Dynamic model for the tissue concentration and oxygen saturation of hemoglobin in relation to blood volume, flow velocity, and oxygen consumption: Implications for functional neuroimaging and coherent hemodynamics spectroscopy (CHS)

Low frequency oscillations reflect neurovascular coupling and disappear after cerebral death

Spectrum power analysis in the low frequency oscillations (LFO) region of functional near infrared spectroscopy (fNIRS) is a promising method to deliver information about brain activation and therefore might be used for prognostication in patients with disorders of consciousness in the neurocritical care unit alongside with established methods. In this study, we measure the cortical hemodynamic response measured by fNIRS in the LFO region following auditory and somatosensory stimulation in healthy subjects. The significant hemodynamic reaction in the contralateral hemisphere correlation with the physiologic electric response suggests neurovascular coupling. In addition, we investigate power spectrum changes in steady state measurements of cerebral death patients and healthy subjects in the LFO region, the frequency of the heartbeat and respiration. The spectral power within the LFO region was lower in the patients with cerebral death compared to the healthy subjects, whereas there were no differences in spectral power for physiological activities such as heartbeat and respiration rate. This finding indicates the cerebral origin of our low frequency measurements. Therefore, LFO measurements are a potential method to detect brain activation in patients with disorders of consciousness and cerebral death. However, further studies in patients are needed to investigate its potential clinical use.

A priori free spectral unmixing with periodic absorbance changes: application for auto-calibrated intraoperative functional brain mapping

Spectral unmixing designates techniques that allow to decompose measured spectra into linear or non-linear combination of spectra of all targets (endmembers). This technique was initially developed for satellite applications, but it is now also widely used in biomedical applications. However, several drawbacks limit the use of these techniques with standard optical devices like RGB cameras. The devices need to be calibrated and a a priori on the observed scene is often necessary. We propose a new method for estimating endmembers and their proportion automatically and without calibration of the acquisition device based on near separable non-negative matrix factorization. This method estimates the endmembers on spectra of absorbance changes presenting periodic events. This is very common in in vivo biomedical and medical optical imaging where hemodynamics dominate the absorbance fluctuations. We applied the method for identifying functional brain areas during neurosurgery using four different RGB cameras (an industrial camera, a smartphone and two surgical microscopes). Results obtained with the auto-calibration method were consistent with the intraoperative gold standards. Endmembers estimated with the auto-calibration method were similar to the calibrated endmembers used in the modified Beer-Lambert law. The similarity was particularly strong when both cardiac and respiratory periodic events were considered. This work can allow a widespread use of spectral imaging in the industrial or medical field.

The Comparison of Early Hemodynamic Response to Single-Pulse Transcranial Magnetic Stimulation following Inhibitory or Excitatory Theta Burst Stimulation on Motor Cortex

We present a new study design aiming to enhance the understanding of the mechanism by which continuous theta burst stimulation (cTBS) or intermittent theta burst stimulation (iTBS) paradigms elicit cortical modulation. Using near-infrared spectroscopy (NIRS), we compared the cortical hemodynamics of the previously inhibited (after cTBS) or excited (after iTBS) left primary motor cortex (M1) as elicited by single-pulse TMS (spTMS) in a cross-over design. Mean relative changes in hemodynamics within 6 s of the stimulus were compared using a two-sample t-test (p < 0.05) and linear mixed model between real and sham stimuli and between stimuli after cTBS and iTBS. Only spTMS after cTBS resulted in a significant increase (p = 0.04) in blood volume (BV) compared to baseline. There were no significant changes in other hemodynamic parameters (oxygenated/deoxygenated hemoglobin). spTMS after cTBS induced a larger increase in BV than spTMS after iTBS (p = 0.021) and sham stimulus after cTBS (p = 0.009). BV showed no significant difference between real and sham stimuli after iTBS (p = 0.37). The greater hemodynamic changes suggest increased vasomotor reactivity after cTBS compared to iTBS. In addition, cTBS could decrease lateral inhibition, allowing activation of surrounding areas after cTBS.

In vivo structural and functional imaging of human nailbed microvasculature using photoacoustic microscopy

Monitoring microvascular structure and function is of great significance for the diagnosis of many diseases. In this study, we demonstrate the feasibility of OR-PAM to nailbed microcirculation detection as a new, to the best of our knowledge, application scenario in humans. We propose a dual-wavelength optical-resolution photoacoustic microscopy (OR-PAM) with improved local-flexible coupling to image human nailbed microvasculature. Microchip lasers with 532 nm wavelength are employed as the pump sources. The 558 nm laser is generated from the 532 nm laser through the stimulated Raman scattering effect. The flowing water, circulated by a peristaltic pump, maintains the acoustic coupling between the ultrasonic transducer and the sample. These designs improve the sensitivity, practicality, and stability of the OR-PAM system for human in vivo experiments. The imaging of the mouse ear demonstrates the ability of our system to acquire structural and functional information. Then, the system is applied to image human nailbed microvasculature. The imaging results reveal that the superficial capillaries are arranged in a straight sagittal pattern, approximately parallel to the long axis of the finger. The arterial and venular limbs are distinguished according to their oxygen saturation differences. Additionally, the images successfully discover the capillary loops with single or multiple twists, the oxygen release at the end of the capillary loop, and the changes when the nailbed is abnormal.

Increased brain microvascular hemoglobin concentrations in children with cerebral malaria

Brain swelling is associated with death from cerebral malaria, but it is unclear whether brain swelling is caused by cerebral edema or vascular congestion-two pathological conditions with distinct effects on tissue hemoglobin concentrations. We used near-infrared spectroscopy (NIRS) to noninvasively study cerebral microvascular hemoglobin concentrations in 46 Malawian children with cerebral malaria. Cerebral malaria was defined by the presence of the malaria parasite Plasmodium falciparum on a blood smear, a Blantyre coma score of 2 or less, and retinopathy. Children with uncomplicated malaria (n = 33) and healthy children (n = 29) were enrolled as comparators. Cerebral microvascular hemoglobin concentrations were higher among children with cerebral malaria compared with those with uncomplicated malaria [median (25th, 75th): 145.2 (95.2, 190.0) μM versus 82.9 (65.7, 105.4) μM, P = 0.008]. Cerebral microvascular hemoglobin concentrations correlated with brain swelling score determined by MRI (r = 0.37, P = 0.03). Fluctuations in cerebral microvascular hemoglobin concentrations over a 30-min time period were characterized using detrended fluctuation analysis (DFA). DFA determined self-similarity of the cerebral microvascular hemoglobin concentration signal to be lower among children with cerebral malaria compared with those with uncomplicated malaria [0.63 (0.54, 0.70) versus 0.91 (0.82, 0.94), P < 0.0001]. The lower self-similarity of the hemoglobin concentration signal in children with cerebral malaria suggested impaired regulation of cerebral blood flow. The elevated cerebral tissue hemoglobin concentration and its correlation with brain swelling suggested that excess blood volume, potentially due to vascular congestion, may contribute to brain swelling in cerebral malaria.

A model of neurovascular coupling and its application to cortical spreading depolarization

Cortical spreading depolarization (CSD) is a neuropathological condition involving propagating waves of neuronal silence, and is related to multiple diseases, such as migraine aura, traumatic brain injury (TBI), stroke, and cardiac arrest, as well as poor outcome of patients. While CSDs of different severity share similar roots on the ion exchange level, they can lead to different vascular responses (namely spreading hyperemia and spreading ischemia). In this paper, we propose a mathematical model relating neuronal activities to predict vascular changes as measured with near-infrared spectroscopy (NIRS) and fMRI recordings, and apply it to the extreme case of CSD, where sustained near-complete neuronal depolarization is seen. We utilize three serially connected models (namely, ion exchange, neurovascular coupling, and hemodynamic model) which are described by differential equations. Propagating waves of ion concentrations, as well as the associated vasodynamics and hemodynamics, are simulated by solving these equations. Our proposed model predicts vasodynamics and hemodynamics that agree both qualitatively and quantitatively with experimental literature. Mathematical modeling and simulation offer a powerful tool to help understand the underlying mechanisms of CSD and help interpret the data. In addition, it helps develop novel monitoring techniques prior to data collection. Our simulated results strongly suggest that fMRI is unable to reliably distinguish between spreading hyperemia and spreading ischemia, while NIRS signals are substantially distinct in the two cases.

