A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy

A Review of Cerebral Hemodynamics During Sleep Using Near-Infrared Spectroscopy

Investigating cerebral hemodynamic changes during regular sleep cycles and sleep disorders is fundamental to understanding the nature of physiological and pathological mechanisms in the regulation of cerebral oxygenation during sleep. Although sleep neuroimaging methods have been studied and have been well-reviewed, they have limitations in terms of technique and experimental design. Neurologists are convinced that Near-infrared spectroscopy (NIRS) provides essential information and can be used to assist the assessment of cerebral hemodynamics, and numerous studies regarding sleep have been carried out based on NIRS. Thus, a brief historical overview of the sleep studies using NIRS will be helpful for the biomedical students, academicians, and engineers to better understand NIRS from various perspectives. In this study, the existing literature on sleep studies is reviewed, and an overview of the NIRS applications is synthesized and provided. The paper first reviews the application scenarios, as well as the patterns of fluctuation of NIRS, which includes the investigation in regular sleep and sleep-disordered breathing. Various factors such as different sleep stages, populations, and degrees of severity were considered. Furthermore, the experimental design and signal processing, as well as the regulation mechanisms involved in regular and pathological sleep, are investigated and discussed. The strengths and weaknesses of the existing NIRS applications are addressed and presented, which can direct further NIRS analysis and utilization.

Changes in Prefrontal Cortical Activity During Walking and Cognitive Functions Among Patients With Parkinson's Disease

Background: Walking becomes more and more degraded as Parkinson's Disease (PD) progresses. Previous research examined factors contributing to this deterioration. Among them, changes in brain cortical activity during walking have been less studied in this clinical population.

Objectives: This study aimed to: (1) investigate changes in dorsolateral prefrontal cortex (DLPFC) activation during usual walking and dual-task walking conditions in patients with PD; (2) examine the association between cortical activity and behavioral/cognitive outcomes; and (3) explore which factors best predict increased activation of the DLPFC during usual walking.

Methods: Eighteen patients with early stage PD and 18 controls performed 4 conditions: (1) standing while subtracting, (2) usual walking, (3) walking while counting forward, and (4) walking while subtracting. Cortical activity in DLPFC, assessed by changes in oxy-hemoglobin (ΔHbO₂) and deoxy-hemoglobin (ΔHbR), was measured using functional near infrared spectroscopy (fNIRS). Gait performance was recorded using wearables sensors. Cognition was also assessed using neuropsychological tests, including the Trail Making Test (TMT).

Results: DLPFC activity was higher in patients compared to controls during both usual walking and walking while subtracting conditions. Patients had impaired walking performance compared to controls only during walking while subtracting task. Moderate-to-strong correlations between ΔHbO₂ and coefficients of variation of all gait parameters were found for usual walking and during walking while counting forward conditions. Part-B of TMT predicted 21% of the variance of ΔHbO₂ during usual walking after adjustment for group status.

Conclusions: The increased DLPFC activity in patients during usual walking suggests a potential compensation for executive deficits. Understanding changes in DLPFC activity during walking may have implications for rehabilitation of gait in patients with PD.

Exploring the relation between brain response to speech at 6-months and language outcomes at 24-months in infants at high and low risk for autism spectrum disorder: A preliminary functional near-infrared spectroscopy study

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Brain response distributed across regions in infants at high risk for autism.

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Brain response localized to anterior regions in 6-month-old low risk infants.

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Comparing groups, high risk infants had reduced response in anterior regions.

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High risk infants had greater response than low risk infants in right posterior.

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Brain response to speech predicted language outcomes in low risk infants only.

Infants at high familial risk for autism spectrum disorder (ASD) are at increased risk for language impairments. Studies have demonstrated that atypical brain response to speech is related to language impairments in this population, but few have examined this relation longitudinally. We used functional near-infrared spectroscopy (fNIRS) to investigate the neural correlates of speech processing in 6-month-old infants at high (HRA) and low risk (LRA) for autism. We also assessed the relation between brain response to speech at 6-months and verbal developmental quotient (VDQ) scores at 24-months. LRA infants exhibited greater brain response to speech in bilateral anterior regions of interest (ROIs) compared to posterior ROIs, while HRA infants exhibited similar brain response across all ROIs. Compared to LRA infants, HRA+ infants who were later diagnosed with ASD had reduced brain response in bilateral anterior ROIs, while HRA- infants who were not later diagnosed with ASD had increased brain response in right posterior ROI. Greater brain response in left anterior ROI predicted VDQ scores for LRA infants only. Findings highlight the importance of studying HRA+ and HRA- infants separately, and implicate a different, more distributed neural system for speech processing in HRA infants that is not related to language functioning.

Effects of Apolipoprotein E Polymorphism on Cerebral Oxygen Saturation After Traumatic Brain Injury

Objective: To investigate the effects of the apolipoprotein E gene (APOE) on the cerebral oxygen saturation of patients after traumatic brain injury (TBI). Methods: Clinical data of 114 patients with TBI and 54 normal people were collected. The APOE genotypes of all subjects were determined by quantitative fluorescent polymerase chain reaction (QF-PCR). The regional cerebral oxygen saturation (rScO₂) of TBI patients and normal people were monitored by near-infrared spectroscopy (NIRS). Results: The mean rScO₂ of patients was (55.06 ± 7.60)% in the early stage of TBI, which was significantly lower than that of normal people (67.21 ± 7.80)% (P < 0.05). Single-factor and multifactor logistic regression analyses showed APOEε4 was an independent risk factor that caused the early decline of rScO2 in TBI patients. Furthermore, in the TBI group, the rScO₂ of APOEε4 carriers (52.23 ± 8.02)% was significantly lower than that of non-ε4 carriers (60.33 ± 7.12)% (P < 0.05). But in the normal group, no significant differences in rScO₂ were found between APOEε4 carriers and non-carriers. Conclusion: The rScO₂ may be significantly decreased after TBI, and APOEε4 may be a risk factor for decreased rScO₂ in the early stage of TBI.

The Influence of an Acute Exercise Bout on Adolescents' Stress Reactivity, Interference Control, and Brain Oxygenation Under Stress

Background

High psychosocial stress can impair executive function in adolescents, whereas acute exercise has been reported to benefit this cognitive domain. The aim of this study was to investigate whether an acute bout of aerobic exercise improves the inhibitory aspect of executive function and the associated dorsolateral prefrontal cortex (DLPFC) oxygenation when under stress.

Methods

Sixty male high school students aged 16–20 years performed a Stroop task (baseline condition) and were randomly assigned to an exercise group (30 min on ergometer at 70% of maximum heart rate) and a control group (30 min of reading). Subsequently, all participants underwent a modified Trier Social Stress Test, which included a Stroop task under enhanced stress. The Stroop tasks in both conditions were combined with functional near-infrared spectroscopy to record changes in DLPFC oxygenation in response to the tasks. Stress reactivity was measured with saliva samples (cortisol, alpha-amylase), heart rate monitoring, and anxiety scores.

