Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults

Functional near-infrared spectroscopy based blood pressure variations and hemodynamic activity of brain monitoring following postural changes: A systematic review

Postural change from supine or sitting to standing up leads to displacement of 300 to 1000 mL of blood from the central parts of the body to the lower limb, which causes a decrease in venous return to the heart, hence decrease in cardiac output, causing a drop in blood pressure. This may lead to falling down, syncope, and in general reducing the quality of daily activities, especially in the elderly and anyone suffering from nervous system disorders such as Parkinson's or orthostatic hypotension (OH). Among different modalities to study brain function, functional near-infrared spectroscopy (fNIRS) is a neuroimaging method that optically measures the hemodynamic response in brain tissue. Concentration changes in oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (HHb) are associated with brain neural activity. fNIRS is significantly more tolerant to motion artifacts compared to fMRI, PET, and EEG. At the same time, it is portable, has a simple structure and usage, is safer, and much more economical. In this article, we systematically reviewed the literature to examine the history of using fNIRS in monitoring brain oxygenation changes caused by sudden changes in body position and its relationship with the blood pressure changes. First, the theory behind brain hemodynamics monitoring using fNIRS and its advantages and disadvantages are presented. Then, a study of blood pressure variations as a result of postural changes using fNIRS is described. It is observed that only 58 % of the references concluded a positive correlation between brain oxygenation changes and blood pressure changes. At the same time, 3 % showed a negative correlation, and 39 % did not show any correlation between them.

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.

Contrast-free dynamic susceptibility contrast using sinusoidal and bolus oxygenation challenges

Deoxygenation-based dynamic susceptibility contrast (dDSC) MRI uses respiratory challenges as a source of endogenous contrast as an alternative to gadolinium injection. These gas challenges induce T2*-weighted MRI signal losses, after which tracer kinetics modeling was applied to calculate cerebral perfusion. This work compares three gas challenges, desaturation (transient hypoxia), resaturation (transient normoxia), and SineO2 (sinusoidal modulation of end-tidal oxygen pressures) in a cohort of 10 healthy volunteers (age 37 ± 11 years; 60% female). Perfusion estimates consisted of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). Calculations were computed using a traditional tracer kinetics model in the time domain for desaturation and resaturation and in the frequency domain for SineO2. High correlations and limits of agreement were observed among the three deoxygenation-based paradigms for CBV, although MTT and CBF estimates varied with the hypoxic stimulus. Cross-modality correlation with gadolinium DSC was lower, particularly for MTT, but on a par with agreement between the other perfusion references. Overall, this work demonstrated the feasibility and reliability of oxygen respiratory challenges to measure brain perfusion. Additional work is needed to assess the utility of dDSC in the diagnostic evaluation of various pathologies such as ischemic strokes, brain tumors, and neurodegenerative diseases.

Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet)

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA.

Neurovascular effects of cocaine: relevance to addiction

Cocaine is a highly addictive drug, and its use is associated with adverse medical consequences such as cerebrovascular accidents that result in debilitating neurological complications. Indeed, brain imaging studies have reported severe reductions in cerebral blood flow (CBF) in cocaine misusers when compared to the brains of healthy non-drug using controls. Such CBF deficits are likely to disrupt neuro-vascular interaction and contribute to changes in brain function. This review aims to provide an overview of cocaine-induced CBF changes and its implication to brain function and to cocaine addiction, including its effects on tissue metabolism and neuronal activity. Finally, we discuss implications for future research, including targeted pharmacological interventions and neuromodulation to limit cocaine use and mitigate the negative impacts.

A systematic review on the assessment of cerebral autoregulation in patients with Large Vessel Occlusion

As the majority of large vessel occlusion (LVO) patients are not treated with revascularization therapies or efficiently revascularized, complementary management strategies are needed. In this article we explore the importance of cerebral autoregulation (CA) assessment in the prediction and/or modification of infarct growth and hemorrhagic transformation. In patients with LVO, these are important factors that affect prognosis. A systematic search of the PubMed, EMBASE databases and a targeted Google search was conducted, resulting in the inclusion of 34 relevant articles. There is an agreement that CA is impaired in patients with LVO; several factors have been identified such as time course, revascularization status, laterality, disease subtype and location, some of which may be potentially modifiable and affect outcomes. The personalized CA assessment of these patients suggests potential for better understanding of the inter-individual variability. Further research is needed for the development of more accurate, noninvasive techniques for continuous monitoring and personalized thresholds for CA.

Workload-dependent hemispheric asymmetries during the emotion-cognition interaction: a close-to-naturalistic fNIRS study

Introduction

We investigated brain activation patterns of interacting emotional distractions and cognitive processes in a close-to-naturalistic functional near-infrared spectroscopy (fNIRS) study.

Methods

Eighteen participants engaged in a monitoring-control task, mimicking common air traffic controller requirements. The scenario entailed experiencing both low and high workload, while concurrently being exposed to emotional speech distractions of positive, negative, and neutral valence.

Results

Our investigation identified hemispheric asymmetries in prefrontal cortex (PFC) activity during the presentation of negative and positive emotional speech distractions at different workload levels. Thereby, in particular, activation in the left inferior frontal gyrus (IFG) and orbitofrontal cortex (OFC) seems to play a crucial role. Brain activation patterns revealed a cross-over interaction indicating workload-dependent left hemispheric inhibition processes during negative distractions and high workload. For positive emotional distractions under low workload, we observed left-hemispheric PFC recruitment potentially associated with speech-related processes. Furthermore, we found a workload-independent negativity bias for neutral distractions, showing brain activation patterns similar to those of negative distractions.

Discussion

In conclusion, lateralized hemispheric processing, regulating emotional speech distractions and integrating emotional and cognitive processes, is influenced by workload levels and stimulus characteristics. These findings advance our understanding of the factors modulating hemispheric asymmetries during the processing and inhibition of emotional distractions, as well as the interplay between emotion and cognition. Moreover, they emphasize the significance of exploring emotion-cognition interactions in more naturalistic settings to gain a deeper understanding of their implications in real-world application scenarios (e.g., working and learning environments).

Assessment of power spectral density of microvascular hemodynamics in skeletal muscles at very low and low-frequency via near-infrared diffuse optical spectroscopies

In this work, we used a hybrid time domain near-infrared spectroscopy (TD-NIRS) and diffuse correlation spectroscopy (DCS) device to retrieve hemoglobin and blood flow oscillations of skeletal muscle microvasculature. We focused on very low (VLF) and low-frequency (LF) oscillations (i.e., frequency lower than 0.145 Hz), that are related to myogenic, neurogenic and endothelial activities. We measured power spectral density (PSD) of blood flow and hemoglobin concentration in four muscles (thenar eminence, plantar fascia, sternocleidomastoid and forearm) of 14 healthy volunteers to highlight possible differences in microvascular hemodynamic oscillations. We observed larger PSDs for blood flow compared to hemoglobin concentration, in particular in case of distal muscles (i.e., thenar eminence and plantar fascia). Finally, we compared the PSDs measured on the thenar eminence of healthy subjects with the ones measured on a septic patient in the intensive care unit: lower power in the endothelial-dependent frequency band, and larger power in the myogenic ones were observed in the septic patient, in accordance with previous works based on laser doppler flowmetry.

