Short separation regression improves statistical significance and better localizes the hemodynamic response obtained by near-infrared spectroscopy for tasks with differing autonomic responses

Lights on music cognition: A systematic and critical review of fNIRS applications and future perspectives

Research investigating the neural processes related to music perception and production constitutes a well-established field within the cognitive neurosciences. While most neuroimaging tools have limitations in studying the complexity of musical experiences, functional Near-Infrared Spectroscopy (fNIRS) represents a promising, relatively new tool for studying music processes in both laboratory and ecological settings, which is also suitable for both typical and pathological populations across development. Here we systematically review fNIRS studies on music cognition, highlighting prospects and potentialities. We also include an overview of fNIRS basic theory, together with a brief comparison to characteristics of other neuroimaging tools. Fifty-nine studies meeting inclusion criteria (i.e., using fNIRS with music as the primary stimulus) are presented across five thematic sections. Critical discussion of methodology leads us to propose guidelines of good practices aiming for robust signal analyses and reproducibility. A continuously updated world map is proposed, including basic information from studies meeting the inclusion criteria. It provides an organized, accessible, and updatable reference database, which could serve as a catalyst for future collaborations within the community. In conclusion, fNIRS shows potential for investigating cognitive processes in music, particularly in ecological contexts and with special populations, aligning with current research priorities in music cognition.

Synchronization of Neurophysiological and Biomechanical Data in a Real-Time Virtual Gait Analysis System (GRAIL): A Proof-of-Principle Study

The investigation of gait and its neuronal correlates under more ecologically valid conditions as well as real-time feedback visualization is becoming increasingly important in neuro-motor rehabilitation research. The Gait Real-time Analysis Interactive Lab (GRAIL) offers advanced opportunities for gait and gait-related research by creating more naturalistic yet controlled environments through immersive virtual reality. Investigating the neuronal aspects of gait requires parallel recording of brain activity, such as through mobile electroencephalography (EEG) and/or mobile functional near-infrared spectroscopy (fNIRS), which must be synchronized with the kinetic and /or kinematic data recorded while walking. This proof-of-concept study outlines the required setup by use of the lab streaming layer (LSL) ecosystem for real-time, simultaneous data collection of two independently operating multi-channel EEG and fNIRS measurement devices and gait kinetics. In this context, a customized approach using a photodiode to synchronize the systems is described. This study demonstrates the achievable temporal accuracy of synchronous data acquisition of neurophysiological and kinematic and kinetic data collection in the GRAIL. By using event-related cerebral hemodynamic activity and visually evoked potentials during a start-to-go task and a checkerboard test, we were able to confirm that our measurement system can replicate known physiological phenomena with latencies in the millisecond range and relate neurophysiological and kinetic data to each other with sufficient accuracy.

Flexible-circuit-based 3-D aware modular optical brain imaging system for high-density measurements in natural settings

Significance

Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic condition remains a significant challenge.

Aim

The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide real-time probe 3-D shape estimation to improve the use of fNIRS in everyday conditions.

Approach

The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3-D positions in real-time to enable advanced tomographic data analysis and motion tracking.

Results

Optical characterization of the MOBI detector reports a noise equivalence power (NEP) of 8.9 and 7.3 pW / H z at 735 nm and 850 nm, respectively, with a dynamic range of 88 dB. The 3-D optode shape acquisition yields an average error of 4.2 mm across 25 optodes in a phantom test compared to positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided.

Conclusions

To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3-D optode position acquisition, combined with lightweight modules (18 g/module) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.

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.

Directed physiological networks in the human prefrontal cortex at rest and post transcranial photobiomodulation

Cerebral infra-slow oscillation (ISO) is a source of vasomotion in endogenic (E; 0.005-0.02 Hz), neurogenic (N; 0.02-0.04 Hz), and myogenic (M; 0.04-0.2 Hz) frequency bands. In this study, we quantified changes in prefrontal concentrations of oxygenated hemoglobin (Δ[HbO]) and redox-state cytochrome c oxidase (Δ[CCO]) as hemodynamic and metabolic activity metrics, and electroencephalogram (EEG) powers as electrophysiological activity, using concurrent measurements of 2-channel broadband near-infrared spectroscopy and EEG on the forehead of 22 healthy participants at rest. After preprocessing, the multi-modality signals were analyzed using generalized partial directed coherence to construct unilateral neurophysiological networks among the three neurophysiological metrics (with simplified symbols of HbO, CCO, and EEG) in each E/N/M frequency band. The links in these networks represent neurovascular, neurometabolic, and metabolicvascular coupling (NVC, NMC, and MVC). The results illustrate that the demand for oxygen by neuronal activity and metabolism (EEG and CCO) drives the hemodynamic supply (HbO) in all E/N/M bands in the resting prefrontal cortex. Furthermore, to investigate the effect of transcranial photobiomodulation (tPBM), we performed a sham-controlled study by delivering an 800-nm laser beam to the left and right prefrontal cortex of the same participants. After performing the same data processing and statistical analysis, we obtained novel and important findings: tPBM delivered on either side of the prefrontal cortex triggered the alteration or reversal of directed network couplings among the three neurophysiological entities (i.e., HbO, CCO, and EEG frequency-specific powers) in the physiological network in the E and N bands, demonstrating that during the post-tPBM period, both metabolism and hemodynamic supply drive electrophysiological activity in directed network coupling of the prefrontal cortex (PFC). Overall, this study revealed that tPBM facilitates significant modulation of the directionality of neurophysiological networks in electrophysiological, metabolic, and hemodynamic activities.

Neuronal Control of Posture in Blind Individuals

The control of posture is guided by the integration of sensory information. Because blind individuals cannot apply visual information to control posture as sighted individuals do they must compensate by the remaining senses. We therefore hypothesize that blind individuals alter their brain activation in the sensorimotor cortex during postural control to compensate for balance control without vision by the increased integration of somatosensory information. Ten blind and ten sighted (matched) individuals controlled posture during conditions with (I) eyes closed / open, and (II) stable / unstable surface conditions. Postural sway was recorded by applying a pressure distribution measuring plate. Brain activation was collected by functional Near InfraRed Spectroscopy (fNIRS) above motor-sensory cortices of the right and left hemispheres. Blind individuals showed significantly increased postural sway when balancing with open eyes on an unstable surface and when compared to sighted individuals. Whereas blind individuals showed significantly increased brain activation when balancing with open eyes on stable and unstable surface conditions, sighted individuals increased their brain oxygenation only during closed eyes and unstable surface conditions. Overall conditions, blind individuals presented significantly increased brain activation in two channels of the left and right hemispheric motor-sensory cortex when compared to sighted individuals. We therefore conclude that sighted individuals increase their brain oxygenation in the sensorimotor cortex during postural control tasks that demand sensory integration processes. Blind individuals are characterized by increased brain activation overall conditions indicating additional sensory integration during postural control. Thus, the sensorimotor cortex of blind individuals adapts to control posture without vision.

Evaluating the Neural Underpinnings of Motivation for Walking Exercise

OBJECTIVE

Motivation is critically important for rehabilitation, exercise, and motor performance, but its neural basis is poorly understood. Recent correlational research suggests that the dorsomedial prefrontal cortex (dmPFC) may be involved in motivation for walking activity and/or descending motor output. This study experimentally evaluated brain activity changes in periods of additional motivation during walking exercise and tested how these brain activity changes relate to self-reported exercise motivation and walking speed.

METHODS

Adults without disability (N = 26; 65% women; 25 [standard deviation = 5] years old) performed a vigorous exercise experiment involving 20 trials of maximal speed overground walking. Half of the trials were randomized to include "extra-motivation" stimuli (lap timer, tracked best lap time, and verbal encouragement). Wearable near-infrared spectroscopy measured oxygenated hemoglobin responses from frontal lobe regions, including the dmPFC, primary sensorimotor, dorsolateral prefrontal, anterior prefrontal, supplementary motor, and dorsal premotor cortices.

RESULTS

Compared with standard trials, participants walked faster during extra-motivation trials (2.43 vs 2.67 m/s; P < .0001) and had higher oxygenated hemoglobin responses in all tested brain regions, including dmPFC (+842 vs +1694 μM; P < .0001). Greater dmPFC activity was correlated with more self-determined motivation for exercise between individuals (r = 0.55; P = .004) and faster walking speed between trials (r = 0.18; P = .0002). dmPFC was the only tested brain region that showed both of these associations.

