Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development

Prefrontal Cortex Responses to Social Video Stimuli in Young Children with and without Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting individuals worldwide and characterized by deficits in social interaction along with the presence of restricted interest and repetitive behaviors. Despite decades of behavioral research, little is known about the brain mechanisms that influence social behaviors among children with ASD. This, in part, is due to limitations of traditional imaging techniques specifically targeting pediatric populations. As a portable and scalable optical brain monitoring technology, functional near infrared spectroscopy (fNIRS) provides a measure of cerebral hemodynamics related to sensory, motor, or cognitive function. Here, we utilized fNIRS to investigate the prefrontal cortex (PFC) activity of young children with ASD and with typical development while they watched social and nonsocial video clips. The PFC activity of ASD children was significantly higher for social stimuli at medial PFC, which is implicated in social cognition/processing. Moreover, this activity was also consistently correlated with clinical measures, and higher activation of the same brain area only during social video viewing was associated with more ASD symptoms. This is the first study to implement a neuroergonomics approach to investigate cognitive load in response to realistic, complex, and dynamic audiovisual social stimuli for young children with and without autism. Our results further confirm that new generation of portable fNIRS neuroimaging can be used for ecologically valid measurements of the brain function of toddlers and preschool children with ASD.

Mental workload assessment by monitoring brain, heart, and eye with six biomedical modalities during six cognitive tasks

Introduction

The efficiency and safety of complex high precision human-machine systems such as in aerospace and robotic surgery are closely related to the cognitive readiness, ability to manage workload, and situational awareness of their operators. Accurate assessment of mental workload could help in preventing operator error and allow for pertinent intervention by predicting performance declines that can arise from either work overload or under stimulation. Neuroergonomic approaches based on measures of human body and brain activity collectively can provide sensitive and reliable assessment of human mental workload in complex training and work environments.

Methods

In this study, we developed a new six-cognitive-domain task protocol, coupling it with six biomedical monitoring modalities to concurrently capture performance and cognitive workload correlates across a longitudinal multi-day investigation. Utilizing two distinct modalities for each aspect of cardiac activity (ECG and PPG), ocular activity (EOG and eye-tracking), and brain activity (EEG and fNIRS), 23 participants engaged in four sessions over 4 weeks, performing tasks associated with working memory, vigilance, risk assessment, shifting attention, situation awareness, and inhibitory control.

Results

The results revealed varying levels of sensitivity to workload within each modality. While certain measures exhibited consistency across tasks, neuroimaging modalities, in particular, unveiled meaningful differences between task conditions and cognitive domains.

Discussion

This is the first comprehensive comparison of these six brain-body measures across multiple days and cognitive domains. The findings underscore the potential of wearable brain and body sensing methods for evaluating mental workload. Such comprehensive neuroergonomic assessment can inform development of next generation neuroadaptive interfaces and training approaches for more efficient human-machine interaction and operator skill acquisition.

On decoding of rapid motor imagery in a diverse population using a high-density NIRS device

Introduction

Functional near-infrared spectroscopy (fNIRS) aims to infer cognitive states such as the type of movement imagined by a study participant in a given trial using an optical method that can differentiate between oxygenation states of blood in the brain and thereby indirectly between neuronal activity levels. We present findings from an fNIRS study that aimed to test the applicability of a high-density (>3000 channels) NIRS device for use in short-duration (2 s) left/right hand motor imagery decoding in a diverse, but not explicitly balanced, subject population. A side aim was to assess relationships between data quality, self-reported demographic characteristics, and brain-computer interface (BCI) performance, with no subjects rejected from recruitment or analysis.

Methods

BCI performance was quantified using several published methods, including subject-specific and subject-independent approaches, along with a high-density fNIRS decoder previously validated in a separate study.

Results

We found that decoding of motor imagery on this population proved extremely challenging across all tested methods. Overall accuracy of the best-performing method (the high-density decoder) was 59.1 +/- 6.7% after excluding subjects where almost no optode-scalp contact was made over motor cortex and 54.7 +/- 7.6% when all recorded sessions were included. Deeper investigation revealed that signal quality, hemodynamic responses, and BCI performance were all strongly impacted by the hair phenotypical and demographic factors under investigation, with over half of variance in signal quality explained by demographic factors alone.

Discussion

Our results contribute to the literature reporting on challenges in using current-generation NIRS devices on subjects with long, dense, dark, and less pliable hair types along with the resulting potential for bias. Our findings confirm the need for increased focus on these populations, accurate reporting of data rejection choices across subject intake, curation, and final analysis in general, and signal a need for NIRS optode designs better optimized for the general population to facilitate more robust and inclusive research outcomes.

Cognitive Effort during Visuospatial Problem Solving in Physical Real World, on Computer Screen, and in Virtual Reality

Spatial cognition plays a crucial role in academic achievement, particularly in science, technology, engineering, and mathematics (STEM) domains. Immersive virtual environments (VRs) have the growing potential to reduce cognitive load and improve spatial reasoning. However, traditional methods struggle to assess the mental effort required for visuospatial processes due to the difficulty in verbalizing actions and other limitations in self-reported evaluations. In this neuroergonomics study, we aimed to capture the neural activity associated with cognitive workload during visuospatial tasks and evaluate the impact of the visualization medium on visuospatial task performance. We utilized functional near-infrared spectroscopy (fNIRS) wearable neuroimaging to assess cognitive effort during spatial-reasoning-based problem-solving and compared a VR, a computer screen, and a physical real-world task presentation. Our results reveal a higher neural efficiency in the prefrontal cortex (PFC) during 3D geometry puzzles in VR settings compared to the settings in the physical world and on the computer screen. VR appears to reduce the visuospatial task load by facilitating spatial visualization and providing visual cues. This makes it a valuable tool for spatial cognition training, especially for beginners. Additionally, our multimodal approach allows for progressively increasing task complexity, maintaining a challenge throughout training. This study underscores the potential of VR in developing spatial skills and highlights the value of comparing brain data and human interaction across different training settings.

Application of functional near-infrared spectroscopy (fNIRS) in tinnitus research: contemporary insights and perspectives

Tinnitus, characterized by phantom sound perception, is a highly disruptive condition lacking clearly effective treatments. Its complex neural mechanisms are not fully elucidated. Functional near-infrared spectroscopy (fNIRS) is a promising neuroimaging tool well-suited for assessing tinnitus due to its quietness, portability, and ability to directly measure cortical hemodynamic responses. This study timely summarizes the recent applications of fNIRS in investigating tinnitus pathology, correlating neuroimaging biomarkers with symptom severity, and evaluating treatment efficacy. Further studies with larger samples are warranted to reproduce existing findings. Thus, fNIRS appears to be a promising tool in tinnitus research. Addressing technical limitations, optimizing control groups, advancing data analysis, integrating standardized, and individualized experimental protocols can facilitate the extended and robust utilization of fNIRS in tinnitus research.