Results

All stress parameters indicated increases in response to the stressor (p < 0.001), with higher alpha-amylase [t(58) = −3.45, p = 0.001, d = 1.93] and anxiety [t(58) = −2.04, p = 0.046, d = 0.53] reactions in the control compared to the exercise group. Controlling for these two parameters, repeated measures analyses of covariance targeting changes in Stroop interference scores showed no main effect of stress [F(1,58) = 3.80, p = 0.056, ηp² = 0.063] and no stress × group interaction [F(1,58) = 0.43, p = 0.517, ηp² = 0.008]. Similarly, there was no main effect of stress [F(1,58) = 2.38, p = 0.128, ηp² = 0.040] and no stress × group interaction [F(1,58) = 2.80, p = 0.100, ηp² = 0.047] for DLPFC oxygenation.

Conclusion

Our study confirms potentially health-enhancing effects of acute exercise on some of the physiological and psychological stress reactivity indicators. However, our data do not support the notion of an effect on interference control and DLPFC activation under stress.

Cortical brain activity in transfemoral or knee-disarticulation prosthesis users performing single- and dual-task walking activities

Introduction

Walking with a prosthesis while performing secondary tasks increases demand on cognitive resources, compromising balance and gait. This study investigated effects of a secondary task on patterns of brain activity and temporospatial gait parameters in individuals using a prosthesis with or without a microprocessor-controlled prosthetic knee(MPK) and controls.

Methods

A cross-sectional study with repeated measures was performed. Twenty-nine individuals with amputations and 16 controls were recruited. Functional near-infrared spectroscopy was used to evaluate changes in oxygenated and de-oxygenated haemoglobin in the prefrontal cortex and temporospatial variables during single-and dual-task walking.

Results

Differences in brain activity were observed within the MPK-group and controls without changes in temporospatial parameters. The Trail-Walking test was associated with highest levels of brain activity in both groups. No differences were observed between single- and dual-task walking in the non-MPK-group (p > 0.05). The Non-MPK and the MPK-group recorded higher levels of brain activity than controls during single-task walking and poorer results on temporospatial variables compared to controls.

Conclusions

For the MPK-group and controls, introduction of a secondary task led to an increase in brain activity. This was not seen in the Non-MPK-group. Significant differences in brain activity were observed in the absence of changes in temporospatial parameters.

Intrinsic organization of cortical networks predicts state anxiety: an functional near-infrared spectroscopy (fNIRS) study

Although state anxiety has been characterized by hyper-responsive subcortical activity and its bottom-up connectivity with cortical regions, the role of cortical networks in state anxiety is not yet well understood. To this end, we decoded individual state anxiety by using a machine-learning approach based on resting-state functional connectivity (RSFC) with functional near-infrared spectroscopy (fNIRS). Our results showed that the RSFC among a set of cortical networks were highly predictive of state anxiety, rather than trait anxiety. Specifically, these networks included connectivity between cortical areas in the default mode network (DMN) and dorsal attention network (DAN), and connectivity within the DMN, which were negatively correlated with state anxiety; connectivity between cortical areas in the DMN and frontoparietal network (FPN), FPN and salience network (SN), FPN and DAN, DMN and SN, which were positively correlated with state anxiety. These findings suggest a predictive role of intrinsic cortical organization in the assessment of state anxiety. The work provides new insights into potential neural mechanisms of emotion states and implications for prognosis, diagnosis, and treatment of affective disorders.

Infants understand collaboration: Neural evidence for 9-month-olds' attribution of shared goals to coordinated joint actions

Interpreting others' actions as goal-directed, even when the actions are unfamiliar, is indispensable for social learning, and can be particularly important for infants, whose own action repertoire is limited. Indeed, young infants have been shown to attribute goals to unfamiliar actions as early as 3 months of age, but this ability appears restricted to actions performed by individuals. In contrast, attributing shared goals to actions performed by multiple individuals seems to emerge only in the second year of life. Considering the restrictions that this would impose on infants' understanding and learning from interactions in their environment, we reexamine this ability by introducing 9-month-old infants to simple joint actions, in which two agents coordinate their actions toward the same goal. To establish whether infants formed an expectation about future actions of these agents, infants' cortical activity was measured using functional near-infrared spectroscopy (fNIRS). The hemodynamic response, recorded in (p)STS, indicated that infants attributed goals to simultaneous and coordinated joint actions of two individuals. Thus, even prior to actively engaging in collaborative activities themselves, infants can attribute shared goals to observed joint actions, enabling infants to learn from, and about, the complementary roles of social interactions, a central characteristic of human culture.

People With Parkinson’s Disease Exhibit Reduced Cognitive and Motor Cortical Activity When Undertaking Complex Stepping Tasks Requiring Inhibitory Control

Background

People with Parkinson’s disease (PD) have difficulties generating quick and accurate steps in anticipation of and/or in response to environmental hazards. However, neural mechanisms underlying performance in cognitively demanding stepping tasks are unclear.

Objective

This study compared activation patterns in cognitive and motor cortical regions using functional near-infrared spectroscopy (fNIRS) between people with PD and age-matched healthy older adults (HOA) during stepping tasks.

Methods

Fifty-two people with PD and 95 HOA performed a simple choice stepping reaction time test (CSRT) and 2 cognitively demanding stepping tests (inhibitory CSRT [iCSRT] and Stroop stepping test [SST]) on a computerized step mat. Cortical activation in the dorsolateral prefrontal cortex (DLPFC), Broca’s area, supplementary motor area (SMA), and premotor cortex (PMC) were recorded using fNIRS. Stepping performance and cortical activity were contrasted between groups and between the CSRT and the iCSRT and SST.

Results

The PD group performed worse than the HOA in all 3 stepping tests. A consistent pattern of interactions indicated differential hemodynamic responses between the groups. Compared with the CSRT, the PD group exhibited reduced DLPFC activity in the iCSRT and reduced SMA and PMC activity in the SST. The HOA exhibited increased DLPFC, SMA, and PMC activity when performing the SST in comparison with the CSRT task.

Conclusions

In contrast to the HOA, the PD group demonstrated reduced cortical activity in the DLPFC, SMA, and PMC during the more complex stepping tasks requiring inhibitory control. This may reflect subcortical and/or multiple pathway damage with subsequent deficient use of cognitive and motor resources.