Intraoperative identification of functional brain areas with RGB imaging using statistical parametric mapping: Simulation and clinical studies

Complementary technique to preoperative fMRI and electrical brain stimulation (EBS) for glioma resection could improve dramatically the surgical procedure and patient care. Intraoperative RGB optical imaging is a technique for localizing functional areas of the human cerebral cortex that can be used during neurosurgical procedures. However, it still lacks robustness to be used with neurosurgical microscopes as a clinical standard. In particular, a robust quantification of biomarkers of brain functionality is needed to assist neurosurgeons. We propose a methodology to evaluate and optimize intraoperative identification of brain functional areas by RGB imaging. This consist in a numerical 3D brain model based on Monte Carlo simulations to evaluate intraoperative optical setups for identifying functional brain areas. We also adapted fMRI Statistical Parametric Mapping technique to identify functional brain areas in RGB videos acquired for 12 patients. Simulation and experimental results were consistent and showed that the intraoperative identification of functional brain areas is possible with RGB imaging using deoxygenated hemoglobin contrast. Optical functional identifications were consistent with those provided by EBS and preoperative fMRI. We also demonstrated that a halogen lighting may be particularity adapted for functional optical imaging. We showed that an RGB camera combined with a quantitative modeling of brain hemodynamics biomarkers can evaluate in a robust way the functional areas during neurosurgery and serve as a tool of choice to complement EBS and fMRI.

Dissociated coupling between cerebral oxygen metabolism and perfusion in the prefrontal cortex during exercise: a NIRS study

Purpose: The present study used near-infrared spectroscopy to investigate the relationships between cerebral oxygen metabolism and perfusion in the prefrontal cortex (PFC) during exercises of different intensities. Methods: A total of 12 recreationally active men (age 24 ± 6 years) were enrolled. They performed 17 min of low-intensity exercise (ExL), followed by 3 min of moderate-intensity exercise (ExM) at constant loads. Exercise intensities for ExL and ExM corresponded to 30% and 45% of the participants' heart rate reserve, respectively. Cardiovascular and respiratory parameters were measured. We used near-infrared time-resolved spectroscopy (TRS) to measure the cerebral hemoglobin oxygen saturation (ScO2) and total hemoglobin concentration ([HbT]), which can indicate the cerebral blood volume (CBV). As the cerebral metabolic rate for oxygen (CMRO2) is calculated using cerebral blood flow (CBF) and ScO2, we assumed a constant power law relationship between CBF and CBV based on investigations by positron emission tomography (PET). We estimated the relative changes in CMRO2 (rCMRO2) and CBV (rCBV) from the baseline. During ExL and ExM, the rate of perceived exertion was monitored, and alterations in the subjects' mood induced by exercise were evaluated using the Profile of Moods Scale-Brief. Results: Three minutes after exercise initiation, ScO2 decreased and rCMRO2 surpassed rCBV in the left PFC. When ExL changed to ExM, cardiovascular variables and the sense of effort increased concomitantly with an increase in [HbT] but not in ScO2, and the relationship between rCMRO2 and rCBV was dissociated in both sides of the PFC. Immediately after ExM, [HbT], and ScO2 increased, and the disassociation between rCMRO2 and rCBV was prominent in both sides of the PFC. While blood pressure decreased and a negative mood state was less prominent following ExM compared with that at rest, ScO2 decreased 15 min after exercise and rCMRO2 surpassed rCBV in the left PFC. Conclusion: Dissociated coupling between cerebral oxidative metabolism and perfusion in the PFC was consistent with the effort required for increased exercise intensity and associated with post-exercise hypotension and altered mood status after exercise. Our result demonstrates the first preliminary results dealing with the coupling between cerebral oxidative metabolism and perfusion in the PFC using TRS.

Attrition rate in infant fNIRS research: A meta-analysis

Understanding the trends and predictors of attrition rate, or the proportion of collected data that is excluded from the final analyses, is important for accurate research planning, assessing data integrity, and ensuring generalizability. In this pre-registered meta-analysis, we reviewed 182 publications in infant (0-24 months) functional near-infrared spectroscopy (fNIRS) research published from 1998 to April 9, 2020, and investigated the trends and predictors of attrition. The average attrition rate was 34.23% among 272 experiments across all 182 publications. Among a subset of 136 experiments that reported the specific reasons for subject exclusion, 21.50% of the attrition was infant-driven, while 14.21% was signal-driven. Subject characteristics (e.g., age) and study design (e.g., fNIRS cap configuration, block/trial design, and stimulus type) predicted the total and subject-driven attrition rates, suggesting that modifying the recruitment pool or the study design can meaningfully reduce the attrition rate in infant fNIRS research. Based on the findings, we established guidelines for reporting the attrition rate for scientific transparency and made recommendations to minimize the attrition rates. This research can facilitate developmental cognitive neuroscientists in their quest toward increasingly rigorous and representative research.

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.

Functional NIRS to detect covert consciousness in neurocritical patients

OBJECTIVE

This pilot study assesses the feasibility to detect covert consciousness in clinically unresponsive patients by means of functional near infrared spectroscopy (fNIRS) in a real intensive care unit setting. We aimed to verify if the hemodynamic response to familiar music measured with fNIRS varies according to the level consciousness of the patients.

METHODS

22 neurocritical patients and 6 healthy controls were included. The experiment consisted in 3 subsequent blocks including a first resting state recording, a period of music playback and a second resting state recording. fNIRS measurement were performed on each subject with two optodes on the forehead. Main oscillatory frequencies of oxyhemoglobin signal were analyzed. Spectral changes of low frequency oscillations (LFO) between subsequent experimental blocks were used as a marker of cortical response. Cortical response was compared to the level of consciousness of the patients and their functional outcome, through validated clinical scores.

RESULTS

Cortical hemodynamic response to music on the left prefrontal brain was associated with the level of consciousness of the patients and with their clinical outcome after three months.

CONCLUSIONS

Variations in LFO spectral power measured with fNIRS may be a new marker of cortical responsiveness to detect covert consciousness in neurocritical patients. Left prefrontal cortex may play an important role in the perception of familiar music.

SIGNIFICANCE

We showed the feasibility of a simple fNIRS approach to detect cortical response in the real setting of an intensive care unit.

Spatial complexity method for tracking brain development and degeneration using functional near-infrared spectroscopy

Brain complexity analysis using functional near-infrared spectroscopy (fNIRS) has attracted attention as a biomarker for evaluating brain development and degeneration processes. However, most methods have focused on the temporal scale without capturing the spatial complexity. In this study, we propose a spatial time-delay entropy (STDE) method as the spatial complexity measure based on the time-delay measure between two oxy-hemoglobin (Δ[HbO]) or two deoxy-hemoglobin (Δ[Hb]) oscillations within the 0.01-0.1 Hz frequency band. To do this, we analyze fNIRS signals recorded from infants in their sleeping state, children, adults, and healthy seniors in their resting states. We also evaluate the effects of various noise to STDE calculations and STDE's performance in distinguishing various developmental age groups. Lastly, we compare the results with the normalized global spatial complexity (NGSC) and sample entropy (SampEn) measures. Among these measures, STDE_HbO (STDE based on Δ[HbO] oscillations) performs best. The STDE value increases with age throughout childhood (p < 0.001), and then decreases in adults and healthy seniors in the 0.01-0.1 Hz frequency band. This trajectory correlates with cerebrovascular development and degeneration. These findings demonstrate that STDE can be used as a new tool for tracking cerebrovascular development and degeneration across a lifespan based on the fNIRS resting-state measurements.