Effects of transcranial magnetic stimulation on dynamic functional networks in stroke patients as assessed by functional near-infrared spectroscopy: a randomized controlled clinical trial

Studies have shown that there is heterogeneity in the efficacy bewteen the low-frequency (LF) and high-frequency (HF) repetitive transcranial magnetic stimulation (rTMS), but the neural mechanisms underlying the differences in efficacy remain unclear. This study aimed to investigate the specific effects of LF- and HF-rTMS on cortial functional network and the process of neural regulation. A total of sixty-eight patients with hemiplegic motor impairment after stroke were randomly allocated to one of three groups: the LF-rTMS, HF-rTMS, and sham groups. Tissue concentrations of oxyhaemoglobin and deoxyhaemoglobin oscillations in cerebral cortex regions were measured by functional near-infrared spectroscopy (fNIRS) in the resting and rTMS states. Four specific time-windows were divided from the trial duration to observe dynamic changes in cortical haemodynamic responses. Compared with sham, LF-rTMS significantly induced the activation of the contralesional superior frontal cortex and premotor cortex, and continuously regulated ipsilesional hemisphere functional networks in stroke patients. However, HF-rTMS did not induce a significant neurovascular coupling response. Our study provided evidence that LF- and HF-rTMS interventions induced different neurovascular coupling responses and demonstrated the cortical functional network change process of rTMS in specific time-windows. These findings may help to understand the differences in the efficacy of rTMS modalities.

Acute effects of (-)-gallocatechin gallate-rich green tea extract on the cerebral hemodynamic response of the prefrontal cortex in healthy humans

Objective

The benefits of long-term consumption of green tea on the brain are well known. However, among many ingredients of green tea, the acute effects of (-)-gallocatechin gallate-rich green tea extract (GCG-GTE), have received comparatively less attention. Herein, we investigated the acute effects of oral ingestion of green tea with GCG-GTE, which contains close replicas of the ingredients of hot green tea, on task-dependent hemodynamics in the prefrontal cortex of healthy adult human brains.

Methods

In this randomized, double-blind, placebo-controlled, parallel group trial, 35 healthy adults completed computerized cognitive tasks that demand activation of the prefrontal cortex at baseline and 1 h after consumption of placebo and 900 mg of GCG-GTE extract supplement. During cognitive testing, hemodynamic responses (change in HbO2 concentration) in the prefrontal cortex were assessed using functional near-infrared spectroscopy (fNIRS).

Results

In fNIRS data, significant group x session interactions were found in the left (p = 0.035) and right (p = 0.036) dorsolateral prefrontal cortex (DLPFC). In behavioral data, despite the numerical increase in the GCG-GTE group and the numerical decrease in the Placebo group, no significant differences were observed in the cognitive performance measure between the groups.

Conclusion

The result suggests a single dose of orally administered GCG-GTE can reduce DLPFC activation in healthy humans even with increased task demand. GCG-GTE is a promising functional material that can affect neural efficiency to lower mental workload during cognitively demanding tasks. However, further studies are needed to verify this.

Functional near-infrared spectroscopy-based prefrontal cortex oxygenation during working memory tasks in sickle cell disease

Significance

Sickle cell disease (SCD), characterized by painful vaso-occlusive crises, is associated with cognitive decline. However, objective quantification of cognitive decline in SCD remains a challenge, and the associated hemodynamics are unknown.

Aim

To address this, we utilized functional near-infrared spectroscopy (fNIRS) to measure prefrontal cortex (PFC) oxygenation responses to N -back working memory tasks in SCD patients and compared them with healthy controls.

Approach

We quantified the PFC oxygenation rate as an index of cognitive activity in each group and compared them. In half of the participants, a Stroop test was administered before they started N -back to elevate their baseline stress level.

Results

In SCD compared to healthy controls, we found that (1) under a high baseline stress level, there were significantly greater oxygenation responses during the 2-back task, further elevated with histories of stroke; (2) there was a marginally slower N -back response time, and it was even slower with a history of stroke; and (3) the task accuracy was not different.

Conclusions

Additional requirements for processing time, PFC resources, and PFC oxygenation in SCD patients offer an important basis for understanding their cognitive decline and highlight the potential of fNIRS for evaluating cognitive functions.

Cross-Subject Emotion Recognition Brain-Computer Interface Based on fNIRS and DBJNet

Functional near-infrared spectroscopy (fNIRS) is a noninvasive brain imaging technique that has gradually been applied in emotion recognition research due to its advantages of high spatial resolution, real time, and convenience. However, the current research on emotion recognition based on fNIRS is mainly limited to within-subject, and there is a lack of related work on emotion recognition across subjects. Therefore, in this paper, we designed an emotion evoking experiment with videos as stimuli and constructed the fNIRS emotion recognition database. On this basis, deep learning technology was introduced for the first time, and a dual-branch joint network (DBJNet) was constructed, creating the ability to generalize the model to new participants. The decoding performance obtained by the proposed model shows that fNIRS can effectively distinguish positive versus neutral versus negative emotions (accuracy is 74.8%, F1 score is 72.9%), and the decoding performance on the 2-category emotion recognition task of distinguishing positive versus neutral (accuracy is 89.5%, F1 score is 88.3%), negative versus neutral (accuracy is 91.7%, F1 score is 91.1%) proved fNIRS has a powerful ability to decode emotions. Furthermore, the results of the ablation study of the model structure demonstrate that the joint convolutional neural network branch and the statistical branch achieve the highest decoding performance. The work in this paper is expected to facilitate the development of fNIRS affective brain-computer interface.

Simultaneous fMRI and tDCS for Enhancing Training of Flight Tasks

There is a gap in our understanding of how best to apply transcranial direct-current stimulation (tDCS) to enhance learning in complex, realistic, and multifocus tasks such as aviation. Our goal is to assess the effects of tDCS and feedback training on task performance, brain activity, and connectivity using functional magnetic resonance imaging (fMRI). Experienced glider pilots were recruited to perform a one-day, three-run flight-simulator task involving varying difficulty conditions and a secondary auditory task, mimicking real flight requirements. The stimulation group (versus sham) received 1.5 mA high-definition HD-tDCS to the right dorsolateral prefrontal cortex (DLPFC) for 30 min during the training. Whole-brain fMRI was collected before, during, and after stimulation. Active stimulation improved piloting performance both during and post-training, particularly in novice pilots. The fMRI revealed a number of tDCS-induced effects on brain activation, including an increase in the left cerebellum and bilateral basal ganglia for the most difficult conditions, an increase in DLPFC activation and connectivity to the cerebellum during stimulation, and an inhibition in the secondary task-related auditory cortex and Broca's area. Here, we show that stimulation increases activity and connectivity in flight-related brain areas, particularly in novices, and increases the brain's ability to focus on flying and ignore distractors. These findings can guide applied neurostimulation in real pilot training to enhance skill acquisition and can be applied widely in other complex perceptual-motor real-world tasks.

A scoping review of different monitoring-technology devices in caring for older adults with cognitive impairment

Various monitoring technologies are being developed to prevent potential complications among older adults with cognitive impairment and improve their cognitive function. This scoping review identified gaps in the development of monitoring-technology devices for cognitive health status and highlights areas that require further inquiry. This study used the Joanna Briggs Institute (JBI) and the PRISMA extension for the checklist for scoping reviews using the eligibility criteria recommended by Population, Concept, and Context (PCC) framework. The study population included adults aged 65 years and above, while the concept and context are monitoring-technology devices utilized in detecting and caring for an older adult with cognitive impairment. Three electronic databases (Medline, Scopus, and Web of Science) were searched, and a total of 21 articles met the selection criteria. Several innovative technology-based devices for screening, assessing, detecting, and monitoring the interventions for older adult cognitive impairment and for family caregivers to ensure the continuity of care were established. Monitoring devices are useful in promoting older adult safety, improving their quality of life by enabling them to live independently for a longer period, and improving their mental wellbeing to help reduce the burden on caregivers by providing them with information concerning the activities of older adults. Moreover, studies have shown that older adults and their caregivers can learn to use these devices effectively and comfortably with proper education and training. The results of this study provide crucial insights into innovative technologies that can be used to assess cognitive health among older adults, which could substantially improve their mental health, and this baseline information can be used for supporting public health policy and enhancing their quality of life.