Signal quality index: an algorithm for quantitative assessment of functional near infrared spectroscopy signal quality

We propose the signal quality index (SQI) algorithm as a novel tool for quantitatively assessing the functional near infrared spectroscopy (fNIRS) signal quality in a numeric scale from 1 (very low quality) to 5 (very high quality). The algorithm comprises two preprocessing steps followed by three consecutive rating stages. The results on a dataset annotated by independent fNIRS experts showed SQI performed significantly better (p<0.05) than PHOEBE (placing headgear optodes efficiently before experimentation) and SCI (scalp coupling index), two existing algorithms, in both quantitatively rating and binary classifying the fNIRS signal quality. Employment of the proposed algorithm to estimate the signal quality before processing the fNIRS signals increases certainty in the interpretations.

Right STS responses to biological motion in infancy - An fNIRS study using point-light walkers

Biological motion perception-our capacity to perceive the intrinsic motion of humans and animals-has been implicated as a precursor of social development in infancy. In the adult brain, several biological motion neural correlates have been identified; of particular importance, the right posterior superior temporal sulcus (rpSTS). We present a study, conducted with fNIRS, which measured brain activations in infants' right posterior temporal region to point-light walkers, a standard stimulus category of biological motion perception studies. Seven-month-old infants (n = 23) participated in a within-subject blocked design with three experimental conditions and one baseline. Infants viewed: an intact upright point-light walker of a person approaching the observer; the same point-light walker stimulus but inverted; and a selected frame from the point-light walker stimulus, approaching the viewer at constant velocity with no articulated motion, close to object motion. We found activations for both the upright and the inverted point-light walkers. The rigid moving point-light walker frame did not elicit any response consistent with a functional activation in this region. Our results suggest that biological motion is processed differently in the right middle posterior temporal cortex in infancy, and that articulated motion is a critical feature in biological motion processing at this early age.

There is No test-retest reliability of brain activation induced by robotic passive hand movement: A functional NIRS study

INTRODUCTION

The basic paradigm of rehabilitation is based on the brain plasticity, and for promoting it, test-retest reliability (TRR) of brain activation in which certain area of the brain is repeatedly activated is required. In this study, we investigated whether the robotic passive movement has the TRR of brain activation. While active training has been shown to have TRR, but there still have been arguments over the TRR by passive movement.

METHODS

In order to test TRR, 10 repetitive sessions and various intervals (1 day, 3 days, 7 days, 23 days, 15 min, and 6 hr) were applied to five subjects, which had the same statistical power as applying two sessions to 50 subjects. In each session, three robot speeds (0.25, 0.5, and 0.75 Hz) were applied to provide passive movement using the robot. The fNIRS signal (oxy-Hb) generated in the primary sensorimotor area (SM1) was measured on a total of 29 channels. At this time, we used activation maps and intraclass correlation coefficient (ICC) values to examine the TRR and the effect of robot speeds and intervals on TRR.

RESULTS

As a result, activation maps showed prominent variation regardless of robot speeds and interval, and the ICC value (=0.002) showed no TRR of brain activation for robotic passive movement.

CONCLUSION

The brain activation induced by the robotic passive movement alone has very poor TRR, suggesting that further enhancement is required to strengthen the TRR by complementing active user engagements.

A consensus guide to using functional near-infrared spectroscopy in posture and gait research

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) is increasingly used in the field of posture and gait to investigate patterns of cortical brain activation while people move freely. fNIRS methods, analysis and reporting of data vary greatly across studies which in turn can limit the replication of research, interpretation of findings and comparison across works.

RESEARCH QUESTION AND METHODS

Considering these issues, we propose a set of practical recommendations for the conduct and reporting of fNIRS studies in posture and gait, acknowledging specific challenges related to clinical groups with posture and gait disorders.

RESULTS

Our paper is organized around three main sections: 1) hardware set up and study protocols, 2) artefact removal and data processing and, 3) outcome measures, validity and reliability; it is supplemented with a detailed checklist.

SIGNIFICANCE

This paper was written by a core group of members of the International Society for Posture and Gait Research and posture and gait researchers, all experienced in fNIRS research, with the intent of assisting the research community to lead innovative and impactful fNIRS studies in the field of posture and gait, whilst ensuring standardization of research.

Global motion detection and censoring in high-density diffuse optical tomography

Motion-induced artifacts can significantly corrupt optical neuroimaging, as in most neuroimaging modalities. For high-density diffuse optical tomography (HD-DOT) with hundreds to thousands of source-detector pair measurements, motion detection methods are underdeveloped relative to both functional magnetic resonance imaging (fMRI) and standard functional near-infrared spectroscopy (fNIRS). This limitation restricts the application of HD-DOT in many challenging imaging situations and subject populations (e.g., bedside monitoring and children). Here, we evaluated a new motion detection method for multi-channel optical imaging systems that leverages spatial patterns across measurement channels. Specifically, we introduced a global variance of temporal derivatives (GVTD) metric as a motion detection index. We showed that GVTD strongly correlates with external measures of motion and has high sensitivity and specificity to instructed motion-with an area under the receiver operator characteristic curve of 0.88, calculated based on five different types of instructed motion. Additionally, we showed that applying GVTD-based motion censoring on both hearing words task and resting state HD-DOT data with natural head motion results in an improved spatial similarity to fMRI mapping. We then compared the GVTD similarity scores with several commonly used motion correction methods described in the fNIRS literature, including correlation-based signal improvement (CBSI), temporal derivative distribution repair (TDDR), wavelet filtering, and targeted principal component analysis (tPCA). We find that GVTD motion censoring on HD-DOT data outperforms other methods and results in spatial maps more similar to those of matched fMRI data.

Recent Developments in Instrumentation of Functional Near-Infrared Spectroscopy Systems

In the last three decades, the development and steady improvement of various optical technologies at the near-infrared region of the electromagnetic spectrum has inspired a large number of scientists around the world to design and develop functional near-infrared spectroscopy (fNIRS) systems for various medical applications. This has been driven further by the availability of new sources and detectors that support very compact and wearable system designs. In this article, we review fNIRS systems from the instrumentation point of view, discussing the associated challenges and state-of-the-art approaches. In the beginning, the fundamentals of fNIRS systems as well as light-tissue interaction at NIR are briefly introduced. After that, we present the basics of NIR systems instrumentation. Next, the recent development of continuous-wave, frequency-domain, and time-domain fNIRS systems are discussed. Finally, we provide a summary of these three modalities and an outlook into the future of fNIRS technology.

Which obstacle attributes place additional demands on higher-level cognitive function in patients with Parkinson's disease?

BACKGROUND

Previous reports show that patients with Parkinson's disease (PD) rely on prefrontal activation to compensate for impaired motor function during complex activities such as obstacle negotiation. However, the influence of the properties of the obstacles on prefrontal activation has not been systematically evaluated. Here, we examined the effects of obstacle height and anticipation time on prefrontal activation in patients with PD and older adults.