Increase in Low-Frequency Oscillations in fNIRS as Cerebral Response to Auditory Stimulation with Familiar Music

Recognition of typical patterns of brain response to external stimuli using near-infrared spectroscopy (fNIRS) may become a gateway to detecting covert consciousness in clinically unresponsive patients. This is the first fNIRS study on the cortical hemodynamic response to favorite music using a frequency domain approach. The aim of this study was to identify a possible marker of cognitive response in healthy subjects by investigating variations in the oscillatory signal of fNIRS in the spectral regions of low-frequency (LFO) and very-low-frequency oscillations (VLFO). The experiment consisted of two periods of exposure to preferred music, preceded and followed by a resting phase. Spectral power in the LFO region increased in all the subjects after the first exposure to music and decreased again in the subsequent resting phase. After the second music exposure, the increase in LFO spectral power was less distinct. Changes in LFO spectral power were more after first music exposure and the repetition-related habituation effect strongly suggest a cerebral origin of the fNIRS signal. Recognition of typical patterns of brain response to specific environmental stimulation is a required step for the concrete validation of a fNIRS-based diagnostic tool.

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.

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.

Advances in translational imaging of the microcirculation

The past few decades have seen an explosion in the development and use of methods for imaging the human microcirculation during health and disease. The confluence of innovative imaging technologies, affordable computing power, and economies of scale have ushered in a new era of "translational" imaging that permit us to peer into blood vessels of various organs in the human body. These imaging techniques include near-infrared spectroscopy (NIRS), positron emission tomography (PET), and magnetic resonance imaging (MRI) that are sensitive to microvascular-derived signals, as well as computed tomography (CT), optical imaging, and ultrasound (US) imaging that are capable of directly acquiring images at, or close to microvascular spatial resolution. Collectively, these imaging modalities enable us to characterize the morphological and functional changes in a tissue's microcirculation that are known to accompany the initiation and progression of numerous pathologies. Although there have been significant advances for imaging the microcirculation in preclinical models, this review focuses on developments in the assessment of the microcirculation in patients with optical imaging, NIRS, PET, US, MRI, and CT, to name a few. The goal of this review is to serve as a springboard for exploring the burgeoning role of translational imaging technologies for interrogating the structural and functional status of the microcirculation in humans, and highlight the breadth of current clinical applications. Making the human microcirculation "visible" in vivo to clinicians and researchers alike will facilitate bench-to-bedside discoveries and enhance the diagnosis and management of disease.

Fluctuations in intracranial pressure can be estimated non-invasively using near-infrared spectroscopy in non-human primates

Intracranial pressure (ICP) is typically measured invasively through a sensor placed inside the brain or a needle inserted into the spinal canal, limiting the patient population on which this assessment can be performed. Currently, non-invasive methods are limited due to lack of sensitivity and thus only apply to extreme cases of increased ICP, instead of use in general clinical practice. We demonstrate a novel application for near-infrared spectroscopy (NIRS) to accurately estimate ICP changes over time. Using a non-human primate (Rhesus Macaque) model, we collected optical data while we induced ICP oscillations at multiple ICP levels obtained by manipulating the height of a fluid column connected via a catheter to the lateral ventricle. Hemodynamic responses to ICP changes were measured at the occipital pole and compared to changes detected by a conventional intraparenchymal ICP probe. We demonstrate that hemoglobin concentrations are highly correlated with induced ICP oscillations and that this response is frequency dependent. We translated the NIRS data into non-invasive ICP measurements via a fitted non-parametric transfer function, demonstrating a match in both magnitude and time alignment with an invasively measured reference. Our results demonstrate that NIRS has the potential for non-invasive ICP monitoring.

Dynamic tracking of microvascular hemoglobin content for continuous perfusion monitoring in the intensive care unit: pilot feasibility study

Purpose: There is a need for bedside methods to monitor oxygen delivery in the microcirculation. Near-infrared spectroscopy commonly measures tissue oxygen saturation, but does not reflect the time-dependent variability of microvascular hemoglobin content (MHC) that attempts to match oxygen supply with demand. The objective of this study is to determine the feasibility of MHC monitoring in critically ill patients using high-resolution near-infrared spectroscopy to assess perfusion in the peripheral microcirculation. Methods: Prospective observational cohort of 36 patients admitted within 48 h at a tertiary intensive care unit. Perfusion was measured on the quadriceps, biceps, and/or deltoid, using the temporal change in optical density at the isosbestic wavelength of hemoglobin (798 nm). Continuous wavelet transform was applied to the hemoglobin signal to delineate frequency ranges corresponding to physiological oscillations in the cardiovascular system. Results: 31/36 patients had adequate signal quality for analysis, most commonly affected by motion artifacts. MHC signal demonstrates inter-subject heterogeneity in the cohort, indicated by different patterns of variability and frequency composition. Signal characteristics were concordant between muscle groups in the same patient, and correlated with systemic hemoglobin levels and oxygen saturation. Signal power was lower for patients receiving vasopressors, but not correlated with mean arterial pressure. Mechanical ventilation directly impacts MHC in peripheral tissue. Conclusion: MHC can be measured continuously in the ICU with high-resolution near-infrared spectroscopy, and reflects the dynamic variability of hemoglobin distribution in the microcirculation. Results suggest this novel hemodynamic metric should be further evaluated for diagnosing microvascular dysfunction and monitoring peripheral perfusion.

Dynamic microcirculation PIPE model for functional neuroimaging, non-neuroimaging, and coherent hemodynamics spectroscopy: blood volume and flow velocity variations, and vascular autoregulation

We present a dynamic microcirculation PIPE model for functional neuroimaging, non-neuroimaging, and coherent hemodynamics spectroscopy. The temporal evolution of the concentration and oxygen saturation of hemoglobin in tissue, comprised of the contributions from the arterioles, capillaries, and venules of microvasculature, is determined by time-resolved hemodynamic and metabolic variations in blood volume, flow velocity, and oxygen consumption with a fluid mechanics treatment. Key parameters regarding microcirculation can be assessed, including the effective blood transit times through the capillaries and the venules, and the rate constant of oxygen release from hemoglobin to tissue. The vascular autoregulation can further be quantified from the relationship between the resolved blood volume and flow velocity variations. The PIPE model shows excellent agreement with the experimental cerebral and cutaneous coherent hemodynamics spectroscopy (CHS) and fMRI-BOLD data. It further identifies the impaired cerebral autoregulation distinctively in hemodialysis patients compared to healthy subjects measured by CHS. This new dynamic microcirculation PIPE model provides a valuable tool for brain and other functional studies with hemodynamic-based techniques. It is instrumental in recovering physiological parameters from analyzing and interpreting the signals measured by hemodynamic-based neuroimaging and non-neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) in response to brain activation, physiological challenges, or physical maneuvers.