CONCLUSION

Simple motivational stimuli during walking exercise seem to upregulate widespread brain regions. Results suggest that dmPFC may be a key brain region linking affective signaling to motor output.

IMPACT

These findings provide a potential biologic basis for the benefits of motivational stimuli, elicited with clinically feasible methods during walking exercise. Future clinical studies could build on this information to develop prognostic biomarkers and test novel brain stimulation targets for enhancing exercise motivation (eg, dmPFC).

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

Significance

The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique.

Aim

We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.

Approach

Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy.

Results

Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow.

Conclusion

We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

Phasic and repetitive self-touch differ in hemodynamic response in the prefrontal cortex-An fNIRS study

Introduction

Each individual touches the own body several 100 times a day. While some researchers propose a self-regulatory function of self-touch, others report that self-touching increases nervousness. This controversy appears to be caused by the fact that researchers did not define the kind of self-touch they examined and actually, referred to different types of self-touch. Thus, kinematically defining different types of self-touch, such as phasic (discrete), repetitive, and irregular, and exploring the neural correlates of the different types will provide insight into the neuropsychological function of self-touching behavior.

Methods

To this aim, we assessed hemodynamic responses in prefrontal brain areas using functional near-infrared spectroscopy (fNIRS) and behavioral responses with NEUROGES®. Fifty-two participants were recorded during three specific kinematically types of self-touch (phasic, irregular, repetitive) that were to be performed on command. The recently developed toolbox Satori was used for the visualization of neuronal processes.

Results

Behaviorally, the participants did not perform irregular self-touch reliably. Neurally, the comparison of phasic, irregular and repetitive self-touch revealed different activation patterns. Repetitive self-touch is associated with stronger hemodynamic responses in the left Orbitofrontal Cortex and the Dorsolateral Prefrontal Cortex than phasic self-touch.

Discussion

These brain areas have been reported to be associated with self-regulatory processes. Furthermore, irregular self-touch appears to be primarily generated by implicit neural control. Thus, by distinguishing kinematically different types of self-touch, our findings shed light on the controverse discussion on the neuropsychological function of self-touch.

Premotor and Posterior Parietal Cortex Activity is Increased for Slow, as well as Fast Walking Poststroke: An fNIRS Study

Methods

Twenty individuals in the chronic stage of stroke walked: (1) at their normal pace, (2) slower than normal, and (3) as fast as possible. Functional near-infrared spectroscopy was used to assess bilateral prefrontal, premotor, sensorimotor, and posterior parietal cortices during walking.

Results

No significant differences in laterality were observed between walking speeds. The ipsilesional prefrontal cortex was overall more active than the contralesional prefrontal cortex. Premotor and posterior parietal cortex activity were larger during slow and fast walking compared to normal-paced walking with no differences between slow and fast walking. Greater increases in brain activation in the ipsilesional prefrontal cortex during fast compared to normal-paced walking related to greater gait speed modulation.

Conclusions

Brain activation is not linearly related to gait speed. Ipsilesional prefrontal cortex, bilateral premotor, and bilateral posterior parietal cortices are important areas for gait speed modulation and could be an area of interest for neurostimulation.

Directed physiological networks in the human prefrontal cortex at rest and post transcranial photobiomodulation

Cerebral infra-slow oscillation (ISO) is a source of vasomotion in endogenic (E; 0.005-0.02 Hz), neurogenic (N; 0.02-0.04 Hz), and myogenic (M; 0.04-0.2 Hz) frequency bands. In this study, we quantified changes in prefrontal concentrations of oxygenated hemoglobin ( Δ [ H b O ] ) and redox-state cytochrome c oxidase ( Δ [ C C O ] ) as hemodynamic and metabolic activity metrics, and electroencephalogram (EEG) powers as electrophysiological activity, using concurrent measurements of 2-channel broadband near-infrared spectroscopy and EEG on the forehead of 22 healthy participants at rest. After preprocessing, the multi-modality signals were analyzed using generalized partial directed coherence to construct unilateral neurophysiological networks among the three neurophysiological metrics (with simplified symbols of HbO, CCO, and EEG) in each E/N/M frequency band. The links in these networks represent neurovascular, neurometabolic, and metabolicvascular coupling (NVC, NMC, and MVC). The results illustrate that the demand for oxygen by neuronal activity and metabolism (EEG and CCO) drives the hemodynamic supply (HbO) in all E/N/M bands in the resting prefrontal cortex. Furthermore, to investigate the effect of transcranial photobiomodulation (tPBM), we performed a sham-controlled study by delivering an 800-nm laser beam to the left and right prefrontal cortex of the same participants. After performing the same data processing and statistical analysis, we obtained novel and important findings: tPBM delivered on either side of the prefrontal cortex triggered the alteration or reversal of directed network couplings among the three neurophysiological entities (i.e., HbO, CCO, and EEG frequency-specific powers) in the physiological network in the E and N bands, demonstrating that during the post-tPBM period, both metabolism and hemodynamic supply drive electrophysiological activity in directed network coupling of the PFC. Overall, this study revealed that tPBM facilitates significant modulation of the directionality of neurophysiological networks in electrophysiological, metabolic, and hemodynamic activities.

Measuring human cerebral blood flow and brain function with fiber-based speckle contrast optical spectroscopy system

Cerebral blood flow (CBF) is crucial for brain health. Speckle contrast optical spectroscopy (SCOS) is a technique that has been recently developed to measure CBF, but the use of SCOS to measure human brain function at large source-detector separations with comparable or greater sensitivity to cerebral rather than extracerebral blood flow has not been demonstrated. We describe a fiber-based SCOS system capable of measuring human brain activation induced CBF changes at 33 mm source detector separations using CMOS detectors. The system implements a pulsing strategy to improve the photon flux and uses a data processing pipeline to improve measurement accuracy. We show that SCOS outperforms the current leading optical modality for measuring CBF, i.e. diffuse correlation spectroscopy (DCS), achieving more than 10x SNR improvement at a similar financial cost. Fiber-based SCOS provides an alternative approach to functional neuroimaging for cognitive neuroscience and health science applications.

Increased Cortical Activity in Novices Compared to Experts During Table Tennis: A Whole-Brain fNIRS Study Using Threshold-Free Cluster Enhancement Analysis

There is a growing interest to understand the neural underpinnings of high-level sports performance including expertise-related differences in sport-specific skills. Here, we aimed to investigate whether expertise level and task complexity modulate the cortical hemodynamics of table tennis players. 35 right-handed table tennis players (17 experts/18 novices) were recruited and performed two table tennis strokes (forehand and backhand) and a randomized combination of them. Cortical hemodynamics, as a proxy for cortical activity, were recorded using functional near-infrared spectroscopy, and the behavioral performance (i.e., target accuracy) was assessed via video recordings. Expertise- and task-related differences in cortical hemodynamics were analyzed using nonparametric threshold-free cluster enhancement. In all conditions, table tennis experts showed a higher target accuracy than novices. Furthermore, we observed expertise-related differences in widespread clusters compromising brain areas being associated with sensorimotor and multisensory integration. Novices exhibited, in general, higher activation in those areas as compared to experts. We also identified task-related differences in cortical activity including frontal, sensorimotor, and multisensory brain areas. The present findings provide empirical support for the neural efficiency hypothesis since table tennis experts as compared to novices utilized a lower amount of cortical resources to achieve superior behavioral performance. Furthermore, our findings suggest that the task complexity of different table tennis strokes is mirrored in distinct cortical activation patterns. Whether the latter findings can be useful to monitor or tailor sport-specific training interventions necessitates further investigations.

Agreement in cerebrovascular reactivity assessed with diffuse correlation spectroscopy across experimental paradigms improves with short separation regression

Significance

Cerebrovascular reactivity (CVR), i.e., the ability of cerebral vasculature to dilate or constrict in response to vasoactive stimuli, is a biomarker of vascular health. Exogenous administration of inhaled carbon dioxide, i.e., hypercapnia (HC), remains the "gold-standard" intervention to assess CVR. More tolerable paradigms that enable CVR quantification when HC is difficult/contraindicated have been proposed. However, because these paradigms feature mechanistic differences in action, an assessment of agreement of these more tolerable paradigms to HC is needed.