Functional brain connectivity after corrective cardiac surgery for critical congenital heart disease: a preliminary near-infrared spectroscopy (NIRS) report

Patients with congenital heart disease (CHD) requiring cardiac surgery in infancy are at high risk for neurodevelopmental impairments. Neonatal imaging studies have reported disruptions of brain functional organization before surgery. Yet, the extent to which functional network alterations are present after cardiac repair remains unexplored. This preliminary study aimed at investigating cortical functional connectivity in 4-month-old infants with repaired CHD, using resting-state functional near-infrared spectroscopy (fNIRS). After fNIRS signal frequency decomposition, we compared values of magnitude-squared coherence as a measure of connectivity strength, between 21 infants with corrected CHD and 31 healthy controls. We identified a subset of connections with differences between groups at an uncorrected statistical level of p < .05 while controlling for sex and maternal socioeconomic status, with most of these connections showing reduced connectivity in infants with CHD. Although none of these differences reach statistical significance after FDR correction, likely due to the small sample size, moderate to large effect sizes were found for group-differences. If replicated, these results would therefore suggest preliminary evidence that alterations of brain functional connectivity are present in the months after cardiac surgery. Additional studies involving larger sample size are needed to replicate our data, and comparisons between pre- and postoperative findings would allow to further delineate alterations of functional brain connectivity in this population.

Pressure stimulus study on acupuncture points with multi-channel multimode-fiber diffuse speckle contrast analysis (MMF-DSCA)

A multi-channel multimode-fiber deep tissue flowmetry system has been constructed based on diffuse speckle contrast analysis (DSCA) for simultaneous blood flow measurements at different locations on the human body. This system has been utilized in an acupuncture study within the field of traditional Chinese medicine (TCM), primarily focusing on acupuncture points along the large intestine meridian. Deep tissue blood flow was monitored at four different acupuncture points (LI1, LI5, LI10, and ST25) with a sampling rate of 60 Hz while applying pressure stimulus on LI4 (hegu or hapgok). Although the blood flow index (BFI) and blood volume (BV) did not exhibit significant changes after the pressure stimulus, an increase in the amplitude and complexity of low-frequency oscillations (LFOs) in microcirculation was observed.

Non-Invasive Continuous Optical Monitoring of Cerebral Blood Flow after Traumatic Brain Injury in Mice Using Fiber Camera-Based Speckle Contrast Optical Spectroscopy

Neurocritical care focuses on monitoring cerebral blood flow (CBF) to prevent secondary brain injuries before damage becomes irreversible. Thus, there is a critical unmet need for continuous neuromonitoring methods to quantify CBF within the vulnerable cortex continuously and non-invasively. Animal models and imaging biomarkers can provide valuable insights into the mechanisms and kinetics of head injury, as well as insights for potential treatment strategies. For this purpose, we implemented an optical technique for continuous monitoring of blood flow changes after a closed head injury in a mouse model, which is based on laser speckle contrast imaging and a fiber camera-based approach. Our results indicate a significant decrease (~10%, p-value < 0.05) in blood flow within 30 min of a closed head injury. Furthermore, the low-frequency oscillation analysis also indicated much lower power in the trauma group compared to the control group. Overall, blood flow has the potential to be a biomarker for head injuries in the early phase of a trauma, and the system is useful for continuous monitoring with the potential for clinical translation.

Differences in time-frequency characteristics between healthy controls and TBI patients during hypercapnia assessed via fNIRS

Damage to the cerebrovascular network is a universal feature of traumatic brain injury (TBI). This damage is present during different phases of the injury and can be non-invasively assessed using functional near infrared spectroscopy (fNIRS). fNIRS signals are influenced by partial arterial carbon dioxide (PaCO2), neurogenic, Mayer waves, respiratory and cardiac oscillations, whose characteristics vary in time and frequency and may differ in the presence of TBI. Therefore, this study aims to investigate differences in time-frequency characteristics of these fNIRS signal components between healthy controls and TBI patients and characterize the changes in their characteristics across phases of the injury. Data from 11 healthy controls and 21 TBI patients were collected during the hypercapnic protocol. Results demonstrated significant differences in low-frequency oscillations between healthy controls and TBI patients, with the largest differences observed in Mayer wave band (0.06 to 0.15 Hz), followed by the PaCO2 band (0.012 to 0.02 Hz). The effects within these bands were opposite, with (i) Mayer wave activity being lower in TBI patients during acute phase of the injury (d = 0.37 [0.16, 0.57]) and decreasing further during subacute (d = 0.66 [0.44, 0.87]) and postacute (d = 0.75 [0.50, 0.99]) phases; (ii) PaCO2 activity being lower in TBI patients only during acute phase of the injury (d = 0.36 [0.15, 0.56]) and stabilizing to healthy levels by the subacute phase. These findings demonstrate that TBI patients have impairments in low frequency oscillations related to different mechanisms and that these impairments evolve differently over the course of injury.

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.

Test-retest reliability of fNIRS in resting-state cortical activity and brain network assessment in stroke patients

Resting-state functional near infrared spectroscopy (fNIRS) scanning has attracted considerable attention in stroke rehabilitation research in recent years. The aim of this study was to quantify the reliability of fNIRS in cortical activity intensity and brain network metrics among resting-state stroke patients, and to comprehensively evaluate the effects of frequency selection, scanning duration, analysis and preprocessing strategies on test-retest reliability. Nineteen patients with stroke underwent two resting fNIRS scanning sessions with an interval of 24 hours. The haemoglobin signals were preprocessed by principal component analysis, common average reference and haemodynamic modality separation (HMS) algorithm respectively. The cortical activity, functional connectivity level, local network metrics (degree, betweenness and local efficiency) and global network metrics were calculated at 25 frequency scales × 16 time windows. The test-retest reliability of each fNIRS metric was quantified by the intraclass correlation coefficient. The results show that (1) the high-frequency band has higher ICC values than the low-frequency band, and the fNIRS metric is more reliable than at the individual channel level when averaged within the brain region channel, (2) the ICC values of the low-frequency band above the 4-minute scan time are generally higher than 0.5, the local efficiency and global network metrics reach high and excellent reliability levels after 4 min (0.5 < ICC < 0.9), with moderate or even poor reliability for degree and betweenness (ICC < 0.5), (3) HMS algorithm performs best in improving the low-frequency band ICC values. The results indicate that a scanning duration of more than 4 minutes can lead to high reliability of most fNIRS metrics when assessing low-frequency resting brain function in stroke patients. It is recommended to use the global correction method of HMS, and the reporting of degree, betweenness and single channel level should be performed with caution. This paper provides the first comprehensive reference for resting-state experimental design and analysis strategies for fNIRS in stroke rehabilitation.

Operational Modal Analysis of Near-Infrared Spectroscopy Measure of 2-Month Exercise Intervention Effects in Sedentary Older Adults with Diabetes and Cognitive Impairment

The Global Burden of Disease Study (GBD 2019 Diseases and Injuries Collaborators) found that diabetes significantly increases the overall burden of disease, leading to a 24.4% increase in disability-adjusted life years. Persistently high glucose levels in diabetes can cause structural and functional changes in proteins throughout the body, and the accumulation of protein aggregates in the brain that can be associated with the progression of Alzheimer's Disease (AD). To address this burden in type 2 diabetes mellitus (T2DM), a combined aerobic and resistance exercise program was developed based on the recommendations of the American College of Sports Medicine. The prospectively registered clinical trials (NCT04626453, NCT04812288) involved two groups: an Intervention group of older sedentary adults with T2DM and a Control group of healthy older adults who could be either active or sedentary. The completion rate for the 2-month exercise program was high, with participants completing on an average of 89.14% of the exercise sessions. This indicated that the program was practical, feasible, and well tolerated, even during the COVID-19 pandemic. It was also safe, requiring minimal equipment and no supervision. Our paper presents portable near-infrared spectroscopy (NIRS) based measures that showed muscle oxygen saturation (SmO2), i.e., the balance between oxygen delivery and oxygen consumption in muscle, drop during bilateral heel rise task (BHR) and the 6 min walk task (6MWT) significantly (p < 0.05) changed at the post-intervention follow-up from the pre-intervention baseline in the T2DM Intervention group participants. Moreover, post-intervention changes from pre-intervention baseline for the prefrontal activation (both oxyhemoglobin and deoxyhemoglobin) showed statistically significant (p < 0.05, q < 0.05) effect at the right superior frontal gyrus, dorsolateral, during the Mini-Cog task. Here, operational modal analysis provided further insights into the 2-month exercise intervention effects on the very-low-frequency oscillations (<0.05 Hz) during the Mini-Cog task that improved post-intervention in the sedentary T2DM Intervention group from their pre-intervention baseline when compared to active healthy Control group. Then, the 6MWT distance significantly (p < 0.01) improved in the T2DM Intervention group at post-intervention follow-up from pre-intervention baseline that showed improved aerobic capacity and endurance. Our portable NIRS based measures have practical implications at the point of care for the therapists as they can monitor muscle and brain oxygenation changes during physical and cognitive tests to prescribe personalized physical exercise doses without triggering individual stress response, thereby, enhancing vascular health in T2DM.

