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

The most fundamental and popular literature on functional near-infrared spectroscopy: a bibliometric analysis of the top 100 most cited articles

Background

Functional near infrared spectroscopy (fNIRS) has developed rapidly in recent years, and there are more and more studies on fNIRS. At present, there is no bibliometric analysis of the top 100 most cited articles on fNIRS research.

Objective

To identify the top 100 most cited articles on fNIRS and analyze those most fundamental and popular articles through bibliometric research methods.

Methods

The literature on fNIRS of web of science from 1990 to 2023 was searched and the top 100 most cited articles were identified by citations. Use the bibliometrix package in R studio and VOSviewer for data analysis and plotting to obtain the output characteristics and citation status of these 100 most cited articles, and analyze research trends in this field through keywords.

Results

A total of 9,424 articles were retrieved from web of science since 1990. The average citation number of the 100 articles was 457.4 (range from 260 to 1,366). Neuroimage published the most articles (n = 31). Villringer, A. from Leipzig University had the largest number of top 100 papers. Harvard University (n = 22) conducted most cited articles. The United States, Germany, Japan, and the United Kingdom had most cited articles, respectively. The most common keywords were near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fMRI, spectroscopy. The fund sources mostly came from National Institutes of Health Unitd States (NIH) and United States Department of Health Human Services (n = 28).

Conclusion

Neuroimage was the most popular journal. The top countries, institutions, and authors were the United States, Harvard University, and Villringer, A., respectively. Researchers and institutions from North America and Europe contributed the most. Near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fmri, spectroscopy, stimulation, blood-flow, light-propagation, infants, tissue comprise the future research directions and potential topic hotspots for fNIRS.

The use of functional near-infrared spectroscopy in tracking neurodevelopmental trajectories in infants and children with or without developmental disorders: a systematic review

Understanding the neurodevelopmental trajectories of infants and children is essential for the early identification of neurodevelopmental disorders, elucidating the neural mechanisms underlying the disorders, and predicting developmental outcomes. Functional Near-Infrared Spectroscopy (fNIRS) is an infant-friendly neuroimaging tool that enables the monitoring of cerebral hemodynamic responses from the neonatal period. Due to its advantages, fNIRS is a promising tool for studying neurodevelopmental trajectories. Although many researchers have used fNIRS to study neural development in infants/children and have reported important findings, there is a lack of synthesized evidence for using fNIRS to track neurodevelopmental trajectories in infants and children. The current systematic review summarized 84 original fNIRS studies and showed a general trend of age-related increase in network integration and segregation, interhemispheric connectivity, leftward asymmetry, and differences in phase oscillation during resting-state. Moreover, typically developing infants and children showed a developmental trend of more localized and differentiated activation when processing visual, auditory, and tactile information, suggesting more mature and specialized sensory networks. Later in life, children switched from recruiting bilateral auditory to a left-lateralized language circuit when processing social auditory and language information and showed increased prefrontal activation during executive functioning tasks. The developmental trajectories are different in children with developmental disorders, with infants at risk for autism spectrum disorder showing initial overconnectivity followed by underconnectivity during resting-state; and children with attention-deficit/hyperactivity disorders showing lower prefrontal cortex activation during executive functioning tasks compared to their typically developing peers throughout childhood. The current systematic review supports the use of fNIRS in tracking the neurodevelopmental trajectories in children. More longitudinal studies are needed to validate the neurodevelopmental trajectories and explore the use of these neurobiomarkers for the early identification of developmental disorders and in tracking the effects of interventions.

Age-dependent neurovascular coupling characteristics in children and adults during general anesthesia

General anesthesia is an indispensable procedure in clinical practice. Anesthetic drugs induce dramatic changes in neuronal activity and cerebral metabolism. However, the age-related changes in neurophysiology and hemodynamics during general anesthesia remain unclear. Therefore, the objective of this study was to explore the neurovascular coupling between neurophysiology and hemodynamics in children and adults during general anesthesia. We analyzed frontal electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals recorded from children (6-12 years old, n = 17) and adults (18-60 years old, n = 25) during propofol-induced and sevoflurane-maintained general anesthesia. The neurovascular coupling was evaluated in wakefulness, maintenance of a surgical state of anesthesia (MOSSA), and recovery by using correlation, coherence and Granger-causality (GC) between the EEG indices [EEG power in different bands and permutation entropy (PE)], and hemodynamic responses the oxyhemoglobin (Δ[HbO]) and deoxy-hemoglobin (Δ[Hb]) from fNIRS in the frequency band in 0.01-0.1 Hz. The PE and Δ[Hb] performed well in distinguishing the anesthesia state (p > 0.001). The correlation between PE and Δ[Hb] was higher than those of other indices in the two age groups. The coherence significantly increased during MOSSA (p < 0.05) compared with wakefulness, and the coherences between theta, alpha and gamma, and hemodynamic activities of children are significantly stronger than that of adults' bands. The GC from neuronal activities to hemodynamic responses decreased during MOSSA, and can better distinguish anesthesia state in adults. Propofol-induced and sevoflurane-maintained combination exhibited age-dependent neuronal activities, hemodynamics, and neurovascular coupling, which suggests the need for separate rules for children's and adults' brain states monitoring during general anesthesia.

mHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics

Hyperspectral imaging acquires data in both the spatial and frequency domains to offer abundant physical or biological information. However, conventional hyperspectral imaging has intrinsic limitations of bulky instruments, slow data acquisition rate, and spatiospectral trade-off. Here we introduce hyperspectral learning for snapshot hyperspectral imaging in which sampled hyperspectral data in a small subarea are incorporated into a learning algorithm to recover the hypercube. Hyperspectral learning exploits the idea that a photograph is more than merely a picture and contains detailed spectral information. A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from a red-green-blue (RGB) image without complete hyperspectral measurements. Hyperspectral learning is capable of recovering full spectroscopic resolution in the hypercube, comparable to high spectral resolutions of scientific spectrometers. Hyperspectral learning also enables ultrafast dynamic imaging, leveraging ultraslow video recording in an off-the-shelf smartphone, given that a video comprises a time series of multiple RGB images. To demonstrate its versatility, an experimental model of vascular development is used to extract hemodynamic parameters via statistical and deep learning approaches. Subsequently, the hemodynamics of peripheral microcirculation is assessed at an ultrafast temporal resolution up to a millisecond, using a conventional smartphone camera. This spectrally informed learning method is analogous to compressed sensing; however, it further allows for reliable hypercube recovery and key feature extractions with a transparent learning algorithm. This learning-powered snapshot hyperspectral imaging method yields high spectral and temporal resolutions and eliminates the spatiospectral trade-off, offering simple hardware requirements and potential applications of various machine learning techniques.

Decreased hemodynamic response to fearful faces relative to neutral faces in the medial frontal cortex of first-episode drug-naïve major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a disabling disease with impaired recognition of emotional facial expressions. However, the evidence is heterogeneous, regarding the mechanism of emotional processing in MDD. Focusing on patients with first-episode drug-naïve MDD, we used functional near-infrared spectroscopy (fNIRS) to investigate whether MDD have characteristic patterns in cerebral activation under facial emotion recognition task (FERT).

METHODS

Thirty-five patients with first-episode drug-naïve MDD and 39 healthy controls (HCs) underwent fNIRS measure to evaluate cerebral hemodynamic response in the frontal and temporal cortex during FERT. The 17-item Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale and Inventory of Depressive Symptomatology-Self Report were applied to assess the symptoms of the patients. Cognitive functions were assessed using THINC-integrated tool.

RESULTS

Hypoactivation in the medial frontal was observed in patients with MDD during recognition of fearful faces relative to neutral faces (F-N faces). Specifically, we found more right lateralized activation in the medial frontal cortex among patients with MDD compared to HCs. Further, the medial frontal activation under the condition of F-N faces was positively correlated to scores of digit symbol substitution test, and negatively relative to severity of depressive symptoms in MDD group.

LIMITATIONS

Our study is cross-sectional designed, and has a relatively small sample size.

CONCLUSIONS

We found abnormal patterns in the medial frontal activation of patients with first-episode drug-naïve MDD in recognition of F-N faces, which correlates with performance in cognitive function and depressive symptoms.

Using functional near-infrared spectroscopy to study the early developing brain: future directions and new challenges

Significance

Functional near-infrared spectroscopy (fNIRS) is a frequently used neuroimaging tool to explore the developing brain, particularly in infancy, with studies spanning from birth to toddlerhood (0 to 2 years). We provide an overview of the challenges and opportunities that the developmental fNIRS field faces, after almost 25 years of research.

Aim

We discuss the most recent advances in fNIRS brain imaging with infants and outlines the trends and perspectives that will likely influence progress in the field in the near future.

Approach

We discuss recent progress and future challenges in various areas and applications of developmental fNIRS from methodological and technological innovations to data processing and statistical approaches.

Results and Conclusions

The major trends identified include uses of fNIRS "in the wild," such as global health contexts, home and community testing, and hyperscanning; advances in hardware, such as wearable technology; assessment of individual variation and developmental trajectories particularly while embedded in studies examining other environmental, health, and context specific factors and longitudinal designs; statistical advances including resting-state network and connectivity, machine learning and reproducibility, and collaborative studies. Standardization and larger studies have been, and will likely continue to be, a major goal in the field, and new data analysis techniques, statistical methods, and collaborative cross-site projects are emerging.

Resting-state coupling between HbO and Hb measured by fNIRS in autism spectrum disorder

To distinguish between children with autism spectrum disorder (ASD) and typically developing (TD) children, we have uncovered a new discriminative feature, hemoglobin coupling. Functional near-infrared spectroscopy (fNIRS) was used to record resting-state hemodynamic fluctuations in the bilateral temporal lobes in 25 children with ASD and 22 TD children, in which the coupling between low frequency oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb) fluctuations was evaluated by Pearson correlation coefficient. The results showed significantly weak coupling in children with ASD in both the left and right, and throughout the whole temporal cortex. To explain this observation, a simulation study was performed using a balloon model, in which we found four related parameters could impact the coupling. This study suggested that hemoglobin coupling might be applied as a new cerebral hemodynamic characteristic for ASD screening or diagnostics.

Impact of Early Hemoglobin Levels on Neurodevelopment Outcomes of Two-Year-Olds in Very Preterm Children

OBJECTIVE

To evaluate, in very preterm infants, the hemoglobin (Hb) levels during the first 24 h and the neurodevelopment outcomes at 24 months of corrected age.

DESIGN, SETTING, AND PATIENTS

We conducted a secondary analysis of the French national prospective and population-based cohort EPIPAGE-2. The eligible study participants were live-born singletons who were born before 32 weeks of gestational age, with early Hb levels who were admitted to the neonatal intensive care unit.

MAIN OUTCOME MEASURES

The early Hb levels for an outcome survival at 24 months of corrected age without neurodevelopmental impairment were measured. The secondary outcomes were survival at discharge and without severe neonatal morbidity.