METHODS

34 patients with PD (age: 67.4 ± 5.7 years; 14 women) and 26 older adults (age: 71.3 ± 8.9 years; 11 women) walked in an obstacle course while negotiating anticipated and unanticipated obstacles (long/short available time response, ART) at heights of 50 mm and 100 mm. Prefrontal activation was measured using functional Near-Infrared Spectroscopy (fNIRS); obstacle negotiation performance was measured using Kinect cameras.

RESULTS

PD patients showed greater increases in prefrontal activation during and after obstacle crossing compared to the older adults (p < 0.001). Obstacle height affected prefrontal activity only when crossing anticipated obstacles (ARTxheight interaction, p = 0.011), in which case higher obstacles were accompanied by higher prefrontal activity. PD patients showed higher levels of activation during unanticipated obstacles, compared to older adults (groupXART: p = 0.015). Different correlations between prefrontal activation and obstacle negotiation strategies were observed in patients and controls.

CONCLUSIONS

These results point to the use of prefrontal activation as a compensatory mechanism in PD. Moreover, the higher activation observed when negotiating more challenging obstacles suggests that there is greater reliance on cognitive resources in these demanding situations that may contribute to the higher risk of falls in PD patients.

Dopaminergic therapy and prefrontal activation during walking in individuals with Parkinson's disease: does the levodopa overdose hypothesis extend to gait?

The "levodopa-overdose hypothesis" posits that dopaminergic replacement therapy (1) increases performance on tasks that depend on the nigrostriatal-pathway (e.g., motor-control circuits), yet (2) decreases performance on tasks that depend upon the mesocorticolimbic-pathway (e.g., prefrontal cortex, PFC). Previous work in Parkinson's disease (PD) investigated this model while focusing on cognitive function. Here, we evaluated whether this model applies to gait in patients with PD and freezing of gait (FOG). Forty participants were examined in both the OFF anti-Parkinsonian medication state (hypo-dopaminergic) and ON state (hyper-dopaminergic) while walking with and without the concurrent performance of a serial subtraction task. Wireless functional near-infrared spectroscopy measured PFC activation during walking. Consistent with the "overdose-hypothesis", performance on the subtraction task decreased (p = 0.027) after dopamine intake. Moreover, the effect of walking condition on PFC activation depended on the dopaminergic state (i.e., interaction effect p = 0.001). Gait significantly improved after levodopa administration (p < 0.001). Nonetheless, PFC activation was higher (p = 0.013) in this state than in the OFF state during usual-walking. This increase in PFC activation in the ON state suggests that dopamine treatment interfered with PFC functioning. Otherwise, PFC activation, putatively a reflection of cognitive compensation, should have decreased. Moreover, in contrast to the OFF state, in the ON state, PFC activation failed to increase (p = 0.313) during dual-tasking, perhaps due to a "ceiling effect". These findings extend the "levodopa-overdose hypothesis" and suggest that it also applies to gait in PD patients. While dopaminergic therapy improves certain aspects of motor performance, optimal treatment should consider the "double-edged sword" of levodopa.

A Cross-species Model of Dual-Task Walking in Young and Older Humans and Rats

Introduction: Dual-task walking is common in daily life but becomes more difficult with aging. Little is known about the neurobiological mechanisms affecting competing cognitive demands. Translational studies with human and animal models are needed to address this gap. This pilot study investigated the feasibility of implementing a novel cross-species dual-task model in humans and rats and aimed to establish preliminary evidence that the model induces a dual-task cost.

Methods: Young and older humans and rats performed an object discrimination task (OD), a baseline task of typical walking (baseline), an alternation turning task on a Figure 8 walking course (Alt), and a dual-task combining object discrimination with the alternation task (AltOD). Primary behavioral assessments including walking speed and correct selections for object discrimination and turning direction. In humans, left prefrontal cortex activity was measured with functional near-infrared spectroscopy (fNIRS).

Results: Human subjects generally performed well on all tasks, but the older adults exhibited a trend for a slowing of walking speed immediately before the turning decision for Alt and AltOD compared to baseline. Older adults also had heightened prefrontal activity relative to young adults for the Alt and AltOD tasks. Older rodents required more training than young rodents to learn the alternation task. When tested on AltOD with and without a 15-s delay between trials, older rodents exhibited a substantial performance deficit for the delayed version on the initial day of testing. Old rats, however, did not show a significant slowing in walking speed with increasing task demand, as was evident in the young rats.

Discussion: This study demonstrates the feasibility and challenges associated with implementing a cross-species dual-task model. While there was preliminary evidence of dual-task cost in both humans and rats, the magnitude of effects was small and not consistent across species. This is likely due to the relative ease of each task in humans and the walking component in rats not being sufficiently challenging. Future versions of this test should make the cognitive tasks more challenging and the motor task in rats more complex.

Functional Near-Infrared Spectroscopy in the Study of Speech and Language Impairment Across the Life Span: A Systematic Review

Purpose Functional brain imaging is playing an increasingly important role in the diagnosis and treatment of communication disorders, yet many populations and settings are incompatible with functional magnetic resonance imaging and other commonly used techniques. We conducted a systematic review of neuroimaging studies using functional near-infrared spectroscopy (fNIRS) with individuals with speech or language impairment across the life span. We aimed to answer the following question: To what extent has fNIRS been used to investigate the neural correlates of speech-language impairment? Method This systematic review was preregistered with PROSPERO, the international prospective register of systematic reviews (CRD42019136464). We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol for preferred reporting items for systematic reviews. The database searches were conducted between February and March of 2019 with the following search terms: (a) fNIRS or functional near-infrared spectroscopy or NIRS or near-infrared spectroscopy, (b) speech or language, and (c) disorder or impairment or delay. Results We found 34 fNIRS studies that involved individuals with speech or language impairment across nine categories: (a) autism spectrum disorders; (b) developmental speech and language disorders; (c) cochlear implantation and deafness; (d) dementia, dementia of the Alzheimer's type, and mild cognitive impairment; (e) locked-in syndrome; (f) neurologic speech disorders/dysarthria; (g) stroke/aphasia; (h) stuttering; and (i) traumatic brain injury. Conclusions Though it is not without inherent challenges, fNIRS may have advantages over other neuroimaging techniques in the areas of speech and language impairment. fNIRS has clinical applications that may lead to improved early and differential diagnosis, increase our understanding of response to treatment, improve neuroprosthetic functioning, and advance neurofeedback.