The prefrontal cortex hemodynamic responses to dual-task paradigms in older adults: A systematic review and meta-analysis

Background

Functional near-infrared spectroscopy (fNIRS) is a method to measure cerebral hemodynamics. Determining the changes in prefrontal cortex (PFC) hemodynamics during dual-task paradigms is essential in explaining alterations in physical activities, especially in older adults.

Aims

To systematically review and meta-analyze the effects of dual-task paradigms on PFC hemodynamics in older adults.

Methods

The search was conducted in PubMed, Scopus, and Web of Science from inception until March 2023 to identify studies on the effects of dual-task paradigms on PFC hemodynamics. The meta-analysis included variables of cerebral hemodynamics, such as oxygenated hemoglobin (HbO₂) and deoxygenated hemoglobin (HbR). The heterogeneity of the included studies was determined using the I² statistic. Additionally, subgroup analysis was conducted to compare the effects of different types of cognitive tasks.

Results

A total of 37 studies were included in the systematic review, 25 studies comprising 2224 older adults were included in the meta-analysis. Our findings showed that inhibitory control and working memory tasks significantly increased HbO₂ in the PFC by 0.53 (p < 0.01, 95% CI = 0.37 to 0.70) and 0.13 (p < 0.01, 95% CI = 0.08 to 0.18) μmol/L, respectively. Overall, HbO₂ was significantly increased during dual-task paradigms by 0.36 μmol/L (P < 0.01, 95% CI = 0.27 to 0.45). Moreover, dual-task paradigms also decreased HbR in the PFC by 0.04 (P < 0.01, 95% CI = -0.07 to -0.01). Specifically, HbR decreased by 0.08 during inhibitory control tasks (p < 0.01, 95% CI = -0.13 to -0.02), but did not change during working memory tasks.

Conclusion

Cognitive tasks related to inhibitory control required greater cognitive demands, indicating higher pfc activation during dual-task paradigms in older adults. for clinical implications, the increase in pfc oxygenated hemoglobin and decrease in pfc deoxygenated hemoglobin may help explain why older adults are more likely to fall during daily activities.

Naturalistic auditory stimuli with fNIRS prefrontal cortex imaging: A potential paradigm for disorder of consciousness diagnostics (a study with healthy participants)

Disorder of consciousness (DOC) is a devastating condition due to brain damage. A patient in this condition is non-responsive, but nevertheless might be conscious at least at some level. Determining the conscious level of DOC patients is important for both medical and ethical reasons, but reliably achieving this has been a major challenge. Naturalistic stimuli in combination with neuroimaging have been proposed as a promising approach for DOC patient diagnosis. Capitalizing on and extending this proposal, the goal of the present study conducted with healthy participants was to develop a new paradigm with naturalistic auditory stimuli and functional near-infrared spectroscopy (fNIRS) - an approach that can be used at the bedside. Twenty-four healthy participants passively listened to 9 min of auditory story, scrambled auditory story, classical music, and scrambled classical music segments while their prefrontal cortex activity was recorded using fNIRS. We found much higher intersubject correlation (ISC) during story compared to scrambled story conditions both at the group level and in the majority of individual subjects, suggesting that fNIRS imaging of the prefrontal cortex might be a sensitive method to capture neural changes associated with narrative comprehension. In contrast, the ISC during the classical music segment did not differ reliably from scrambled classical music and was also much lower than the story condition. Our main result is that naturalistic auditory stories with fNIRS might be used in a clinical setup to identify high-level processing and potential consciousness in DOC patients.

Differences in symmetrical low-frequency oscillations among healthy subjects, and those with stroke or peripheral arterial disease

Low-frequency oscillations (LFOs) observed in near-infrared spectroscopy (NIRS) reflect autonomic physiological processes, and may serve as useful indicators for detecting and monitoring circulatory dysfunction. The aim of this study was to reveal whether LFOs can be used as vascular perfusion biomarkers to differentiate different types and degrees of vascular lesions based on clinical patient data. Materials and Methods: In this study, healthy controls, ischemic stroke patients and peripheral atherosclerosis patients completed a resting-state LFO detection experiment. LFOs were collected simultaneously at peripheral right and left earlobes, fingertips and toes, along with coherence and phase shift analyses processing. Results: The results showed that the coherence coefficients of symmetric peripheral positions and the absolute value-phase shifts of fingers and toes can be used to distinguish healthy individuals, ischemic stroke patients and peripheral atherosclerosis patients. The symmetric earlobes' absolute value-phase shifts could be used to differentiate mild and severe ischemic stroke patients; the coherence coefficients and absolute value-phase shifts of the symmetric toes could be used to differentiate mild and severe peripheral arteriosclerosis patients. The accuracy of differentiating between types of patients was 70%; those with different degrees of peripheral atherosclerosis was 85%, and those with different degrees of ischemic stroke was 72%. Conclusions: LFOs can serve as vascular perfusion biomarkers to differentiate types and degrees of vascular lesions. Therefore, LFOs have the potential to provide valuable patient information to assist researchers and clinicians in identifying specific peripheral circulatory damage subgroups.

Editorial Special Section on Biomedical Diffuse Optics for the Brain

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

Study of Motion Sickness Model Based on fNIRS Multiband Features during Car Rides

Motion sickness is a common physiological discomfort phenomenon during car rides. In this paper, the functional near-infrared spectroscopy (fNIRS) technique was used in real-world vehicle testing. The fNIRS technique was utilized to model the relationship between changes in blood oxygenation levels in the prefrontal cortex of passengers and motion sickness symptoms under different motion conditions. To enhance the accuracy of motion sickness classification, the study utilized principal component analysis (PCA) to extract the most significant features from the test data. Wavelet decomposition was used to extract the power spectrum entropy (PSE) features of five frequency bands highly related to motion sickness. The correlation between motion sickness and cerebral blood oxygen levels was modeled by a 6-point scale calibration for the subjective evaluation of the degree of passenger motion sickness. A support vector machine (SVM) was used to build a motion sickness classification model, achieving an accuracy of 87.3% with the 78 sets of data. However, individual analysis of the 13 subjects showed a varying range of accuracy from 50% to 100%, suggesting the presence of individual differences in the relationship between cerebral blood oxygen levels and motion sickness symptoms. Thus, the results demonstrated that the magnitude of motion sickness during the ride was closely related to the change in the PSE of the five frequency bands of cerebral prefrontal blood oxygen, but further studies are needed to investigate individual variability.