Aim

We aim to determine the agreement of CVR assessed during HC, breath-hold (BH), and resting state (RS) paradigms.

Approach

Healthy adults were subject to HC, BH, and RS paradigms. End tidal carbon dioxide (EtCO2) and cerebral blood flow (CBF, assessed with diffuse correlation spectroscopy) were monitored continuously. CVR (%/mmHg) was quantified via linear regression of CBF versus EtCO2 or via a general linear model (GLM) that was used to minimize the influence of systemic and extracerebral signal contributions.

Results

Strong agreement ( CCC ≥ 0.69 ; R ≥ 0.76 ) among CVR paradigms was demonstrated when utilizing a GLM to regress out systemic/extracerebral signal contributions. Linear regression alone showed poor agreement across paradigms ( CCC ≤ 0.35 ; R ≤ 0.45 ).

Conclusions

More tolerable experimental paradigms coupled with regression of systemic/extracerebral signal contributions may offer a viable alternative to HC for assessing CVR.

Trigeminal stimulation is required for neural representations of bimodal odor localization: A time-resolved multivariate EEG and fNIRS study

Whereas neural representations of spatial information are commonly studied in vision, olfactory stimuli might also be able to create such representations via the trigeminal system. We explored in two independent multi-method electroencephalography-functional near-infrared spectroscopy (EEG+fNIRS) experiments (n1=18, n2=14) if monorhinal odor stimuli can evoke spatial representations in the brain. We tested whether this representation depends on trigeminal properties of the stimulus, and if the retention in short-term memory follows the "sensorimotor recruitment theory", using multivariate representational similarity analysis (RSA). We demonstrate that the delta frequency band up to 5 Hz across the scull entail spatial information of which nostril has been stimulated. Delta frequencies were localized in a network involving primary and secondary olfactory, motor-sensory and occipital regions. RSA on fNIRS data showed that monorhinal stimulations evoke neuronal representations in motor-sensory regions and that this representation is kept stable beyond the time of perception. These effects were no longer valid when the odor stimulus did not sufficiently stimulate the trigeminal nerve as well. Our results are first evidence that the trigeminal system can create spatial representations of bimodal odors in the brain and that these representations follow similar principles as the other sensory systems.

fNIRS is sensitive to leg activity in the primary motor cortex after systemic artifact correction

BACKGROUND

functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool to study cortical activity during movement and gait that requires further validation. This study aimed to assess (1) whether fNIRS can detect the difficult-to-measure leg area of the primary motor cortex (M1) and distinguish it from the hand area; and (2) whether fNIRS can differentiate between automatic (i.e., not requiring one's attention) and non-automatic movement processes. Special attention was attributed to systemic artifacts (i.e., changes in blood pressure, heart rate, breathing) which were assessed and corrected by short channels, i.e., fNIRS channels which are mainly sensitive to superficial scalp hemodynamics.

METHODS

Twenty-three seated, healthy participants tapped four fingers on a keyboard or tapped the right foot on four squares on the floor in a specific order given by a 12-digit sequence (e.g., 434141243212). Two different sequences were executed: a beforehand learned (i.e., automatic) version and a newly learned (i.e., non-automatic) version. A 36-channel fNIRS device including 12 short channels covered multiple motor-related cortical areas including M1. The fNIRS data were analyzed with a general linear model (GLM). Correlation between the expected functional hemodynamic responses (i.e. task regressor) and the short channels (i.e. nuisance regressors), necessitated performing a separate short channel regression instead of integrating them in the GLM.

RESULTS

Consistent with the M1 somatotopy, we found significant HbO increases of very large effect size in the lateral M1 channels during finger tapping (Cohen's d = 1.35, p<0.001) and significant HbO increases of moderate effect size in the medial M1 channels during foot tapping (Cohen's d = 0.8, p<0.05). The cortical activity differences between automatic and non-automatic tasks were not significantly different. Importantly, leg movements produced large systemic fluctuations, which were adequately removed by the use of all available short channels.

DISCUSSION

Our results indicate that fNIRS is sensitive to leg activity in M1, though the sensitivity is lower than for finger activity and requires rigorous correction for systemic fluctuations. We furthermore highlight that systemic artifacts may result in an unreliable GLM analysis when short channels show signals that are similar to the expected hemodynamic responses.

Acute effects of nitrate and breakfast on working memory, cerebral blood flow, arterial stiffness, and psychological factors in adolescents: Study protocol for a randomised crossover trial

BACKGROUND

Inorganic nitrate has been shown to acutely improve working memory in adults, potentially by altering cerebral and peripheral vasculature. However, this remains unknown in adolescents. Furthermore, breakfast is important for overall health and psychological well-being. Therefore, this study will investigate the acute effects of nitrate and breakfast on working memory performance, task-related cerebral blood flow (CBF), arterial stiffness, and psychological outcomes in Swedish adolescents.

METHODS

This randomised crossover trial will recruit at least 43 adolescents (13-15 years old). There will be three experimental breakfast conditions: (1) none, (2) low-nitrate (normal breakfast), and (3) high-nitrate (concentrated beetroot juice with normal breakfast). Working memory (n-back tests), CBF (task-related changes in oxygenated and deoxygenated haemoglobin in the prefrontal cortex), and arterial stiffness (pulse wave velocity and augmentation index) will be measured twice, immediately after breakfast and 130 min later. Measures of psychological factors and salivary nitrate/nitrite will be assessed once before the conditions and at two-time points after the conditions.

DISCUSSION

This study will provide insight into the acute effects of nitrate and breakfast on working memory in adolescents and to what extent any such effects can be explained by changes in CBF. This study will also shed light upon whether oral intake of nitrate may acutely improve arterial stiffness and psychological well-being, in adolescents. Consequently, results will indicate if nitrate intake from beetroot juice or if breakfast itself could acutely improve cognitive, vascular, and psychological health in adolescents, which can affect academic performance and have implications for policies regarding school meals.

TRIAL REGISTRATION

The trial has been prospectively registered on 21/02/2022 at https://doi.org/10.1186/ISRCTN16596056. Trial number: ISRCTN16596056.

How much do time-domain functional near-infrared spectroscopy (fNIRS) moments improve estimation of brain activity over traditional fNIRS?

SIGNIFICANCE

Advances in electronics have allowed the recent development of compact, high channel count time domain functional near-infrared spectroscopy (TD-fNIRS) systems. Temporal moment analysis has been proposed for increased brain sensitivity due to the depth selectivity of higher order temporal moments. We propose a general linear model (GLM) incorporating TD moment data and auxiliary physiological measurements, such as short separation channels, to improve the recovery of the HRF.

AIMS

We compare the performance of previously reported multi-distance TD moment techniques to commonly used techniques for continuous wave (CW) fNIRS hemodynamic response function (HRF) recovery, namely block averaging and CW GLM. Additionally, we compare the multi-distance TD moment technique to TD moment GLM.

APPROACH

We augmented resting TD-fNIRS moment data (six subjects) with known synthetic HRFs. We then employed block averaging and GLM techniques with "short-separation regression" designed both for CW and TD to recover the HRFs. We calculated the root mean square error (RMSE) and the correlation of the recovered HRF to the ground truth. We compared the performance of equivalent CW and TD techniques with paired t-tests.

RESULTS

We found that, on average, TD moment HRF recovery improves correlations by 98% and 48% for HbO and HbR respectively, over CW GLM. The improvement on the correlation for TD GLM over TD moment is 12% (HbO) and 27% (HbR). RMSE decreases 56% and 52% (HbO and HbR) for TD moment compared to CW GLM. We found no statistically significant improvement in the RMSE for TD GLM compared to TD moment.

CONCLUSIONS

Properly covariance-scaled TD moment techniques outperform their CW equivalents in both RMSE and correlation in the recovery of the synthetic HRFs. Furthermore, our proposed TD GLM based on moments outperforms regular TD moment analysis, while allowing the incorporation of auxiliary measurements of the confounding physiological signals from the scalp.

