep and surface hemodynamic signal from functional time resolved transcranial near infrared spectroscopy compared to skin flowmotion

Near-wall hemodynamic parameters of finger arteries altered by hand-transmitted vibration

BACKGROUND

Sustained exposure to high-level hand-transmitted vibrations may result in angioneurotic disorders, which partly originate from vibration-altered hemodynamics in the finger arteries when repeating these disturbances throughout working life. Hence, the aim of this study is to assess the most relevant hemodynamic descriptors in the digital arteries, determine the relationship between the latter and vibration features, and gain better understanding of the physiological mechanisms involved.

METHODS

An experimental setup, mainly comprised of an ultra-high frequency ultrasound scanner and a vibration shaker, was used to image the digital proper volar arteries of the forefinger. Raw ultrasound data were post-processed by custom-made numerical routines to supply a pulsatile fluid mechanics model for computing the hemodynamic descriptors. Twenty-four healthy volunteers participated in the measurement campaign. Classical statistical methods were then applied to the dataset and also the wavelet transform for calculating the signal power in the frequency bands matching cardiac, respiratory, myogenic and neurogenic activities.

RESULTS

The artery diameter, the wall shear stress - WSS - and the WSS temporal gradient - WSSTG - were found to be the most relevant descriptors. Vibration-induced WSS was divided by three compared to its basal value whatever the vibration frequency and it was proportional to log2 of the acceleration level. Marked increases in WSSTG when stopping vibration might also lead to adverse health effects. Vibration caused a drop in WSS power for the frequency band associated with the neurogenic activity of the sympathetic nervous system.

CONCLUSION

This study may pave the way for a new framework to prevent vibration-induced vascular risk.

The past, present, and prospective on UV-VIS-NIR skin photonics and spectroscopy-a wavelength guide

The study and applications of in vivo skin optics have been openly documented as early as the year 1954, or possibly earlier. To date, challenges in analyzing the complexities of this field remain, with wide scopes requiring more scrutiny. Recent advances in spectroscopic research and multivariate analytics allow a closer look into applications potentially for detecting or monitoring diseases. One of the challenges in this field is in establishing a reference for applications which correspond to certain bandwidths. This article reviews the scope on past research on skin spectroscopy, and the clinical aspects which have or may have applications on disease detection or enhancing diagnostics. A summary is supplied on the technicalities surrounding the measurements reported in literature, focused towards the wavelength-dependent applications in themes central to the respective research. Analytics on the topology of the papers' data cited in this work is also provided for a statistical perspective. In short, this paper strives to immediately inform the reader with possible applications via the spectroscopic devices at hand. Graphical Abstract .

The Valsalva maneuver: an indispensable physiological tool to differentiate intra versus extracranial near-infrared signal

Developing near-infrared spectroscopy (NIRS) parameter recovery techniques to more specifically resolve brain physiology from that of the overlying tissue is an important part of improving the clinical utility of the technology. The Valsalva maneuver (VM) involves forced expiration against a closed glottis causing widespread venous congestion within the context of a fall in cardiac output. Due to the specific anatomical confines and metabolic demands of the brain we believe a properly executed VM has the ability to separate haemodynamic activity of brain tissue from that of the overlying scalp as observed by NIRS, and confirmed by functional magnetic resonance imaging (fMRI). Healthy individuals performed a series of standing maximum effort VMs under separate observation by frequency domain near-infrared spectroscopy (FD-NIRS) and fMRI. Nine individuals completed the clinical protocol (6 males, age 21-40). During the VMs, brain and extracranial tissue targeted signal were significantly different (opposite direction of change) in both fMRI and NIRS (p=0.00025 and 0.00115 respectively), with robust cross correlation of parameters between modalities. Four of these individuals performed further VMs after infiltrating 2% xylocaine/1:100,000 epinephrine (vasoconstrictor) into scalp tissue beneath the probes. No significant difference in the cerebrally derived parameters was observed. The maximum effort VM has the ability to separate NIRS observable physiology of the brain from the overlying extracranial tissue. Observations made by this FD cerebral NIRS device are comparable with fMRI in this context.