Analysis of Respiratory Sinus Arrhythmia and Directed Information Flow between Brain and Body Indicate Different Management Strategies of fMRI-Related Anxiety

Background: Respiratory sinus arrhythmia (RSA) denotes decrease of cardiac beat-to-beat intervals (RRI) during inspiration and RRI increase during expiration, but an inverse pattern (termed negative RSA) was also found in healthy humans with elevated anxiety. It was detected using wave-by-wave analysis of cardiorespiratory rhythms and was considered to reflect a strategy of anxiety management involving the activation of a neural pacemaker. Results were consistent with slow breathing, but contained uncertainty at normal breathing rates (0.2–0.4 Hz). Objectives and methods: We combined wave-by-wave analysis and directed information flow analysis to obtain information on anxiety management at higher breathing rates. We analyzed cardiorespiratory rhythms and blood oxygen level-dependent (BOLD) signals from the brainstem and cortex in 10 healthy fMRI participants with elevated anxiety. Results: Three subjects with slow respiratory, RRI, and neural BOLD oscillations showed 57 ± 26% negative RSA and significant anxiety reduction by 54 ± 9%. Six participants with breathing rate of ~0.3 Hz showed 41 ± 16% negative RSA and weaker anxiety reduction. They presented significant information flow from RRI to respiration and from the middle frontal cortex to the brainstem, which may result from respiration-entrained brain oscillations, indicating another anxiety management strategy. Conclusion: The two analytical approaches applied here indicate at least two different anxiety management strategies in healthy subjects.

The impact of vasomotion on analysis of rodent fMRI data

Introduction

Small animal fMRI is an essential part of translational research in the cognitive neurosciences. Due to small dimensions and animal physiology preclinical fMRI is prone to artifacts that may lead to misinterpretation of the data. To reach unbiased translational conclusions, it is, therefore, crucial to identify potential sources of experimental noise and to develop correction methods for contributions that cannot be avoided such as physiological noise. Aim of this study was to assess origin and prevalence of hemodynamic oscillations (HDO) in preclinical fMRI in rat, as well as their impact on data analysis.

Methods

Following the development of algorithms for HDO detection and suppression, HDO prevalence in fMRI measurements was investigated for different anesthetic regimens, comprising isoflurane and medetomidine, and for both gradient echo and spin echo fMRI sequences. In addition to assessing the effect of vasodilation on HDO, it was studied if HDO have a direct neuronal correlate using local field potential (LFP) recordings. Finally, the impact of HDO on analysis of fMRI data was assessed, studying both the impact on calculation of activation maps as well as the impact on brain network analysis. Overall, 303 fMRI measurements and 32 LFP recordings were performed in 71 rats.

Results

In total, 62% of the fMRI measurements showed HDO with a frequency of (0.20 ± 0.02) Hz. This frequent occurrence indicated that HDO cannot be generally neglected in fMRI experiments. Using the developed algorithms, HDO were detected with a specificity of 95%, and removed efficiently from the signal time courses. HDO occurred brain-wide under vasoconstrictive conditions in both small and large blood vessels. Vasodilation immediately interrupted HDO, which, however, returned within 1 h under vasoconstrictive conditions. No direct neuronal correlate of HDO was observed in LFP recordings. HDO significantly impacted analysis of fMRI data, leading to altered cluster sizes and F-values for activated voxels, as well as altered brain networks, when comparing data with and without HDO.

Discussion

We therefore conclude that HDO are caused by vasomotion under certain anesthetic conditions and should be corrected during fMRI data analysis to avoid bias.

Neurovascular, Metabolic, and Glymphatic Dynamics of the Brain Measured with fNIRS

We developed a multidistance and multiwavelength continuous wave NIRS instrument to detect dynamic changes in oxygenated and deoxygenated hemoglobin (oxy- and deoxy-Hb), oxidized cytochrome-c-oxidase (oxCCO) and water of the brain and muscle. We performed measurements of the forehead during resting state and paced breathing and of the forearm during ischemic challenge in human adults. Time series analysis focusing on rhythmic signals over different time scales and different depths of the tissue revealed specific patterns of phase relationships among the signals in each of the measurement. This method can be a promising tool to understand the dynamic interaction among the neurovascular, metabolic and glymphatic system in a wide variety of subject fields.

Reliable Fast (20 Hz) Acquisition Rate by a TD fNIRS Device: Brain Resting-State Oscillation Studies

A high power setup for multichannel time-domain (TD) functional near infrared spectroscopy (fNIRS) measurements with high efficiency detection system was developed. It was fully characterized based on international performance assessment protocols for diffuse optics instruments, showing an improvement of the signal-to-noise ratio (SNR) with respect to previous analogue devices, and allowing acquisition of signals with sampling rate up to 20 Hz and source-detector distance up to 5 cm. A resting-state measurement on the motor cortex of a healthy volunteer was performed with an acquisition rate of 20 Hz at a 4 cm source-detector distance. The power spectrum for the cortical oxy- and deoxyhemoglobin is also provided.

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.

Assessment of dynamic cerebral autoregulation in near-infrared spectroscopy using short channels: A feasibility study in acute ischemic stroke patients

Introduction

In acute ischemic stroke, progressive impairment of cerebral autoregulation (CA) is frequent and associated with unfavorable outcomes. Easy assessment of cerebral blood flow and CA in stroke units bedside tools like near-infrared spectroscopy (NIRS) might improve early detection of CA deterioration. This study aimed to assess dynamic CA with multichannel CW-NIRS in acute ischemic stroke (AIS) patients compared to agematched healthy controls.

Methods

CA reaction was amplified by changes in head of bed position. Long- and short channels were used to monitor systemic artery pressure- and intracranial oscillations simultaneously. Gain and phase shift in spontaneous low- and very low-frequency oscillations (LFO, VLFO) of blood pressure were assessed.

Results

A total of 54 participants, 27 with AIS and 27 age-matched controls were included. Gain was significantly lower in the AIS group in the LFO range (i) when the upper body was steadily elevated to 30. and (ii) after its abrupt elevation to 30°. No other differences were found between groups.

Discussion

This study demonstrates the feasibility of NIRS short channels to measure CA in AIS patients in one single instrument. A lower gain in AIS might indicate decreased CA activity in this pilot study, but further studies investigating the role of NIRS short channels in AIS are needed.

Correcting cardiorespiratory noise in resting-state functional MRI data acquired in critically ill patients

Resting-state functional MRI is being used to develop diagnostic, prognostic and therapeutic biomarkers for critically ill patients with severe brain injuries. In studies of healthy volunteers and non-critically ill patients, prospective cardiorespiratory data are routinely collected to remove non-neuronal fluctuations in the resting-state functional MRI signal during analysis. However, the feasibility and utility of collecting cardiorespiratory data in critically ill patients on a clinical MRI scanner are unknown. We concurrently acquired resting-state functional MRI (repetition time = 1250 ms) and cardiac and respiratory data in 23 critically ill patients with acute severe traumatic brain injury and in 12 healthy control subjects. We compared the functional connectivity results from two approaches that are commonly used to correct cardiorespiratory noise: (i) denoising with cardiorespiratory data (i.e. image-based method for retrospective correction of physiological motion effects in functional MRI) and (ii) standard bandpass filtering. Resting-state functional MRI data in 7 patients could not be analysed due to imaging artefacts. In 6 of the remaining 16 patients (37.5%), cardiorespiratory data were either incomplete or corrupted. In patients (n = 10) and control subjects (n = 10), the functional connectivity results corrected with the image-based method for retrospective correction of physiological motion effects in functional MRI did not significantly differ from those corrected with bandpass filtering of 0.008-0.125 Hz. Collectively, these findings suggest that, in critically ill patients with severe traumatic brain injury, there is limited feasibility and utility to denoising the resting-state functional MRI signal with prospectively acquired cardiorespiratory data.