Functional near infrared spectroscopy for brain functional connectivity analysis: A graph theoretic approach

Background

Functional Near-Infrared Spectroscopy is an optical brain monitoring technique which uses NIRS to perform functional neuroimaging. It uses near-infrared light for measuring brain activity and to estimate the cortical hemodynamic activity in the brain due to motor activity. Functional NIRS measures the changes in oxygen levels in oxygenated and deoxygenated hemoglobin by optical absorption. One of the main challenges in the analysis of fNIRS signals is the signal degradation due to the interference from noise and artifacts from multiple sources.

Methods

In this context, this research aims to analyze the connectivity between different regions of the brain using graph theory and hence the geometrical association of brain networks in terms of functional parameters. In this study, the impact of two noise removal processes (CBSI and TDDR), along with two types of correlation fNIRS such as Pearson's Correlation (PC), and Cross Correlation (CC) and various whole-brain network architectures on the reproducibility of graph measurements for individual participants has been carefully examined for different densities ranging from 5% to 50%.The graph measures' repeatability at the individual level was studied using the test-retest variability (TRT).

Results

The test-retest variability for global measurements in binary networks was substantially large at low densities, regardless of the noise removal method or the kind of correlation. Very low test -reset values are observed for weighted networks and great reproducibility for measures of the entire graph. When comparing the test-retest values for various methods, the kind of correlation, the absolute value of the correlation, and the weight calculation method on the raw correlation value all had significant major effects.

Conclusion

Based on a weighted network with the absolute cross correlation functioning as the weight, this study revealed that normalized global graph measurements were reliable. The node definition techniques that were utilized to remove noise were not essential for the normalized graph measures to be reproducible.

The Pitfalls and Perspectives of Assessing Olfactory Function via Optical Brain Imaging

Olfaction is critical for maintaining daily life activities. It is crucial to measure olfactory performance for the diagnosis and treatment of certain neurodegenerative diseases. Moreover, impairments and a lack of quality in the olfactory system may indicate the early diagnosis of some diseases such as Parkinson's. In this context, there are several imaging methods available for evaluating olfactory function. In addition to the conventional methods used in measuring the brain's responsiveness to olfactory stimuli, this article presents a systematic review of the current applicability of optical brain imaging (i.e., functional near-infrared spectroscopy) in the evaluation of olfactory function. A database literature search was conducted in PubMed, Scopus, the Web of Science, and ScienceDirect. This review excluded animal studies, clinical studies, pathology- or neurodegenerative disease-related studies, newborn-related studies, cross-modal- and dual-task-related studies, and non-original research studies. Thus, seven studies were examined to discuss the pitfalls and perspectives of the use of optical brain imaging under olfactory stimulation. As for this conclusion, they can be used to evaluate olfactory performance in healthy individuals through the interpretation of hemodynamic changes. Further studies are needed to standardize the applicability of these optical imaging techniques.

Interdisciplinary views of fNIRS: Current advancements, equity challenges, and an agenda for future needs of a diverse fNIRS research community

Functional Near-Infrared Spectroscopy (fNIRS) is an innovative and promising neuroimaging modality for studying brain activity in real-world environments. While fNIRS has seen rapid advancements in hardware, software, and research applications since its emergence nearly 30 years ago, limitations still exist regarding all three areas, where existing practices contribute to greater bias within the neuroscience research community. We spotlight fNIRS through the lens of different end-application users, including the unique perspective of a fNIRS manufacturer, and report the challenges of using this technology across several research disciplines and populations. Through the review of different research domains where fNIRS is utilized, we identify and address the presence of bias, specifically due to the restraints of current fNIRS technology, limited diversity among sample populations, and the societal prejudice that infiltrates today's research. Finally, we provide resources for minimizing bias in neuroscience research and an application agenda for the future use of fNIRS that is equitable, diverse, and inclusive.

Haptic shared control improves neural efficiency during myoelectric prosthesis use

Clinical myoelectric prostheses lack the sensory feedback and sufficient dexterity required to complete activities of daily living efficiently and accurately. Providing haptic feedback of relevant environmental cues to the user or imbuing the prosthesis with autonomous control authority have been separately shown to improve prosthesis utility. Few studies, however, have investigated the effect of combining these two approaches in a shared control paradigm, and none have evaluated such an approach from the perspective of neural efficiency (the relationship between task performance and mental effort measured directly from the brain). In this work, we analyzed the neural efficiency of 30 non-amputee participants in a grasp-and-lift task of a brittle object. Here, a myoelectric prosthesis featuring vibrotactile feedback of grip force and autonomous control of grasping was compared with a standard myoelectric prosthesis with and without vibrotactile feedback. As a measure of mental effort, we captured the prefrontal cortex activity changes using functional near infrared spectroscopy during the experiment. It was expected that the prosthesis with haptic shared control would improve both task performance and mental effort compared to the standard prosthesis. Results showed that only the haptic shared control system enabled users to achieve high neural efficiency, and that vibrotactile feedback was important for grasping with the appropriate grip force. These results indicate that the haptic shared control system synergistically combines the benefits of haptic feedback and autonomous controllers, and is well-poised to inform such hybrid advancements in myoelectric prosthesis technology.

Emerging Materials, Wearables, and Diagnostic Advancements in Therapeutic Treatment of Brain Diseases

Among the most critical health issues, brain illnesses, such as neurodegenerative conditions and tumors, lower quality of life and have a significant economic impact. Implantable technology and nano-drug carriers have enormous promise for cerebral brain activity sensing and regulated therapeutic application in the treatment and detection of brain illnesses. Flexible materials are chosen for implantable devices because they help reduce biomechanical mismatch between the implanted device and brain tissue. Additionally, implanted biodegradable devices might lessen any autoimmune negative effects. The onerous subsequent operation for removing the implanted device is further lessened with biodegradability. This review expands on current developments in diagnostic technologies such as magnetic resonance imaging, computed tomography, mass spectroscopy, infrared spectroscopy, angiography, and electroencephalogram while providing an overview of prevalent brain diseases. As far as we are aware, there hasn't been a single review article that addresses all the prevalent brain illnesses. The reviewer also looks into the prospects for the future and offers suggestions for the direction of future developments in the treatment of brain diseases.

Similarities and differences in the induction and regulation of the negative emotions fear and disgust: A functional near infrared spectroscopy study

Affective processing, including induction and regulation of emotion, activates neural networks, induces physiological responses, and generates subjective experience. Dysregulation of these processes can lead to maladaptive behavior and even psychiatric morbidity. Multimodal studies of emotion thus not only help elucidate the nature of emotion, but also contribute to important clinical insights. In the present study, we compared the induction (EI) and effortful regulation (ER) with reappraisal of fear and disgust in healthy subjects using functional near infrared spectroscopy (fNIRS) in conjunction with electrodermal activity (EDA). During EI, there was significant activation in medial prefrontal cortex (PFC) for fear and more widespread activation for disgust, with right lateral PFC significantly more active during disgust compared to fear. ER was equally effective for fear and disgust reducing subjective emotion rating by roughly 45%. Compared to baseline, there was no increased PFC activity for fear during ER, while for disgust lateral PFC was significantly more active. Significant differences between the two negative emotions were also observed in sympathetic nerve activity as reflected in EDA during EI, but not during ER. Lastly, compared to men, women had higher emotion rating for both fear and disgust without corresponding differences in EDA. In conclusion, in the present study we show that emotion induction was associated with differential activation in both PFC and sympathetic nerve activity for fear and disgust. These differences were however less prominent during emotion regulation. We discuss the potential interpretation of our results and their implications regarding our understanding of negative emotion processing.