Elevation of intracranial pressure affects the relationship between hemoglobin concentration and neuronal activation in human somatosensory cortex

During neuronal activation, a local decrease of deoxygenated hemoglobin concentration (deoxy‐Hb) occurs which is the basis of functional brain imaging with blood oxygenation level dependent functional magnetic resonance imaging (BOLD‐fMRI). Elevated intracranial pressure (eICP) has been shown to impair functional deoxy‐Hb changes. This study investigated this effect and its relation to the underlying neuronal activity in the human primary somatosensory cortex (SI). Functional near‐infrared spectroscopy (fNIRS) during somatosensory evoked potentials (SEP) monitoring was performed on 75 subjects during conditions of median nerve stimulation (MNS) and resting state, combined with normal breathing (NB) and eICP by escalating breathing maneuvers (breath holding [BH], Valsalva maneuver with 15 mmHg [V15] and 35 mmHg expiratory pressure [V35]). During NB, fNIRS revealed a typical oxygenated hemoglobin concentration (oxy‐Hb) increase with deoxy‐Hb decrease during MNS enabling SI brain mapping. Breathing maneuvers associated eICP produced a known global change of oxy‐Hb and deoxy‐Hb with and without MNS. When subtracting measurements during resting state from measurements during MNS, neither functional oxy‐Hb nor deoxy‐Hb changes could be recovered while SEPs remained unchanged. In conclusion, Valsalva‐induced eICP prevents oxy‐Hb and deoxy‐Hb changes during neuronal activation in SI. This finding raises questions on the validity of oxy‐Hb‐ and deoxy‐Hb‐based brain imaging (e.g., BOLD‐fMRI) during eICP.

The Temporal Confounding Effects of Extra-cerebral Contamination Factors on the Hemodynamic Signal Measured by Functional Near-Infrared Spectroscopy

Introduction: Functional near-infrared spectroscopy (fNIRS) has been broadly applied for optical brain imaging. This method is hemodynamic-based functional brain imaging relying on the measurement of the neurovascular coupling to detect changes in cerebral neuronal activities. The extra-cerebral hemodynamic changes are important contaminating factors in fNIRS measurements. This error signal can be misinterpreted as cerebral activities during fNIRS studies. Recently, it was assumed that temporal changes in deoxygenated hemoglobin concentration [HHb] was hardly affected by superficial blood flow, and it was proposed that the activation maps could be determined from [HHb] at large source-detector separation. Methods: In the current study, we measured the temporal changes in [HHb] using a continueswave fNIRS device at large source-detector separation, while superficial blood flow was stimulated by infrared lasers. A mesh-based Monte Carlo code was applied to estimate fNIRS sensitivity to superficial hemodynamic changes in a realistic 3D MRI-based brain phantom. Results: First, we simulated photon migration in a four-layered human-head slab model to calculate PPLs and fNIRS sensitivity. Then, the localization of the infrared laser inside a realistic brain model was studied using the Monte Carlo method. Finally, the changes in [HHb] over the prefrontal cortex of six adult males were measured by fNIRS at a source-detector separation of 3 cm. The results demonstrated that the relation between fNIRS sensitivity and an increase in S-D separation was nonlinear and a correlation between shallow and deep signals was observed. Conclusion: The presented results demonstrated that the temporal changes in the superficial blood flow could strongly affect HHb measurement at large source-detector separation. Hence, the cerebral activity map extracted from the [HHb] signal was mainly contaminated by superficial blood flow.

Time Domain Near Infrared Spectroscopy Device for Monitoring Muscle Oxidative Metabolism: Custom Probe and In Vivo Applications

Measurement of muscle oxidative metabolism is of interest for monitoring the training status in athletes and the rehabilitation process in patients. Time domain near infrared spectroscopy (TD NIRS) is an optical technique that allows the non-invasive measurement of the hemodynamic parameters in muscular tissue: concentrations of oxy- and deoxy-hemoglobin, total hemoglobin content, and tissue oxygen saturation. In this paper, we present a novel TD NIRS medical device for muscle oxidative metabolism. A custom-printed 3D probe, able to host optical elements for signal acquisition from muscle, was develop for TD NIRS in vivo measurements. The system was widely characterized on solid phantoms and during in vivo protocols on healthy subjects. In particular, we tested the in vivo repeatability of the measurements to quantify the error that we can have by repositioning the probe. Furthermore, we considered a series of acquisitions on different muscles that were not yet previously performed with this custom probe: a venous-arterial cuff occlusion of the arm muscle, a cycling exercise, and an isometric contraction of the vastus lateralis.