Functional near-infrared spectroscopy imaging of the prefrontal cortex during a naturalistic comedy movie

Naturalistic stimulation (i.e., movies and auditory narratives of some minutes' length) has been a powerful approach to bringing more real-life experiences into laboratory experiments. Data-driven, intersubject correlation (ISC) analysis permits examining to what extent activity in a specific brain region correlates across participants during exposure to a naturalistic stimulus, as well as testing whether neural activity correlates with behavioral measures. Notably, most of the previous research with naturalistic stimuli was conducted using functional fMRI (fMRI). Here, we tested whether a naturalistic approach and the ISC are feasible using functional near-infrared spectroscopy (fNIRS) - the imaging method particularly suited for populations of patients and children. Fifty-three healthy adult participants watched twice a 3-min segment of a Charlie Chaplin movie while we recorded the brain activity on the surface of their prefrontal cortex using fNIRS. In addition, an independent group of 18 participants used a continuous scoring procedure to rate the extent to which they felt that different parts of the movie fragment were funny. Our two findings were as follows. First, we found higher-than-zero ISC in fNIRS signals in the prefrontal cortex lobes, a result that was particularly high in the oxygenated channels during the first repetition of the movie. Second, we found a significant negative correlation between oxygenated brain signals and ratings of the movie's humorousness. In a series of control analyses we demonstrated that this latter correlation could not be explained by various non-humor-related movie sensory properties (e.g., auditory volume and image brightness). The key overall outcome of the present study is that fNIRS in combination with the naturalistic paradigms and the ISC might be a sensitive and powerful research method to explore cognitive processing. Our results also suggest a potential role of the prefrontal cortex in humor appreciation.

Increased cortical activation and enhanced functional connectivity in the prefrontal cortex ensure dynamic postural balance during dual-task obstacle negotiation in the older adults: A fNIRS study

OBJECTIVE

By analyzing the cortical activation and functional connectivity of the prefrontal cortex (PFC) during dual-task obstacle negotiation in the older adults, cognitive resources allocation and neural regulatory mechanisms of aging brain were shed light on in complex walking conditions.

METHODS

Twenty-eight healthy right-handed subjects participated in the study, including 15 men and 13 women (age: 68.6 ± 4.1 years, height: 162.96 ± 6.05 cm, weight: 63.63 ± 9.64 kg). There were four tasks: Normal Walk (NW), Obstacle Negotiation during Normal Walk (NW + ON), Walk while performing Cognitive Task (WCT), and Obstacle Negotiation during Walk while performing Cognitive Task (WCT + ON). Participants wore functional near-infrared spectroscopy (fNIRS) to collect hemodynamic signals from various regions of interest (ROIs) in the PFC, while the three-dimensional motion capture system was used to test the gait velocity. Cognitive task data was recorded.

RESULTS

In WCT + ON, the HbO₂ concentration change value (△HbO₂) of the left dorsolateral prefrontal cortex was significantly greater than that in the other three tasks (p < 0.05), and the△HbO₂ of the right dorsolateral prefrontal cortex was significantly greater than that in NW + ON (p < 0.05). The gait velocities in the four tasks were significantly different (p < 0.05) (NW > WCT > NW + ON > WCT + ON). There was no significant difference in cognitive performance between in the WCT and WCT + ON (p > 0.05). In WCT + ON, the left and right dorsolateral prefrontal areas had strong functional connectivity and the left frontal pole was most widely connected to the other ROIs. Compared to that in NW, the functional connectivity of the left prefrontal lobe was significantly enhanced in WCT + ON (p < 0.05).

CONCLUSIONS

As walking difficulty increased, the PFC activation in the older adults changed from right-sided to bilateral activation, indicating that the left PFC cognitive resources compensated for the right PFC in dual-task obstacle negotiation. The cognitive resources recruitment in dual-task obstacle negotiation might be achieved by synchronization and coordination of associated brain areas in the PFC, primarily to maintain dynamic postural balance when walking.

Driver's turning intent recognition model based on brain activation and contextual information

Traffic situations like turning at intersections are destined for safety-critical situations and accidents. Human errors are one of the main reasons for accidents in these situations. A model that recognizes the driver's turning intent could help to reduce accidents by warning the driver or stopping the vehicle before a dangerous turning maneuver. Most models that aim at predicting the probability of a driver's turning intent use only contextual information, such as gap size or waiting time. The objective of this study is to investigate whether the combination of context information and brain activation measurements enhances the recognition of turning intent. We conducted a driving simulator study while simultaneously measuring brain activation using high-density fNIRS. A neural network model for turning intent recognition was trained on the fNIRS and contextual data. The input variables were analyzed using SHAP (SHapley Additive exPlanations) feature importance analysis to show the positive effect of the inclusion of brain activation data. Both the model's evaluation and the feature importance analysis suggest that the combination of context information and brain activation leads to an improved turning intent recognition. The fNIRS results showed increased brain activation differences during the "turn" decision-making phase before turning execution in parts of the left motor cortices, such as the primary motor cortex (PMC; putative BA 4), premotor area (PMA; putative BA 6), and supplementary motor area (SMA; putative BA 8). Furthermore, we also observed increased activation differences in the left prefrontal areas, potentially in the left middle frontal gyrus (putative BA 9), which has been associated with the control of executive functions, such as decision-making and action planning. We hypothesize that brain activation measurements could be a more direct indicator with potentially high specificity for the turning behavior and thus help to increase the recognition model's performance.

Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research.

Comparing fixed-array and functionally-defined channel of interest approaches to infant functional near-infrared spectroscopy data

Functional near-infrared spectroscopy (fNIRS) is increasingly used to study brain function in infants, but the development and standardization of analysis techniques for use with infant fNIRS data have not paced other technical advances. Here we quantify and compare the effects of different methods of analysis of infant fNIRS data on two independent fNIRS datasets involving 6–9-month-old infants and a third simulated infant fNIRS dataset. With each, we contrast results from a traditional, fixed-array analysis with several functional channel of interest (fCOI) analysis approaches. In addition, we tested the effects of varying the number and anatomical location of potential data channels to be included in the fCOI definition. Over three studies we find that fCOI approaches are more sensitive than fixed-array analyses, especially when channels of interests were defined within-subjects. Applying anatomical restriction and/or including multiple channels in the fCOI definition does not decrease and in some cases increases sensitivity of fCOI methods. Based on these results, we recommend that researchers consider employing fCOI approaches to the analysis of infant fNIRS data and provide some guidelines for choosing between particular fCOI approaches and settings for the study of infant brain function and development.

Correction of global physiology in resting-state functional near-infrared spectroscopy

Significance: Resting-state functional connectivity (RSFC) analyses of functional near-infrared spectroscopy (fNIRS) data reveal cortical connections and networks across the brain. Motion artifacts and systemic physiology in evoked fNIRS signals present unique analytical challenges, and methods that control for systemic physiological noise have been explored. Whether these same methods require modification when applied to resting-state fNIRS (RS-fNIRS) data remains unclear. Aim: We systematically examined the sensitivity and specificity of several RSFC analysis pipelines to identify the best methods for correcting global systemic physiological signals in RS-fNIRS data. Approach: Using numerically simulated RS-fNIRS data, we compared the rates of true and false positives for several connectivity analysis pipelines. Their performance was scored using receiver operating characteristic analysis. Pipelines included partial correlation and multivariate Granger causality, with and without short-separation measurements, and a modified multivariate causality model that included a non-traditional zeroth-lag cross term. We also examined the effects of pre-whitening and robust statistical estimators on performance. Results: Consistent with previous work on bivariate correlation models, our results demonstrate that robust statistics and pre-whitening are effective methods to correct for motion artifacts and autocorrelation in the fNIRS time series. Moreover, we found that pre-filtering using principal components extracted from short-separation fNIRS channels as part of a partial correlation model was most effective in reducing spurious correlations due to shared systemic physiology when the two signals of interest fluctuated synchronously. However, when there was a temporal lag between the signals, a multivariate Granger causality test incorporating the short-separation channels was better. Since it is unknown if such a lag exists in experimental data, we propose a modified version of Granger causality that includes the non-traditional zeroth-lag term as a compromising solution. Conclusions: A combination of pre-whitening, robust statistical methods, and partial correlation in the processing pipeline to reduce autocorrelation, motion artifacts, and global physiology are suggested for obtaining statistically valid connectivity metrics with RS-fNIRS. Further studies should validate the effectiveness of these methods using human data.