Changes in cerebral oxygenation and cerebral blood flow during hemodialysis - A simultaneous near-infrared spectroscopy and positron emission tomography study

Near-infrared spectroscopy (NIRS) is used to monitor cerebral tissue oxygenation (rSO₂) depending on cerebral blood flow (CBF), cerebral blood volume and blood oxygen content. We explored whether NIRS might be a more easy applicable proxy to [¹⁵O]H₂O positron emission tomography (PET) for detecting CBF changes during hemodialysis. Furthermore, we compared potential determinants of rSO₂ and CBF. In 12 patients aged ≥ 65 years, NIRS and PET were performed simultaneously: before (T1), early after start (T2), and at the end of hemodialysis (T3). Between T1 and T3, the relative change in frontal rSO₂ (ΔrSO₂) was -8 ± 9% (P = 0.001) and -5 ± 11% (P = 0.08), whereas the relative change in frontal gray matter CBF (ΔCBF) was -11 ± 18% (P = 0.009) and -12 ± 16% (P = 0.007) for the left and right hemisphere, respectively. ΔrSO₂ and ΔCBF were weakly correlated for the left (ρ 0.31, P = 0.4), and moderately correlated for the right (ρ 0.69, P = 0.03) hemisphere. The Bland-Altman plot suggested underestimation of ΔCBF by NIRS. Divergent associations of pH, pCO₂ and arterial oxygen content with rSO₂ were found compared to corresponding associations with CBF. In conclusion, NIRS could be a proxy to PET to detect intradialytic CBF changes, although NIRS and PET capture different physiological parameters of the brain.

Dynamic cerebral autoregulation estimates derived from near infrared spectroscopy and transcranial Doppler are similar after correction for transit time and blood flow and blood volume oscillations

We analysed mean arterial blood pressure, cerebral blood flow velocity, oxygenated haemoglobin and deoxygenated haemoglobin signals to estimate dynamic cerebral autoregulation. We compared macrovascular (mean arterial blood pressure-cerebral blood flow velocity) and microvascular (oxygenated haemoglobin-deoxygenated haemoglobin) dynamic cerebral autoregulation estimates during three different conditions: rest, mild hypocapnia and hypercapnia. Microvascular dynamic cerebral autoregulation estimates were created by introducing the constant time lag plus constant phase shift model, which enables correction for transit time, blood flow and blood volume oscillations (TT-BF/BV correction). After TT-BF/BV correction, a significant agreement between mean arterial blood pressure-cerebral blood flow velocity and oxygenated haemoglobin-deoxygenated haemoglobin phase differences in the low frequency band was found during rest (left: intraclass correlation=0.6, median phase difference 29.5° vs. 30.7°, right: intraclass correlation=0.56, median phase difference 32.6° vs. 39.8°) and mild hypocapnia (left: intraclass correlation=0.73, median phase difference 48.6° vs. 43.3°, right: intraclass correlation=0.70, median phase difference 52.1° vs. 61.8°). During hypercapnia, the mean transit time decreased and blood volume oscillations became much more prominent, except for very low frequencies. The transit time related to blood flow oscillations was remarkably stable during all conditions. We conclude that non-invasive microvascular dynamic cerebral autoregulation estimates are similar to macrovascular dynamic cerebral autoregulation estimates, after TT-BF/BV correction is applied. These findings may increase the feasibility of non-invasive continuous autoregulation monitoring and guided therapy in clinical situations.

Phase dual-slopes in frequency-domain near-infrared spectroscopy for enhanced sensitivity to brain tissue: First applications to human subjects

We present a first in vivo application of phase dual-slopes (DSϕ), measured with frequency-domain near-infrared spectroscopy on four healthy human subjects, to demonstrate their enhanced sensitivity to cerebral hemodynamics. During arterial blood pressure oscillations elicited at a frequency of 0.1 Hz, we compare three different ways to analyze either intensity (I) or phase (ϕ) data collected on the subject's forehead at multiple source-detector distances: Single-distance, single-slope and DS. Theoretical calculations based on diffusion theory show that the method with the deepest maximal sensitivity (at about 11 mm) is DSϕ. The in vivo results indicate a qualitative difference of phase data (especially DSϕ) and intensity data (especially single-distance intensity [SDI]), which we assign to stronger contributions from scalp hemodynamics to SDI and from cortical hemodynamics to DSϕ. Our findings suggest that scalp hemodynamic oscillations may be dominated by blood volume dynamics, whereas cortical hemodynamics may be dominated by blood flow velocity dynamics.

Reduced-order modeling of hemodynamics across macroscopic through mesoscopic circulation scales

We propose a hemodynamic reduced-order model bridging macroscopic and mesoscopic blood flow circulation scales from arteries to capillaries. In silico tree-like vascular geometries, mathematically described by graphs, are synthetically generated by means of stochastic growth algorithms constrained by statistical morphological and topological principles. Scale-specific pruning gradation of the tree is then proposed in order to fit computational budget requirement. Different compliant structural models with respect to pressure loads are used depending on vessel walls thicknesses and structures, which vary considerably from macroscopic to mesoscopic circulation scales. Nonlinear rheological properties of blood are also included, and microcirculation network responses are computed for different rheologies. Numerical results are in very good agreement with available experimental measurements. The computational model captures the dynamic transition between large- to small-scale flow pulsatility speeds and magnitudes and wall shear stresses, which have wide-ranging physiological influences.

Cerebral Microcirculatory Blood Flow Dynamics During Rest and a Continuous Motor Task

Objectives: To examine the brain’s microcirculatory response over the course of a continuous 5-min elbow movement task in order to estimate its potential role in grading vaso-neural coupling compared to the macrocirculatory response.

Methods: We simultaneously recorded cerebral blood flow velocity (CBFV), changes in oxygenated/deoxygenated hemoglobin concentrations ([oxHb], [deoxHb]), blood pressure (BP), and end-tidal CO₂ over 5-min periods of rest and left elbow movements in 24 healthy persons (13 women and 11 men of mean age ± SD, 38 ± 11 years). A low frequency range (0.07–0.15 Hz) was used for analysis by transfer function estimates of phase and gain.

Results: Elbow movement led to a small BP increase (mean BP at rest 83 mm Hg, at movement 87; p < 0.01) and a small ETCO₂ decrease (at rest 44.6 mm Hg, at movement 41.7 mm Hg; p < 0.01). Further, it increased BP-[oxHb] phase from 55° (both sides) to 74° (right; p < 0.05)/69° (left; p < 0.05), and BP-[deoxHb] phase from 264° (right)/270° (left) to 288° (right; p < 0.05)/297° (left; p = 0.09). The cerebral mean transit time at 0.1 Hz of 5.6 s of rest remained unchanged by movement. Elbow movement significantly decreased BP-CBFV gain on both sides, and BP-CBFV phase only on the right side (p = 0.05).

Conclusion: Elbow movement leads to an increased time delay between BP and [oxHb]/[deoxHb] while leaving the cerebral mean transit time unchanged. Phase shifting is usually the more robust parameter when using a transfer function to estimate dynamic cerebral autoregulation; phase shifting at the microcirculatory level seems to be a better marker of VNC-induced changes than phase shifting between BP and CBFV.

Modeling and classification of voluntary and imagery movements for brain-computer interface from fNIR and EEG signals through convolutional neural network

Practical brain-computer interface (BCI) demands the learning-based adaptive model that can handle diverse problems. To implement a BCI, usually functional near-infrared spectroscopy (fNIR) is used for measuring functional changes in brain oxygenation and electroencephalography (EEG) for evaluating the neuronal electric potential regarding the psychophysiological activity. Since the fNIR modality has an issue of temporal resolution, fNIR alone is not enough to achieve satisfactory classification accuracy as multiple neural stimuli are produced by voluntary and imagery movements. This leads us to make a combination of fNIR and EEG with a view to developing a BCI model for the classification of the brain signals of the voluntary and imagery movements. This work proposes a novel approach to prepare functional neuroimages from the fNIR and EEG using eight different movement-related stimuli. The neuroimages are used to train a convolutional neural network (CNN) to formulate a predictive model for classifying the combined fNIR-EEG data. The results reveal that the combined fNIR-EEG modality approach along with a CNN provides improved classification accuracy compared to a single modality and conventional classifiers. So, the outcomes of the proposed research work will be very helpful in the implementation of the finer BCI system.