Effects of Personalized Cognitive Training with the Machine Learning Algorithm on Neural Efficiency in Healthy Younger Adults

To date, neural efficiency, an ability to economically utilize mental resources, has not been investigated after cognitive training. The purpose of this study was to provide customized cognitive training and confirm its effect on neural efficiency by investigating prefrontal cortex (PFC) activity using functional near-infrared spectroscopy (fNIRS). Before training, a prediction algorithm based on the PFC activity with logistic regression was used to predict the customized difficulty level with 86% accuracy by collecting data when subjects performed four kinds of cognitive tasks. In the next step, the intervention study was designed using one pre-posttest group. Thirteen healthy adults participated in the virtual reality (VR)-based spatial cognitive training, which was conducted four times a week for 30 min for three weeks with customized difficulty levels for each session. To measure its effect, the trail-making test (TMT) and hemodynamic responses were measured for executive function and PFC activity. During the training, VR-based spatial cognitive performance was improved, and hemodynamic values were gradually increased as the training sessions progressed. In addition, after the training, the performance on the trail-making task (TMT) demonstrated a statistically significant improvement, and there was a statistically significant decrease in the PFC activity. The improved performance on the TMT coupled with the decreased PFC activity could be regarded as training-induced neural efficiency. These results suggested that personalized cognitive training could be effective in improving executive function and neural efficiency.

A Graph-Based Nonlinear Dynamic Characterization of Motor Imagery Toward an Enhanced Hybrid BCI

Decoding neural responses from multimodal information sources, including electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), has the transformative potential to advance hybrid brain-computer interfaces (hBCIs). However, existing modest performance improvement of hBCIs might be attributed to the lack of computational frameworks that exploit complementary synergistic properties in multimodal features. This study proposes a multimodal data fusion framework to represent and decode synergistic multimodal motor imagery (MI) neural responses. We hypothesize that exploiting EEG nonlinear dynamics adds a new informative dimension to the commonly combined EEG-fNIRS features and will ultimately increase the synergy between EEG and fNIRS features toward an enhanced hBCI. The EEG nonlinear dynamics were quantified by extracting graph-based recurrence quantification analysis (RQA) features to complement the commonly used spectral features for an enhanced multimodal configuration when combined with fNIRS. The high-dimensional multimodal features were further given to a feature selection algorithm relying on the least absolute shrinkage and selection operator (LASSO) for fused feature selection. Linear support vector machine (SVM) was then used to evaluate the framework. The mean hybrid classification performance improved by up to 15% and 4% compared to the unimodal EEG and fNIRS, respectively. The proposed graph-based framework substantially increased the contribution of EEG features for hBCI classification from 28.16% up to 52.9% when introduced the nonlinear dynamics and improved the performance by approximately 2%. These findings suggest that graph-based nonlinear dynamics can increase the synergy between EEG and fNIRS features for an enhanced MI response representation that is not dominated by a single modality.

Portable wireless and fibreless fNIRS headband compares favorably to a stationary headcap-based system

This study’s purpose is to characterize the performance of a prototype functional near-infrared spectroscopy (fNIRS) headband meant to enable quick and easy measurements from the sensorimotor cortices. The fact that fNIRS is well-suited to ergonomic designs (i.e., their ability to be made wireless, their relative robustness to movement artifacts among other characteristics) has resulted in many recent examples of novel ergonomic fNIRS systems; however, the optical nature of fNIRS measurement presents an inherent challenge to measurement at areas of the brain underlying haired parts of the head. It is for this reason that the majority of ergonomic fNIRS systems that have been developed to date target the prefrontal cortex. In the present study we compared the performance of a novel, portable fNIRS headband compared with a stationary full headcap fNIRS system to measure sensorimotor activity during simple upper- and lower-extremity tasks, in healthy individuals >50 years of age. Both fNIRS systems demonstrated the expected pattern of hemodynamic activity in both upper- and lower-extremity tasks, and a comparison of the contrast-to-noise ratio between the two systems suggests the prototype fNIRS headband is non-inferior to a full head cap fNIRS system regarding the ability to detect a physiological response at the sensorimotor cortex during these tasks. These results suggest the use of a wireless and fibreless fNIRS design is feasible for measurement at the sensorimotor 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.

Neuroadaptive Training via fNIRS in Flight Simulators

Training to master a new skill often takes a lot of time, effort, and financial resources, particularly when the desired skill is complex, time sensitive, or high pressure where lives may be at risk. Professions such as aircraft pilots, surgeons, and other mission-critical operators that fall under this umbrella require extensive domain-specific dedicated training to enable learners to meet real-world demands. In this study, we describe a novel neuroadaptive training protocol to enhance learning speed and efficiency using a neuroimaging-based cognitive workload measurement system in a flight simulator. We used functional near-infrared spectroscopy (fNIRS), which is a wearable, mobile, non-invasive neuroimaging modality that can capture localized hemodynamic response and has been used extensively to monitor the anterior prefrontal cortex to estimate cognitive workload. The training protocol included four sessions over 2 weeks and utilized realistic piloting tasks with up to nine levels of difficulty. Learners started at the lowest level and their progress adapted based on either behavioral performance and fNIRS measures combined (neuroadaptive) or performance measures alone (control). Participants in the neuroadaptive group were found to have significantly more efficient training, reaching higher levels of difficulty or significantly improved performance depending on the task, and showing consistent patterns of hemodynamic-derived workload in the dorsolateral prefrontal cortex. The results of this study suggest that a neuroadaptive personalized training protocol using non-invasive neuroimaging is able to enhance learning of new tasks. Finally, we outline here potential avenues for further optimization of this fNIRS based neuroadaptive training approach. As fNIRS mobile neuroimaging is becoming more practical and accessible, the approaches developed here can be applied in the real world in scale.

Behavioral, cortical and autonomic effects of single-dose escitalopram on the induction and regulation of fear and disgust: Comparison with single-session psychological emotion regulation with reappraisal

INTRODUCTION

Adaptive and successful emotion regulation, the ability to flexibly exert voluntary control over emotional experience and the ensuing behavior, is vital for optimal daily functioning and good mental health. In clinical settings, pharmacological and psychological interventions are widely employed to modify pathological emotion processing and ameliorate its deleterious consequences.

METHODS

In this study, we investigated the acute effects of single-dose escitalopram on the induction and regulation of fear and disgust in healthy subjects. Furthermore, we compared these pharmacological effects with psychological emotion regulation that utilized a cognitive strategy with reappraisal. Emotion induction and regulation tasks were performed before and 4 h after ingestion of placebo or 10 mg escitalopram in a randomized, double-blind design. The International Affective Picture System (IAPS) was used as a source of images, with threat-related pictures selected for fear and disease and contamination-related pictures for disgust. Behavioral data, electrodermal activity (EDA), and functional near-infrared spectroscopy (fNIRS) recordings were collected.

RESULTS

Escitalopram significantly reduced emotion intensity for both fear and disgust during emotion induction, albeit with differing electrodermal and hemodynamic activity patterns for the two negative emotions. At rest, i.e., in the absence of emotive stimuli, escitalopram increased sympathetic activity during the fear but not during the disgust experiments. For both fear and disgust, emotion regulation with reappraisal was more effective in reducing emotion intensity compared to pharmacological intervention with escitalopram or placebo.