A wide field-of-view, modular, high-density diffuse optical tomography system for minimally constrained three-dimensional functional neuroimaging

The ability to produce high-quality images of human brain function in any environment and during unconstrained movement of the subject has long been a goal of neuroimaging research. Diffuse optical tomography, which uses the intensity of back-scattered near-infrared light from multiple source-detector pairs to image changes in haemoglobin concentrations in the brain, is uniquely placed to achieve this goal. Here, we describe a new generation of modular, fibre-less, high-density diffuse optical tomography technology that provides exceptional sensitivity, a large dynamic range, a field-of-view sufficient to cover approximately one-third of the adult scalp, and also incorporates dedicated motion sensing into each module. Using in-vivo measures, we demonstrate a noise-equivalent power of 318 fW, and an effective dynamic range of 142 dB. We describe the application of this system to a novel somatomotor neuroimaging paradigm that involves subjects walking and texting on a smartphone. Our results demonstrate that wearable high-density diffuse optical tomography permits three-dimensional imaging of the human brain function during overt movement of the subject; images of somatomotor cortical activation can be obtained while subjects move in a relatively unconstrained manner, and these images are in good agreement with those obtained while the subjects remain stationary. The scalable nature of the technology we described here paves the way for the routine acquisition of high-quality, three-dimensional, whole-cortex diffuse optical tomography images of cerebral haemodynamics, both inside and outside of the laboratory environment, which has profound implications for neuroscience.

Exclusive detection of cerebral hemodynamics in functional near-infrared spectroscopy by reflectance modulation of the scalp surface

SIGNIFICANCE

Functional near-infrared spectroscopy (fNIRS) is a technique for detecting regional hemodynamic responses associated with neural activation in the cerebral cortex. The absorption changes due to hemodynamic changes in the scalp cause considerable signal contamination in the fNIRS measurement. A method for extracting hemodynamic changes in the cerebral tissue is required for reliable fNIRS measurement.

AIM

To exclusively detect cerebral functional hemodynamic changes, we developed an fNIRS technique using reflectance modulation of the scalp surface.

APPROACH

The theoretical feasibility of the proposed method was proven by a simulation calculation of light propagation. Its practical feasibility was evaluated by a phantom experiment and brain activation simulation mimicking human fNIRS experiments.

RESULTS

The simulation calculation revealed that the partial path length of the scalp was changed by reflectance modulation of the scalp surface. The influence of absorption change in the superficial layer was successfully reduced by the proposed method, using only measurement data, in the phantom experiment. The proposed method was applicable to human experiments of standard designs, achieving statistical significance within an acceptable experimental time-frame.

CONCLUSIONS

Removal of the scalp hemodynamic effect by the proposed technique will increase the quality of fNIRS data, particularly in measurements in neonates and infants that typically would require a dense optode arrangement.

On Your Mark, Get Set, Self-Control, Go: A Differentiated View on the Cortical Hemodynamics of Self-Control during Sprint Start

Most sports are self-control demanding. For example, during a sprint start, athletes have to respond as fast as possible to the start signal (action initiation) while suppressing the urge to start too early (action inhibition). Here, we examined the cortical hemodynamic response to these demands by measuring activity in the two lateral prefrontal cortices (lPFC), a central area for self-control processes. We analyzed activity within subregions of the lPFC, while subjects performed a sprint start, and we assessed if activation varied as a function of hemisphere and gender. In a counterbalanced within-subject design, 39 participants (age: mean (M) = 22.44, standard deviation (SD) = 5.28, 22 women) completed four sprint start conditions (blocks). In each block, participants focused on inhibition (avoid false start), initiation (start fast), no start (do not start) and a combined condition (start fast; avoid false start). We show that oxyhemoglobin in the lPFC increased after the set signal and this increase did not differ between experimental conditions. Increased activation was primarily observed in ventral areas of the lPFC, but only in males, and this increase did not vary between hemispheres. This study provides further support for the involvement of the ventral lPFC during a sprint start, while highlighting gender differences in the processing of sprint start-induced self-control demands.

Integration of Spatial Information Increases Reproducibility in Functional Near-Infrared Spectroscopy

As functional near-infrared spectroscopy (fNIRS) is developed as a neuroimaging technique and becomes an option to study a variety of populations and tasks, the reproducibility of the fNIRS signal is still subject of debate. By performing test-retest protocols over different functional tasks, several studies agree that the fNIRS signal is reproducible over group analysis, but the inter-subject and within-subject reproducibility is poor. The high variability at the first statistical level is often attributed to global systemic physiology. In the present work, we revisited the reproducibility of the fNIRS signal during a finger-tapping task across multiple sessions on the same and different days. We expanded on previous studies by hypothesizing that the lack of spatial information of the optodes contributes to the low reproducibility in fNIRS, and we incorporated a real-time neuronavigation protocol to provide accurate cortical localization of the optodes. Our proposed approach was validated in 10 healthy volunteers, and our results suggest that the addition of neuronavigation can increase the within-subject reproducibility of the fNIRS data, particularly in the region of interest. Unlike traditional approaches to positioning the optodes, in which low intra-subject reproducibility has been found, we were able to obtain consistent and robust activation of the contralateral primary motor cortex at the intra-subject level using a neuronavigation protocol. Overall, our findings support the hypothesis that at least part of the variability in fNIRS cannot be only attributed to global systemic physiology. The use of neuronavigation to guide probe positioning, as proposed in this work, has impacts to longitudinal protocols performed with fNIRS.

Is Cortical Activation During Walking Different Between Parkinson’s Disease Motor Subtypes?

Parkinson’s disease (PD) is often classified into tremor dominant (TD) and postural instability gait disorder (PIGD) subtypes. Degeneration of subcortical/cortical pathways is different between PD subtypes, which leads to differences in motor behavior. However, the influence of PD subtype on cortical activity during walking remains poorly understood. Therefore, we aimed to investigate the influence of PD motor subtypes on cortical activity during unobstructed walking and obstacle avoidance. Seventeen PIGD and 19 TD patients performed unobstructed walking and obstacle avoidance conditions. Brain activity was measured using a mobile functional near-infrared spectroscopy–electroencephalography (EEG) systems, and gait parameters were analyzed using an electronic carpet. Concentrations of oxygenated hemoglobin (HbO2) of the prefrontal cortex (PFC) and EEG absolute power from alpha, beta, and gamma bands in FCz, Cz, CPz, and Oz channels were calculated. These EEG channels correspond to supplementary motor area, primary motor cortex, posterior parietal cortex, and visual cortex, respectively. Postural instability gait disorder patients presented higher PFC activity than TD patients, regardless of the walking condition. Tremor dominant patients presented reduced beta power in the Cz channel during obstacle avoidance compared to unobstructed walking. Both TD and PIGD patients decreased alpha and beta power in the FCz and CPz channels. In conclusion, PIGD patients need to recruit additional cognitive resources from the PFC for walking. Both TD and PIGD patients presented changes in the activation of brain areas related to motor/sensorimotor areas in order to maintain balance control during obstacle avoidance, being that TD patients presented further changes in the motor area (Cz channel) to avoid obstacles.