Dual-slope method for enhanced depth sensitivity in diffuse optical spectroscopy

Using diffusion theory, we show that a dual-slope method is more effective than single-slope methods or single-distance methods at enhancing sensitivity to deeper tissue. The dual-slope method requires a minimum of two sources and two detectors arranged in specially configured arrays. In particular, we present diffusion theory results for a symmetrical linear array of two sources (separated by 55 mm) that sandwich two detectors (separated by 15 mm), for which dual slopes achieve maximal sensitivity at a depth of about 5 mm for direct current (DC) intensity (as measured in continuous-wave spectroscopy) and 11 mm for phase (as measured in frequency-domain spectroscopy) under typical values of the tissue optical properties (absorption coefficient: ∼0.01mm^-1, reduced scattering coefficient: ∼1mm^-1). This result is a major advance over single-distance or single-slope data, which feature maximal sensitivity to shallow tissue (<2mm for the intensity, <5mm for the phase).

Axial variation of deoxyhemoglobin density as a source of the low-frequency time lag structure in blood oxygenation level-dependent signals

Perfusion-related information is reportedly embedded in the low-frequency component of a blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. The blood-propagation pattern through the cerebral vascular tree is detected as an interregional lag variation of spontaneous low-frequency oscillations (sLFOs). Mapping of this lag, or phase, has been implicitly treated as a projection of the vascular tree structure onto real space. While accumulating evidence supports the biological significance of this signal component, the physiological basis of the “perfusion lag structure,” a requirement for an integrative resting-state fMRI-signal model, is lacking. In this study, we conducted analyses furthering the hypothesis that the sLFO is not only largely of systemic origin, but also essentially intrinsic to blood, and hence behaves as a virtual tracer. By summing the small fluctuations of instantaneous phase differences between adjacent vascular regions, a velocity response to respiratory challenges was detected. Regarding the relationship to neurovascular coupling, the removal of the whole lag structure, which can be considered as an optimized global-signal regression, resulted in a reduction of inter-individual variance while preserving the fMRI response. Examination of the T2* and S₀, or non-BOLD, components of the fMRI signal revealed that the lag structure is deoxyhemoglobin dependent, while paradoxically presenting a signal-magnitude reduction in the venous side of the cerebral vasculature. These findings provide insight into the origin of BOLD sLFOs, suggesting that they are highly intrinsic to the circulating blood.

Multi-distance frequency-domain optical measurements of coherent cerebral hemodynamics

We report non-invasive, bilateral optical measurements on the forehead of five healthy human subjects, of 0.1 Hz oscillatory hemodynamics elicited either by cyclic inflation of pneumatic thigh cuffs, or by paced breathing. Optical intensity and the phase of photon-density waves were collected with frequency-domain near-infrared spectroscopy at seven source-detector distances (11-40 mm). Coherent hemodynamic oscillations are represented by phasors of oxyhemoglobin (O) and deoxyhemoglobin (D) concentrations, and by the vector D/O that represents the amplitude ratio and phase difference of D and O. We found that, on average, the amplitude ratio (|D/O|) and the phase difference (∠(D/O)) obtained with single-distance intensity at 11-40 mm increase from 0.1 and -330°, to 0.2 and -200°, respectively. Single-distance phase and the intensity slope featured a weaker dependence on source-detector separation, and yielded |D/O| and ∠(D/O) values of about 0.5 and -200°, respectively, at distances greater than 20 mm. The key findings are: (1) single-distance phase and intensity slope are sensitive to deeper tissue compared to single-distance intensity; (2) deeper tissue hemodynamic oscillations, which more closely represent the brain, feature D and O phasors that are consistent with a greater relative flow-to-volume contributions in brain tissue compared to extracerebral, superficial tissue.

Influence of intra-abdominal pressure on the amplitude of fluctuations of cerebral hemoglobin concentration in the respiratory band

An intra-abdominal pressure (IAP) is correlated with cerebral perfusion, in a mechanism of reducing venous outflow. The elevated intra-abdominal pressure leads to an increase in the intracranial pressure and a decrease in the cerebral perfusion pressure. We studied the relationship between the IAP and the cerebral oxygenation with the use of the near infrared spectroscopy technique during a gynecological surgery. The changes in hemoglobin concentrations were analyzed in the time-frequency domain in the frequency band related to respiration. The measurements were carried out in 15 subjects who underwent laparoscopic surgery. During the laparoscopy, the intra-abdominal cavity was insufflated with CO₂, which caused a controlled increase in the IAP. It was observed that the amplitudes of respiration-related waves present in hemoglobin concentration signals show an increase of 1.5 to 8.5 times during elevation of the IAP by 15 mmHg.

Quantitative measurements of cerebral blood flow with near-infrared spectroscopy

We propose a new near-infrared spectroscopy (NIRS) method for quantitative measurements of cerebral blood flow (CBF). Because this method uses concepts of coherent hemodynamics spectroscopy (CHS), we identify this new method with the acronym NIRS-CHS. We tested this method on the prefrontal cortex of six healthy human subjects during mean arterial pressure (MAP) transients induced by the rapid deflation of pneumatic thigh cuffs. A comparison of CBF dynamics measured with NIRS-CHS and with diffuse correlation spectroscopy (DCS) showed a good agreement for characteristic times of the CBF transient. We also report absolute measurements of baseline CBF with NIRS-CHS (69 ± 6 ml/100g/min over the six subjects). NIRS-CHS can provide more accurate measurements of CBF with respect to previously reported NIRS surrogates of CBF.

Frequency-resolved analysis of coherent oscillations of local cerebral blood volume, measured with near-infrared spectroscopy, and systemic arterial pressure in healthy human subjects

We report a study on twenty-two healthy human subjects of the dynamic relationship between cerebral hemoglobin concentration ([HbT]), measured with near-infrared spectroscopy (NIRS) in the prefrontal cortex, and systemic arterial blood pressure (ABP), measured with finger plethysmography. [HbT] is a measure of local cerebral blood volume (CBV). We induced hemodynamic oscillations at discrete frequencies in the range 0.04-0.20 Hz with cyclic inflation and deflation of pneumatic cuffs wrapped around the subject's thighs. We modeled the transfer function of ABP and [HbT] in terms of effective arterial (K(a)) and venous (K(v)) compliances, and a cerebral autoregulation time constant (τ(AR)). The mean values (± standard errors) of these parameters across the twenty-two subjects were K(a) = 0.01 ± 0.01 μM/mmHg, K(v) = 0.09 ± 0.05 μM/mmHg, and τ(AR) = 2.2 ± 1.3 s. Spatially resolved measurements in a subset of eight subjects reveal a spatial variability of these parameters that may exceed the inter-subject variability at a set location. This study sheds some light onto the role that ABP and cerebral blood flow (CBF) play in the dynamics of [HbT] measured with NIRS, and paves the way for new non-invasive optical studies of cerebral blood flow and cerebral autoregulation.

Depth dependence of coherent hemodynamics in the human head

We report a near-infrared spectroscopy (NIRS) study of coherent hemodynamic oscillations measured on the human forehead at multiple source-detector distances (1 to 4 cm). The physiological source of the coherent hemodynamics is arterial blood pressure oscillations at a frequency of 0.1 Hz, induced by cyclic inflation (to a pressure of 200 mmHg) and deflation of two thigh cuffs wrapped around the subject's thighs. To interpret our results, we use a recently developed hemodynamic model and a phasor representation of the oscillations of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations in the tissue (phasors O, D, and T, respectively). The increase in the phase angle between D and O at larger source-detector separations is assigned to greater flow versus volume contributions and to a stronger blood flow autoregulation in deeper tissue (brain cortex) with respect to superficial tissue (scalp and skull). The relatively constant phase lag of T versus arterial blood pressure oscillations at all source-detector distances was assigned to competing effects from stronger autoregulation and smaller arterial-to-venous contributions in deeper tissue with respect to superficial tissue. We demonstrate the application of a hemodynamic model to interpret coherent hemodynamics measured with NIRS and to assess the different nature of shallow (extracerebral) versus deep (cerebral) tissue hemodynamics.