RESULTS

Of the 2158 singletons of <32 weeks with mean early Hb levels of 15.4 (±2.4) g/dL, 1490 of the infants (69%) had a follow-up at two years of age. An early Hb of 15.2 g/dL is the minimum receiving operating characteristic curve at the 24 months risk-free level, but the area under the curve at 0.54 (close to 50%) indicates that this rate was not informative. In logistic regression, no association was found between early Hb levels and outcomes at two years of age (aOR 0.966; 95% CI [0.775-1.204]; p = 0.758) but rather there was a correlation found with severe morbidity (aOR 1.322; 95% CI [1.003-1.743]; p = 0.048). A risk stratification tree showed that male newborns of >26 weeks with Hb of <15.5 g/dL (n = 703) were associated with a poor outcome at 24 months (OR 1.9; CI: [1.5-2.4] p < 0.01).

CONCLUSIONS

Early low Hb levels are associated with major neonatal morbidities in VP singletons, but not with neurodevelopment outcomes at two years of age, except in male infants of >26 Weeks GA.

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.

fNIRS-Based Dynamic Functional Connectivity Reveals the Innate Musical Sensing Brain Networks in Preterm Infants

Humans have the ability to appreciate and create music. However, why and how humans have this distinctive ability to perceive music remains unclear. Additionally, the investigation of the innate perceiving skill in humans is compounded by the fact that we have been actively and passively exposed to auditory stimuli or have systematically learnt music after birth. Therefore, to explore the innate musical perceiving ability, infants with preterm birth may be the most suitable population. In this study, the auditory brain networks were explored using dynamic functional connectivity-based reliable component analysis (RCA) in preterm infants during music listening. The brain activation was captured by portable functional near-infrared spectroscopy (fNIRS) to simulate a natural environment for preterm infants. The components with the maximum inter-subject correlation were extracted. The generated spatial filters identified the shared spatial structural features of functional brain connectivity across subjects during listening to the common music, exhibiting a functional synchronization between the right temporal region and the frontal and motor cortex, and synchronization between the bilateral temporal regions. The specific pattern is responsible for the functions involving music comprehension, emotion generation, language processing, memory, and sensory. The fluctuation of the extracted components and the phase variation demonstrates the interactions between the extracted brain networks to encode musical information. These results are critically important for our understanding of the underlying mechanisms of the innate perceiving skills at early ages of human during naturalistic music listening.

Open access dataset of task-free hemodynamic activity in 4-month-old infants during sleep using fNIRS

Spontaneous, task-free, hemodynamic activity of the brain provides useful information about its functional organization, as it can describe how different brain regions communicate to each other. Neuroimaging studies measuring the spontaneous activity of the brain are conducted while the participants are not engaged in a particular task or receiving any external stimulation. This approach is particularly useful in developmental populations as brain activity can be measured without the need for infant compliance and the risks of data contamination due to motion artifacts. In this project we sought to i) characterize the intrinsic functional organization of the brain in 4-month-old infants and ii) investigate whether bilingualism, as a specific environmental factor, could lead to adaptations on functional brain network development at this early age. Measures of spontaneous hemodynamic activity were acquired in 4-month-old infants (n = 104) during natural sleep using functional near-infrared spectroscopy (fNIRS). Emphasis was placed on acquiring high-quality data that could lead to reproducible results and serve as a valuable resource for researchers investigating the developing functional connectome.

Measurement(s)	spontaneous hemodynamic brain activity
Technology Type(s)	functional near infrared spectroscopy

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.

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.

Differential age-dependent development of inter-area brain connectivity in term and preterm neonates

BACKGROUND

Among preterm infants, higher morbidities of neurological disturbances and developmental delays are critical issues. Resting-state networks (RSNs) in the brain are suitable measures for assessing higher-level neurocognition. Since investigating task-related brain activity is difficult in neonates, assessment of RSNs provides invaluable insight into their neurocognitive development.

METHODS

The participants, 32 term and 71 preterm neonates, were divided into three groups based on gestational age (GA) at birth. Cerebral hemodynamic activity of RSNs was measured using functional near-infrared spectroscopy in the temporal, frontal, and parietal regions.

RESULTS

High-GA preterm infants (GA ≥ 30 weeks) had a significantly stronger RSN than low-GA preterm infants and term infants. Regression analyses of RSNs as a function of postnatal age (PNA) revealed a steeper regression line in the high-GA preterm and term infants than in the low-GA infants, particularly for inter-area brain connectivity between the frontal and left temporal areas.

CONCLUSIONS

Slower PNA-dependent development of the frontal-temporal network found only in the low-GA group suggests that significant brain growth optimal in the intrauterine environment takes place before 30 weeks of gestation. The present study suggests a likely reason for the high incidence of neurodevelopmental impairment in early preterm infants.

IMPACT

Resting-state fNIRS measurements in three neonate groups differing in gestational age (GA) showed stronger networks in the high-GA preterm infants than in the term and low-GA infants, which was partly explained by postnatal age (PNA). Regression analyses revealed a similar PNA-dependence in the development of the inter-area networks in the frontal and temporal lobes in the high-GA and term infants, and significantly slower development in the low-GA infants. These results suggest that optimal intrauterine brain growth takes place before 30 weeks of gestation. This explains one of the reasons for the high incidence of neurodevelopmental impairment in early preterm infants.