Effect of blood flow restriction on tissue oxygenation during knee extension

PURPOSE

Time-resolved near-infrared spectroscopy was used to quantify tissue oxy- and deoxyhemoglobin concentrations ([HbO2] and [HbR]) and O2 saturation (stO2) in the oblique fibers of the vastus medialis muscle and brain prefrontal cortex during knee extension with and without blood flow restriction (BFR).

METHODS

Six young healthy males performed three sets of knee extensions on a dynamometer (50% one-repetition maximum) separated by 90-s rest periods in three conditions: 1) until fatigue without BFR (fatigue), 2) until fatigue with BFR (100 mm Hg cuff constriction around thigh (BFR)), 3) same number of repetitions from condition 2 without BFR (matched). Each condition was performed on a separate visit.

RESULTS

BFR was associated with higher [HbR] at the oblique fibers of the vastus medialis muscle (rest 1: 57.8 (BFR) vs 35.0 μM (matched); P < 0.0001) and a significantly lower stO2 during recovery periods between sets (7.5%-11.2 % lower than non-BFR conditions for rest 1 and 2, P < 0.0001). Using a piecewise linear spline method, a spike in [HbR] was observed before the onset of HbR clearance during recovery, causing HbR clearance to begin at a higher concentration (81 (BFR) vs 62 μM (matched), P = 0.029). [HbO2] kinetics during recovery were also affected by BFR, with longer duration (BFR, 51 s; matched, 31 s; P = 0.047) but lower rate of increase (BFR, 58 μM·min; matched, 89 μM·min; P = 0.004) during recovery. In the prefrontal cortex, BFR was associated with increased [HbR], diminished increase in [HbO2], and higher subjective exertion.

CONCLUSIONS

These findings yield insight into possible physiological mechanisms of BFR and suggest a role of time-resolved near-infrared spectroscopy in monitoring and optimization of BFR exercise on an individual basis.

Tutorial on platform for optical topography analysis tools

Optical topography/functional near-infrared spectroscopy (OT/fNIRS) is a functional imaging technique that noninvasively measures cerebral hemoglobin concentration changes caused by neural activities. The fNIRS method has been extensively implemented to understand the brain activity in many applications, such as neurodisorder diagnosis and treatment, cognitive psychology, and psychiatric status evaluation. To assist users in analyzing fNIRS data with various application purposes, we developed a software called platform for optical topography analysis tools (POTATo). We explain how to handle and analyze fNIRS data in the POTATo package and systematically describe domain preparation, temporal preprocessing, functional signal extraction, statistical analysis, and data/result visualization for a practical example of working memory tasks. This example is expected to give clear insight in analyzing data using POTATo. The results specifically show the activated dorsolateral prefrontal cortex is consistent with previous studies. This emphasizes analysis robustness, which is required for validating decent preprocessing and functional signal interpretation. POTATo also provides a self-developed plug-in feature allowing users to create their own functions and incorporate them with established POTATo functions. With this feature, we continuously encourage users to improve fNIRS analysis methods. We also address the complications and resolving opportunities in signal analysis.

Age-related alterations in phase synchronization of oxyhemoglobin concentration changes in prefrontal tissues as measured by near-infrared spectroscopy signals

The prefrontal cortex plays an important role in planning complex cognitive behavior, personality expression, and decision making. This study aims to assess the phase synchronization of signals of the oxyhemoglobin concentration changes (Δ[HbO2]) in the left and right prefrontal tissues through near-infrared spectroscopy (NIRS) with wavelet phase coherence (WPCO) method. The NIRS signals were continuously recorded from the left and right prefrontal lobes in 43 healthy elderly subjects (age: 69.6 ± 8.4 years) and 40 young healthy subjects (age: 24.5 ± 1.7 years) during the resting state. Phase synchronization between the left and right prefrontal oscillations in six frequency intervals (I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; IV, 0.021-0.052 Hz; V, 0.0095-0.021 Hz; and VI, 0.005-0.0095 Hz) was analyzed using the WPCO method. The WPCO values of elderly subjects were significantly lower in frequency intervals I (F=7.376, p=0.010) and III (F=6.418, p=0.016) than those of the young subjects. Low phase coherence in intervals I and III indicates reduced synchronization of cardiac activity in the prefrontal area and weakened prefrontal functional connectivity, respectively.