Revealing the spatiotemporal requirements for accurate subject identification with resting-state functional connectivity: a simultaneous fNIRS-fMRI study

SIGNIFICANCE

Brain fingerprinting refers to identifying participants based on their functional patterns. Despite its success with functional magnetic resonance imaging (fMRI), brain fingerprinting with functional near-infrared spectroscopy (fNIRS) still lacks adequate validation.

AIM

We investigated how fNIRS-specific acquisition features (limited spatial information and nonneural contributions) influence resting-state functional connectivity (rsFC) patterns at the intra-subject level and, therefore, brain fingerprinting.

APPROACH

We performed multiple simultaneous fNIRS and fMRI measurements in 29 healthy participants at rest. Data were preprocessed following the best practices, including the removal of motion artifacts and global physiology. The rsFC maps were extracted with the Pearson correlation coefficient. Brain fingerprinting was tested with pairwise metrics and a simple linear classifier.

RESULTS

Our results show that average classification accuracy with fNIRS ranges from 75% to 98%, depending on the number of runs and brain regions used for classification. Under the right conditions, brain fingerprinting with fNIRS is close to the 99.9% accuracy found with fMRI. Overall, the classification accuracy is more impacted by the number of runs and the spatial coverage than the choice of the classification algorithm.

CONCLUSIONS

This work provides evidence that brain fingerprinting with fNIRS is robust and reliable for extracting unique individual features at the intra-subject level once relevant spatiotemporal constraints are correctly employed.

Association between carotid atherosclerosis and brain activation patterns during the Stroop task in older adults: An fNIRS investigation

There is an increasing body of evidence suggesting that vascular disease could contribute to cognitive decline and overt dementia. Of particular interest is atherosclerosis, as it is not only associated with dementia, but could be a potential mechanism through which cardiovascular disease directly impacts brain health. In this work, we evaluated the differences in functional near infrared spectroscopy (fNIRS)-based measures of brain activation, task performance, and the change in central hemodynamics (mean arterial pressure (MAP) and heart rate (HR)) during a Stroop color-word task in individuals with atherosclerosis, defined as bilateral carotid plaques (n = 33) and healthy age-matched controls (n = 33). In the healthy control group, the left prefrontal cortex (LPFC) was the only region showing evidence of activation when comparing the incongruous with the nominal Stroop test. A smaller extent of brain activation was observed in the Plaque group compared with the healthy controls (1) globally, as measured by oxygenated hemoglobin (p = 0.036) and (2) in the LPFC (p = 0.02) and left sensorimotor cortices (LMC)(p = 0.008) as measured by deoxygenated hemoglobin. There were no significant differences in HR, MAP, or task performance (both in terms of the time required to complete the task and number of errors made) between Plaque and control groups. These results suggest that carotid atherosclerosis is associated with altered functional brain activation patterns despite no evidence of impaired performance of the Stroop task or central hemodynamic changes.

Phase-dependent Brain Activation of the Frontal and Parietal Regions During Walking After Stroke - An fNIRS Study

Background

Recovery of walking post-stroke is highly variable. Accurately measuring and documenting functional brain activation characteristics during walking can help guide rehabilitation. Previous work in this area has been limited to investigations of frontal brain regions and have not utilized recent technological and analytical advances for more accurate measurements. There were three aims for this study: to characterize the hemodynamic profile during walking post-stroke, to investigate regional changes in brain activation during different phases of walking, and to related brain changes to clinical measures.

Methods

Functional near-infrared spectroscopy (fNIRS) along the pre-frontal, premotor, sensorimotor, and posterior parietal cortices was used on twenty individuals greater than six months post-stroke. Individual fNIRS optodes were digitized and used to estimate channel locations on each participant and short separation channels were used to control for extracerebral hemodynamic changes. Participants walked at their comfortable pace several times along a hallway while brain activation was recorded. Exploratory cluster analysis was conducted to determine if there was a link between brain activation and clinical measures.

Results

Sustained activation was observed in the pre-frontal cortex with the ipsilesional hemisphere showing greater activation compared to the contralesional side. Sensorimotor cortex was active during the early, acceleration stage of walking only. Posterior parietal cortex showed changes in activation during the later, steady-state stage of walking. Faster gait speeds also related to increased activation in contralesional sensorimotor and posterior parietal cortices. Exploratory analysis clustered participants into two distinct groups based on their brain activation profiles and generally showed that individuals with greater activation tended to have better physical outcomes.

Conclusions

These findings can guide future research for obtaining adequate power and determining factors that can be used as effect modifiers to reduce inter-subject variability. Overall, this is the first study to report specific oxygenated and deoxygenated hemoglobin changes in frontal to parietal regions during walking in the stroke population. Our results shed light on the importance of measuring brain activation across the cortex and show the importance of pre-frontal, sensorimotor, and posterior parietal cortices in walking after a stroke.

Predicting the Degree of Distracted Driving Based on fNIRS Functional Connectivity: A Pilot Study

Distracted driving is one of the main causes of traffic accidents. By predicting the attentional state of drivers, it is possible to prevent distractions and promote safe driving. In this study, we developed a model that could predict the degree of distracted driving based on brain activity. Changes in oxyhemoglobin concentrations were measured in drivers while driving a real car using functional near-infrared spectroscopy (fNIRS). A regression model was constructed for each participant using functional connectivity as an explanatory variable and brake reaction time to random beeps while driving as an objective variable. As a result, we were able to construct a prediction model with the mean absolute error of 5.58 × 102 ms for the BRT of the 12 participants. Furthermore, the regression model with the highest prediction accuracy for each participant was analyzed to gain a better understanding of the neural basis of distracted driving. The 11 of 12 models that showed significant accuracy were classified into five clusters by hierarchical clustering based on their functional connectivity edges used in each cluster. The results showed that the combinations of the dorsal attention network (DAN)-sensory-motor network (SMN) and DAN-ventral attention network (VAN) connections were common in all clusters and that these networks were essential to predict the degree of distraction in complex multitask driving. They also confirmed the existence of multiple types of prediction models with different within- and between-network connectivity patterns. These results indicate that it is possible to predict the degree of distracted driving based on the driver's brain activity during actual driving. These results are expected to contribute to the development of safe driving systems and elucidate the neural basis of distracted driving.

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.

Enhancement of Frequency-Specific Hemodynamic Power and Functional Connectivity by Transcranial Photobiomodulation in Healthy Humans

Transcranial photobiomodulation (tPBM) has been considered a safe and effective brain stimulation modality being able to enhance cerebral oxygenation and neurocognitive function. To better understand the underlying neurophysiological effects of tPBM in the human brain, we utilized a 111-channel functional near infrared spectroscopy (fNIRS) system to map cerebral hemodynamic responses over the whole head to 8-min tPBM with 1,064-nm laser given on the forehead of 19 healthy participants. Instead of analyzing broad-frequency hemodynamic signals (0–0.2 Hz), we investigated frequency-specific effects of tPBM on three infra-slow oscillation (ISO) components consisting of endogenic, neurogenic, and myogenic vasomotions. Significant changes induced by tPBM in spectral power of oxygenated hemoglobin concentration (Δ[HbO]), functional connectivity (FC), and global network metrics at each of the three ISO frequency bands were identified and mapped topographically for frequency-specific comparisons. Our novel findings revealed that tPBM significantly increased endogenic Δ[HbO] powers over the right frontopolar area near the stimulation site. Also, we demonstrated that tPBM enabled significant enhancements of endogenic and myogenic FC across cortical regions as well as of several global network metrics. These findings were consistent with recent reports and met the expectation that myogenic oscillation is highly associated with endothelial activity, which is stimulated by tPBM-evoked nitric oxide (NO) release.

Frontal, Sensorimotor, and Posterior Parietal Regions Are Involved in Dual-Task Walking After Stroke

Background

Walking within the community requires the ability to walk while simultaneously completing other tasks. After a stroke, completing an additional task while walking is significantly impaired, and it is unclear how the functional activity of the brain may impact this.