Association of Exercise with Inhibitory Control and Prefrontal Brain Activity Under Acute Psychosocial Stress

Psychosocial stress has negative effects on cognition in adolescents. The aim of this study was to investigate whether physical exercise can buffer such effects on inhibitory control and associated cortical brain areas. Forty-two male high school students aged 16-20 years and with either low or high exercise levels performed a Stroop task under stress-free conditions and after the Trier Social Stress Test (TSST). Oxygenation of the dorsolateral prefrontal cortex (DLPFC) was measured with functional near-infrared spectroscopy. For inhibitory control, there was no significant primary effect of condition (F(1,40) = 1.09, p = 303., ηp² = 0.027) and no significant condition × group interaction (F(1,40) = 2.40, p = 0.129, ηp² = 0.057). For DLPFC oxygenation, a significant primary effect of condition was observed (F (1,38) = 6.10, p = 0.018, ηp² = 0.138). However, the condition × group interaction (F (1,38) = 0.05, p = 0.823, ηp² = 0.001) remained not significant. Adolescents' exercise level was not associated with inhibitory control before and after stress. An impact of stress on a neurocognitive level was observed.

Short-channel regression in functional near-infrared spectroscopy is more effective when considering heterogeneous scalp hemodynamics

Significance: The reliability of functional near-infrared spectroscopy (fNIRS) measurements is reduced by systemic physiology. Short-channel regression algorithms aim at removing systemic "noise" by subtracting the signal measured at a short source-detector separation (mainly scalp hemodynamics) from the one of a long separation (brain and scalp hemodynamics). In literature, incongruent approaches on the selection of the optimal regressor signal are reported based on different assumptions on scalp hemodynamics properties. Aim: We investigated the spatial and temporal distribution of scalp hemodynamics over the sensorimotor cortex and evaluated its influence on the effectiveness of short-channel regressions. Approach: We performed hand-grasping and resting-state experiments with five subjects, measuring with 16 optodes over sensorimotor areas, including eight 8-mm channels. We performed detailed correlation analyses of scalp hemodynamics and evaluated 180 hand-grasping and 270 simulated (overlaid on resting-state measurements) trials. Five short-channel regressor combinations were implemented with general linear models. Three were chosen according to literature, and two were proposed based on additional physiological assumptions [considering multiple short channels and their Mayer wave (MW) oscillations]. Results: We found heterogeneous hemodynamics in the scalp, coming on top of a global close-to-homogeneous behavior (correlation 0.69 to 0.92). The results further demonstrate that short-channel regression always improves brain activity estimates but that better results are obtained when heterogeneity is assumed. In particular, we highlight that short-channel regression is more effective when combining multiple scalp regressors and when MWs are additionally included. Conclusion: We shed light on the selection of optimal regressor signals for improving the removal of systemic physiological artifacts in fNIRS. We conclude that short-channel regression is most effective when assuming heterogeneous hemodynamics, in particular when combining spatial- and frequency-specific information. A better understanding of scalp hemodynamics and more effective short-channel regression will promote more accurate assessments of functional brain activity in clinical and research settings.

Levodopa Facilitates Prefrontal Cortex Activation During Dual Task Walking in Parkinson Disease

Background. Although dopaminergic medication improves dual task walking in people with Parkinson disease (PD), the underlying neural mechanisms are not yet fully understood. As prefrontal cognitive resources are involved in dual task walking, evaluation of the prefrontal cortex (PFC) is required. Objective. To investigate the effect of dopaminergic medication on PFC activity and gait parameters during dual task walking in people with PD. Methods. A total of 20 individuals with PD (69.8 ± 5.9 years) and 30 healthy older people (68.0 ± 5.6 years) performed 2 walking conditions: single and dual task (walking while performing a digit vigilance task). A mobile functional near infrared spectroscopy system and an electronic sensor carpet were used to analyze PFC activation and gait parameters, respectively. Relative concentrations of oxygenated hemoglobin (HbO2) from the left and right PFC were measured. Results. People with PD in the off state did not present changes in HbO2 level in the left PFC across walking conditions. In contrast, in the on state, they presented increased HbO2 levels during dual task compared with single task. Regardless of medication state, people with PD presented increased HbO2 levels in the right PFC during dual task walking compared with single task. The control group demonstrated increased PFC activity in both hemispheres during dual task compared with single task. People with PD showed increases in both step length and velocity in the on state compared with the off state. Conclusions. PD limits the activation of the left PFC during dual task walking, and dopaminergic medication facilitates its recruitment.

Cortical Tasks-Based Optimal Filter Selection: An fNIRS Study

Functional near-infrared spectroscopy (fNIRS) is one of the latest noninvasive brain function measuring technique that has been used for the purpose of brain-computer interfacing (BCI). In this paper, we compare and analyze the effect of six most commonly used filtering techniques (i.e., Gaussian, Butterworth, Kalman, hemodynamic response filter (hrf), Wiener, and finite impulse response) on classification accuracies of fNIRS-BCI. To conclude with the best optimal filter for a specific cortical task owing to a specific cortical region, we divided our experimental tasks according to the three main cortical regions: prefrontal, motor, and visual cortex. Three different experiments were performed for prefrontal and motor execution tasks while one for visual stimuli. The tasks performed for prefrontal include rest (R) vs mental arithmetic (MA), R vs object rotation (OB), and OB vs MA. Similarly, for motor execution, R vs left finger tapping (LFT), R vs right finger tapping (RFT), and LFT vs RFT. Likewise, for the visual cortex, R vs visual stimuli (VS) task. These experiments were performed for ten trials with five subjects. For consistency among extracted data, six statistical features were evaluated using oxygenated hemoglobin, namely, slope, mean, peak, kurtosis, skewness, and variance. Combination of these six features was used to classify data by the nonlinear support vector machine (SVM). The classification accuracies obtained from SVM by using hrf and Gaussian were significantly higher for R vs MA, R vs OB, R vs RFT, and R vs VS and Wiener filter for OB vs MA. Similarly, for R vs LFT and LFT vs RFT, hrf was found to be significant p<0.05. These results show the feasibility of using hrf for effective removal of noises from fNIRS data.

Decoding Mental Workload in Virtual Environments: A fNIRS Study using an Immersive n-back Task

Virtual Reality (VR) has emerged as a novel paradigm for immersive applications in training, entertainment, rehabilitation, and other domains. In this paper, we investigate the automatic classification of mental workload from brain activity measured through functional near-infrared spectroscopy (fNIRS) in VR. We present results from a study which implements the established n-back task in an immersive visual scene, including physical interaction. Our results show that user workload can be detected from fNIRS signals in immersive VR tasks both person-dependently and -adaptively.