Effects of Increasing Neuromuscular Electrical Stimulation Current Intensity on Cortical Sensorimotor Network Activation: A Time Domain fNIRS Study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O₂Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O₂Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O₂Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes

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.

Improved cerebral oxygenation response and executive performance as a function of cardiorespiratory fitness in older women: a fNIRS study

Cardiorespiratory fitness has been shown to protect and enhance cognitive and brain functions, but little is known about the cortical mechanisms that underlie these changes in older adults. In this study, functional near infrared spectroscopy (fNIRS) was used to investigate variations in oxyhemoglobin [HbO2] and in deoxyhemoglobin [HHb] in the dorsolateral prefrontal cortex (DLPFC) during the performance of an executive control task in older women with different levels of cardiorespiratory fitness (VO2max). Thirty-four women aged 60-77 years were classified as high-fit and low-fit based on VO2max measures. They all performed a control counting (CNT) task and the Random Number Generation (RNG) task at two different paces (1 number/1 s and 1 number/1.5 s), allowing to manipulate task difficulty, while hemodynamic responses in the bilateral DLPFCs were recorded using continuous-wave NIRS. The behavioral data revealed that the high-fit women showed significantly better performance on the RNG tasks compared with the low-fit women. The high-fit women showed significant increases in [HbO2] responses in both left and right DLPFCs during the RNG task, while the low-fit women showed significantly less activation in the right DLPFC compared with the right DLPFC of the high-fit women and compared with their own left DLPFC. At the level of the whole sample, increases in the [HbO2] responses in the right DLPFC were found to mediate in part the relationship between VO2max level and executive performance during the RNG task at 1.5 s but not at 1 s. These results provide support for the cardiorespiratory fitness hypothesis and suggest that higher levels of aerobic fitness in older women are related to increased cerebral oxygen supply to the DLPFC, sustaining better cognitive performance.

Greater contribution of cerebral than extracerebral hemodynamics to near-infrared spectroscopy signals for functional activation and resting-state connectivity in infants

While near-infrared spectroscopy (NIRS) has been increasingly applied to neuroimaging and functional connectivity studies in infants, it has not been quantitatively examined as to what extent the deep tissue (such as cerebral tissue) as opposed to shallow tissue (such as scalp), contributes to NIRS signals measured in infants. A method for separating the effects of deep- and shallow-tissue layers was applied to data of nine sleeping three-month-old infants who had been exposed to 3-s speech sounds or silence (i.e., resting state) and whose hemodynamic changes over their bilateral temporal cortices had been measured by using an NIRS system with multiple source-detector (S-D) distances. The deep-layer contribution was found to be large during resting [67% at S-D 20 mm, 78% at S-D 30 mm for oxygenated hemoglobin (oxy-Hb)] as well as during the speech condition (72% at S-D 20 mm, 82% at S-D 30 mm for oxy-Hb). A left-right connectivity analysis showed that correlation coefficients between left and right channels did not differ between original- and deep-layer signals under no-stimulus conditions and that of original- and deep-layer signals were larger than those of the shallow layer. These results suggest that NIRS signals obtained in infants with appropriate S-D distances largely reflected cerebral hemodynamic changes.

Towards a near infrared spectroscopy-based estimation of operator attentional state

Given the critical risks to public health and safety that can involve lapses in attention (e.g., through implication in workplace accidents), researchers have sought to develop cognitive-state tracking technologies, capable of alerting individuals engaged in cognitively demanding tasks of potentially dangerous decrements in their levels of attention. The purpose of the present study was to address this issue through an investigation of the reliability of optical measures of cortical correlates of attention in conjunction with machine learning techniques to distinguish between states of full attention and states characterized by reduced attention capacity during a sustained attention task. Seven subjects engaged in a 30 minutes duration sustained attention reaction time task with near infrared spectroscopy (NIRS) monitoring over the prefrontal and the right parietal areas. NIRS signals from the first 10 minutes of the task were considered as characterizing the ‘full attention’ class, while the NIRS signals from the last 10 minutes of the task were considered as characterizing the ‘attention decrement’ class. A two-class support vector machine algorithm was exploited to distinguish between the two levels of attention using appropriate NIRS-derived signal features. Attention decrement occurred during the task as revealed by the significant increase in reaction time in the last 10 compared to the first 10 minutes of the task (p<.05). The results demonstrate relatively good classification accuracy, ranging from 65 to 90%. The highest classification accuracy results were obtained when exploiting the oxyhemoglobin signals (i.e., from 77 to 89%, depending on the cortical area considered) rather than the deoxyhemoglobin signals (i.e., from 65 to 66%). Moreover, the classification accuracy increased to 90% when using signals from the right parietal area rather than from the prefrontal cortex. The results support the feasibility of developing cognitive tracking technologies using NIRS and machine learning techniques.