Methods

Twenty individual in the chronic stage post-stroke participated in this study. Functional near-infrared spectroscopy (fNIRS) was used to measure prefrontal, pre-motor, sensorimotor, and posterior parietal cortices during walking and walking while completing secondary verbal tasks of varying difficulty. Changes in brain activity during these tasks were measured and relationships were accessed between brain activation changes and cognitive or motor abilities.

Results

Significantly larger activations were found for prefrontal, pre-motor, and posterior parietal cortices during dual-task walking. Increasing dual-task walking challenge did not result in an increase in brain activation in these regions. Higher general cognition related to lower increases in activation during the easier dual-task. With the harder dual-task, a trend was also found for higher activation and less motor impairment.

Conclusions

This is the first study to show that executive function, motor preparation/planning, and sensorimotor integration areas are all important for dual-task walking post-stroke. A lack of further brain activation increase with increasing challenge suggests a point at which a trade-off between brain activation and performance occurs. Further research is needed to determine if training would result in further increases in brain activity or improved performance.

Open-source FlexNIRS: A low-cost, wireless and wearable cerebral health tracker

Currently, there is great interest in making neuroimaging widely accessible and thus expanding the sampling population for better understanding and preventing diseases. The use of wearable health devices has skyrocketed in recent years, allowing continuous assessment of physiological parameters in patients and research cohorts. While most health wearables monitor the heart, lungs and skeletal muscles, devices targeting the brain are currently lacking. To promote brain health in the general population, we developed a novel, low-cost wireless cerebral oximeter called FlexNIRS. The device has 4 LEDs and 3 photodiode detectors arranged in a symmetric geometry, which allows for a self-calibrated multi-distance method to recover cerebral hemoglobin oxygenation (SO₂) at a rate of 100 Hz. The device is powered by a rechargeable battery and uses Bluetooth Low Energy (BLE) for wireless communication. We developed an Android application for portable data collection and real-time analysis and display. Characterization tests in phantoms and human participants show very low noise (noise-equivalent power <70 fW/√Hz) and robustness of SO₂ quantification in vivo. The estimated cost is on the order of $50/unit for 1000 units, and our goal is to share the device with the research community following an open-source model. The low cost, ease-of-use, smart-phone readiness, accurate SO₂ quantification, real time data quality feedback, and long battery life make prolonged monitoring feasible in low resource settings, including typically medically underserved communities, and enable new community and telehealth applications.

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.

Individual differences in skill acquisition and transfer assessed by dual task training performance and brain activity

Assessment of expertise development during training program primarily consists of evaluating interactions between task characteristics, performance, and mental load. Such a traditional assessment framework may lack consideration of individual characteristics when evaluating training on complex tasks, such as driving and piloting, where operators are typically required to execute multiple tasks simultaneously. Studies have already identified individual characteristics arising from intrinsic, context, strategy, personality, and preference as common predictors of performance and mental load. Therefore, this study aims to investigate the effect of individual difference in skill acquisition and transfer using an ecologically valid dual task, behavioral, and brain activity measures. Specifically, we implemented a search and surveillance task (scanning and identifying targets) using a high-fidelity training simulator for the unmanned aircraft sensor operator, acquired behavioral measures (scan, not scan, over scan, and adaptive target find scores) using simulator-based analysis module, and measured brain activity changes (oxyhemoglobin and deoxyhemoglobin) from the prefrontal cortex (PFC) using a portable functional near-infrared spectroscopy (fNIRS) sensor array. The experimental protocol recruited 13 novice participants and had them undergo three easy and two hard sessions to investigate skill acquisition and transfer, respectively. Our results from skill acquisition sessions indicated that performance on both tasks did not change when individual differences were not accounted for. However inclusion of individual differences indicated that some individuals improved only their scan performance (Attention-focused group), while others improved only their target find performance (Accuracy-focused group). Brain activity changes during skill acquisition sessions showed that mental load decreased in the right anterior medial PFC (RAMPFC) in both groups regardless of individual differences. However, mental load increased in the left anterior medial PFC (LAMPFC) of Attention-focused group and decreased in the Accuracy-focused group only when individual differences were included. Transfer results showed no changes in performance regardless of grouping based on individual differences; however, mental load increased in RAMPFC of Attention-focused group and left dorsolateral PFC (LDLPFC) of Accuracy-focused group. Efficiency and involvement results suggest that the Attention-focused group prioritized the scan task, while the Accuracy-focused group prioritized the target find task. In conclusion, training on multitasks results in individual differences. These differences may potentially be due to individual preference. Future studies should incorporate individual differences while assessing skill acquisition and transfer during multitask training.

Systemic physiology augmented functional near-infrared spectroscopy hyperscanning: a first evaluation investigating entrainment of spontaneous activity of brain and body physiology between subjects

Significance: Functional near-infrared spectroscopy (fNIRS) enables measuring the brain activity of two subjects while they interact, i.e., the hyperscanning approach. Aim: In our exploratory study, we extended classical fNIRS hyperscanning by adding systemic physiological measures to obtain systemic physiology augmented fNIRS (SPA-fNIRS) hyperscanning while blocking and not blocking the visual communication between the subjects. This approach enables access brain-to-brain, brain-to-body, and body-to-body coupling between the subjects simultaneously. Approach: Twenty-four pairs of subjects participated in the experiment. The paradigm consisted of two subjects that sat in front of each other and had their eyes closed for 10 min, followed by a phase of 10 min where they made eye contact. Brain and body activity was measured continuously by SPA-fNIRS. Results: Our study shows that making eye contact for a prolonged time causes significant changes in brain-to-brain, brain-to-body, and body-to-body coupling, indicating that eye contact is followed by entrainment of the physiology between subjects. Subjects that knew each other generally showed a larger trend to change between the two conditions. Conclusions: The main point of this study is to introduce a new framework to investigate brain-to-brain, body-to-body, and brain-to-body coupling through a simple social experimental paradigm. The study revealed that eye contact leads to significant synchronization of spontaneous activity of the brain and body physiology. Our study is the first that employed the SPA-fNIRS approach and showed its usefulness to investigate complex interpersonal physiological changes.

Multivariate Kalman filter regression of confounding physiological signals for real-time classification of fNIRS data

Significance: Functional near-infrared spectroscopy (fNIRS) is a noninvasive technique for measuring hemodynamic changes in the human cortex related to neural function. Due to its potential for miniaturization and relatively low cost, fNIRS has been proposed for applications, such as brain-computer interfaces (BCIs). The relatively large magnitude of the signals produced by the extracerebral physiology compared with the ones produced by evoked neural activity makes real-time fNIRS signal interpretation challenging. Regression techniques incorporating physiologically relevant auxiliary signals such as short separation channels are typically used to separate the cerebral hemodynamic response from the confounding components in the signal. However, the coupling of the extra-cerebral signals is often noninstantaneous, and it is necessary to find the proper delay to optimize nuisance removal. Aim: We propose an implementation of the Kalman filter with time-embedded canonical correlation analysis for the real-time regression of fNIRS signals with multivariate nuisance regressors that take multiple delays into consideration. Approach: We tested our proposed method on a previously acquired finger tapping dataset with the purpose of classifying the neural responses as left or right. Results: We demonstrate computationally efficient real-time processing of 24-channel fNIRS data (400 samples per second per channel) with a two order of selective magnitude decrease in cardiac signal power and up to sixfold increase in the contrast-to-noise ratio compared with the nonregressed signals. Conclusion: The method provides a way to obtain better distinction of brain from non-brain signals in real time for BCI application with fNIRS.

Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, allowing for bedside imaging of brain function. While promising, fNIRS suffers from non-neural signal contaminations (i.e., systemic physiological noise), which can increase correlation across fNIRS channels, leading to spurious rsFC networks. In the present work, we hypothesized that additional measurements with short channels, heart rate, mean arterial pressure, and end-tidal CO2 could provide a better understanding of the effects of systemic physiology on fNIRS-based resting-state networks. To test our hypothesis, we acquired 12 min of resting-state data from 10 healthy participants. Unlike previous studies, we investigated the efficacy of different pre-processing approaches in extracting resting-state networks. Our results are in agreement with previous studies and reinforce the fact that systemic physiology can overestimate rsFC. We expanded on previous work by showing that removal of systemic physiology decreases intra- and inter-subject variability, increasing the ability to detect neural changes in rsFC across groups and over longitudinal studies. Our results show that by removing systemic physiology, fNIRS can reproduce resting-state networks often reported with functional magnetic resonance imaging (fMRI). Finally, the present work details the effects of systemic physiology and outlines how to remove (or at least ameliorate) their contributions to fNIRS signals acquired at rest.