Perspective: Prospects of non-invasive sensing of the human brain with diffuse optical imaging

Since the initial demonstration of near-infrared spectroscopy (NIRS) for noninvasive measurements of brain perfusion and metabolism in the 1970s, and its application to functional brain studies (fNIRS) in the 1990s, the field of noninvasive optical studies of the brain has been continuously growing. Technological developments, data analysis advances, and novel areas of application keep advancing the field. In this article, we provide a view of the state of the field of cerebral NIRS, starting with a brief historical introduction and a description of the information content of the NIRS signal. We argue that NIRS and fNIRS studies should always report data of both oxy- and deoxyhemoglobin concentrations in brain tissue, as they complement each other to provide more complete functional and physiological information, and may help identify different types of confounds. One significant challenge is the assessment of absolute tissue properties, be them optical or physiological, so that relative measurements account for the vast majority of NIRS and fNIRS applications. However, even relative measurements of hemodynamics or metabolic changes face the major problem of a potential contamination from extracerebral tissue layers. Accounting for extracerebral contributions to fNIRS signals is one of the most critical barriers in the field. We present some of the approaches that were proposed to tackle this challenge in the study of cerebral hemodynamics and functional connectivity. Finally, we critically compare fNIRS and functional magnetic resonance imaging (fMRI) by relating their measurements in terms of signal and noise, and by commenting on their complementarity.

The meaning of "coherent" and its quantification in coherent hemodynamics spectroscopy

We have recently introduced a new technique, coherent hemodynamics spectroscopy (CHS), which aims at characterizing a specific kind of tissue hemodynamics that feature a high level of covariation with a given physiological quantity. In this study, we carry out a detailed analysis of the significance of coherence and phase synchronization between oscillations of arterial blood pressure (ABP) and total hemoglobin concentration ([Hbt]), measured with near-infrared spectroscopy (NIRS) during a typical protocol for CHS, based on a cyclic thigh cuff occlusion and release. Even though CHS is based on a linear time invariant model between ABP (input) and NIRS measurands (outputs), for practical reasons in a typical CHS protocol, we induce finite "groups" of ABP oscillations, in which each group is characterized by a different frequency. For this reason, ABP (input) and NIRS measurands (output) are not stationary processes, and we have used wavelet coherence and phase synchronization index (PSI), as a metric of coherence and phase synchronization, respectively. PSI was calculated by using both the wavelet cross spectrum and the Hilbert transform. We have also used linear coherence (which requires stationary process) for comparison with wavelet coherence. The method of surrogate data is used to find critical values for the significance of covariation between ABP and [Hbt]. Because we have found similar critical values for wavelet coherence and PSI by using five of the most used methods of surrogate data, we propose to use the data-independent Gaussian random numbers (GRNs), for CHS. By using wavelet coherence and wavelet cross spectrum, and GRNs as surrogate data, we have found the same results for the significance of coherence and phase synchronization between ABP and [Hbt]: on a total set of 20 periods of cuff oscillations, we have found 17 coherent oscillations and 17 phase synchronous oscillations. Phase synchronization assessed with Hilbert transform yielded similar results with 14 phase synchronous oscillations. Linear coherence and wavelet coherence overall yielded similar number of significant values. We discuss possible reasons for this result. Despite the similarity of linear and wavelet coherence, we argue that wavelet coherence is preferable, especially if one wants to use baseline spontaneous oscillations, in which phase locking and coherence between signals might be only temporary.

Symbolic time series analysis of fNIRS signals in brain development assessment

OBJECTIVE

Assessing an infant's brain development remains a challenge for neuroscientists and pediatricians despite great technological advances. As a non-invasive neuroimaging tool, functional near-infrared spectroscopy (fNIRS) has great advantages in monitoring an infant's brain activity. To explore the dynamic features of hemodynamic changes in infants, in-pattern exponent (IPE), anti-pattern exponent (APE), as well as permutation cross-mutual information (PCMI) based on symbolic dynamics are proposed to measure the phase differences and coupling strength in oxyhemoglobin (HbO) and deoxyhemoglobin (Hb) signals from fNIRS.

APPROACH

First, simulated sinusoidal oscillation signals and four coupled nonlinear systems were employed for performance assessments. Hilbert transform based measurements of hemoglobin phase oxygenation and deoxygenation (hPod) and phase-locking index of hPod (hPodL) were calculated for comparison. Then, the IPE, APE and PCMI indices from resting state fNIRS data of preterm, term infants and adults were calculated to estimate the phase difference and coupling of HbO and Hb. All indices' performance was assessed by the degree of monotonicity (DoM). The box plots and coefficients of variation (CV) were employed to assess the measurements and robustness in the results.

MAIN RESULTS

In the simulation analysis, IPE and APE can distinguish the phase difference of two sinusoidal oscillation signals. Both hPodL and PCMI can track the strength of two coupled nonlinear systems. Compared to hPodL, the PCMI had higher DoM indices in measuring the coupling of two nonlinear systems. In the fNIRS data analysis, similar to hPod, the IPE and APE can distinguish preterm, term infants, and adults in 0.01-0.05 Hz, 0.05-0.1 Hz, and 0.01-0.1 Hz frequency bands, respectively. PCMI more effectively distinguished the term and preterm infants than hPodL in the 0.05-0.1 Hz frequency band. As symbolic time series measures, the IPE and APE were able to detect the brain developmental changes in subjects of different ages. PCMI can assess the resting-state HbO and Hb coupling changes across different developmental ages, which may reflect the metabolic and neurovascular development.

SIGNIFICANCE

The symbolic-based methodologies are promising measures for fNIRS in estimating the brain development, especially in assessing newborns' brain developmental status.

Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease

SUMMARY

In this report we introduce a weak-model approach for examination of the intrinsic time-varying properties of the hemoglobin signal, with the aim of advancing the application of functional near infrared spectroscopy (fNIRS) for the detection of breast cancer, among other potential uses. The developed methodology integrates concepts from stochastic network theory with known modulatory features of the vascular bed, and in doing so provides access to a previously unrecognized dense feature space that is shown to have promising diagnostic potential. Notable features of the methodology include access to this information solely from measures acquired in the resting state, and analysis of these by treating the various components of the hemoglobin (Hb) signal as a co-varying interacting system.

APPROACH

The principal data-transform kernel projects Hb state-space trajectories onto a coordinate system that constitutes a finite-state representation of covariations among the principal elements of the Hb signal (i.e., its oxygenated (ΔoxyHb) and deoxygenated (ΔdeoxyHb) forms and the associated dependent quantities: total hemoglobin (ΔtotalHb = ΔoxyHb + ΔdeoxyHb), hemoglobin oxygen saturation (ΔHbO2Sat = 100Δ(oxyHb/totalHb)), and tissue-hemoglobin oxygen exchange (ΔHbO2Exc = ΔdeoxyHb-ΔoxyHb)). The resulting ten-state representation treats the evolution of this signal as a one-space, spatiotemporal network that undergoes transitions from one state to another. States of the network are defined by the algebraic signs of the amplitudes of the time-varying components of the Hb signal relative to their temporal mean values. This assignment produces several classes of coefficient arrays, most with a dimension of 10×10.

BIOLOGICAL MOTIVATION

Motivating our approach is the understanding that effector mechanisms that modulate blood delivery to tissue operate on macroscopic scales, in a spatially and temporally varying manner. Also recognized is that this behavior is sensitive to nonlinear actions of these effectors, which include the binding properties of hemoglobin. Accessible phenomenology includes measures of the kinetics and probabilities of network dynamics, which we treat as surrogates for the actions of feedback mechanisms that modulate tissue-vascular coupling.