Gender difference in functional activity of 4-months-old infants during sleep: A functional near-infrared spectroscopy study

Sex differences emerge early in infancy. A number of earlier studies have investigated the resting-state network of infant sleep states, and there have been many studies using functional near-infrared spectroscopy (fNIRS) to examine the effects of infant language learning on changes in oxyhemoglobin and deoxyhemoglobin levels. However, studies examining sex differences from the resting-state network of infant sleep states are scarce. This study uses an open access dataset of task-free hemodynamic activity in 4-month-old infants during sleep by fNIRS, to identify some difference between male and female infants. We used Power Spectral Density showing at which frequencies the data variation/variance is high. We have also analyzed some gender differences by analyzing the relationship between individual channels, the degree of activation, etc. The results of this study showed that female and male infants had different Power Spectral Density for oxyhemoglobin and deoxyhemoglobin at rest, showing stronger differences at frontoparietal network, somatomotor network, visual network and dorsal network. This may be due to the differences in the timing or extent of development of those networks. These differences will provide some assistance in future studies of the early education of male and female infants.

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.

Most favorable stimulation duration in the sensorimotor cortex for fNIRS-based BCI

One of the primary objectives of the brain-computer interface (BCI) is to obtain a command with higher classification accuracy within the shortest possible time duration. Therefore, this study evaluates several stimulation durations to propose a duration that can yield the highest classification accuracy. Furthermore, this study aims to address the inherent delay in the hemodynamic responses (HRs) for the command generation time. To this end, HRs in the sensorimotor cortex were evaluated for the functional near-infrared spectroscopy (fNIRS)-based BCI. To evoke brain activity, right-hand-index finger poking and tapping tasks were used. In this study, six different stimulation durations (i.e., 1, 3, 5, 7, 10, and 15 s) were tested on 10 healthy male subjects. Upon stimulation, different temporal features and multiple time windows were utilized to extract temporal features. The extracted features were then classified using linear discriminant analysis. The classification results using the main HR showed that a 5 s stimulation duration could yield the highest classification accuracy, i.e., 74%, with a combination of the mean and maximum value features. However, the results were not significantly different from the classification accuracy obtained using the 15 s stimulation. To further validate the results, a classification using the initial dip was performed. The results obtained endorsed the finding with an average classification accuracy of 73.5% using the features of minimum peak and skewness in the 5 s window. The results based on classification using the initial dip for 5 s were significantly different from all other tested stimulation durations (p < 0.05) for all feature combinations. Moreover, from the visual inspection of the HRs, it is observed that the initial dip occurred as soon as the task started, but the main HR had a delay of more than 2 s. Another interesting finding is that impulsive stimulation in the sensorimotor cortex can result in the generation of a clearer initial dip phenomenon. The results reveal that the command for the fNIRS-based BCI can be generated using the 5 s stimulation duration. In conclusion, the use of the initial dip can reduce the time taken for the generation of commands and can be used to achieve a higher classification accuracy for the fNIRS-BCI within a 5 s task duration rather than relying on longer durations.

Global entrainment in the brain-body-environment: retrospective and prospective views

We celebrate the 60th anniversary of Biological Cybernetics. It has also been 30 years since "Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment" was published in Biological Cybernetics (Taga et al. in Biol Cybern 65(3):147-159, 1991). I would like to look back on the creation of this paper and discuss its subsequent development and future perspectives.

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.

Correcting physiological noise in whole-head functional near-infrared spectroscopy

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) has been increasingly employed to monitor cerebral hemodynamics in normal and diseased conditions. However, fNIRS suffers from its susceptibility to superficial activity and systemic physiological noise. The objective of the study was to establish a noise reduction method for fNIRS in a whole-head montage.

NEW METHOD

We have developed an automated denoising method for whole-head fNIRS. A high-density montage consisting of 109 long-separation channels and 8 short-separation channels was used for recording. Auxiliary sensors were also used to measure motion, respiration and pulse simultaneously. The method incorporates principal component analysis and general linear model to identify and remove a globally uniform superficial component. Our denoising method was evaluated in experimental data acquired from a group of healthy human subjects during a visually cued motor task and further compared with a minimal preprocessing method and three established denoising methods in the literature. Quantitative metrics including contrast-to-noise ratio, within-subject standard deviation and adjusted coefficient of determination were evaluated.

RESULTS

After denoising, whole-head topography of fNIRS revealed focal activations concurrently in the primary motor and visual areas.

COMPARISON WITH EXISTING METHODS

Analysis showed that our method improves upon the four established preprocessing methods in the literature.

CONCLUSIONS

An automatic, effective and robust preprocessing pipeline was established for removing physiological noise in whole-head fNIRS recordings. Our method can enable fNIRS as a reliable tool in monitoring large-scale, network-level brain activities for clinical uses.

Monitoring anesthesia using simultaneous functional Near Infrared Spectroscopy and Electroencephalography

OBJECTIVE

This study aims to understand the neural and hemodynamic responses during general anesthesia in order to develop a comprehensive multimodal anesthesia depth monitor using simultaneous functional Near Infrared Spectroscopy (fNIRS) and Electroencephalogram (EEG).

METHODS

37 adults and 17 children were monitored with simultaneous fNIRS and EEG, during the complete general anesthesia process. The coupling of fNIRS signals with neuronal signals (EEG) was calculated. Measures of complexity (sample entropy) and phase difference were also quantified from fNIRS signals to identify unique fNIRS based biomarkers of general anesthesia.

RESULTS

A significant decrease in the complexity and power of fNIRS signals characterize the anesthesia maintenance phase. Furthermore, responses to anesthesia vary between adults and children in terms of neurovascular coupling and frontal EEG alpha power.

CONCLUSIONS

This study shows that fNIRS signals could reliably quantify the underlying neuronal activity under general anesthesia and clearly distinguish the different phases throughout the procedure in adults and children (with less accuracy).

