Load-dependent relationships between frontal fNIRS activity and performance: A data-driven PLS approach

Cardiac vagal activity changes moderated the association of cognitive and cerebral hemodynamic variations in the prefrontal cortex

Phasic cardiac vagal activity (CVA), reflecting ongoing, moment-to-moment psychophysiological adaptations to environmental changes, can serve as a predictor of individual difference in executive function, particularly executive performance. However, the relationship between phasic CVA and executive function demands requires further validation because of previous inconsistent findings. Moreover, it remains unclear what types of phasic changes of CVA may be adaptive in response to heightened executive demands. This study used the standard N-back task to induce different levels of working memory (WM) load and combined functional Near-Infrared Spectroscopy (fNIRS) with a multipurpose polygraph to investigate the variations of CVA and its interactions with cognitive and prefrontal responses as executive demands increased in fifty-two healthy young subjects. Our results showed phasic decreases in CVA as WM load increased (t (51) = -3.758, p < 0.001, Cohen's d = 0.526). Furthermore, phasic changes of CVA elicited by increased executive demands moderated the association of cognitive and cerebral hemodynamic variations in the prefrontal cortex (B = 0.038, SE = 0.014, p < 0.05). Specifically, as executive demands increased, individuals with larger phasic CVA withdrawal showed a positive relationship between cognitive and hemodynamic variations in the prefrontal cortex (β = 0.281, p = 0.031). No such significant relationship was observed in individuals with smaller phasic CVA withdrawal. The current findings demonstrate a decrease in CVA with increasing executive demands and provide empirical support for the notion that a larger phasic CVA withdrawal can be considered adaptive in situations requiring high executive function demands.

A multimodal dataset for investigating working memory in presence of music: a pilot study

Introduction

Decoding an individual's hidden brain states in responses to musical stimuli under various cognitive loads can unleash the potential of developing a non-invasive closed-loop brain-machine interface (CLBMI). To perform a pilot study and investigate the brain response in the context of CLBMI, we collect multimodal physiological signals and behavioral data within the working memory experiment in the presence of personalized musical stimuli.

Methods

Participants perform a working memory experiment called the n-back task in the presence of calming music and exciting music. Utilizing the skin conductance signal and behavioral data, we decode the brain's cognitive arousal and performance states, respectively. We determine the association of oxygenated hemoglobin (HbO) data with performance state. Furthermore, we evaluate the total hemoglobin (HbT) signal energy over each music session.

Results

A relatively low arousal variation was observed with respect to task difficulty, while the arousal baseline changes considerably with respect to the type of music. Overall, the performance index is enhanced within the exciting session. The highest positive correlation between the HbO concentration and performance was observed within the higher cognitive loads (3-back task) for all of the participants. Also, the HbT signal energy peak occurs within the exciting session.

Discussion

Findings may underline the potential of using music as an intervention to regulate the brain cognitive states. Additionally, the experiment provides a diverse array of data encompassing multiple physiological signals that can be used in the brain state decoder paradigm to shed light on the human-in-the-loop experiments and understand the network-level mechanisms of auditory stimulation.

Evaluation of the learning state of online video courses based on functional near infrared spectroscopy

Studying brain activity during online learning will help to improve research on brain function based on real online learning situations, and will also promote the scientific evaluation of online education. Existing research focuses on enhancing learning effects and evaluating the learning process associated with online learning from an attentional perspective. We aimed to comparatively analyze the differences in prefrontal cortex (PFC) activity during resting, studying, and question-answering states in online learning and to establish a classification model of the learning state that would be useful for the evaluation of online learning. Nineteen university students performed experiments using functional near-infrared spectroscopy (fNIRS) to monitor the prefrontal lobes. The resting time at the start of the experiment was the resting state, watching 13 videos was the learning state, and answering questions after the video was the answering state. Differences in student activity between these three states were analyzed using a general linear model, 1s fNIRS data clips, and features, including averages from the three states, were classified using machine learning classification models such as support vector machines and k-nearest neighbor. The results show that the resting state is more active than learning in the dorsolateral prefrontal cortex, while answering questions is the most active of the three states in the entire PFC, and k-nearest neighbor achieves 98.5% classification accuracy for 1s fNIRS data. The results clarify the differences in PFC activity between resting, learning, and question-answering states in online learning scenarios and support the feasibility of developing an online learning assessment system using fNIRS and machine learning techniques.