DISCUSSION

We concluded that emotion regulation with reappraisal and acute administration of escitalopram, but not placebo, reduce emotion intensity for both fear and disgust, with cognitive regulation being significantly more efficient compared to pharmacological regulation under the conditions of this study. Results from the fNIRS and EDA recordings support the concept of differential mechanisms of emotion regulation that could be emotion-specific.

Medial prefrontal brain activity correlates with emerging symptoms of anxiety and depression in late adolescence: A fNIRS study

The brain undergoes dramatic changes over the course of the adolescent years, and these developmental changes are implicated in the emergence of disorders that involve negative emotionality. Late adolescence might be the window within which brain networks manifest vulnerabilities to depressive and anxiety symptomology; particularly within the prefrontal cortex (PFC), which houses emotional control (dorsolateral) and emotional processing (medial) nodes. Given the comorbidity of depressive and anxious symptomology, it may be that the neural signature is similar for both within the developing PFC. In a sample of 67 adolescents (M = 15.97 years, SD = 1.36), we used functional near-infrared spectroscopy (fNIRS) to examine the neural signature of emergent anxiety and depressive symptoms among younger and older adolescents. We further examined the extent to which neural signatures of anxiety and depressive symptoms within the PFC were similar or different. Findings revealed that self-reported anxiety and depressive symptoms were highly correlated, and that the neural signatures of both within the PFC were similar, corresponding with the medial subregions of the PFC (i.e., those involved in evaluative processing). These findings were evident only in later adolescence, suggesting the possibility of a common vulnerability for anxiety and depressive disorders emerging around this developmental window.

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.

Working Memory Performance under a Negative Affect Is More Susceptible to Higher Cognitive Workloads with Different Neural Haemodynamic Correlates

The effect of stress on task performance is complex, too much or too little stress negatively affects performance and there exists an optimal level of stress to drive optimal performance. Task difficulty and external affective factors are distinct stressors that impact cognitive performance. Neuroimaging studies showed that mood affects working memory performance and the correlates are changes in haemodynamic activity in the prefrontal cortex (PFC). We investigate the interactive effects of affective states and working memory load (WML) on working memory task performance and haemodynamic activity using functional near-infrared spectroscopy (fNIRS) neuroimaging on the PFC of healthy participants. We seek to understand if haemodynamic responses could tell apart workload-related stress from situational stress arising from external affective distraction. We found that the haemodynamic changes towards affective stressor- and workload-related stress were more dominant in the medial and lateral PFC, respectively. Our study reveals distinct affective state-dependent modulations of haemodynamic activity with increasing WML in n-back tasks, which correlate with decreasing performance. The influence of a negative effect on performance is greater at higher WML, and haemodynamic activity showed evident changes in temporal, and both spatial and strength of activation differently with WML.

Examining the relationships among adolescent health behaviours, prefrontal function, and academic achievement using fNIRS

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Prior studies document effects of lifestyle behaviors on the brain and academics.

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Among adolescents we found that activity and eating both predict task performance.

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Activity also predicts functional activation in the right lateral dlPFC, but not grades.

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Substance use predicted worse grades but not brain-related mediators.

Several adolescent health behaviours have been hypothesized to improve academic performance via their beneficial impact on cognitive control and functional aspects of the prefrontal cortex (PFC). The primary objective of this study is to examine the association between lifestyle behaviours and academic performance in a sample of adolescents, and to examine the extent to which activity within the PFC and behavioural indices of inhibition may mediate this relationship. Sixty-seven adolescents underwent two study sessions five days apart. Sleep and physical activity were measured using wrist-mounted accelerometry; eating habits, substance use and academic achievement were measured by self-report. Prefrontal function was quantified by Multi-Source Interference Task (MSIT) performance, and task-related activity via functional near-infrared spectroscopy (fNIRS). Higher levels of physical activity predicted higher MSIT accuracy scores (β = .321, ρ = 0.019) as well as greater activation within the right dlPFC (b = .008, SE = .004, ρ = .0322). Frequency of fast-food consumption and substance use were negatively associated with MSIT accuracy scores (β = −0.307, ρ = .023) and Math grades (b = −3.702, SE = 1.563, ρ = .022), respectively. Overall, the results of this study highlight the importance of lifestyle behaviours as predictors of prefrontal function and academic achievement in youth.

Real-World fNIRS Brain Activity Measurements during Ashtanga Vinyasa Yoga

Functional near-infrared spectroscopy (fNIRS) is often praised for its portability and robustness towards motion artifacts. While an increasing body of fNIRS research in real-world environments is emerging, most fNIRS studies are still conducted in laboratories, and do not incorporate larger movements performed by participants. This study extends fNIRS applications in real-world environments by conducting a single-subject observational study of a yoga practice with considerable movement (Ashtanga Vinyasa Yoga) in a participant’s natural environment (their apartment). The results show differences in cognitive load (prefrontal cortex activation) when comparing technically complex postures to relatively simple ones, but also some contrasts with surprisingly little difference. This study explores the boundaries of real-world cognitive load measurements, and contributes to the empirical knowledge base of using fNIRS in realistic settings. To the best of our knowledge, this is the first demonstration of fNIRS brain imaging recorded during any moving yoga practice. Future work with fNIRS should take advantage of this by accomplishing studies with considerable real-world movement.

A New Statistical Approach for fNIRS Hyperscanning to Predict Brain Activity of Preschoolers' Using Teacher's

Hyperscanning studies using functional Near-Infrared Spectroscopy (fNIRS) have been performed to understand the neural mechanisms underlying human-human interactions. In this study, we propose a novel methodological approach that is developed for fNIRS multi-brain analysis. Our method uses support vector regression (SVR) to predict one brain activity time series using another as the predictor. We applied the proposed methodology to explore the teacher-student interaction, which plays a critical role in the formal learning process. In an illustrative application, we collected fNIRS data of the teacher and preschoolers’ dyads performing an interaction task. The teacher explained to the child how to add two numbers in the context of a game. The Prefrontal cortex and temporal-parietal junction of both teacher and student were recorded. A multivariate regression model was built for each channel in each dyad, with the student’s signal as the response variable and the teacher’s ones as the predictors. We compared the predictions of SVR with the conventional ordinary least square (OLS) predictor. The results predicted by the SVR model were statistically significantly correlated with the actual test data at least one channel-pair for all dyads. Overall, 29/90 channel-pairs across the five dyads (18 channels 5 dyads = 90 channel-pairs) presented significant signal predictions withthe SVR approach. The conventional OLS resulted in only 4 out of 90 valid predictions. These results demonstrated that the SVR could be used to perform channel-wise predictions across individuals, and the teachers’ cortical activity can be used to predict the student brain hemodynamic response.

The Role of Visual Features in Text-Based CAPTCHAs: An fNIRS Study for Usable Security

To mitigate dictionary attacks or similar undesirable automated attacks to information systems, developers mostly prefer using CAPTCHA challenges as Human Interactive Proofs (HIPs) to distinguish between human users and scripts. Appropriate use of CAPTCHA requires a setup that balances between robustness and usability during the design of a challenge. The previous research reveals that most usability studies have used accuracy and response time as measurement criteria for quantitative analysis. The present study aims at applying optical neuroimaging techniques for the analysis of CAPTCHA design. The functional Near-Infrared Spectroscopy technique was used to explore the hemodynamic responses in the prefrontal cortex elicited by CAPTCHA stimulus of varying types. The findings suggest that regions in the left and right dorsolateral and right dorsomedial prefrontal cortex respond to the degrees of line occlusion, rotation, and wave distortions present in a CAPTCHA. The systematic addition of the visual effects introduced nonlinear effects on the behavioral and prefrontal oxygenation measures, indicative of the emergence of Gestalt effects that might have influenced the perception of the overall CAPTCHA figure.