ABBaH teens: Activity Breaks for Brain Health in adolescents: study protocol for a randomized crossover trial

Background

Physical activity breaks are widely being implemented in school settings as a solution to increase academic performance and reduce sitting time. However, the underlying physiological mechanisms suggested to improve cognitive function from physical activity and the frequency, intensity, and duration of the breaks remain unknown. This study will investigate the effects of frequent, short physical activity breaks during prolonged sitting on task-related prefrontal cerebral blood flow, cognitive performance, and psychological factors. Additionally, the moderating and mediating effects of arterial stiffness on changes in cerebral blood flow will be tested.

Methods

This is a protocol for a randomized crossover study that will recruit 16 adolescents (13–14 years old). Participants will undergo three different conditions in a randomized order, on three separate days, involving sitting 80 min with a different type of break every 17 min for 3 min. The breaks will consist of (1) seated social breaks, (2) simple resistance activities, and (3) step-up activities. Before and after the 80-min conditions, prefrontal cerebral blood flow changes will be measured using functional near-infrared spectroscopy (primary outcome), while performing working memory tasks (1-, 2-, and 3-back tests). Arterial stiffness (augmentation index and pulse wave velocity) and psychological factors will also be assessed pre and post the 80-min interventions.

Discussion

Publication of this protocol will help to increase rigor in science. The results will inform regarding the underlying mechanisms driving the association between physical activity breaks and cognitive performance. This information can be used for designing effective and feasible interventions to be implemented in schools.

Trial registration

www.ClinicalTrials.gov, NCT04552626. Retrospectively registered on September 21, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05972-5.

Characterizing reproducibility of cerebral hemodynamic responses when applying short-channel regression in functional near-infrared spectroscopy

Significance: Functional near-infrared spectroscopy (fNIRS) enables the measurement of brain activity noninvasively. Optical neuroimaging with fNIRS has been shown to be reproducible on the group level and hence is an excellent research tool, but the reproducibility on the single-subject level is still insufficient, challenging the use for clinical applications. Aim: We investigated the effect of short-channel regression (SCR) as an approach to obtain fNIRS measurements with higher reproducibility on a single-subject level. SCR simultaneously considers contributions from long- and short-separation channels and removes confounding physiological changes through the regression of the short-separation channel information. Approach: We performed a test-retest study with a hand grasping task in 15 healthy subjects using a wearable fNIRS device, optoHIVE. Relevant brain regions were localized with transcranial magnetic stimulation to ensure correct placement of the optodes. Reproducibility was assessed by intraclass correlation, correlation analysis, mixed effects modeling, and classification accuracy of the hand grasping task. Further, we characterized the influence of SCR on reproducibility. Results: We found a high reproducibility of fNIRS measurements on a single-subject level ( ICC single = 0.81 and correlation r = 0.81 ). SCR increased the reproducibility from 0.64 to 0.81 ( ICC single ) but did not affect classification (85% overall accuracy). Significant intersubject variability in the reproducibility was observed and was explained by Mayer wave oscillations and low raw signal strength. The raw signal-to-noise ratio (threshold at 40 dB) allowed for distinguishing between persons with weak and strong activations. Conclusions: We report, for the first time, that fNIRS measurements are reproducible on a single-subject level using our optoHIVE fNIRS system and that SCR improves reproducibility. In addition, we give a benchmark to easily assess the ability of a subject to elicit sufficiently strong hemodynamic responses. With these insights, we pave the way for the reliable use of fNIRS neuroimaging in single subjects for neuroscientific research and clinical applications.

fNIRS brain measures of ongoing nociception during surgical incisions under anesthesia

Significance: Functional near-infrared spectroscopy (fNIRS) has evaluated pain in awake and anesthetized states. Aim: We evaluated fNIRS signals under general anesthesia in patients undergoing knee surgery for anterior cruciate ligament repair. Approach: Patients were split into groups: those with regional nerve block (NB) and those without (non-NB). Continuous fNIRS measures came from three regions: the primary somatosensory cortex (S1), known to be involved in evaluation of nociception, the lateral prefrontal cortex (BA9), and the polar frontal cortex (BA10), both involved in higher cortical functions (such as cognition and emotion). Results: Our results show three significant differences in fNIRS signals to incision procedures between groups: (1) NB compared with non-NB was associated with a greater net positive hemodynamic response to pain procedures in S1; (2) dynamic correlation between the prefrontal cortex (PreFC) and S1 within 1 min of painful procedures are anticorrelated in NB while positively correlated in non-NB; and (3) hemodynamic measures of activation were similar at two separate time points during surgery (i.e., first and last incisions) in PreFC and S1 but showed significant differences in their overlap. Comparing pain levels immediately after surgery and during discharge from postoperative care revealed no significant differences in the pain levels between NB and non-NB. Conclusion: Our data suggest multiple pain events that occur during surgery using devised algorithms could potentially give a measure of "pain load." This may allow for evaluation of central sensitization (i.e., a heightened state of the nervous system where noxious and non-noxious stimuli is perceived as painful) to postoperative pain levels and the resulting analgesic consumption. This evaluation could potentially predict postsurgical chronic neuropathic pain.

Offset analgesia is associated with opposing modulation of medial versus dorsolateral prefrontal cortex activations: A functional near-infrared spectroscopy study

Offset analgesia is defined by a dramatic drop in perceived pain intensity with a relatively small decrease in noxious input. Although functional magnetic resonance imaging studies implicate subcortical descending inhibitory circuits during offset analgesia, the role of cortical areas remains unclear. The current study identifies cortical correlates of offset analgesia using functional near infrared spectroscopy (fNIRS). Twenty-four healthy volunteers underwent fNIRS scanning during offset (OS) and control (Con) heat stimuli applied to the forearm. After controlling for non-neural hemodynamic responses in superficial tissues, widespread increases in cortical oxygenated hemoglobin concentration were observed, reflecting cortical activation during heat pain. OS-Con contrasts revealed deactivations in bilateral medial prefrontal cortex (mPFC) and bilateral somatosensory cortex (SSC) associated with offset analgesia. Right dorsolateral prefrontal cortex (dlPFC) showed activation only during OS. These data demonstrate opposing cortical activation patterns during offset analgesia and support a model in which right dlPFC underlies ongoing evaluation of pain intensity change. With predictions of decreasing pain intensity, right dlPFC activation likely inhibits ascending noxious input via subcortical pathways resulting in SSC and mPFC deactivation. This study identifies cortical circuitry underlying offset analgesia and introduces the use of fNIRS to study pain modulation in an outpatient clinical environment.

Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals

In this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model's fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals.

Measurement of Adult Human Brain Responses to Breath-Holding by Multi-Distance Hyperspectral Near-Infrared Spectroscopy

A major limitation of near-infrared spectroscopy (NIRS) is its high sensitivity to the scalp and low sensitivity to the brain of adult humans. In the present work we used multi-distance hyperspectral NIRS (hNIRS) to investigate the optimal source-detector distances, wavelength ranges, and analysis techniques to separate cerebral responses to 30 s breath-holds (BHs) from the responses in the superficial tissue layer in healthy adult humans. We observed significant responses to BHs in the scalp hemodynamics. Cerebral responses to BHs were detected in the cytochrome C oxidase redox (rCCO) at 4 cm without using data from the short-distance channel. Using the data from the 1 cm channel in the two-layer regression algorithm showed that cerebral hemodynamic and rCCO responses also occurred at 3 cm. We found that the waveband 700–900 nm was optimal for the detection of cerebral responses to BHs in adults.

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.