Brain activation during the N-back working memory task in individuals with spinal cord injury: a functional near-infrared spectroscopy study

Cognitive impairments have frequently been reported in individuals with spinal cord injury (SCI) across different domains such as working memory, attention, and executive function. The mechanism of cognitive impairment after SCI is not well understood due to the heterogeneity of SCI sample populations, and may possibly be due to factors such as cardiovascular dysfunction, concomitant traumatic brain injury (TBI), hypoxia, sleep disorders, and body temperature dysregulation. In this study, we implement the Neuropsychiatric Unit Cognitive Assessment Tool (NUCOG) to assess cognitive differences between individuals with SCI and age-matched able-bodied (AB) controls. We then use an N-back working memory task and functional near-infrared spectroscopy (fNIRS) to elucidate the neurovascular correlates of cognitive function in individuals with SCI. We observed significant differences between the SCI and AB groups on measures of executive function on the NUCOG test. On the N-back task, across the three levels of difficulty: 0-back, 2-back, and 3-back, no significant differences were observed between the SCI and AB group; however, both groups performed worse as the level of difficulty increased. Although there were no significant differences in N-back performance scores between the two groups, functional brain hemodynamic activity differences were observed between the SCI and AB groups, with the SCI group exhibiting higher maximum oxygenated hemoglobin concentration in the right inferior parietal lobe. These findings support the use of fNIRS to study cognitive function in individuals with SCI and may provide a useful tool during rehabilitation to obtain quantitative functional brain activity metrics.

Validation of a mobile fNIRS device for measuring working memory load in the prefrontal cortex

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that measures cortical blood flow to infer neural activation. Traditionally limited to laboratory settings due to high costs and complex operation, recent advancements have introduced mobile fNIRS devices, significantly broadening the scope of potential research participants. This study validates the use of the Mendi, a two-channel mobile fNIRS system, for measuring prefrontal oxyhemoglobin concentration changes during an n-back task. We manipulated task difficulty through different n-back levels (one-back versus three-back), revealing increased oxyhemoglobin concentrations in the prefrontal cortex during the more demanding three-back task compared to the one-back task. This finding demonstrates the Mendi's ability to distinguish between low and high cognitive task loads. Behavioural data, showing a decrease in accuracy under high load conditions, further corroborates these neuroimaging findings. Our study validates the Mendi mobile fNIRS system as an effective tool for assessing working memory load and underscores its potential in enhancing neuroscientific research accessibility. The user-friendly and cost-effective nature of mobile fNIRS systems like the Mendi opens up neuroscientific research to a diverse set of participants, enabling the investigation of neural processes in real-world environments across a variety of demographic groups.

Distinct age-related brain activity patterns in the prefrontal cortex when increasing cognitive load: A functional near-infrared spectroscopy study

Researchers have long observed distinct brain activity patterns in older adults compared with younger adults that correlate with cognitive performance. Mainly, older adults tend to show over-recruitment of bilateral brain regions during lower task loads and improved performance interpreted as compensation, but not observed at higher loads. However, there are discrepancies about whether increases in activity are compensatory and whether older adults can show compensation at higher loads. Our aim was to examine age-related differences in prefrontal cortex (PFC) activity and cognitive performance using functional near-infrared spectroscopy (fNIRS) during single and dual N-back tasks. Twenty-seven young adults (18-27 years) and 31 older adults (64-84 yrs) took part in the study. We used a robust fNIRS data methodology consisting of channel and region of interest analyses. Results showed differences in performance between task load conditions and age-related differences in reaction times but no age-group effects for accuracy. Older adults exhibited more bilateral PFC activation compared with young adults across all tasks and showed increases in brain activity in high compared to low load conditions. Our findings further support previous reports showing that older adults use compensatory recruitment of additional brain regions in PFC to maintain cognitive performance but go against the notion that such compensation is not present at higher cognitive loads. Additionally, our results indicate that fNIRS is a sensitive tool that can characterize adaptive cortical changes in healthy aging.