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation processes on multiple time scales. The goal of the present study was to identify the main physiological noise contributions in fNIRS forehead signals and to develop a method for physiological de-noising of fNIRS data. To achieve this goal we combined concurrent time-domain fNIRS and peripheral physiology recordings with wavelet coherence analysis (WCA). Depth selectivity was achieved by analyzing moments of photon time-of-flight distributions provided by time-domain fNIRS. Simultaneously, mean arterial blood pressure (MAP), heart rate (HR), and skin blood flow (SBF) on the forehead were recorded. WCA was employed to quantify the impact of physiological processes on fNIRS signals separately for different time scales. We identified three main processes contributing to physiological noise in fNIRS signals on the forehead. The first process with the period of about 3 s is induced by respiration. The second process is highly correlated with time lagged MAP and HR fluctuations with a period of about 10 s often referred as Mayer waves. The third process is local regulation of the facial SBF time locked to the task-evoked fNIRS signals. All processes affect oxygenated haemoglobin concentration more strongly than that of deoxygenated haemoglobin. Based on these results we developed a set of physiological regressors, which were used for physiological de-noising of fNIRS signals. Our results demonstrate that proposed de-noising method can significantly improve the sensitivity of fNIRS to cerebral signals.

Assessment of cerebral perfusion in post-traumatic brain injury patients with the use of ICG-bolus tracking method

The aim of this study was to verify the usefulness of the time-resolved optical method utilizing diffusely reflected photons and fluorescence signals combined with intravenous injection of indocyanine green (ICG) in the assessment of brain perfusion in post-traumatic brain injury patients. The distributions of times of flight (DTOFs) of diffusely reflected photons were acquired together with the distributions of times of arrival (DTAs) of fluorescence photons. The data analysis methodology was based on the observation of delays between the signals of statistical moments (number of photons, mean time of flight and variance) of DTOFs and DTAs related to the inflow of ICG to the extra- and intracerebral tissue compartments. Eleven patients with brain hematoma, 15 patients with brain edema and a group of 9 healthy subjects were included in this study. Statistically significant differences between parameters obtained in healthy subjects and patients with brain hematoma and brain edema were observed. The best optical parameter to differentiate patients and control group was variance of the DTOFs or DTAs. Results of the study suggest that time-resolved optical monitoring of inflow of the ICG seems to be a promising tool for detecting cerebral perfusion insufficiencies in critically ill patients.

Cytochrome c oxidase response to changes in cerebral oxygen delivery in the adult brain shows higher brain-specificity than haemoglobin

The redox state of cerebral mitochondrial cytochrome c oxidase monitored with near-infrared spectroscopy (Δ[oxCCO]) is a signal with strong potential as a non-invasive, bedside biomarker of cerebral metabolic status. We hypothesised that the higher mitochondrial density of brain compared to skin and skull would lead to evidence of brain-specificity of the Δ[oxCCO] signal when measured with a multi-distance near-infrared spectroscopy (NIRS) system. Measurements of Δ[oxCCO] as well as of concentration changes in oxygenated (Δ[HbO₂]) and deoxygenated haemoglobin (Δ[HHb]) were taken at multiple source-detector distances during systemic hypoxia and hypocapnia (decrease in cerebral oxygen delivery), and hyperoxia and hypercapnia (increase in cerebral oxygen delivery) from 15 adult healthy volunteers. Increasing source-detector spacing is associated with increasing light penetration depth and thus higher sensitivity to cerebral changes. An increase in Δ[oxCCO] was observed during the challenges that increased cerebral oxygen delivery and the opposite was observed when cerebral oxygen delivery decreased. A consistent pattern of statistically significant increasing amplitude of the Δ[oxCCO] response with increasing light penetration depth was observed in all four challenges, a behaviour that was distinctly different from that of the haemoglobin chromophores, which did not show this statistically significant depth gradient. This depth-dependence of the Δ[oxCCO] signal corroborates the notion of higher concentrations of CCO being present in cerebral tissue compared to extracranial components and highlights the value of NIRS-derived Δ[oxCCO] as a brain-specific signal of cerebral metabolism, superior in this aspect to haemoglobin.