SIGNIFICANCE

A multimodal approach incorporating the specific differences between age groups, provides a reliable measure of anesthesia depth.

Shedding light on neuroscience: Two decades of functional near-infrared spectroscopy applications and advances from a bibliometric perspective

Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical brain-imaging technique that detects changes in hemoglobin concentration in the cerebral cortex. fNIRS devices are safe, silent, portable, robust against motion artifacts, and have good temporal resolution. fNIRS is reliable and trustworthy, as well as an alternative and a complement to other brain-imaging modalities, such as electroencephalography or functional magnetic resonance imaging. Given these advantages, fNIRS has become a well-established tool for neuroscience research, used not only for healthy cortical activity but also as a biomarker during clinical assessment in individuals with schizophrenia, major depressive disorder, bipolar disease, epilepsy, Alzheimer's disease, vascular dementia, and cancer screening. Owing to its wide applicability, studies on fNIRS have increased exponentially over the last two decades. In this study, scientific publications indexed in the Web of Science databases were collected and a bibliometric-type methodology was developed. For this purpose, a comprehensive science mapping analysis, including top-ranked authors, journals, institutions, countries, and co-occurring keywords network, was conducted. From a total of 2310 eligible documents, 6028 authors and 531 journals published fNIRS-related papers, Fallgatter published the highest number of articles and was the most cited author. University of Tübingen in Germany has produced the most trending papers since 2000. USA was the most prolific country with the most active institutions, followed by China, Japan, Germany, and South Korea. The results also revealed global trends in emerging areas of research, such as neurodevelopment, aging, and cognitive and emotional assessment.

Group-level cortical functional connectivity patterns using fNIRS: assessing the effect of bilingualism in young infants

Significance: Early monolingual versus bilingual experience induces adaptations in the development of linguistic and cognitive processes, and it modulates functional activation patterns during the first months of life. Resting-state functional connectivity (RSFC) is a convenient approach to study the functional organization of the infant brain. RSFC can be measured in infants during natural sleep, and it allows to simultaneously investigate various functional systems. Adaptations have been observed in RSFC due to a lifelong bilingual experience. Investigating whether bilingualism-induced adaptations in RSFC begin to emerge early in development has important implications for our understanding of how the infant brain's organization can be shaped by early environmental factors. Aims: We attempt to describe RSFC using functional near-infrared spectroscopy (fNIRS) and to examine whether it adapts to early monolingual versus bilingual environments. We also present an fNIRS data preprocessing and analysis pipeline that can be used to reliably characterize RSFC in development and to reduce false positives and flawed results interpretations. Methods: We measured spontaneous hemodynamic brain activity in a large cohort ( N = 99 ) of 4-month-old monolingual and bilingual infants using fNIRS. We implemented group-level approaches based on independent component analysis to examine RSFC, while providing proper control for physiological confounds and multiple comparisons. Results: At the group level, we describe the functional organization of the 4-month-old infant brain in large-scale cortical networks. Unbiased group-level comparisons revealed no differences in RSFC between monolingual and bilingual infants at this age. Conclusions: High-quality fNIRS data provide a means to reliably describe RSFC patterns in the infant brain. The proposed group-level RSFC analyses allow to assess differences in RSFC across experimental conditions. An effect of early bilingual experience in RSFC was not observed, suggesting that adaptations might only emerge during explicit linguistic tasks, or at a later point in development.

Evidence of Neurovascular Un-Coupling in Mild Alzheimer's Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data

Alzheimer’s disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively (p = 0.028 and p = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 (p = 2.17 × 10⁻⁵). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.

Low fraction of fetal haemoglobin is associated with retinopathy of prematurity in the very preterm infant

Background

Blood loss and adult blood transfusions are common during the neonatal period in preterm infants. The objective of the study was to clarify if degree of loss of fetal haemoglobin (HbF) was associated with later retinopathy of prematurity (ROP).

Methods

Retrospective observational cohort study. In total, 452 infants born <30 gestational weeks at a tertiary level neonatal intensive care unit in Sweden in 2009–2015 were included, 385 of whom had final ROP outcome. Mean fractions of HbF (%) during the first postnatal week were calculated from 11 861 arterial blood gas analyses. The relationship between fractions of HbF (%) and ROP was evaluated.

Results

The mean (SD) gestational age (GA) at birth was 26.4 (1.8) weeks. In total, 104 (27 %) infants developed ROP. Higher fraction of HbF (%) was associated with a lower prevalence of ROP, OR by a 10% increase 0.83 (95% CI: 0.71 to 0.97; p=0.019), following adjustment for GA at birth, small for GA and sex. Infants with HbF (%) in the lowest quartile had OR of 22.0 (95% CI: 8.1 to 59.2; p<0.001) for ROP development compared with those in the highest quartile. The predictive ability (area under the curve) of HbF (%) in the full model during the first week was 0.849 for ROP.

Conclusions

Early low fraction of HbF is independently associated with abnormal retinal neurovascular development in the very preterm infant. The potential benefit of minimising blood loss on development of ROP will be investigated in a multicenter randomised trial (NCT04239690).