Friend or foe: classifying collaborative interactions using fNIRS

To succeed, effective teams depend on both cooperative and competitive interactions between individual teammates. Depending on the context, cooperation and competition can amplify or neutralize a team's problem solving ability. Therefore, to assess successful collaborative problem solving, it is first crucial to distinguish competitive from cooperative interactions. We investigate the feasibility of using lightweight brain sensors to distinguish cooperative from competitive interactions in pairs of participants (N=84) playing a decision-making game involving uncertain outcomes. We measured brain activity using functional near-infrared spectroscopy (fNIRS) from social, motor, and executive areas during game play alone and in competition or cooperation with another participant. To distinguish competitive, cooperative, and alone conditions, we then trained support vector classifiers using combinations of features extracted from fNIRS data. We find that features from social areas of the brain outperform other features for discriminating competitive, cooperative, and alone conditions in cross-validation. Comparing the competitive and alone conditions, social features yield a 5% improvement over motor and executive features. Social features show promise as means of distinguishing competitive and cooperative environments in problem solving settings. Using fNIRS data provides a real-time measure of subjective experience in an ecologically valid environment. These results have the potential to inform intelligent team monitoring to provide better real-time feedback and improve team outcomes in naturalistic settings.

Individualized Mental Fatigue Does Not Impact Neuromuscular Function and Exercise Performance

INTRODUCTION

Recent studies have questioned previous empirical evidence that mental fatigue negatively impacts physical performance. The purpose of this study was to investigate the critical role of individual differences in mental fatigue susceptibility by analyzing the neurophysiological and physical responses to an individualized mental fatigue task.

METHODS

In a preregistered ( https://osf.io/xc8nr/ ), randomized, within-participant design experiment, 22 recreational athletes completed a time to failure test at 80% of their peak power output under mental fatigue (individual mental effort) or control (low mental effort). Before and after the cognitive tasks, subjective feeling of mental fatigue, neuromuscular function of the knee extensors, and corticospinal excitability were measured. Sequential Bayesian analysis until it reached strong evidence in favor of the alternative hypothesis (BF 10 > 6) or the null hypothesis (BF 10 < 1/6) were conducted.

RESULTS

The individualized mental effort task resulted in a higher subjective feeling of mental fatigue in the mental fatigue condition (0.50 (95% confidence interval (CI), 0.39-0.62)) arbitrary units compared with control (0.19 (95% CI, 0.06-0.339)) arbitrary unit. However, exercise performance was similar in both conditions (control: 410 (95% CI, 357-463) s vs mental fatigue: 422 (95% CI, 367-477) s, BF 10 = 0.15). Likewise, mental fatigue did not impair knee extensor maximal force-generating capacity (BF 10 = 0.928) and did not change the extent of fatigability or its origin after the cycling exercise.

CONCLUSIONS

There is no evidence that mental fatigue adversely affects neuromuscular function or physical exercise; even if mental fatigue is individualized, computerized tasks seem not to affect physical performance.

Neural correlates of valence-dependent belief and value updating during uncertainty reduction: An fNIRS study

Selective use of new information is crucial for adaptive decision-making. Combining a gamble bidding task with assessing cortical responses using functional near-infrared spectroscopy (fNIRS), we investigated potential effects of information valence on behavioral and neural processes of belief and value updating during uncertainty reduction in young adults. By modeling changes in the participants' expressed subjective values using a Bayesian model, we dissociated processes of (i) updating beliefs about statistical properties of the gamble, (ii) updating values of a gamble based on new information about its winning probabilities, as well as (iii) expectancy violation. The results showed that participants used new information to update their beliefs and values about the gambles in a quasi-optimal manner, as reflected in the selective updating only in situations with reducible uncertainty. Furthermore, their updating was valence-dependent: information indicating an increase in winning probability was underweighted, whereas information about a decrease in winning probability was updated in good agreement with predictions of the Bayesian decision theory. Results of model-based and moderation analyses showed that this valence-dependent asymmetry was associated with a distinct contribution of expectancy violation, besides belief updating, to value updating after experiencing new positive information regarding winning probabilities. In line with the behavioral results, we replicated previous findings showing involvements of frontoparietal brain regions in the different components of updating. Furthermore, this study provided novel results suggesting a valence-dependent recruitment of brain regions. Individuals with stronger oxyhemoglobin responses during value updating was more in line with predictions of the Bayesian model while integrating new information that indicates an increase in winning probability. Taken together, this study provides first results showing expectancy violation as a contributing factor to sub-optimal valence-dependent updating during uncertainty reduction and suggests limitations of normative Bayesian decision theory.