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NIRS was used to measure oxidised cytochrome c oxidase (Δ[oxCCO]) in healthy brain.

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Δ[oxCCO] changed in the same direction as changes in cerebral oxygen delivery.

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Magnitude of Δ[oxCCO] response increased with increasing light penetration depth.

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Corresponding haemoglobin changes showed no dependence on light penetration depth.

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NIRS-measured Δ[oxCCO] has higher brain specificity than haemoglobin.

A portable wireless near-infrared spatially resolved spectroscopy system for use on brain and muscle

We have designed, built and successfully tested a prototype portable and wireless near-infrared spectroscopy system. It takes forward the well-established series of NIRO spectroscopy instruments made by Hamamatsu Photonics (Hamamatsu City, Japan). It uses an identical optical probe, and has a data acquisition rate of 10 Hz. It illuminates the tissue with laser diode sources at 3 wavelengths of 775, 810 and 850 nm, and detects the reflected light with 2 silicon photodiode detectors at 2 different separations, enabling spatially resolved spectroscopy to be performed. We have tested it with both in vitro and in vivo experiments to establish its basic functionality for use in studies of both brain and muscle.

Neurovascular coupling: in vivo optical techniques for functional brain imaging

Optical imaging techniques reflect different biochemical processes in the brain, which is closely related with neural activity. Scientists and clinicians employ a variety of optical imaging technologies to visualize and study the relationship between neurons, glial cells and blood vessels. In this paper, we present an overview of the current optical approaches used for the in vivo imaging of neurovascular coupling events in small animal models. These techniques include 2-photon microscopy, laser speckle contrast imaging (LSCI), voltage-sensitive dye imaging (VSDi), functional photoacoustic microscopy (fPAM), functional near-infrared spectroscopy imaging (fNIRS) and multimodal imaging techniques. The basic principles of each technique are described in detail, followed by examples of current applications from cutting-edge studies of cerebral neurovascular coupling functions and metabolic. Moreover, we provide a glimpse of the possible ways in which these techniques might be translated to human studies for clinical investigations of pathophysiology and disease. In vivo optical imaging techniques continue to expand and evolve, allowing us to discover fundamental basis of neurovascular coupling roles in cerebral physiology and pathophysiology.

Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis

To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation performance of our method, we used the correlation coefficients of a laser-Doppler flowmetry (LDF) signal and a nearest 5-mm S-D distance channel signal with the shallow signal. We demonstrated that the shallow signals have a higher temporal correlation with the LDF signals and with the 5-mm S-D distance channel than the deep signals. These results show the MD-ICA method can discriminate between deep and shallow signals.

Measuring cerebral hemodynamics with a modified magnetoencephalography system

Magnetoencephalography (MEG) systems are designed to noninvasively measure magnetic fields produced by neural electrical currents. This project examines the possibility of measuring hemodynamics with an MEG system that has been modified with dc electromagnets to measure magnetic susceptibility while maintaining the capability of measuring neural dynamics. A forward model is presented that simulates the interaction of an applied magnetic field with changes in magnetic susceptibility in the brain associated with hemodynamics. Model predictions are compared with an experiment where deionized water was pumped into an inverted flask under the MEG sensor array of superconducting quantum interference device (SQUID) gradiometers (R(2) = 0.98, p < 0.001). The forward model was used to simulate the SQUID readouts from hemodynamics in the scalp and brain induced by performing the Valsalva maneuver. Experimental human subject recordings (N = 10) were made from the prefrontal region during Valsalva using concurrent measurement with the modified MEG system and near-infrared spectroscopy (NIRS). The NIRS deoxyhemoglobin signal was found to correlate significantly with the SQUID readouts (R(2) = 0.84, p < 0.01). SQUID noise was found to increase with the applied field, which will need to be mitigated in future work. These results demonstrate the potential and technical challenges of measuring cerebral hemodynamics with a modified MEG system.