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

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

Using the General Linear Model to Improve Performance in fNIRS Single Trial Analysis and Classification: A Perspective

Within a decade, single trial analysis of functional Near Infrared Spectroscopy (fNIRS) signals has gained significant momentum, and fNIRS joined the set of modalities frequently used for active and passive Brain Computer Interfaces (BCI). A great variety of methods for feature extraction and classification have been explored using state-of-the-art Machine Learning methods. In contrast, signal preprocessing and cleaning pipelines for fNIRS often follow simple recipes and so far rarely incorporate the available state-of-the-art in adjacent fields. In neuroscience, where fMRI and fNIRS are established neuroimaging tools, evoked hemodynamic brain activity is typically estimated across multiple trials using a General Linear Model (GLM). With the help of the GLM, subject, channel, and task specific evoked hemodynamic responses are estimated, and the evoked brain activity is more robustly separated from systemic physiological interference using independent measures of nuisance regressors, such as short-separation fNIRS measurements. When correctly applied in single trial analysis, e.g., in BCI, this approach can significantly enhance contrast to noise ratio of the brain signal, improve feature separability and ultimately lead to better classification accuracy. In this manuscript, we provide a brief introduction into the GLM and show how to incorporate it into a typical BCI preprocessing pipeline and cross-validation. Using a resting state fNIRS data set augmented with synthetic hemodynamic responses that provide ground truth brain activity, we compare the quality of commonly used fNIRS features for BCI that are extracted from (1) conventionally preprocessed signals, and (2) signals preprocessed with the GLM and physiological nuisance regressors. We show that the GLM-based approach can provide better single trial estimates of brain activity as well as a new feature type, i.e., the weight of the individual and channel-specific hemodynamic response function (HRF) regressor. The improved estimates yield features with higher separability, that significantly enhance accuracy in a binary classification task when compared to conventional preprocessing—on average +7.4% across subjects and feature types. We propose to adapt this well-established approach from neuroscience to the domain of single-trial analysis and preprocessing wherever the classification of evoked brain activity is of concern, for instance in BCI.

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

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

A functional near-infrared spectroscopy (fNIRS) examination of how self-initiated sequential movements become automatic

The neural mechanisms underlying movement automaticity have been investigated using PET and fMRI and more recently functional near-infrared spectroscopy (fNIRS). As fNIRS is an emerging technique, the objective of the present study was to replicate the functional magnetic resonance imaging-related motor sequence findings as reported by Wu et al. (J Neurophysiol 91:1690-1698, https://doi.org/10.1152/jn.01052.2003, 2004) using fNIRS. Seventeen right-handed participants practiced self-initiated sequential finger movements of two lengths (4 and 12) until a level of automaticity was achieved. Automaticity was evaluated by performing a visual-letter-counting task concurrently with the sequential finger movements. Our data were unable to replicate the pre-to-post-practice decrease in cortical activity in the left dorsolateral prefrontal cortex for both motor sequence tasks. The findings did reveal increased contribution from the right hemisphere following learning. The observed lateralization is suggestive of explicit learning and the involvement of working memory in motor sequence production.

Functional Near-Infrared Spectroscopy to Study Cerebral Hemodynamics in Older Adults During Cognitive and Motor Tasks: A Review

The integrity of the frontal areas of the brain, specifically the prefrontal cortex, are critical to preserve cognition and mobility in late life. Prefrontal cortex regions are involved in executive functions and gait control and have been related to the performance of dual-tasks. Dual-task performance assessment may help identify older adults at risk of negative health outcomes. As an alternative to neuroimaging techniques that do not allow assessment during actual motion, functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive technique that can assess neural activation through the measurement of cortical oxygenated and deoxygenated hemoglobin levels, while the person is performing a motor task in a natural environment as well as during cognitive tasks. The aim of this review was to describe the use of fNIRS to study frontal lobe hemodynamics during cognitive, motor and dual-tasks in older adults. From the 46 included publications, 20 studies used only cognitive tasks, three studies used motor tasks and 23 used dual-tasks. Our findings suggest that fNIRS detects changes in frontal activation in older adults (cognitively healthy and mild cognitive impairment), especially while performing cognitive and dual-tasks. In both the comparison between older and younger adults, and in people with different neurological conditions, compared to healthier controls, the prefrontal cortex seems to experience a higher activation, which could be interpreted in the context of proposed neural inefficiency and limited capacity models. Further research is needed to establish standardized fNIRS protocols, study the cerebral hemodynamic in different neurological and systemic conditions that might influence cortical activation and explore its role in predicting incident health outcomes such as dementia.

Functional near-infrared spectroscopy for speech protocols: characterization of motion artifacts and guidelines for improving data analysis

Monitoring speech tasks with functional near-infrared spectroscopy (fNIRS) enables investigation of speech production mechanisms and informs treatment strategies for speech-related disorders such as stuttering. Unfortunately, due to movement of the temporalis muscle, speech production can induce relative movement between probe optodes and skin. These movements generate motion artifacts during speech tasks. In practice, spurious hemodynamic responses in functional activation signals arise from lack of information about the consequences of speech-related motion artifacts, as well as from lack of standardized processing procedures for fNIRS signals during speech tasks. To this end, we characterize the effects of speech production on fNIRS signals, and we introduce a systematic analysis to ameliorate motion artifacts. The study measured 50 healthy subjects performing jaw movement (JM) tasks and found that JM produces two different patterns of motion artifacts in fNIRS. To remove these unwanted contributions, we validate a hybrid motion-correction algorithm based sequentially on spline interpolation and then wavelet filtering. We compared performance of the hybrid algorithm with standard algorithms based on spline interpolation only and wavelet decomposition only. The hybrid algorithm corrected 94% of the artifacts produced by JM, and it did not lead to spurious responses in the data. We also validated the hybrid algorithm during a reading task performed under two different conditions: reading aloud and reading silently. For both conditions, we observed significant cortical activation in brain regions related to reading. Moreover, when comparing the two conditions, good agreement of spatial and temporal activation patterns was found only when data were analyzed using the hybrid approach. Overall, the study demonstrates a standardized processing scheme for fNIRS data during speech protocols. The scheme decreases spurious responses and intersubject variability due to motion artifacts.

Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis

For the robust estimation of evoked brain activity from functional Near-Infrared Spectroscopy (fNIRS) signals, it is crucial to reduce nuisance signals from systemic physiology and motion. The current best practice incorporates short-separation (SS) fNIRS measurements as regressors in a General Linear Model (GLM). However, several challenging signal characteristics such as non-instantaneous and non-constant coupling are not yet addressed by this approach and additional auxiliary signals are not optimally exploited. We have recently introduced a new methodological framework for the unsupervised multivariate analysis of fNIRS signals using Blind Source Separation (BSS) methods. Building onto the framework, in this manuscript we show how to incorporate the advantages of regularized temporally embedded Canonical Correlation Analysis (tCCA) into the supervised GLM. This approach allows flexible integration of any number of auxiliary modalities and signals. We provide guidance for the selection of optimal parameters and auxiliary signals for the proposed GLM extension. Its performance in the recovery of evoked HRFs is then evaluated using both simulated ground truth data and real experimental data and compared with the GLM with short-separation regression. Our results show that the GLM with tCCA significantly improves upon the current best practice, yielding significantly better results across all applied metrics: Correlation (HbO max. +45%), Root Mean Squared Error (HbO max. −55%), F-Score (HbO up to 3.25-fold) and p-value as well as power spectral density of the noise floor. The proposed method can be incorporated into the GLM in an easily applicable way that flexibly combines any available auxiliary signals into optimal nuisance regressors. This work has potential significance both for conventional neuroscientific fNIRS experiments as well as for emerging applications of fNIRS in everyday environments, medicine and BCI, where high Contrast to Noise Ratio is of importance for single trial analysis.