Muscle and cerebral oxygenation during cycling in chronic obstructive pulmonary disease: A scoping review

To synthesize evidence for prefrontal cortex (PFC), quadriceps, and respiratory muscle oxygenation using near-infrared spectroscopy (NIRS) during cycling in individuals with chronic obstructive pulmonary disease (COPD). A scoping review was performed searching databases (inception-August 2020): Ovid MEDLINE, EMBASE, Cochrane Systematic Reviews, Cochrane Central Register of Controlled Clinical Trials, CINAHL, SPORTDiscus and Pedro. The search focused on COPD, cycling, and NIRS outcomes. 29 studies (541 COPD participants) were included. Compared to healthy individuals (8 studies), COPD patients at lower cycling workloads had more rapid increases in vastus lateralis (VL) deoxygenated hemoglobin (HHb); lower increases in VL total hemoglobin (tHb) and blood flow; and lower muscle tissue saturation (StO₂). Heliox and bronchodilators were associated with smaller and slower increases in VL HHb. Heliox increased VL and intercostal blood flow compared to room air and supplemental oxygen in COPD patients (1 study). PFC oxygenated hemoglobin (O₂Hb) increased in COPD individuals during cycling in 5 of 8 studies. Individuals with COPD and heart failure demonstrated worse VL and PFC NIRS outcomes compared to patients with only COPD-higher or more rapid increase in VL HHb and no change or decrease in PFC O₂Hb. Individuals with COPD present with a mismatch between muscle oxygen delivery and utilization, characterized by more rapid increase in VL HHb, lower muscle O₂Hb and lower muscle StO₂. PFC O₂Hb increases or tends to increase in individuals with COPD during exercise, but this relationship warrants further investigation. NIRS can be used to identify key deoxygenation thresholds during exercise to inform PFC and muscle oxygenation.

Relationship Between Age and Cerebral Hemodynamic Response to Breath Holding: A Functional Near-Infrared Spectroscopy Study

Cerebrovascular reactivity (CVR) is routinely measured as a predictor of stroke in people with a high risk of ischemic attack. Neuroimaging techniques such as emission tomography, magnetic resonance imaging, and transcranial doppler are frequently used to measure CVR even though each technique has its limitations. Functional near-infrared spectroscopy (fNIRS), also based on the principle of neurovascular coupling, is relatively inexpensive, portable, and allows for the quantification of oxy- and deoxy-hemoglobin concentration changes at a high temporal resolution. This study examines the relationship between age and CVR using fNIRS in 45 young healthy adult participants aged 18-41 years (6 females, 26.64 ± 5.49 years) performing a simple breath holding task. Eighteen of the 45 participants were scanned again after a week to evaluate the feasibility of fNIRS in reliably measuring CVR. Results indicate (a) a negative relationship between age and hemodynamic measures of breath holding task in the sensorimotor cortex of 45 individuals and (b) widespread positive coactivation within medial sensorimotor regions and between medial sensorimotor regions with supplementary motor area and prefrontal cortex during breath holding with increasing age. The intraclass correlation coefficient (ICC) indicated only a low to fair/good reliability of the breath hold hemodynamic measures from sensorimotor and prefrontal cortices. However, the average hemodynamic response to breath holding from the two sessions were found to be temporally and spatially in correspondence. Future improvements in the sensitivity and reliability of fNIRS metrics could facilitate fNIRS-based assessment of cerebrovascular function as a potential clinical tool.

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.

Tinnitus and auditory cortex: using adapted functional near-infrared spectroscopy to measure resting-state functional connectivity

OBJECTIVE

Tinnitus, phantom sound perception, arises from aberrant brain activity within auditory cortex. In tinnitus animal models, auditory cortex neurons show increased spontaneous firing and neural synchrony. In humans, similar hyperactivation in auditory cortex has been displayed with functional near-infrared spectroscopy (fNIRS). Resting-state functional connectivity (RSFC) or increased connectivity between brain regions has also been shown in tinnitus using fNIRS. However, current fNIRS technology utilizes infrared (IR)-sources and IR-detectors placed on the scalp that restricts (~3 cm depth IR penetration) signal capture to outer cerebral cortex due to skin and skull bone. To overcome this limitation, in this proof of concept study, we adapted fNIRS probes to fit in the external auditory canal (EAC) to physically place IR-probes deeper within the skull thereby extracting neural signals from deeper auditory cortex.

METHODS

Twenty adults with tinnitus and 20 nontinnitus controls listened to periods of silence and broadband noise before and after 5 min of silence to calculate RSFC. Concurrent scalp probes over auditory cortex and an adapted probe placed in the right EAC were utilized.

RESULTS

For standard probes, left and right auditory cortex in tinnitus showed increased RSFC to each other and to other nonauditory cortices. Interestingly, adapted fNIRS probes showed trends toward increased RSFC.

CONCLUSION

While many areas for the adapted probes did not reach significance, these data using a highly innovative and newly created probe adapting fNIRS technology to the EAC substantiates our previously published data in human tinnitus and concurrently validates this technology as a useful and expanded brain imaging modality.

Examining Mental Workload in a Spatial Navigation Transfer Game via Functional near Infrared Spectroscopy

The goal of this study was to examine the effects of task-related variables, such as the difficulty level, problem scenario, and experiment week, on performance and mental workload of 27 healthy adult subjects during problem solving within the spatial navigation transfer (SNT) game. The study reports task performance measures such as total time spent on a task (TT) and reaction time (RT); neurophysiological measures involving the use of functional near-infrared spectroscopy (fNIRS); and a subjective rating scale for self-assessment of mental workload (NASA TLX) to test the related hypothesis. Several within-subject repeated-measures factorial ANOVA models were developed to test the main hypothesis. The results revealed a number of interaction effects for the dependent measures of TT, RT, fNIRS, and NASA TLX. The results showed (1) a decrease in TT and RT across the three levels of difficulty from Week 1 to Week 2; (2) an increase in TT and RT for high and medium cognitive load tasks as compared to low cognitive load tasks in both Week 1 and Week 2; (3) an overall increase in oxygenation from Week 1 to Week 2. These findings confirmed that both the behavioral performance and mental workload were sensitive to task manipulations.

The Role of the Prefrontal Cortex and Functional Connectivity during Maritime Operations: An fNIRS study

INTRODUCTION

Watchkeeping is a significant activity during maritime operations, and failures of sustained attention and decision-making can increase the likelihood of a collision.

METHODS

A study was conducted in a ship bridge simulator where 40 participants (20 experienced/20 inexperienced) performed: (1) a 20-min period of sustained attention to locate a target vessel and (2) a 10-min period of decision-making/action selection to perform an evasive maneuver. Half of the participants also performed an additional task of verbally reporting the position of their vessel. Activation of the prefrontal cortex (PFC) was captured via a 15-channel functional near-infrared spectroscopy (fNIRS) montage, and measures of functional connectivity were calculated frontal using graph-theoretic measures.

RESULTS

Neurovascular activation of right lateral area of the PFC decreased during sustained attention and increased during decision-making. The graph-theoretic analysis revealed that density declined during decision-making in comparison with the previous period of sustained attention, while local clustering declined during sustained attention and increased when participants prepared their evasive maneuver. A regression analysis revealed an association between network measures and behavioral outcomes, with respect to spotting the target vessel and making an evasive maneuver.