Cortical activation of neuromuscular electrical stimulation synchronized mirror neuron rehabilitation strategies: an fNIRS study

Background

The mirror neuron system (MNS) plays a key role in the neural mechanism underlying motor learning and neural plasticity. Action observation (AO), action execution (AE), and a combination of both, known as action imitation (AI), are the most commonly used rehabilitation strategies based on MNS. It is possible to enhance the cortical activation area and amplitude by combining traditional neuromuscular electrical stimulation (NMES) with other top-down and active rehabilitation strategies based on the MNS theory.

Objective

This study aimed to explore the cortical activation patterns induced by NMES synchronized with rehabilitation strategies based on MNS, namely NMES+AO, NMES+AE, and NMES+AI. In addition, the study aimed to assess the feasibility of these three novel rehabilitative treatments in order to provide insights and evidence for the design, implementation, and application of brain-computer interfaces.

Methods

A total of 70 healthy adults were recruited from July 2022 to February 2023, and 66 of them were finally included in the analysis. The cortical activation patterns during NMES+AO, NMES+AE, and NMES+AI were detected using the functional Near-Infrared Spectroscopy (fNIRS) technique. The action to be observed, executed, or imitated was right wrist and hand extension, and two square-shaped NMES electrodes were placed on the right extensor digitorum communis. A block design was adopted to evaluate the activation intensity of the left MNS brain regions.

Results

General linear model results showed that compared with the control condition, the number of channels significantly activated (PFDR < 0.05) in the NMES+AO, NMES+AE, and NMES+AI conditions were 3, 9, and 9, respectively. Region of interest (ROI) analysis showed that 2 ROIs were significantly activated (PFDR < 0.05) in the NMES+AO condition, including BA6 and BA44; 5 ROIs were significantly activated in the NMES+AE condition, including BA6, BA40, BA44, BA45, and BA46; and 6 ROIs were significantly activated in the NMES+AI condition, including BA6, BA7, BA40, BA44, BA45, and BA46.

Conclusion

The MNS was activated during neuromuscular electrical stimulation combined with an AO, AE, and AI intervention. The synchronous application of NMES and mirror neuron rehabilitation strategies is feasible in clinical rehabilitation. The fNIRS signal patterns observed in this study could be used to develop brain-computer interface and neurofeedback therapy rehabilitation devices.

You can touch this! Brain correlates of aesthetic processing of active fingertip exploration of material surfaces

The haptic exploration and aesthetic processing of all kinds of materials' surfaces are part of everyday life. In the present study, functional near-infrared spectroscopy (fNIRS) was used to investigate the brain correlates of active fingertip exploration of material surfaces and subsequent aesthetic judgments of their pleasantness (feels good or bad?). In absence of other sensory modalities, individuals (n = 21) performed lateral movements on a total of 48 textile and wood surfaces varying in terms of their roughness. Behavioral results confirmed the influence of the stimuli's roughness on aesthetic judgments, with smoother textures being rated as feeling better than rough textures. At the neural level, fNIRS activation results revealed an overall increased engagement of the contralateral sensorimotor areas as well as left prefrontal areas. Moreover, the perceived pleasantness modulated specific activations of left prefrontal areas with increasing pleasantness showing greater activations of these regions. Interestingly, this positive relationship between the individual aesthetic judgments and brain activity was most pronounced for smooth woods. These results demonstrate that positively valenced touch by actively exploring material surfaces is linked to left prefrontal activity and extend previous findings of affective touch underlying passive movements on hairy skin. We suggest that fNIRS can be a valuable tool to provide new insights in the field of experimental aesthetics.