A Prediction Model of Extubation Failure Risk in Preterm Infants

Objectives: This study aimed to identify variables and develop a prediction model that could estimate extubation failure (EF) in preterm infants. Study Design: We enrolled 128 neonates as a training cohort and 58 neonates as a validation cohort. They were born between 2015 and 2020, had a gestational age between 25^0/7 and 29^6/7 weeks, and had been treated with mechanical ventilation through endotracheal intubation (MVEI) because of acute respiratory distress syndrome. In the training cohort, we performed univariate logistic regression analysis along with stepwise discriminant analysis to identify EF predictors. A monogram based on five predictors was built. The concordance index and calibration plot were used to assess the efficiency of the nomogram in the training and validation cohorts. Results: The results of this study identified a 5-min Apgar score, early-onset sepsis, hemoglobin before extubation, pH before extubation, and caffeine administration as independent risk factors that could be combined for accurate prediction of EF. The EF nomogram was created using these five predictors. The area under the receiver operator characteristic curve was 0.824 (95% confidence interval 0.748-0.900). The concordance index in the training and validation cohorts was 0.824 and 0.797, respectively. The calibration plots showed high coherence between the predicted probability of EF and actual observation. Conclusions: This EF nomogram was a useful model for the precise prediction of EF risk in preterm infants who were between 25^0/7 and 29^6/7 weeks' gestational age and treated with MVEI because of acute respiratory distress syndrome.

Design and validation of a mechanically flexible and ultra-lightweight high-density diffuse optical tomography system for functional neuroimaging of newborns

Significance: Neonates are a highly vulnerable population. The risk of brain injury is greater during the first days and weeks after birth than at any other time of life. Functional neuroimaging that can be performed longitudinally and at the cot-side has the potential to improve our understanding of the evolution of multiple forms of neurological injury over the perinatal period. However, existing technologies make it very difficult to perform repeated and/or long-duration functional neuroimaging experiments at the cot-side. Aim: We aimed to create a modular, high-density diffuse optical tomography (HD-DOT) technology specifically for neonatal applications that is ultra-lightweight, low profile and provides high mechanical flexibility. We then sought to validate this technology using an anatomically accurate dynamic phantom. Approach: An advanced 10-layer rigid-flexible printed circuit board technology was adopted as the basis for the DOT modules, which allows for a compact module design that also provides the flexibility needed to conform to the curved infant scalp. Two module layouts were implemented: dual-hexagon and triple-hexagon. Using in-built board-to-board connectors, the system can be configured to provide a vast range of possible layouts. Using epoxy resin, thermochromic dyes, and MRI-derived 3D-printed moulds, we constructed an electrically switchable, anatomically accurate dynamic phantom. This phantom was used to quantify the imaging performance of our flexible, modular HD-DOT system. Results: Using one particular module configuration designed to cover the infant sensorimotor system, the device provided 36 source and 48 detector positions, and over 700 viable DOT channels per wavelength, ranging from 10 to ∼ 45    mm over an area of approximately 60    cm 2 . The total weight of this system is only 70 g. The signal changes from the dynamic phantom, while slow, closely simulated real hemodynamic response functions. Using difference images obtained from the phantom, the measured 3D localization error provided by the system at the depth of the cortex was in the of range 3 to 6 mm, and the lateral image resolution at the depth of the neonatal cortex is estimated to be as good as 10 to 12 mm. Conclusions: The HD-DOT system described is ultra-low weight, low profile, can conform to the infant scalp, and provides excellent imaging performance. It is expected that this device will make functional neuroimaging of the neonatal brain at the cot-side significantly more practical and effective.

Applications of functional near-infrared spectroscopy (fNIRS) in neonates

Functional near-infrared spectroscopy (fNIRS) is a method of monitoring brain oxygenation. This technique investigates hemodynamic changes in the cerebral cortex. fNIRS is widely used in clinical and scientific research. In this review, we focus on the applications of fNIRS on neonates. Here, applications form two distinct categories: task associated studies, and hemoglobin phase change studies. fNIRS is non-invasive, easily performed, and repeatable. However, it has limited monitoring depth and spatial resolution when used in newborns. Moreover, with recent technological advances, it is now possible to explore neuronal activity patterns using fNIRS in both healthy and pathological conditions. For more than 20 years, fNIRS has enabled clinicians to gain insight into cerebral development and mechanisms of injury in neonates. fNIRS is a useful supplement to existing technologies due to its ability to interrogate the neonatal brain function.

Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study

Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05-0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.

Using Functional Near-Infrared Spectroscopy to Assess Brain Activation Evoked by Guilt and Shame

Functional near-infrared spectroscopy (fNIRS) is a promising brain imaging modality for studying the neural substrates of moral emotions. However, the feasibility of using fNIRS to measure moral emotions has not been established. In the present study, we used fNIRS to detect the brain activation evoked by two typical moral emotions-guilt and shame. We presented the participants with guilt and shame context to evoke emotional responses and measured the brain activity by using fNIRS. The univariate general linear model analysis showed significant activations for both emotions in the orbitofrontal cortex, dorsolateral prefrontal cortex, and middle temporal gyrus, and specific activation for guilt in the right temporoparietal junction. The multivariate classification analysis showed an overall recognition accuracy of 52.50%, which was significantly higher than the chance level in classifying the guilt, shame, and neutral emotions. These results suggested the feasibility of using fNIRS to assess the brain activation evoked by guilt and shame and demonstrated the potentials of fNIRS in studying the neural correlates of moral emotions.

More than meets the eye: The neural development of emotion face processing during infancy

This study explored the impact of infant temperament and maternal stress on the development of the infant medial prefrontal cortex (mPFC) among sixteen 6-8-month-old infants. Functional Near Infrared Spectroscopy (fNIRS) was used to measure activation of the infant mPFC in response to angry, happy, and sad faces. Infant temperament and dimensions of maternal stress were measured with the Infant Behavior Questionnaire and the Parenting Stress Index Respectively. Infants with high negative emotionality demonstrated increased mPFC activation in association with all emotion face conditions. Negative emotionality moderated the effect of total maternal stress on mPFC activation to angry and sad faces. Mother-infant dysfunctional interaction was related to increased mPFC activation associated with happy faces, supporting the "novelty hypothesis", in which the mPFC responds more strongly to unique experiences. Therefore, this study provides additional evidence that infant temperament and the quality of the mother-infant relationship influence the development of the mPFC and how infants process emotions.