Prefrontal cortical connectivity and coupling of infraslow oscillation in the resting human brain: a 2-channel broadband NIRS study

The resting-state infraslow oscillation (ISO) of the cerebral cortex reflects the neurophysiological state of the human brain. ISO results from distinct vasomotion with endogenic (E), neurogenic (N), and myogenic (M) frequency bands. Quantification of prefrontal ISO in cortical hemodynamics and metabolism in the resting human brain may facilitate the identification of objective features that are characteristic of certain brain disorders. The goal of this study was to explore and quantify the prefrontal ISO of the cortical concentration changes of oxygenated hemoglobin (Δ[HbO]) and redox-state cytochrome c oxidase (Δ[CCO]) as hemodynamic and metabolic activity metrics in all 3 E/N/M bands. Two-channel broadband near-infrared spectroscopy (2-bbNIRS) enabled measurements of the forehead of 26 healthy young participants in a resting state once a week for 5 weeks. After quantifying the ISO spectral amplitude (SA) and coherence at each E/N/M band, several key and statistically reliable metrics were obtained as features: (i) SA of Δ[HbO] at all E/N/M bands, (ii) SA of Δ[CCO] in the M band, (iii) bilateral connectivity of hemodynamics and metabolism across the E and N bands, and (iv) unilateral hemodynamic–metabolic coupling in each of the E and M bands. These features have promising potential to be developed as objective biomarkers for clinical applications in the future.

Physiological Mechanisms and Significance of Intracranial B Waves

Objective

Recently published studies have described slow spontaneous cerebral blood flow (CBF) and cerebrospinal fluid (CSF) oscillations measured by magnetic resonance imaging (MRI) as potential drivers of brain glymphatic flow, with a similar frequency as intracranial B-waves. Aiming to establish the relationship between these waveforms, we performed additional analysis of frequency and waveform parameters, of our previously published transcranial Doppler (TCD) and intracranial pressure (ICP) recordings of intracranial B waves, to compare to published MRI frequency measurements of CBF and CSF slow oscillations.

Patients and Methods

We analyzed digital recordings of B waves in 29 patients with head injury, including middle cerebral artery (MCA) flow velocity (FV), ICP, end tidal CO₂, and arterial blood pressure (ABP). A subset of these recordings demonstrated high B wave activity and was further analyzed for parameters including frequency, interaction, and waveform distribution curve features. These measures were compared to published similar measurements of spontaneous CBF and CSF fluctuations evaluated using MRI.

Results

In patients with at least 10% amplitude B wave activity, the MCA blood flow velocity oscillations comprising the B waves, had a maximum amplitude at 0.0245 Hz, and time derivative a maximum amplitude at 0.035 Hz. The frequency range of the B waves was between 0.6–2.3 cycles per min (0.011-0.038 Hz), which is in the same range as MRI measured CBF slow oscillations, reported in human volunteers. Waveform asymmetry in MCA velocity and ICP cycles during B waves, was also similar to published MRI measured CBF slow oscillations. Cross-correlation analysis showed equivalent time derivatives of FV vs. ICP in B waves, compared to MRI measured CBF slow oscillations vs. CSF flow fluctuations.

Conclusions

The TCD and ICP recordings of intracranial B waves show a similar frequency range as CBF and CSF flow oscillations measured using MRI, and share other unique morphological wave features. These findings strongly suggest a common physiological mechanism underlying the two classes of phenomena. The slow blood flow and volume oscillations causing intracranial B waves appear to be part of a cascade that may provide a significant driving force for compartmentalized CSF movement and facilitate glymphatic flow.

Central effects of galcanezumab in migraine: a pilot study on Steady State Visual Evoked Potentials and occipital hemodynamic response in migraine patients

BACKGROUND

The discovery of the prominent action of Calcitonin Gene Related Peptide -CGRP- on trigeminal afferents and meningeal vessels, opened a new era in migraine treatment. However, how the block of nociceptive afferents could act on central mechanisms of migraine is still not clear. In this pilot study we aimed to test the effect of 3 months Galcanezumab (CGA) therapy on occipital visual reactivity in migraine patients, using the Steady State Visual Evoked Potentials-SSVEPs and Functional Near Infrared Spectroscopy -fNIRS.

METHOD

Thirteen migraine patients underwent clinical and neurophysiological examination in basal condition (T0), 1 h after GCA injection (T1) and after 3 months of GCA treatment (T2). Ten healthy volunteers were also evaluated.

RESULTS

At T2, there was a reduction of headache frequency and disability. At T2, the EEG power significantly diminished as compared to T0 and T1 at occipital sites, and the topographical analysis confirmed a restoration of SSVEPs within normal values. The Oxyhemoglobin levels in occipital cortex, which were basically increased during visual stimulation in migraine patients, reverted to normal values at T2.

CONCLUSIONS

The present pilot study indicates that Galcanezumab could act on cortical targets located beyond the pain network, restoring the abnormal occipital reactivity. This effect could indicate the possible disease modifying properties of CGRP related monoclonal antibodies.

Entropy Could Quantify Brain Activation Induced by Mechanical Impedance-Restrained Active Arm Motion: A Functional NIRS Study

Brain activation has been used to understand brain-level events associated with cognitive tasks or physical tasks. As a quantitative measure for brain activation, we propose entropy in place of signal amplitude and beta value, which are widely used, but sometimes criticized for their limitations and shortcomings as such measures. To investigate the relevance of our proposition, we provided 22 subjects with physical stimuli through elbow extension-flexion motions by using our exoskeleton robot, measured brain activation in terms of entropy, signal amplitude, and beta value; and compared entropy with the other two. The results show that entropy is superior, in that its change appeared in limited, well established, motor areas, while signal amplitude and beta value changes appeared in a widespread fashion, contradicting the modularity theory. Entropy can predict increase in brain activation with task duration, while the other two cannot. When stimuli shifted from the rest state to the task state, entropy exhibited a similar increase as the other two did. Although entropy showed only a part of the phenomenon induced by task strength, it showed superiority by showing a decrease in brain activation that the other two did not show. Moreover, entropy was capable of identifying the physiologically important location.

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near‐infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task‐evoked and spontaneous hemodynamic oscillations of non‐cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task‐evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency‐resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi‐channel and multi‐distance recordings. We found significant task‐related fluctuations for oxy‐ and deoxy‐hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non‐cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro‐visceral link.

We proposed the use of rhythmic mental arithmetic tasks to induce cyclic oscillations in multi‐distance fNIRS signals measured on the forehead, suitable for effective frequency‐domain analysis to better identify the actual neural functional response. We confirm the impairment of deep signals by task‐evoked non‐cerebral confounds, while providing evidence for an inverse oxygenation response in the frontopolar cortex.

Oscillator decomposition of infant fNIRS data

The functional near-infrared spectroscopy (fNIRS) can detect hemodynamic responses in the brain and the data consist of bivariate time series of oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) on each channel. In this study, we investigate oscillatory changes in infant fNIRS signals by using the oscillator decompisition method (OSC-DECOMP), which is a statistical method for extracting oscillators from time series data based on Gaussian linear state space models. OSC-DECOMP provides a natural decomposition of fNIRS data into oscillation components in a data-driven manner and does not require the arbitrary selection of band-pass filters. We analyzed 18-ch fNIRS data (3 minutes) acquired from 21 sleeping 3-month-old infants. Five to seven oscillators were extracted on most channels, and their frequency distribution had three peaks in the vicinity of 0.01-0.1 Hz, 1.6-2.4 Hz and 3.6-4.4 Hz. The first peak was considered to reflect hemodynamic changes in response to the brain activity, and the phase difference between oxy-Hb and deoxy-Hb for the associated oscillators was at approximately 230 degrees. The second peak was attributed to cardiac pulse waves and mirroring noise. Although these oscillators have close frequencies, OSC-DECOMP can separate them through estimating their different projection patterns on oxy-Hb and deoxy-Hb. The third peak was regarded as the harmonic of the second peak. By comparing the Akaike Information Criterion (AIC) of two state space models, we determined that the time series of oxy-Hb and deoxy-Hb on each channel originate from common oscillatory activity. We also utilized the result of OSC-DECOMP to investigate the frequency-specific functional connectivity. Whereas the brain oscillator exhibited functional connectivity, the pulse waves and mirroring noise oscillators showed spatially homogeneous and independent changes. OSC-DECOMP is a promising tool for data-driven extraction of oscillation components from biological time series data.