Mandibular prognathism attenuates brain blood flow induced by chewing

Mastication is closely related to brain function. Animal experiments have revealed that tooth loss has a negative influence on brain function. Clinical studies also suggest that normal occlusion is an essential factor for favorable brain function. Mandibular prognathism (MP) usually results in occlusal dysfunction. However, the relationship between MP and brain function remains unclear. In the present study, we examined the relationship between MP and brain function by measuring brain blood flow (BBF). Seventeen subjects with normal occlusion (NORM) and 25 patients with MP participated in this study. The number of occlusal contacts were counted. Electromyography of the masseter muscles during clenching was also recorded. BBF was measured with non-invasive functional near-infrared spectroscopy during calculation task and chewing task. The number of the occlusal contacts and masseter muscle activity were lower in MP compared with NORM. The calculation task increased BBF in both groups. The chewing task also increased BBF in the inferior frontal gyrus in both groups, although the increase in MP was smaller than in NORM. We discovered that patients with MP exhibited a smaller increase in BBF at the inferior frontal gyrus during chewing as compared with NORM. As such, MP would negatively affect brain function.

Information Content of Prefrontal Cortex Activity Quantifies the Difficulty of Narrated Stories

The ability to realize the individuals' impressions during the verbal communication allows social robots to significantly facilitate their social interactions in such areas as child education and elderly care. However, such impressions are highly subjective and internalized and therefore cannot be easily comprehended through behavioural observations. Although brain-machine interface suggests the utility of the brain information in human-robot interaction, previous studies did not consider its potential for estimating the internal impressions during verbal communication. In this article, we introduce a novel approach to estimation of the individuals' perceived difficulty of stories using the quantified information content of their prefrontal cortex activity. We demonstrate the robustness of our approach by showing its comparable performance in face-to-face, humanoid, speaker, and video-chat settings. Our results contribute to the field of socially assistive robotics by taking a step toward enabling robots determine their human companions' perceived difficulty of conversations, thereby enabling these media to sustain their communication with humans by adapting to individuals' pace and interest in response to conversational nuances and complexity.

A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.

A Functional Near-Infrared Spectroscopy Study on the Cortical Haemodynamic Responses During the Maastricht Acute Stress Test

In order to better understand stress responses, neuroimaging studies have investigated the underlying neural correlates of stress. Amongst other brain regions, they highlight the involvement of the prefrontal cortex. The aim of the present study was to explore haemodynamic changes in the prefrontal cortex during the Maastricht Acute Stress Test (MAST) using mobile functional Near-Infrared Spectroscopy (fNIRS), examining the stress response in an ecological environment. The MAST includes a challenging mental arithmic task and a physically stressful ice-water task. In a between-subject design, participants either performed the MAST or a non-stress control condition. FNIRS data were recorded throughout the test. Additionally, subjective stress ratings, heart rate and salivary cortisol were evaluated, confirming a successful stress induction. The fNIRS data indicated significantly increased neural activity of brain regions of the dorsolateral prefrontal cortex (dlPFC) and the orbitofrontal cortex (OFC) in response to the MAST, compared to the control condition. Furthermore, the mental arithmetic task indicated an increase in neural activity in brain regions of the dlPFC and OFC; whereas the physically stressful hand immersion task indicated a lateral decrease of neural activity in the left dlPFC. The study highlights the potential use of mobile fNIRS in clinical and applied (stress) research.

Theories and Methods for Labeling Cognitive Workload: Classification and Transfer Learning

There are a number of key data-centric questions that must be answered when developing classifiers for operator functional states. "Should a supervised or unsupervised learning approach be used? What degree of labeling and transformation must be performed on the data? What are the trade-offs between algorithm flexibility and model interpretability, as generally these features are at odds?" Here, we focus exclusively on the labeling of cognitive load data for supervised learning. We explored three methods of labeling cognitive states for three-state classification. The first method labels states derived from a tertiary split of trial difficulty during a spatial memory task. The second method was more adaptive; it employed a mixed-effects stress-strain curve and estimated an individual's performance asymptotes with respect to the same spatial memory task. The final method was similar to the second approach; however, it employed a mixed-effects Rasch model to estimate individual capacity limits within the context of item response theory for the spatial memory task. To assess the strength of each of these labeling approaches, we compared the area under the curve (AUC) for receiver operating curves (ROCs) from elastic net and random forest classifiers. We chose these classifiers based on a combination of interpretability, flexibility, and past modeling success. We tested these techniques across two groups of individuals and two tasks to test the effects of different labeling techniques on cross-person and cross-task transfer. Overall, we observed that the Rasch model labeling paired with a random forest classifier led to the best model fits and showed evidence of both cross-person and cross-task transfer.

A Combined EEG-fNIRS Study Investigating Mechanisms Underlying the Association between Aerobic Fitness and Inhibitory Control in Young Adults

The current evidence suggests that aerobic fitness is associated with inhibitory control of executive functioning in children and older adults. However, the relative contributions of different neurophysiological mechanisms to this relation remain unclear and have not yet been examined in young adults. The present study aimed to compare inhibitory control between high and low-fit young adult men, and to investigate a possible mediation of fitness effects by conflict monitoring (N450 component of event-related potentials) and lateralized oxygenation difference (LOD) in the DLPFC. For the present cross-sectional study, participants with different physical activity levels were recruited and divided into low-fit and high-fit participants based on relative power on the PWC170. A Stroop Color-Word task was administered and combined EEG-fNIRS was simultaneously utilized to assess the N450 and LOD, because these parameters are linked with behavioral performance. The results of the statistical analysis showed that high-fitcompared to low-fit participants showed less Stroop interference and lower negativity of the N450, whereas no difference was found for LOD. Path-analyses further revealed that the relation between aerobic fitness levels and Stroop interference was indirect and mediated by N450. In contrast, LOD was inversely correlated with Stroop interference, but did not explain the relation of aerobic fitness with behavioral performance. The present findings indicate that greater inhibitory control in high- compared to low-fit young men can be explained by more effective conflict monitoring. Moreover, young adults with left-lateralizedDLPFC oxygenation also show higher inhibitory control, but this oxygenation pattern is not influenced by aerobic fitness.