CONCLUSIONS

The right lateral area of the PFC is sensitive to watchkeeping and decision-making during operational performance. Graph-theoretic measures allow us to quantify patterns of functional connectivity and were predictive of safety-critical performance.

Tinnitus and auditory cortex; Using adapted functional near-infrared-spectroscopy to expand brain imaging in humans

Objectives

Phantom sound perception (tinnitus) may arise from altered brain activity within auditory cortex. Auditory cortex neurons in tinnitus animal models show increased spontaneous firing rates. This may be a core characteristic of tinnitus. Functional near‐infrared spectroscopy (fNIRS) has shown similar findings in human auditory cortex. Current fNIRS approaches with cap recordings are limited to ∼3 cm depth of signal penetration due to the skull thickness. To address this limitation, we present an innovative fNIRS approach via probes adapted to the external auditory canal. The adapted probes were placed deeper and closer to temporal lobe of the brain to bypass confining skull bone and improve neural recordings.

Methods

Twenty adults with tinnitus and 20 nontinnitus controls listened to periods of silence and broadband noise (BBN) during standard cap and adapted ear canal fNIRS neuroimaging. The evaluators were not blinded, but the protocol and postprocessing for the two groups were identical.

Results

Standard fNIRS measurements in participants with tinnitus revealed increased auditory cortex activity during silence that was suppressed during auditory stimulation with BBN. Conversely, controls displayed increased activation with noise but not during silence. Importantly, adapted ear canal fNIRs probes showed similar hemodynamic responses seen with cap probes in both tinnitus and controls.

Conclusions

In this proof of concept study, we have successfully fabricated, adapted, and utilized a novel fNIRS technology that replicates established findings from traditional cap fNIRS probes. This exciting new innovation, validated by replicating previous and current cap findings in auditory cortex, may have applications to future studies to investigate brain changes not only in tinnitus but in other pathologic states that may involve the temporal lobe and surrounding brain regions.

Level of Evidence

NA.

An fNIRS-Based Motor Imagery BCI for ALS: A Subject-Specific Data-Driven Approach

OBJECTIVE

Functional near-infrared spectroscopy (fNIRS) has recently gained momentum in research on motor-imagery (MI)-based brain-computer interfaces (BCIs). However, strikingly, most of the research effort is primarily devoted to enhancing fNIRS-based BCIs for healthy individuals. The ability of patients with amyotrophic lateral sclerosis (ALS), among the main BCI end-users to utilize fNIRS-based hemodynamic responses to efficiently control an MI-based BCI, has not yet been explored. This study aims to quantify subject-specific spatio-temporal characteristics of ALS patients' hemodynamic responses to MI tasks, and to investigate the feasibility of using these responses as a means of communication to control a binary BCI.

METHODS

Hemodynamic responses were recorded using fNIRS from eight patients with ALS while performing MI-Rest tasks. The generalized linear model (GLM) analysis was conducted to statistically estimate and evaluate individualized spatial activation. Selected channel sets were statistically optimized for classification. Subject-specific discriminative features, including a proposed data-driven estimated coefficient obtained from GLM, and optimized classification parameters were identified and used to further evaluate the performance using a linear support vector machine (SVM) classifier.

RESULTS

Inter-subject variations were observed in spatio-temporal characteristics of patients' hemodynamic responses. Using optimized classification parameters and feature sets, all subjects could successfully use their MI hemodynamic responses to control a BCI with an average classification accuracy of 85.4% ± 9.8%.

SIGNIFICANCE

Our results indicate a promising application of fNIRS-based MI hemodynamic responses to control a binary BCI by ALS patients. These findings highlight the importance of subject-specific data-driven approaches for identifying discriminative spatio-temporal characteristics for an optimized BCI performance.

Combining the intersubject correlation analysis and the multivariate distance matrix regression to evaluate associations between fNIRS signals and behavioral data from ecological experiments

The development of methods to analyze data acquired using functional near-infrared spectroscopy (fNIRS) in experiments similar to real-life situations is of great value in modern applied neuroscience. One of the most used methods to analyze fNIRS signals consists of the application of the general linear model on the observed hemodynamic signals. However, it implies limitations on the experimental design that must be constrained by triggers related to the stimuli protocols (such as block design or event related). In this work, a novel methodology is proposed to overcome such restrictions and allow more flexible protocols. The method combines the intersubject correlation analysis and the multivariate distance matrix regression to evaluate the brain-behavior relationship of subjects submitted to experiments with no trigger-based protocols. Its applicability is demonstrated throughout a naturalistic experiment about emotions conveyed by music. Thirty-two participants freely listened to instrumental excerpts from the operatic repertoire and reported the valences of the emotions conveyed by the musical segments. The method was able to find a statistically significant correlation between the subjects' fNIRS signals and valences of their emotional responses, for the excerpt that evoked the most negative valence. This result illustrates the potential of this approach as an alternative method to analyze fNIRS signals from experiments in which block design or task-related paradigms might not be suitable.

A Cross-Sectional Study on Central Sensitization and Autonomic Changes in Fibromyalgia

Fibromyalgia is a multi-symptomatic disorder characterized by generalized pain. The pathophysiology of fibromyalgia is supposedly an interplay between central nervous system hyper-responsiveness, autonomic dysfunction, and peripheral pain. In this cross-sectional study, the objective was to assess central sensitization and autonomic activity in patients with fibromyalgia compared with control. Fifty adults diagnosed with fibromyalgia by the modified American College of Rheumatology 2010 criteria and an equal number of age- and sex-matched controls participated in the study in an urban tertiary care hospital. Central sensitization was assessed by history and by evidence of increased prefrontal cortical activity as measured by cortical oxygenation using functional near-infrared spectroscopy. Autonomic activity was assessed by heart rate variability, electrodermal activity, and deep breathing test in three physiological states: rest, sympathetic stress (cold pressor test), and deep breathing. Mann–Whitney U-test, paired t-test, Wilcoxon test, and Friedman test with Bonferroni a priori were used to analyze the data. Cortical activity was significantly higher in the fibromyalgia group than control. There was no significant difference in autonomic activity between the fibromyalgia and control groups. In the fibromyalgia group, variable degrees of sympathetic hyperactivity and normal parasympathetic activity were observed. Central sensitization may be playing a primary role in the pathophysiology of generalized pain in fibromyalgia.

Methodological Approaches and Recommendations for Functional Near-Infrared Spectroscopy Applications in HF/E Research

OBJECTIVE

The objective of this study was to systematically document current methods and protocols employed when using functional near-infrared spectroscopy (fNIRS) techniques in human factors and ergonomics (HF/E) research and generate recommendations for conducting and reporting fNIRS findings in HF/E applications.

METHOD

A total of 1,687 articles were identified through Ovid-MEDLINE, PubMed, Web of Science, and Scopus databases, of which 37 articles were included in the review based on review inclusion/exclusion criteria.

RESULTS

A majority of the HF/E fNIRS investigations were found in transportation, both ground and aviation, and in assessing cognitive (e.g., workload, working memory) over physical constructs. There were large variations pertaining to data cleaning, processing, and analysis approaches across the studies that warrant standardization of methodological approaches. The review identified major challenges in transparency and reporting of important fNIRS data collection and analyses specifications that diminishes study replicability, introduces potential biases, and increases likelihood of inaccurate results. As such, results reported in existing fNIRS studies need to be cautiously approached.

CONCLUSION

To improve the quality of fNIRS investigations and/or to facilitate its adoption and integration in different HF/E applications, such as occupational ergonomics and rehabilitation, recommendations for fNIRS data collection, processing, analysis, and reporting are provided.