Investigating Differences in Behavior and Brain in Human-Human and Human-Autonomous Vehicle Interactions in Time-Critical Situations

Some studies provide evidence that humans could actively exploit the alleged technological advantages of autonomous vehicles (AVs). This implies that humans may tend to interact differently with AVs as compared to human driven vehicles (HVs) with the knowledge that AVs are programmed to be risk-averse. Hence, it is important to investigate how humans interact with AVs in complex traffic situations. Here, we investigated whether participants would value interactions with AVs differently compared to HVs, and if these differences can be characterized on the behavioral and brain-level. We presented participants with a cover story while recording whole-head brain activity using fNIRS that they were driving under time pressure through urban traffic in the presence of other HVs and AVs. Moreover, the AVs were programmed defensively to avoid collisions and had faster braking reaction times than HVs. Participants would receive a monetary reward if they managed to finish the driving block within a given time-limit without risky driving maneuvers. During the drive, participants were repeatedly confronted with left-lane turning situations at unsignalized intersections. They had to stop and find a gap to turn in front of an oncoming stream of vehicles consisting of HVs and AVs. While the behavioral results did not show any significant difference between the safety margin used during the turning maneuvers with respect to AVs or HVs, participants tended to be more certain in their decision-making process while turning in front of AVs as reflected by the smaller variance in the gap size acceptance as compared to HVs. Importantly, using a multivariate logistic regression approach, we were able to predict whether the participants decided to turn in front of HVs or AVs from whole-head fNIRS in the decision-making phase for every participant (mean accuracy = 67.2%, SD = 5%). Channel-wise univariate fNIRS analysis revealed increased brain activation differences for turning in front of AVs compared to HVs in brain areas that represent the valuation of actions taken during decision-making. The insights provided here may be useful for the development of control systems to assess interactions in future mixed traffic environments involving AVs and HVs.

Measuring Arterial Pulsatility With Dynamic Inflow Magnitude Contrast

The pulsatility of blood flow through cerebral arteries is clinically important, as it is intrinsically associated with cerebrovascular health. In this study we outline a new MRI approach to measuring the real-time pulsatile flow in cerebral arteries, which is based on the inflow phenomenon associated with fast gradient-recalled-echo acquisitions. Unlike traditional phase-contrast techniques, this new method, which we dub dynamic inflow magnitude contrast (DIMAC), does not require velocity-encoding gradients as sensitivity to flow velocity is derived purely from the inflow effect. We achieved this using a highly accelerated single slice EPI acquisition with a very short TR (15 ms) and a 90° flip angle, thus maximizing inflow contrast. We simulate the spoiled GRE signal in the presence of large arteries and perform a sensitivity analysis. The sensitivity analysis demonstrates that in the regime of high inflow contrast, DIMAC shows much greater sensitivity to flow velocity over blood volume changes. We support this theoretical prediction with in-vivo data collected in two separate experiments designed to demonstrate the utility of the DIMAC signal contrast. We perform a hypercapnia challenge experiment in order to experimentally modulate arterial tone within subjects, and thus modulate the arterial pulsatile flow waveform. We also perform a thigh-cuff release challenge, designed to induce a transient drop in blood pressure, and demonstrate that the continuous DIMAC signal captures the complex transient change in the pulsatile and non-pulsatile components of flow. In summary, this study proposes a new role for a well-established source of MR image contrast and demonstrates its potential for measuring both steady-state and dynamic changes in arterial tone.

A deep convolutional neural network for estimating hemodynamic response function with reduction of motion artifacts in fNIRS

OBJECTIVE

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique for monitoring hemoglobin concentration changes in a non-invasive manner. However, subject movements are often significant sources of artifacts. While several methods have been developed for suppressing this confounding noise, the conventional techniques have limitations on optimal selections of model parameters across participants or brain regions. To address this shortcoming, we aim to propose a method based on a deep convolutional neural network (CNN).

APPROACH

The U-net is employed as a CNN architecture. Specifically, large-scale training and testing data are generated by combining variants of hemodynamic response function (HRF) with experimental measurements of motion noises. The neural network is then trained to reconstruct hemodynamic response coupled to neuronal activity with a reduction of motion artifacts.

MAIN RESULTS

Using extensive analysis, we show that the proposed method estimates the task-related HRF more accurately than the existing methods of wavelet decomposition and autoregressive models. Specifically, the mean squared error and variance of HRF estimates, based on the CNN, are the smallest among all methods considered in this study. These results are more prominent when the semi-simulated data contains variants of shapes and amplitudes of HRF.

SIGNIFICANCE

The proposed CNN method allows for accurately estimating amplitude and shape of HRF with significant reduction of motion artifacts. This method may have a great potential for monitoring HRF changes in real-life settings that involve excessive motion artifacts.

Metabolic Connectivity and Hemodynamic-Metabolic Coherence of Human Prefrontal Cortex at Rest and Post Photobiomodulation Assessed by Dual-Channel Broadband NIRS

Billions of neurons in the human brain form neural networks with oscillation rhythms. Infra-slow oscillation (ISO) presents three main physiological sources: endogenic, neurogenic, and myogenic vasomotions. Having an in vivo methodology for the absolute quantification of ISO from the human brain can facilitate the detection of brain abnormalities in cerebral hemodynamic and metabolic activities. In this study, we introduced a novel measurement-plus-analysis framework for the non-invasive quantification of prefrontal ISO by (1) taking dual-channel broadband near infrared spectroscopy (bbNIRS) measurements from 12 healthy humans during a 6-min rest and 4-min post transcranial photobiomodulation (tPBM) and (2) performing wavelet transform coherence (WTC) analysis on the measured time series data. The WTC indexes (IC, between 0 and 1) enabled the assessment of ipsilateral hemodynamic-metabolic coherence and bilateral functional connectivity in each ISO band of the human prefrontal cortex. At rest, bilateral hemodynamic connectivity was consistent across the three ISO bands (IC ≅ 0.66), while bilateral metabolic connectivity was relatively weaker. For post-tPBM/sham comparison, our analyses revealed three key findings: 8-min, right-forehead, 1064-nm tPBM (1) enhanced the amplitude of metabolic oscillation bilaterally, (2) promoted the bilateral metabolic connectivity of neurogenic rhythm, and (3) made the main effect on endothelial cells, causing alteration of hemodynamic-metabolic coherence on each side of the prefrontal cortex.

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.

The neurodevelopmental basis of humor appreciation: A fNIRS study of young children

Humor is crucial for social development. Despite this, very few studies have examined the neurodevelopment of humor in very young children, and none to date have used functional near-infrared spectroscopy (fNIRS) to study this important cognitive construct. The main aim of the current study was to characterize the neural basis of humor processing in young children between the ages of 6–8 years. Thirty-five healthy children (6–8 years old) watched funny and neutral video clips while undergoing fNIRS imaging. We observed activation increases in left temporo-occipito-parietal junction (TOPJ), inferior-parietal lobe (IPL), dorsolateral-prefrontal cortex (DLPFC) and right inferior frontal gyrus (IFG) and superior parietal lobe (SPL) regions. Activation in left TOPJ was positively correlated with age. In addition, we found that coherence increased in humor viewing compared to neutral content, mainly between remote regions. This effect was different for boys and girls, as boys showed a more pronounced increase in coherence for funny compared to neutral videos, more so in frontoparietal networks. These results expand our understanding of the neurodevelopment of humor by highlighting the effect of age on the neural basis of humor appreciation as well as emphasizing different developmental trajectories of boys and girls.