Reduction of Onset Delay in Functional Near-Infrared Spectroscopy: Prediction of HbO/HbR Signals

An intrinsic problem when using hemodynamic responses for the brain-machine interface is the slow nature of the physiological process. In this paper, a novel method that estimates the oxyhemoglobin changes caused by neuronal activations is proposed and validated. In monitoring the time responses of blood-oxygen-level-dependent signals with functional near-infrared spectroscopy (fNIRS), the early trajectories of both oxy- and deoxy-hemoglobins in their phase space are scrutinized. Furthermore, to reduce the detection time, a prediction method based upon a kernel-based recursive least squares (KRLS) algorithm is implemented. In validating the proposed approach, the fNIRS signals of finger tapping tasks measured from the left motor cortex are examined. The results show that the KRLS algorithm using the Gaussian kernel yields the best fitting for both ΔHbO (i.e., 87.5%) and ΔHbR (i.e., 85.2%) at q = 15 steps ahead (i.e., 1.63 s ahead at a sampling frequency of 9.19 Hz). This concludes that a neuronal activation can be concluded in about 0.1 s with fNIRS using prediction, which enables an almost real-time practice if combined with EEG.

Non-contact acquisition of brain function using a time-extracted compact camera

A revolution in functional brain imaging techniques is in progress in the field of neurosciences. Optical imaging techniques, such as high-density diffuse optical tomography (HD-DOT), in which source-detector pairs of probes are placed on subjects' heads, provide better portability than conventional functional magnetic resonance imaging (fMRI) equipment. However, these techniques remain costly and can only acquire images at up to a few measurements per square centimetre, even when multiple detector probes are employed. In this study, we demonstrate functional brain imaging using a compact and affordable setup that employs nanosecond-order pulsed ordinary laser diodes and a time-extracted image sensor with superimposition capture of scattered components. Our technique can simply and easily attain a high density of measurement points without requiring probes to be attached, and can directly capture two-dimensional functional brain images. We have demonstrated brain activity imaging using a phantom that mimics the optical properties of an adult human head, and with a human subject, have measured cognitive brain activation while the subject is solving simple arithmetical tasks.

Assessing Neural Compensation With Visuospatial Working Memory Load Using Near-Infrared Imaging

Alzheimer's disease is characterized by the progressive deterioration of cognitive abilities particularly working memory while mild cognitive impairment (MCI) represents its prodrome. It is generally believed that neural compensation is intact in MCI but absent in Alzheimer's disease. This study investigated the effects of increasing task load as a means to induce neural compensation through a novel visual working memory (VSWM) task using functional near-infrared spectroscopy (fNIRS). The bilateral prefrontal cortex (PFC) was explored due to its relevance in VSWM and neural compensation. A total of 31 healthy controls (HC), 12 patients with MCI and 18 patients with mild Alzheimer's disease (mAD) were recruited. Although all groups showed sensitivity in terms of behavioral performance (i.e. score) towards increasing task load (level 1 to 3), only in MCI load effect on cortical response (as measured by fNIRS) was significant. At lower task load, bilateral PFC activation did not differ between MCI and HC. Neural compensation in the form of hyperactivation was only noticeable in MCI with a moderate task load. Lack of hyperactivation in mAD, coupled with significantly poorer task performance across task loads, suggested the inability to compensate due to a greater degree of neurodegeneration. Our findings provided an insight into the interaction of cognitive load theory and neural compensatory mechanisms. The experiment results demonstrated the feasibility of inducing neural compensation with the proposed VSWM task at the right amount of cognitive load. This may provide a promising avenue to develop an effective cognitive training and rehabilitation for dementia population.

Cerebral hemodynamic responses in preterm-born neonates to visual stimulation: classification according to subgroups and analysis of frontotemporal-occipital functional connectivity

How neurovascular coupling develops in preterm-born neonates has been largely neglected in scientific research. We measured visually evoked (flicker light) hemodynamic responses (HRs) in preterm-born neonates ( n = 25 , gestational age: 31.71 ± 3.37 weeks, postnatal age: 25.48 ± 23.94 days) at the visual cortex (VC) and left frontotemporal lobe (FTL) using functional near-infrared spectroscopy (fNIRS) neuroimaging. We found that the HR characteristics show a large intersubject variability but could be classified into three groups according to the changes of oxyhemoglobin concentration at the VC [(A) increase, (B) decrease, or (C) inconclusive]. In groups A and B, the HRs at the left FTL were correlated with those at the VC, indicating the presence of a frontotemporal-occipital functional connectivity. Neonates in group A had a higher weight at measurement compared to those in group B, and had the lowest baseline total hemoglobin concentration and hematocrit compared to group C. To the best of our knowledge, this is the first fNIRS study showing (1) that the HRs of preterm-born neonates need to be classified into subgroups, (2) that the subgroups differed in terms of weight at measurement, and (3) that HRs can be observed also at the FTL during visual stimulation. These findings add insights into how neurovascular coupling develops in preterm-born neonates.

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.

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.