FINDINGS

Qualitative and quantitative features of this space, and their potential to serve as markers of disease, have been explored by examining continuous-wave fNIRS 3D tomographic time series obtained from the breasts of women who do and do not have breast cancer. Inspection of the coefficient arrays reveals that they are governed predominantly by first-order rate processes, and that each array class exhibits preferred structure that is mainly independent of the others. Discussed are strategies that may serve to extend evaluation of the accessible feature space and how the character of this information holds potential for development of novel clinical and preclinical uses.

Detailed view on slow sinusoidal, hemodynamic oscillations on the human brain cortex by Fourier transforming oxy/deoxy hyperspectral images

Slow sinusoidal, hemodynamic oscillations (SSHOs) around 0.1 Hz are frequently seen in mammalian and human brains. In four patients undergoing epilepsy surgery, subtle but robust fluctuations in oxy‐ and deoxyhemoglobin were detected using hyperspectral imaging of the cortex. These SSHOs were stationary during the entire 4 to 10 min acquisition time. By Fourier filtering the oxy‐ and deoxyhemoglobin time signals with a small bandwidth, SSHOs became visible within localized regions of the brain, with distinctive frequencies and a continuous phase variation within that region. SSHOs of deoxyhemoglobin appeared to have an opposite phase and 11% smaller amplitude with respect to the oxyhemoglobin SSHOs. Although the origin of SSHOs remains unclear, we find indications that the observed SSHOs may embody a local propagating hemodynamic wave with velocities in line with capillary blood velocities, and conceivably related to vasomotion and maintenance of adequate tissue perfusion. Hyperspectral imaging of the human cortex during surgery allow in‐depth characterization of SSHOs, and may give further insight in the nature and potential (clinical) use of SSHOs.

Dynamic autoregulation of cerebral blood flow measured non-invasively with fast diffuse correlation spectroscopy

Cerebral autoregulation (CA) maintains cerebral blood flow (CBF) in the presence of systemic blood pressure changes. Brain injury can cause loss of CA and resulting dysregulation of CBF, and the degree of CA impairment is a functional indicator of cerebral tissue health. Here, we demonstrate a new approach to noninvasively estimate cerebral autoregulation in healthy adult volunteers. The approach employs pulsatile CBF measurements obtained using high-speed diffuse correlation spectroscopy (DCS). Rapid thigh-cuff deflation initiates a chain of responses that permits estimation of rates of dynamic autoregulation in the cerebral microvasculature. The regulation rate estimated with DCS in the microvasculature (median: 0.26 s-1, inter quartile range: 0.19 s-1) agrees well (R = 0.81, slope = 0.9) with regulation rates measured by transcranial Doppler ultrasound (TCD) in the proximal vasculature (median: 0.28 s-1, inter quartile range: 0.10 s-1). We also obtained an index of systemic autoregulation in concurrently measured scalp microvasculature. Systemic autoregulation begins later than cerebral autoregulation and exhibited a different rate (0.55 s-1, inter quartile range: 0.72 s-1). Our work demonstrates the potential of diffuse correlation spectroscopy for bedside monitoring of cerebral autoregulation in the microvasculature of patients with brain injury.

Hemoglobin phase of oxygenation and deoxygenation in early brain development measured using fNIRS

A crucial issue in neonatal medicine is the impact of preterm birth on the developmental trajectory of the brain. Although a growing number of studies have shown alterations in the structure and function of the brain in preterm-born infants, we propose a method to detect subtle differences in neurovascular and metabolic functions in neonates and infants. Functional near-infrared spectroscopy (fNIRS) was used to obtain time-averaged phase differences between spontaneous low-frequency (less than 0.1 Hz) oscillatory changes in oxygenated hemoglobin (oxy-Hb) and those in deoxygenated hemoglobin (deoxy-Hb). This phase difference was referred to as hemoglobin phase of oxygenation and deoxygenation (hPod) in the cerebral tissue of sleeping neonates and infants. We examined hPod in term, late preterm, and early preterm infants with no evidence of clinical issues and found that all groups of infants showed developmental changes in the values of hPod from an in-phase to an antiphase pattern. Comparison of hPod among the groups revealed that developmental changes in hPod in early preterm infants precede those in late preterm and term infants at term equivalent age but then, progress at a slower pace. This study suggests that hPod measured using fNIRS is sensitive to the developmental stage of the integration of circular, neurovascular, and metabolic functions in the brains of neonates and infants.

Correlation between Cerebral Hemodynamic and Perfusion Pressure Changes in Non-Human Primates

The mechanism that maintains a stable blood flow in the brain despite changes in cerebral perfusion pressure (CPP), and therefore guaranties a constant supply of oxygen and nutrients to the neurons, is known as cerebral autoregulation (CA). In a certain range of CPP, blood flow is mediated by a vasomotor adjustment in vascular resistance through dilation of blood vessels. CA is known to be impaired in diseases like traumatic brain injury, Parkinson's disease, stroke, hydrocephalus and others. If CA is impaired, blood flow and pressure changes are coupled and the oxygen supply might be unstable. Lassen's blood flow autoregulation curve describes this mechanism, where a plateau of stable blood flow in a specific range of CPP corresponds to intact autoregulation. Knowing the limits of this plateau and maintaining CPP within these limits can improve patient outcome. Since CPP is influenced by both intracranial pressure and arterial blood pressure, long term changes in either can lead to autoregulation impairment. Non-invasive methods for monitoring blood flow autoregulation are therefore needed. We propose to use Near infrared spectroscopy (NIRS) to fill this need. NIRS is an optical technique, which measures microvascular changes in cerebral hemoglobin concentration. We pe erformed experiments on non-human primates during exsanguination to demonstrate that the limits of blood flow autoregulation can be accessed with NIRS.

Optical oximetry of volume-oscillating vascular compartments: contributions from oscillatory blood flow

We present a quantitative analysis of dynamic diffuse optical measurements to obtain oxygen saturation of hemoglobin in volume oscillating compartments. We used a phasor representation of oscillatory hemodynamics at the heart rate and respiration frequency to separate the oscillations of tissue concentrations of oxyhemoglobin (O) and deoxyhemoglobin (D) into components due to blood volume (subscript V V ) and blood flow (subscript F F ): O=O V +O F O=OV+OF , D=D V +D F D=DV+DF . This is achieved by setting the phase angle Arg(O F )−Arg(O) Arg(OF)−Arg(O) , which can be estimated by a hemodynamic model that we recently developed. We found this angle to be −72  deg −72  deg for the cardiac pulsation at 1 Hz, and −7  deg −7  deg for paced breathing at 0.1 Hz. Setting this angle, we can obtain the oxygen saturation of hemoglobin of the volume-oscillating vascular compartment, S V =|O V |/(|O V |+|D V |) SV=|OV|/(|OV|+|DV|) . We demonstrate this approach with cerebral near-infrared spectroscopy measurements on healthy volunteers at rest (n=4 n=4 ) and during 0.1 Hz paced breathing (n=3 n=3 ) with a 24-channel system. Rest data at the cardiac frequency were used to calculate the arterial saturation, S (a) S(a) ; over all subjects and channels, we found ⟨S V ⟩=⟨S (a) ⟩=0.96±0.02 ⟨SV⟩=⟨S(a)⟩=0.96±0.02 . In the case of paced breathing, we found ⟨S V ⟩=0.66±0.14 ⟨SV⟩=0.66±0.14 , which reflects venous-dominated hemodynamics at the respiratory frequency.