Neuroergonomic Assessment of Wheelchair Control Using Mobile fNIRS

For over two centuries, the wheelchair has been one of the most common assistive devices for individuals with locomotor impairments without many modifications. Wheelchair control is a complex motor task that increases both the physical and cognitive workload. New wheelchair interfaces, including Power Assisted devices, can further augment users by reducing the required physical effort, however little is known on the mental effort implications. In this study, we adopted a neuroergonomic approach utilizing mobile and wireless functional near infrared spectroscopy (fNIRS) based brain monitoring of physically active participants. 48 volunteers (30 novice and 18 experienced) self-propelled on a wheelchair with and without a PowerAssist interface in both simple and complex realistic environments. Results indicated that as expected, the complex more difficult environment led to lower task performance complemented by higher prefrontal cortex activity compared to the simple environment. The use of the PowerAssist feature had significantly lower brain activation compared to traditional manual control only for novices. Expertise led to a lower brain activation pattern within the middle frontal gyrus, complemented by performance metrics that involve lower cognitive workload. Results here confirm the potential of the Neuroergonomic approach and that direct neural activity measures can complement and enhance task performance metrics. We conclude that the cognitive workload benefits of PowerAssist are more directed to new users and difficult settings. The approach demonstrated here can be utilized in future studies to enable greater personalization and understanding of mobility interfaces within real-world dynamic environments.

Neuroergonomic Assessment of Hot Beverage Preparation and Consumption: An EEG and EDA Study

Neuroergonomics is an emerging field that investigates the human brain about behavioral performance in natural environments and everyday settings. This study investigated the body and brain activity correlates of a typical daily activity, hot beverage preparation, and consumption in a realistic office environment where participants performed natural daily tasks. Using wearable, battery operated and wireless Electroencephalogram (EEG) and Electrodermal activity (EDA) sensors, neural and physiological responses were measured in untethered, freely moving participants who prepared hot beverages using two different machines (a market leader and follower as determined by annual US sales). They later consumed the drinks they had prepared in three blocks. Emotional valence was estimated using frontal asymmetry in EEG alpha band power and emotional arousal was estimated from EDA tonic and phasic activity. Results from 26 participants showed that the market-leading coffee machine was more efficient to use based on self-reports, behavioral performance measures, and there were significant within-subject differences in valence between the two machine use. Moreover, the market leader user interface led to greater self-reported product preference, which was further supported by significant differences in measured arousal and valence (EDA and EEG, respectively) during coffee production and consumption. This is the first study that uses a multimodal and comprehensive assessment of coffee machine use and beverage consumption in a naturalistic work environment. Approaches described in this study can be adapted in the future to other task-specific machine usability and consumer neuroscience studies.

Functional Near-Infrared Spectroscopy for the Classification of Motor-Related Brain Activity on the Sensor-Level

Sensor-level human brain activity is studied during real and imaginary motor execution using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation spatial dynamics exhibit pronounced hemispheric lateralization when performing motor tasks with the left and right hands. This fact allowed us to reveal biomarkers of hemodynamical response of the motor cortex on the motor execution, and use them for designing a sensing method for classification of the type of movement. The recognition accuracy of real movements is close to 100%, while the classification accuracy of imaginary movements is lower but quite high (at the level of 90%). The advantage of the proposed method is its ability to classify real and imaginary movements with sufficiently high efficiency without the need for recalculating parameters. The proposed system can serve as a sensor of motor activity to be used for neurorehabilitation after severe brain injuries, including traumas and strokes.

A Novel Application of Levenshtein Distance for Assessment of High-Level Motor Planning Underlying Performance During Learning of Complex Motor Sequences

Few studies have examined high-level motor plans underlying cognitive-motor performance during practice of complex action sequences. These investigations have assessed performance through fairly simple metrics without examining how practice affects the structures of action sequences. By adapting the Levenshtein distance (LD) method to the motor domain, we propose a computational approach to accurately capture performance dynamics during practice of action sequences. Practice performance dynamics were assessed by computing the LD based on the number of insertions, deletions, and substitutions of actions needed to transform any sequence into a reference sequence (having a minimal number of actions to complete the task). Also, combining LD-based performance with mental workload metrics allowed assessment of cognitive-motor efficiency dynamics. This approach was tested on the Tower of Hanoi task. The findings revealed that throughout practice this method could capture: i) action sequence performance improvements as indexed by a reduced LD (decrease of insertions and substitutions), ii) structural modifications of the high-level plans, iii) an attenuation of mental workload, and iv) enhanced cognitive-motor efficiency. This effort complements prior work examining the practice of complex action sequences in healthy adults and has potential for probing cognitive-motor impairment in clinical populations as well as the development/assessment of cognitive robotic controllers.

Frontal brain activity in individuals at risk for schizophrenic psychosis and bipolar disorder during the emotional Stroop task - an fNIRS study

OBJECTIVES

The emotional Stroop effect is defined as increased reaction times to emotional stimuli compared to neutral ones. It has been often reported in the literature, on both behavioral and neurophysiological level. The goal of this study was to investigate the frontal brain activation in individuals at risk for schizophrenic psychosis and bipolar disorder during an emotional Stroop task. We expected to observe decreased activation in the at-risk individuals compared to the healthy controls.

METHODS

Individuals at high risk for psychosis (HR), at ultra-high risk for psychosis (UHR), at risk for bipolar disorder (BIP) and healthy controls (HC) performed an emotional Stroop task, which included positively, negatively and neutrally valenced words. Functional near-infrared spectroscopy (fNIRS) was used to measure levels of oxygenated hemoglobin (O2Hb) representing brain activity in the dorsolateral prefrontal and frontotemporal cortex.

RESULTS

Results showed significantly decreased levels of O2Hb in the right dorsolateral prefrontal cortex (DLPFC) in the HR and UHR groups compared to the HC, indicating lower activity. Even though the decrease was independent from the valence of the words, it was the most visible for the negative ones. Moreover, significantly lower O2Hb levels in the frontotemporal cortex (FTC) were observed in all at risk groups compared to the HC.

CONCLUSIONS

Lower activity in the FTC in groups at risk for psychosis and bipolar disorder reflects unspecific dysfunctions. Decreased activity in the DLPFC in the HR and UHR groups indicates that hypofrontality can be found already in individuals at risk for schizophrenic psychosis.

Multimodal Affective State Assessment Using fNIRS + EEG and Spontaneous Facial Expression

Human facial expressions are regarded as a vital indicator of one's emotion and intention, and even reveal the state of health and wellbeing. Emotional states have been associated with information processing within and between subcortical and cortical areas of the brain, including the amygdala and prefrontal cortex. In this study, we evaluated the relationship between spontaneous human facial affective expressions and multi-modal brain activity measured via non-invasive and wearable sensors: functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) signals. The affective states of twelve male participants detected via fNIRS, EEG, and spontaneous facial expressions were investigated in response to both image-content stimuli and video-content stimuli. We propose a method to jointly evaluate fNIRS and EEG signals for affective state detection (emotional valence as positive or negative). Experimental results reveal a strong correlation between spontaneous facial affective expressions and the perceived emotional valence. Moreover, the affective states were estimated by the fNIRS, EEG, and fNIRS + EEG brain activity measurements. We show that the proposed EEG + fNIRS hybrid method outperforms fNIRS-only and EEG-only approaches. Our findings indicate that the dynamic (video-content based) stimuli triggers a larger affective response than the static (image-content based) stimuli. These findings also suggest joint utilization of facial expression and wearable neuroimaging, fNIRS, and EEG, for improved emotional analysis and affective brain-computer interface applications.