A working memory deficit among dyslexic readers with no phonological impairment as measured using the n-back task: an fNIR study

Data indicated that dyslexic individuals exhibited difficulties on tasks involving Working Memory (WM). Previous studies have suggested that these deficits stem from impaired processing in the Phonological Loop (PL). The PL impairment was connected to poor phonological processing. However, recent data has pointed to the Central Executive (CE) system as another source of WM deficit in dyslexic readers. This opened a debate whether the WM deficit stems solely from PL or can also be seen as an outcome of poor CE processing. In an attempt to verify this question, the current study compared adult skilled and compensated dyslexic readers with no impairment of phonological skills. The participants' PL and CE processing were tested by using the fNIR device attached to the frontal lobe and measured the changes in brain oxygen values when performing N-back task. As it was previously suggested, the N = 0 represented PL and N = 1 to 3 represent CE processing. It was hypothesized that dyslexic readers who show non-impaired phonological skills will exhibit deficits mainly in the CE subsystem and to a lesser extent in the PL. Results indicated that the two reading level groups did not differ in their accuracy and reaction times in any of the N-Back conditions. However, the dyslexic readers demonstrated significant lower maximum oxyHb values in the upper left frontal lobe, mainly caused due to a significant lower activity under the N = 1 condition. Significant task effects were found in the medial left hemisphere, and the high medial right hemisphere. In addition, significant correlations between fNIR-features, reading performance and speed of processing were found. The higher oxyHb values, the better reading and speed of processing performance obtained. The results of the current study support the hypothesis that at least for the group of dyslexics with non-impaired PL, WM deficit stems from poor CE activity.

The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy

A major methodological challenge of functional near-infrared spectroscopy (fNIRS) is its high sensitivity to haemodynamic fluctuations in the scalp. Superficial fluctuations contribute on the one hand to the physiological noise of fNIRS, impairing the signal-to-noise ratio, and may on the other hand be erroneously attributed to cerebral changes, leading to false positives in fNIRS experiments. Here we explore the localisation, time course and physiological origin of task-evoked superficial signals in fNIRS and present a method to separate them from cortical signals. We used complementary fNIRS, fMRI, MR-angiography and peripheral physiological measurements (blood pressure, heart rate, skin conductance and skin blood flow) to study activation in the frontal lobe during a continuous performance task. The General Linear Model (GLM) was applied to analyse the fNIRS data, which included an additional predictor to account for systemic changes in the skin. We found that skin blood volume strongly depends on the cognitive state and that sources of task-evoked systemic signals in fNIRS are co-localized with veins draining the scalp. Task-evoked superficial artefacts were mainly observed in concentration changes of oxygenated haemoglobin and could be effectively separated from cerebral signals by GLM analysis. Based on temporal correlation of fNIRS and fMRI signals with peripheral physiological measurements we conclude that the physiological origin of the systemic artefact is a task-evoked sympathetic arterial vasoconstriction followed by a decrease in venous volume. Since changes in sympathetic outflow accompany almost any cognitive and emotional process, we expect scalp vessel artefacts to be present in a wide range of fNIRS settings used in neurocognitive research. Therefore a careful separation of fNIRS signals originating from activated brain and from scalp is a necessary precondition for unbiased fNIRS brain activation maps.

Load-dependent brain activation assessed by time-domain functional near-infrared spectroscopy during a working memory task with graded levels of difficulty

We evaluated frontal brain activation during a mixed attentional/working memory task with graded levels of difficulty in a group of 19 healthy subjects, by means of time-domain functional near-infrared spectroscopy (fNIRS). Brain activation was assessed, and load-related oxy- and deoxy-hemoglobin changes were studied. Generalized linear model (GLM) was applied to the data to explore the metabolic processes occurring during the mental effort and, possibly, their involvement in short-term memorization. GLM was applied to the data twice: for modeling the task as a whole and for specifically investigating brain activation at each cognitive load. This twofold employment of GLM allowed (1) the extraction and isolation of different information from the same signals, obtained through the modeling of different cognitive categories (sustained attention and working memory), and (2) the evaluation of model fitness, by inspection and comparison of residuals (i.e., unmodeled part of the signal) obtained in the two different cases. Results attest to the presence of a persistent attentional-related metabolic activity, superimposed to a task-related mnemonic contribution. Some hemispherical differences have also been highlighted frontally: deoxy-hemoglobin changes manifested a strong right lateralization, whereas modifications in oxy- and total hemoglobin showed a medial localization. The present work successfully explored the capability of fNIRS to detect the two neurophysiological categories under investigation and distinguish their activation patterns.