Blood-pressure-induced oscillations of deoxy- and oxyhemoglobin concentrations are in-phase in the healthy breast and out-of-phase in the healthy brain

We present a near-infrared spectroscopy (NIRS) study of local hemodynamics in the breast and the brain (prefrontal cortex) of healthy volunteers in a protocol involving periodic perturbations to the systemic arterial blood pressure. These periodic perturbations were achieved by cyclic inflation (to a pressure of 200 mmHg) and deflation (at frequencies of 0.046, 0.056, 0.063, 0.071, and 0.083 Hz) of two pneumatic cuffs wrapped around the subject’s thighs. As a result of these systemic perturbations, the concentrations of deoxy- and oxyhemoglobin in tissue (D and O , respectively) oscillate at the set frequency. We found that the oscillations of D and O in breast tissue are in-phase at all frequencies considered, a result that we attribute to dominant contributions from blood volume oscillations. In contrast, D and O oscillations in brain tissue feature a frequency-dependent phase difference, which we attribute to significant contributions from cerebral blood flow oscillations. Frequency-resolved measurements of D and O oscillations are exploited by the technique of coherent hemodynamics spectroscopy for the assessment of cerebrovascular parameters and cerebral autoregulation. We show the relevant physiological information content of NIRS measurements of oscillatory hemodynamics, which have qualitatively distinct features in the healthy breast and healthy brain.

Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy

Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can also affect regional blood flow and may confound haemodynamics-based neuroimaging. Measurements with functional near-infrared spectroscopy (fNIRS) may additionally be confounded by blood flow and oxygenation changes in extracerebral tissue layers. Here we investigate these confounds using an extended version of an existing computational model of cerebral physiology, ‘BrainSignals’. Our results show that confounding from systemic physiological factors is able to produce misleading haemodynamic responses in both positive and negative directions. By applying the model to data from previous fNIRS studies, we demonstrate that such potentially deceptive responses can indeed occur in at least some experimental scenarios. It is therefore important to record the major potential confounders in the course of fNIRS experiments. Our model may then allow the observed behaviour to be attributed among the potential causes and hence reduce identification errors.

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Confounding of fNIRS haemoglobin signals is simulated using a computational model.

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Model is extended to simulate scalp haemodynamics.

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Changes in blood pressure and CO₂ can mimic and mask functional activation.

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Experimental recording of systemic factors is recommended to aid interpretation.

Cerebral blood flow and autoregulation: current measurement techniques and prospects for noninvasive optical methods

Cerebral blood flow (CBF) and cerebral autoregulation (CA) are critically important to maintain proper brain perfusion and supply the brain with the necessary oxygen and energy substrates. Adequate brain perfusion is required to support normal brain function, to achieve successful aging, and to navigate acute and chronic medical conditions. We review the general principles of CBF measurements and the current techniques to measure CBF based on direct intravascular measurements, nuclear medicine, X-ray imaging, magnetic resonance imaging, ultrasound techniques, thermal diffusion, and optical methods. We also review techniques for arterial blood pressure measurements as well as theoretical and experimental methods for the assessment of CA, including recent approaches based on optical techniques. The assessment of cerebral perfusion in the clinical practice is also presented. The comprehensive description of principles, methods, and clinical requirements of CBF and CA measurements highlights the potentially important role that noninvasive optical methods can play in the assessment of neurovascular health. In fact, optical techniques have the ability to provide a noninvasive, quantitative, and continuous monitor of CBF and autoregulation.

fMRI at High Spatial Resolution: Implications for BOLD-Models

As high-resolution functional magnetic resonance imaging (fMRI) and fMRI of cortical layers become more widely used, the question how well high-resolution fMRI signals reflect the underlying neural processing, and how to interpret laminar fMRI data becomes more and more relevant. High-resolution fMRI has shown laminar differences in cerebral blood flow (CBF), volume (CBV), and neurovascular coupling. Features and processes that were previously lumped into a single voxel become spatially distinct at high resolution. These features can be vascular compartments such as veins, arteries, and capillaries, or cortical layers and columns, which can have differences in metabolism. Mesoscopic models of the blood oxygenation level dependent (BOLD) response therefore need to be expanded, for instance, to incorporate laminar differences in the coupling between neural activity, metabolism and the hemodynamic response. Here we discuss biological and methodological factors that affect the modeling and interpretation of high-resolution fMRI data. We also illustrate with examples from neuropharmacology and the negative BOLD response how combining BOLD with CBF- and CBV-based fMRI methods can provide additional information about neurovascular coupling, and can aid modeling and interpretation of high-resolution fMRI.

In vivo photoacoustic microscopy of human cuticle microvasculature with single-cell resolution

As a window on the microcirculation, human cuticle capillaries provide rich information about the microvasculature, such as its morphology, density, dimensions, or even blood flow speed. Many imaging technologies have been employed to image human cuticle microvasculature. However, almost none of these techniques can noninvasively observe the process of oxygen release from single red blood cells (RBCs), an observation which can be used to study healthy tissue functionalities or to diagnose, stage, or monitor diseases. For the first time, we adapted single-cell resolution photoacoustic (PA) microscopy (PA flowoxigraphy) to image cuticle capillaries and quantified multiple functional parameters. Our results show more oxygen release in the curved cuticle tip region than in other regions of a cuticle capillary loop, associated with a low of RBC flow speed in the tip region. Further analysis suggests that in addition to the RBC flow speed, other factors, such as the drop of the partial oxygen pressure in the tip region, drive RBCs to release more oxygen in the tip region.

Low-Dimensional Models of "Neuro-Glio-Vascular Unit" for Describing Neural Dynamics under Normal and Energy-Starved Conditions

The motivation of developing simple minimal models for neuro-glio-vascular (NGV) system arises from a recent modeling study elucidating the bidirectional information flow within the NGV system having 89 dynamic equations (1). While this was one of the first attempts at formulating a comprehensive model for neuro-glio-vascular system, it poses severe restrictions in scaling up to network levels. On the contrary, low-­dimensional models are convenient devices in simulating large networks that also provide an intuitive understanding of the complex interactions occurring within the NGV system. The key idea underlying the proposed models is to describe the glio-vascular system as a lumped system, which takes neural firing rate as input and returns an “energy” variable (analogous to ATP) as output. To this end, we present two models: biophysical neuro-energy (Model 1 with five variables), comprising K_ATP channel activity governed by neuronal ATP dynamics, and the dynamic threshold (Model 2 with three variables), depicting the dependence of neural firing threshold on the ATP dynamics. Both the models show different firing regimes, such as continuous spiking, phasic, and tonic bursting depending on the ATP production coefficient, ɛ_p, and external current. We then demonstrate that in a network comprising such energy-dependent neuron units, ɛ_p could modulate the local field potential (LFP) frequency and amplitude. Interestingly, low-frequency LFP dominates under low ɛ_p conditions, which is thought to be reminiscent of seizure-like activity observed in epilepsy. The proposed “neuron-energy” unit may be implemented in building models of NGV networks to simulate data obtained from multimodal neuroimaging systems, such as functional near infrared spectroscopy coupled to electroencephalogram and functional magnetic resonance imaging coupled to electroencephalogram. Such models could also provide a theoretical basis for devising optimal neurorehabilitation strategies, such as non-invasive brain stimulation for stroke patients.

Fast blood flow monitoring in deep tissues with real-time software correlators

We introduce, validate and demonstrate a new software correlator for high-speed measurement of blood flow in deep tissues based on diffuse correlation spectroscopy (DCS). The software correlator scheme employs standard PC-based data acquisition boards to measure temporal intensity autocorrelation functions continuously at 50 - 100 Hz, the fastest blood flow measurements reported with DCS to date. The data streams, obtained in vivo for typical source-detector separations of 2.5 cm, easily resolve pulsatile heart-beat fluctuations in blood flow which were previously considered to be noise. We employ the device to separate tissue blood flow from tissue absorption/scattering dynamics and thereby show that the origin of the pulsatile DCS signal is primarily flow, and we monitor cerebral autoregulation dynamics in healthy volunteers more accurately than with traditional instrumentation as a result of increased data acquisition rates. Finally, we characterize measurement signal-to-noise ratio and identify count rate and averaging parameters needed for optimal performance.