Effect of prewhitening in resting-state functional near-infrared spectroscopy data

Near-infrared spectroscopy (NIRS) offers the potential to characterize resting-state functional connectivity (RSFC) in populations that are not easily assessed otherwise, such as young infants. In addition to the advantages of NIRS, one should also consider that the RS-NIRS signal requires specific data preprocessing and analysis. In particular, the RS-NIRS signal shows a colored frequency spectrum, which can be observed as temporal autocorrelation, thereby introducing spurious correlations. To address this issue, prewhitening of the RS-NIRS signal has been recently proposed as a necessary step to remove the signal temporal autocorrelation and therefore reduce false-discovery rates. However, the impact of this step on the analysis of experimental RS-NIRS data has not been thoroughly assessed prior to the present study. Here, the results of a standard preprocessing pipeline in a RS-NIRS dataset acquired in infants are compared with the results after incorporating two different prewhitening algorithms. Our results with a standard preprocessing replicated previous studies. Prewhitening altered RSFC patterns and disrupted the antiphase relationship between oxyhemoglobin and deoxyhemoglobin. We conclude that a better understanding of the effect of prewhitening on RS-NIRS data is still needed before directly considering its incorporation to the standard preprocessing pipeline.

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.

Neuronal Activation Detection Using Vector Phase Analysis with Dual Threshold Circles: A Functional Near-Infrared Spectroscopy Study

In this paper, a new vector phase diagram differentiating the initial decreasing phase (i.e. initial dip) and the delayed hemodynamic response (HR) phase of oxy-hemoglobin changes ( Δ HbO) of functional near-infrared spectroscopy (fNIRS) is developed. The vector phase diagram displays the trajectories of Δ HbO and deoxy-hemoglobin changes ( Δ HbR), as orthogonal components, in the Δ HbO- Δ HbR polar coordinates. To determine the occurrence of an initial dip, dual threshold circles (an inner circle from the resting state, an outer circle from the peak values of the initial dip and the main HR) are incorporated into the phase diagram for making decisions. The proposed scheme is then applied to a brain-computer interface scheme, and its performance is evaluated in classifying two finger tapping tasks (right-hand thumb and little finger) from the left motor cortex. Three gamma functions are used to model the initial dip, the main HR, and the undershoot in generating the designed HR function. In classifying two tapping tasks, the signal mean and signal minimum values during 0-2.5 s, as features of initial dip, are used. The linear discriminant analysis was utilized as a classifier. The experimental results show that the active brain locations of the two tasks were quite distinctive ( p < 0.05 ), and moreover, spatially specific if using the initial dip map at 4 s in comparison to the map of HRs at 14 s. Also, the average classification accuracy was improved from 59% to 74.9% when using the phase diagram of dual threshold circles.

The cerebral hemodynamic response to phonetic changes of speech in preterm and term infants: The impact of postmenstrual age

Higher brain dysfunction, such as language delay, is a major concern among preterm infants. Cerebral substrates of cognitive development in preterm infants remain elusive, partly because of limited methods. The present study focuses on hemodynamic response patterns for brain function by using near-infrared spectroscopy. Specifically, the study investigates gestational differences in the hemodynamic response pattern evoked in response to phonetic changes of speech and cerebral hemispheric specialization of the auditory area in preterm infants (n = 60) and term infants (n = 20). Eighty neonates born between 26 and 41 weeks of gestational age (GA) were tested from 33 to 41 weeks of postmenstrual age (PMA). We analyzed the hemodynamic response pattern to phonemic and prosodic contrasts for multiple channels on temporal regions and the laterality index of the auditory area. Preterm infants younger than 39 weeks of PMA showed significantly atypical hemodynamic patterns, with an inverted response shape. Partial correlation analysis of the typicality score of hemodynamic response revealed a significant positive correlation with PMA. The laterality index of preterm infants from 39 weeks of PMA demonstrated a tendency rightward dominance for prosodic changes similar to term infants. We provide new evidence that alterations in hemodynamic regulation and the functional system for phonemic and prosodic processing in preterm infants catch up by their projected due dates.

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Hemodynamic responses to speech were examined in 80 preterm and term neonates.

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fNIRS measured hemispheric specialization to phonemic and prosodic contrasts.

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Some preterm infants showed atypical hemodynamics with an inverted response shape.

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Postmenstrual age was related to hemodynamic patterns and functional lateralization.

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Functional hemodynamic regulation of preterm infants caught up by the expected dates.

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.

Spatial variation in the hemoglobin phase of oxygenation and deoxygenation in the developing cortex of infants

Spontaneous low-frequency oscillatory changes in oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) are observed using functional near-infrared spectroscopy (fNIRS). A previous study showed that the time-averaged phase difference between oxy-Hb and deoxy-Hb changes, referred to as hemoglobin phase of oxygenation and deoxygenation (hPod), is sensitive to the development of the cortex. We examined phase-locking index of hPod, referred to as [Formula: see text], in addition to hPod, in neonates and 3- and 6-month-old infants using the 94-channel fNIRS data, which covered large lateral regions of the cortex. The results showed that (1) developmental changes in hPod exhibited spatial dependency; (2) [Formula: see text] increased between the neonate group and 3-month-old infant group over the posterior, but not anterior, regions of the cortex; and (3) the cortical regions of each age group were clustered in several domains with specific characteristics of hPod and [Formula: see text]. This study indicates that the neonatal cortex is composed of regions with specific characteristics of hPod and [Formula: see text], and drastic changes occur between the neonatal period and 3 months of age. This study suggests that hPod and [Formula: see text] are sensitive to the cortical region-specific development of the circulatory, blood flow, metabolic, and neurovascular functions in young infants.