Evaluation of fNIRS signal components elicited by cognitive and hypercapnic stimuli

Functional near infrared spectroscopy (fNIRS) measurements are confounded by signal components originating from multiple physiological causes, whose activities may vary temporally and spatially (across tissue layers, and regions of the cortex). Furthermore, the stimuli can induce evoked effects, which may lead to over or underestimation of the actual effect of interest. Here, we conducted a temporal, spectral, and spatial analysis of fNIRS signals collected during cognitive and hypercapnic stimuli to characterize effects of functional versus systemic responses. We utilized wavelet analysis to discriminate physiological causes and employed long and short source-detector separation (SDS) channels to differentiate tissue layers. Multi-channel measures were analyzed further to distinguish hemispheric differences. The results highlight cardiac, respiratory, myogenic, and very low frequency (VLF) activities within fNIRS signals. Regardless of stimuli, activity within the VLF band had the largest contribution to the overall signal. The systemic activities dominated the measurements from the short SDS channels during cognitive stimulus, but not hypercapnic stimulus. Importantly, results indicate that characteristics of fNIRS signals vary with type of the stimuli administered as cognitive stimulus elicited variable responses between hemispheres in VLF band and task-evoked temporal effect in VLF, myogenic and respiratory bands, while hypercapnic stimulus induced a global response across both hemispheres.

Changes in resting-state measures of prostate cancer patients exposed to androgen deprivation therapy

The aim of the present work is to describe the differences in rs-fMRI measures (Amplitude of low frequency fluctuations [ALFF], Regional Homogeneity [ReHo] and Functional Connectivity [FC]) between patients exposed to Androgen deprivation therapy (ADT) and a control group. Forty-nine ADT patients and fifteen PC-non-ADT patients (Controls) were included in the study. A neuropsychological evaluation and a resting-state fMRI was performed to evaluate differences in ALFF and ReHo. Region of interest (ROI) analysis was also performed. ROIs were selected among those whose androgen receptor expression (at RNA-level) was the highest. FC analysis was performed using the same ROIs. Higher ALFF in frontal regions and temporal regions was identified in Controls than in ADT patients. In the ROI analysis, higher activity for Controls than ADT patients was shown in the left inferior frontal gyrus and in the left precentral gyrus. Lower ALFF in the right hippocampus and the lateral geniculate nucleus of the right thalamus was identified for Controls than ADT patients. Higher ReHo was observed in Controls in the left parietal-occipital area. Finally, ADT patients presented an increase of FC in more regions than Controls. These differences may reflect an impairment in brain functioning in ADT users.

Hemodynamic changes associated with common EEG patterns in critically ill patients: Pilot results from continuous EEG-fNIRS study

Functional near-infrared spectroscopy (fNIRS) is currently the only non-invasive method allowing for continuous long-term assessment of cerebral hemodynamic. We evaluate the feasibility of using continueous electroencephalgraphy (cEEG)-fNIRS to study the cortical hemodynamic associated with status epilepticus (SE), burst suppression (BS) and periodic discharges (PDs). Eleven adult comatose patients admitted to the neuroICU for SE were recruited, and cEEG-fNIRS monitoring was performed to measure concentration changes in oxygenated (HbO) and deoxygenated hemoglobin (HbR). Seizures were associated with a large increase HbO and a decrease in HbR whose durations were positively correlated with the seizures' length. Similar observations were made for hemodynamic changes associated with bursts, showing overall increases in HbO and decreases in HbR relative to the suppression periods. PDs were seen to induce widespread HbO increases and HbR decreases. These results suggest that normal neurovascular coupling is partially retained with the hemodynamic response to the detected EEG patterns in these patients. However, the shape and distribution of the response were highly variable. This work highlighted the feasibility of conducting long-term cEEG-fNIRS to monitor hemodynamic changes over a large cortical area in critically ill patients, opening new routes for better understanding and management of abnormal EEG patterns in neuroICU.

Rhythmic Change of Cortical Hemodynamic Signals Associated with Ongoing Nociception in Awake and Anesthetized Individuals: An Exploratory Functional Near Infrared Spectroscopy Study

BACKGROUND

Patients undergoing surgical procedures are vulnerable to repetitive evoked or ongoing nociceptive barrage. Using functional near infrared spectroscopy, the authors aimed to evaluate the cortical hemodynamic signal power changes during ongoing nociception in healthy awake volunteers and in surgical patients under general anesthesia. The authors hypothesized that ongoing nociception to heat or surgical trauma would induce reductions in the power of cortical low-frequency hemodynamic oscillations in a similar manner as previously reported using functional magnetic resonance imaging for ongoing pain.

METHODS

Cortical hemodynamic signals during noxious stimuli from the fontopolar cortex were evaluated in two groups: group 1, a healthy/conscious group (n = 15, all males) where ongoing noxious and innocuous heat stimulus was induced by a contact thermode to the dorsum of left hand; and group 2, a patient/unconscious group (n = 13, 3 males) receiving general anesthesia undergoing knee surgery. The fractional power of low-frequency hemodynamic signals was compared across stimulation conditions in the healthy awake group, and between patients who received standard anesthesia and those who received standard anesthesia with additional regional nerve block.

RESULTS

A reduction of the total fractional power in both groups-specifically, a decrease in the slow-5 frequency band (0.01 to 0.027 Hz) of oxygenated hemoglobin concentration changes over the frontopolar cortex-was observed during ongoing noxious stimuli in the healthy awake group (paired t test, P = 0.017; effect size, 0.70), and during invasive procedures in the surgery group (paired t test, P = 0.003; effect size, 2.16). The reduction was partially reversed in patients who received a regional nerve block that likely diminished afferent nociceptive activity (two-sample t test, P = 0.002; effect size, 2.34).

CONCLUSIONS

These results suggest common power changes in slow-wave cortical hemodynamic oscillations during ongoing nociceptive processing in conscious and unconscious states. The observed signal may potentially promote future development of a surrogate signal to assess ongoing nociception under general anesthesia.

EDITOR’S PERSPECTIVE

Investigation of effect of modulation frequency on high-density diffuse optical tomography image quality

Significance: By incorporating multiple overlapping functional near-infrared spectroscopy (fNIRS) measurements, high-density diffuse optical tomography (HD-DOT) images human brain function with fidelity comparable to functional magnetic resonance imaging (fMRI). Previous work has shown that frequency domain high-density diffuse optical tomography (FD-HD-DOT) may further improve image quality over more traditional continuous wave (CW) HD-DOT. Aim: The effects of modulation frequency on image quality as obtainable with FD-HD-DOT is investigated through simulations with a realistic noise model of functional activations in human head models, arising from 11 source modulation frequencies between CW and 1000 MHz. Approach: Simulations were performed using five representative head models with an HD regular grid of 158 light sources and 166 detectors and an empirically derived noise model. Functional reconstructions were quantitatively assessed with multiple image quality metrics including the localization error (LE), success rate, full width at half maximum, and full volume at half maximum (FVHM). All metrics were evaluated against CW-based models. Results: Compared to CW, localization accuracy is improved by >40% throughout brain depths of 13 to 25 mm below the surface with 300 to 500 MHz modulation frequencies. Additionally, the reliable field of view in brain tissue is enlarged by 35% to 48% within an optimal frequency of 300 MHz after considering realistic noise, depending on the dynamic range of the system. Conclusions: These results point to the tremendous opportunities in further development of high bandwidth FD-HD-DOT system hardware for applications in human brain mapping.