Development of an Integrated EEG/fNIRS Brain Function Monitoring System

In this study, a fully integrated electroencephalogram/functional near-infrared spectroscopy (EEG/fNIRS) brain monitoring system was designed to fulfill the demand for a miniaturized, light-weight, low-power-consumption, and low-cost brain monitoring system as a potential tool with which to screen for brain diseases. The system is based on the ADS1298IPAG Analog Front-End (AFE) and can simultaneously acquire two-channel EEG signals with a sampling rate of 250 SPS and six-channel fNIRS signals with a sampling rate of 8 SPS. AFE is controlled by Teensy 3.2 and powered by a lithium polymer battery connected to two protection circuits and regulators. The acquired EEG and fNIRS signals are monitored and stored using a Graphical User Interface (GUI). The system was evaluated by implementing several tests to verify its ability to simultaneously acquire EEG and fNIRS signals. The implemented system can acquire EEG and fNIRS signals with a CMRR of -115 dB, power consumption of 0.75 mW/ch, system weight of 70.5 g, probe weight of 3.1 g, and a total cost of USD 130. The results proved that this system can be qualified as a low-cost, light-weight, low-power-consumption, and fully integrated EEG/fNIRS brain monitoring system.

Brain–Computer Interfacing Using Functional Near-Infrared Spectroscopy (fNIRS)

Functional Near-Infrared Spectroscopy (fNIRS) is a wearable optical spectroscopy system originally developed for continuous and non-invasive monitoring of brain function by measuring blood oxygen concentration. Recent advancements in brain–computer interfacing allow us to control the neuron function of the brain by combining it with fNIRS to regulate cognitive function. In this review manuscript, we provide information regarding current advancement in fNIRS and how it provides advantages in developing brain–computer interfacing to enable neuron function. We also briefly discuss about how we can use this technology for further applications.

Investigating Language and Domain-General Processing in Neurotypicals and Individuals With Aphasia - A Functional Near-Infrared Spectroscopy Pilot Study

Brain reorganization patterns associated with language recovery after stroke have long been debated. Studying mechanisms of spontaneous and treatment-induced language recovery in post-stroke aphasia requires a network-based approach given the potential for recruitment of perilesional left hemisphere language regions, homologous right hemisphere language regions, and/or spared bilateral domain-general regions. Recent hardware, software, and methodological advances in functional near-infrared spectroscopy (fNIRS) make it well-suited to examine this question. fNIRS is cost-effective with minimal contraindications, making it a robust option to monitor treatment-related brain activation changes over time. Establishing clear activation patterns in neurotypical adults during language and domain-general cognitive processes via fNIRS is an important first step. Some fNIRS studies have investigated key language processes in healthy adults, yet findings are challenging to interpret in the context of methodological limitations. This pilot study used fNIRS to capture brain activation during language and domain-general processing in neurotypicals and individuals with aphasia. These findings will serve as a reference when interpreting treatment-related changes in brain activation patterns in post-stroke aphasia in the future. Twenty-four young healthy controls, seventeen older healthy controls, and six individuals with left hemisphere stroke-induced aphasia completed two language tasks (i.e., semantic feature, picture naming) and one domain-general cognitive task (i.e., arithmetic) twice during fNIRS. The probe covered bilateral frontal, parietal, and temporal lobes and included short-separation detectors for scalp signal nuisance regression. Younger and older healthy controls activated core language regions during semantic feature processing (e.g., left inferior frontal gyrus pars opercularis) and lexical retrieval (e.g., left inferior frontal gyrus pars triangularis) and domain-general regions (e.g., bilateral middle frontal gyri) during hard versus easy arithmetic as expected. Consistent with theories of post-stroke language recovery, individuals with aphasia activated areas outside the traditional networks: left superior frontal gyrus and left supramarginal gyrus during semantic feature judgment; left superior frontal gyrus and right precentral gyrus during picture naming; and left inferior frontal gyrus pars opercularis during arithmetic processing. The preliminary findings in the stroke group highlight the utility of using fNIRS to study language and domain-general processing in aphasia.

Towards Neuroscience of the Everyday World (NEW) using functional Near-Infrared Spectroscopy

Functional Near-Infrared Spectroscopy (fNIRS) assesses human brain activity by noninvasively measuring changes of cerebral hemoglobin concentrations caused by modulation of neuronal activity. Recent progress in signal processing and advances in system design, such as miniaturization, wearability and system sensitivity, have strengthened fNIRS as a viable and cost-effective complement to functional Magnetic Resonance Imaging (fMRI), expanding the repertoire of experimental studies that can be performed by the neuroscience community. The availability of fNIRS and Electroencephalography (EEG) for routine, increasingly unconstrained, and mobile brain imaging is leading towards a new domain that we term "Neuroscience of the Everyday World" (NEW). In this light, we review recent advances in hardware, study design and signal processing, and discuss challenges and future directions towards achieving NEW.

Decoding of semantic categories of imagined concepts of animals and tools in fNIRS

Objective.Semantic decoding refers to the identification of semantic concepts from recordings of an individual's brain activity. It has been previously reported in functional magnetic resonance imaging and electroencephalography. We investigate whether semantic decoding is possible with functional near-infrared spectroscopy (fNIRS). Specifically, we attempt to differentiate between the semantic categories of animals and tools. We also identify suitable mental tasks for potential brain-computer interface (BCI) applications.Approach.We explore the feasibility of a silent naming task, for the first time in fNIRS, and propose three novel intuitive mental tasks based on imagining concepts using three sensory modalities: visual, auditory, and tactile. Participants are asked to visualize an object in their minds, imagine the sounds made by the object, and imagine the feeling of touching the object. A general linear model is used to extract hemodynamic responses that are then classified via logistic regression in a univariate and multivariate manner.Main results.We successfully classify all tasks with mean accuracies of 76.2% for the silent naming task, 80.9% for the visual imagery task, 72.8% for the auditory imagery task, and 70.4% for the tactile imagery task. Furthermore, we show that consistent neural representations of semantic categories exist by applying classifiers across tasks.Significance.These findings show that semantic decoding is possible in fNIRS. The study is the first step toward the use of semantic decoding for intuitive BCI applications for communication.

Targeting brain regions of interest in functional near-infrared spectroscopy-Scalp-cortex correlation using subject-specific light propagation models

Targeting specific brain regions of interest by the accurate positioning of optodes (emission and detection probes) on the scalp remains a challenge for functional near‐infrared spectroscopy (fNIRS). Since fNIRS data does not provide any anatomical information on the brain cortex, establishing the scalp‐cortex correlation (SCC) between emission‐detection probe pairs on the scalp and the underlying brain regions in fNIRS measurements is extremely important. A conventional SCC is obtained by a geometrical point‐to‐point manner and ignores the effect of light scattering in the head tissue that occurs in actual fNIRS measurements. Here, we developed a sensitivity‐based matching (SBM) method that incorporated the broad spatial sensitivity of the probe pair due to light scattering into the SCC for fNIRS. The SCC was analyzed between head surface fiducial points determined by the international 10–10 system and automated anatomical labeling brain regions for 45 subject‐specific head models. The performance of the SBM method was compared with that of three conventional geometrical matching (GM) methods. We reveal that the light scattering and individual anatomical differences in the head affect the SCC, which indicates that the SBM method is compulsory to obtain the precise SCC. The SBM method enables us to evaluate the activity of cortical regions that are overlooked in the SCC obtained by conventional GM methods. Together, the SBM method could be a promising approach to guide fNIRS users in designing their probe arrangements and in explaining their measurement data.

Cortical hemodynamics as a function of handgrip strength and cognitive performance: a cross-sectional fNIRS study in younger adults

BACKGROUND

There is growing evidence for a positive correlation between measures of muscular strength and cognitive abilities. However, the neurophysiological correlates of this relationship are not well understood so far. The aim of this study was to investigate cortical hemodynamics [i.e., changes in concentrations of oxygenated (oxyHb) and deoxygenated hemoglobin (deoxyHb)] as a possible link between measures of muscular strength and cognitive performance.

METHODS

In a cohort of younger adults (n = 39, 18-30 years), we assessed (i) handgrip strength by a handhold dynamometer, (ii) short-term working memory performance by using error rates and reaction times in the Sternberg task, and (iii) cortical hemodynamics of the prefrontal cortex (PFC) via functional near-infrared spectroscopy (fNIRS).

RESULTS

We observed low to moderate negative correlations (rp =  ~ - 0.38 to - 0.51; p < 0.05) between reaction time and levels of oxyHb in specific parts of the PFC. Furthermore, we noticed low to moderate positive correlations (rp =  ~ 0.34 to 0.45; p < 0.05) between reaction times and levels of deoxyHb in distinct parts of the PFC. Additionally, higher levels of oxyHb (rp (35) = 0.401; p = 0.014) and lower levels of deoxyHb (rp (34) = - 0.338; p = 0.043) in specific parts of the PFC were linked to higher percentage of correct answers. We also found low to moderate correlations (p < 0.05) between measures of handgrip strength and levels of oxyHb (rp =  ~ 0.35; p < 0.05) and levels of deoxyHb (rp =  ~ - 0.25 to - 0.49; p < 0.05) in specific parts of the PFC. However, there was neither a correlation between cognitive performance and handgrip strength nor did cortical hemodynamics in the PFC mediate the relationship between handgrip strength and cognitive performance (p > 0.05).

CONCLUSION

The present study provides evidence for a positive neurobehavioral relationship between cortical hemodynamics and cognitive performance. Our findings further imply that in younger adults higher levels of handgrip strength positively influence cortical hemodynamics although the latter did not necessarily culminate in better cognitive performance. Future research should examine whether the present findings can be generalized to other cohorts (e.g., older adults).

Optical brain imaging and its application to neurofeedback

Besides passive recording of brain electric or magnetic activity, also non-ionizing electromagnetic or optical radiation can be used for real-time brain imaging. Here, changes in the radiation's absorption or scattering allow for continuous in vivo assessment of regional neurometabolic and neurovascular activity. Besides magnetic resonance imaging (MRI), over the last years, also functional near-infrared spectroscopy (fNIRS) was successfully established in real-time metabolic brain imaging. In contrast to MRI, fNIRS is portable and can be applied at bedside or in everyday life environments, e.g., to restore communication and movement. Here we provide a comprehensive overview of the history and state-of-the-art of real-time optical brain imaging with a special emphasis on its clinical use towards neurofeedback and brain-computer interface (BCI) applications. Besides pointing to the most critical challenges in clinical use, also novel approaches that combine real-time optical neuroimaging with other recording modalities (e.g. electro- or magnetoencephalography) are described, and their use in the context of neuroergonomics, neuroenhancement or neuroadaptive systems discussed.

Comparison of short-channel separation and spatial domain filtering for removal of non-neural components in functional near-infrared spectroscopy signals

Significance: With the increasing popularity of functional near-infrared spectroscopy (fNIRS), the need to determine localization of the source and nature of the signals has grown. Aim: We compare strategies for removal of non-neural signals for a finger-thumb tapping task, which shows responses in contralateral motor cortex and a visual checkerboard viewing task that produces activity within the occipital lobe. Approach: We compare temporal regression strategies using short-channel separation to a spatial principal component (PC) filter that removes global signals present in all channels. For short-channel temporal regression, we compare non-neural signal removal using first and combined first and second PCs from a broad distribution of short channels to limited distribution on the forehead. Results: Temporal regression of non-neural information from broadly distributed short channels did not differ from forehead-only distribution. Spatial PC filtering provides results similar to short-channel separation using the temporal domain. Utilizing both first and second PCs from short channels removes additional non-neural information. Conclusions: We conclude that short-channel information in the temporal domain and spatial domain regression filtering methods remove similar non-neural components represented in scalp hemodynamics from fNIRS signals and that either technique is sufficient to remove non-neural components.

Functional brain connectivity related to surgical skill dexterity in physical and virtual simulation environments

Significance: Surgical simulators, both virtual and physical, are increasingly used as training tools for teaching and assessing surgical technical skills. However, the metrics used for assessment in these simulation environments are often subjective and inconsistent. Aim: We propose functional activation metrics, derived from brain imaging measurements, to objectively assess the correspondence between brain activation with surgical motor skills for subjects with varying degrees of surgical skill. Approach: Cortical activation based on changes in the oxygenated hemoglobin (HbO) of 36 subjects was measured using functional near-infrared spectroscopy at the prefrontal cortex (PFC), primary motor cortex, and supplementary motor area (SMA) due to their association with motor skill learning. Inter-regional functional connectivity metrics, namely, wavelet coherence (WCO) and wavelet phase coherence were derived from HbO changes to correlate brain activity to surgical motor skill levels objectively. Results: One-way multivariate analysis of variance found a statistically significant difference in the inter-regional WCO metrics for physical simulator based on Wilk's Λ for expert versus novice, F ( 10,1 ) = 7495.5 , p < 0.01 . Partial eta squared effect size for the inter-regional WCO metrics was found to be highest between the central prefrontal cortex (CPFC) and SMA, CPFC-SMA ( η 2 = 0.257 ). Two-tailed Mann-Whitney U tests with a 95% confidence interval showed baseline equivalence and a statistically significant ( p < 0.001 ) difference in the CPFC-SMA WPCO metrics for the physical simulator training group ( 0.960 ± 0.045 ) versus the untrained control group ( 0.735 ± 0.177 ) following training for 10 consecutive days in addition to the pretest and posttest days. Conclusion: We show that brain functional connectivity WCO metric corresponds to surgical motor skills in the laparoscopic physical simulators. Functional connectivity between the CPFC and the SMA is lower for subjects that exhibit expert surgical motor skills than untrained subjects in laparoscopic physical simulators.

NIRS-KIT: a MATLAB toolbox for both resting-state and task fNIRS data analysis

Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to probe human brain function during task state and resting state. However, the existing analysis toolboxes mainly focus on task activation analysis, few software packages can assist resting-state fNIRS studies. Aim: We aimed to provide a versatile and easy-to-use toolbox to perform analysis for both resting state and task fNIRS. Approach: We developed a MATLAB toolbox called NIRS-KIT that works for both resting-state analysis and task activation detection. Results: NIRS-KIT implements common and necessary processing steps for performing fNIRS data analysis, including data preparation, quality control, preprocessing, individual-level analysis, group-level statistics with several popular statistical models, and multiple comparison correction methods, and finally results visualization. For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided. Additionally, NIRS-KIT also supports activation analysis for task fNIRS. Conclusions: NIRS-KIT offers an open source tool for researchers to analyze resting-state and/or task fNIRS data in one suite. It contains several key features: (1) good compatibility, supporting multiple fNIRS recording systems, data formats of NIRS-SPM and Homer2, and the shared near-infrared spectroscopy format data format recommended by the fNIRS society; (2) flexibility, supporting customized preprocessing scripts; (3) ease-to-use, allowing processing fNIRS signals in batch manner with user-friendly graphical user interfaces; and (4) feature-packed data viewing and result visualization. We anticipate that this NIRS-KIT will facilitate the development of the fNIRS field.

Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling

Significance: Contamination of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow (CBF) due to systemic physiology remains a significant challenge in the clinical translation of DCS for neuromonitoring. Tunable, multi-layer Monte Carlo-based (MC) light transport models have the potential to remove extracerebral flow cross-talk in cerebral blood flow index ( CBF i ) estimates. Aim: We explore the effectiveness of MC DCS models in recovering accurate CBF i changes in the presence of strong systemic physiology variations during a hypercapnia maneuver. Approach: Multi-layer slab and head-like realistic (curved) geometries were used to run MC simulations of photon propagation through the head. The simulation data were post-processed into models with variable extracerebral thicknesses and used to fit DCS multi-distance intensity autocorrelation measurements to estimate CBF i timecourses. The results of the MC CBF i values from a set of human subject hypercapnia sessions were compared with CBF i values estimated using a semi-infinite analytical model, as commonly used in the field. Results: Group averages indicate a gradual systemic increase in blood flow following a different temporal profile versus the expected rapid CBF response. Optimized MC models, guided by several intrinsic criteria and a pressure modulation maneuver, were able to more effectively separate CBF i changes from scalp blood flow influence than the analytical fitting, which assumed a homogeneous medium. Three-layer models performed better than two-layer ones; slab and curved models achieved largely similar results, though curved geometries were closer to physiological layer thicknesses. Conclusion: Three-layer, adjustable MC models can be useful in separating distinct changes in scalp and brain blood flow. Pressure modulation, along with reasonable estimates of physiological parameters, can help direct the choice of appropriate layer thicknesses in MC models.