Transcranial direct current stimulation over the right dorsolateral prefrontal cortex increases oxyhemoglobin concentration and cognitive performance dependent on cognitive load

Transcranial direct current stimulation (tDCS) has been explored as a potential method for cognitive enhancement. tDCS may induce a cascade of neurophysiological changes including alterations in cerebral oxygenation. However, the effects of tDCS on the cognitive-cerebral oxygenation interaction remains unclear. Further, oxygenation variability across individuals remains minimally controlled for. The purpose of this sham-controlled study was to test the effects of anodal tDCS over the right dorsolateral prefrontal cortex (DLPFC) on the interaction between working memory and cerebral oxygenation while controlling for individual oxygenation variability. Thirty-three adults received resting-state functional near-infrared spectroscopy (fNIRS) recordings over bilateral prefrontal cortices. Following this, working memory was tested using a Toulouse n-back task concurrently paired with fNIRS, with measurements taken before and after 20 min of anodal or sham tDCS at 1.5 mA. With individual oxygenation controlled for, anodal tDCS was found to increase the oxyhemoglobin concentration over the right DLPFC during the 2-back (q = .015) and 3-back (q = .008) conditions. Additionally, anodal tDCS was found to improve accuracy during the 3-back task by 13.4 % (p = .028) and decrease latency by 250 ms (p = .013). The increase in oxyhemoglobin was strongly correlated with increases in accuracy (p = .041) and decreases in latency during the 3-back span (p = .017). Taken together, anodal tDCS over the right DLPFC was found to regionally increase oxyhemoglobin concentrations and improve working memory performance in higher cognitive load conditions.

Shedding light on functional near-infrared spectroscopy and open science practices

Open science practices work to increase methodological rigor, transparency, and replicability of published findings. We aim to reflect on what the functional near-infrared spectroscopy (fNIRS) community has done to promote open science practices in fNIRS research and set goals to accomplish over the next 10 years.

Changes in task performance and frontal cortex activation within and over sessions during the n-back task

The n-back task is a popular paradigm for studying neurocognitive processing at varying working memory loads. Although much is known about the effects of load on behavior and neural activation during n-back performance, the temporal dynamics of such effects remain unclear. Here, we investigated the within- and between-session stability and consistency of task performance and frontal cortical activation during the n-back task using functional near-infrared spectroscopy (fNIRS). Forty healthy young adults performed the 1-back and 3-back conditions three times per condition. They then undertook identical retest sessions 3 weeks later (M = 21.2 days, SD = 0.9). Over the course of the task, activation in the participants' frontopolar, dorsomedial, dorsolateral, ventrolateral, and posterolateral frontal cortices was measured with fNIRS. We found significantly improved working memory performance (difference between 1-back and 3-back accuracies) over time both within and between sessions. All accuracy and reaction time measures exhibited good to excellent consistency within and across sessions. Additionally, changes in frontal oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) concentration were maintained over time across timescales, except that load-dependent (3-back > 1-back) HbO changes, particularly in the ventrolateral PFC, diminished over separate sessions. The consistency of fNIRS measures varied greatly, with changes in 3-back dorsolateral and ventrolateral HbO demonstrating fair-to-good consistency both within and between sessions. Overall, this study clarified the temporal dynamics of task performance and frontal activation during the n-back task. The findings revealed the neural mechanisms underlying the change in n-back task performance over time and have practical implications for future n-back research.

Functional near-infrared spectroscopy measures of neural activity in children with and without developmental language disorder during a working memory task

INTRODUCTION

Children with developmental language disorder (DLD) exhibit cognitive deficits that interfere with their ability to learn language. Little is known about the functional neuroanatomical differences between children developing typically (TD) and children with DLD.

METHODS

Using functional near-infrared spectroscopy, we recorded oxygenated hemoglobin (O₂ hb) concentration values associated with neural activity in children with and without DLD during an auditory N-back task that included 0-back, 1-back, and 2-back conditions. Analyses focused on the left dorsolateral prefrontal cortex (DLPFC) and left inferior parietal lobule (IPL). Multilevel models were constructed with accuracy, response time, and O₂ hb as outcome measures, with 0-back outcomes as fixed effects to control for sustained attention.

RESULTS

Children with DLD were significantly less accurate than their TD peers at both the 1-back and 2-back tasks, and they demonstrated slower response times during 2-back. In addition, children in the TD group demonstrated significantly greater sensitivity to increased task difficulty, showing increased O₂ hb to the IPL during 1-back and to the DLPFC during the 2-back, whereas the DLD group did not. A secondary analysis revealed that higher O₂ hb in the DLPFC predicted better task accuracy across groups.

CONCLUSION

When task difficulty increased, children with DLD failed to recruit the DLPFC for monitoring information and the IPL for processing information. Reduced memory capacity and reduced engagement likely contribute to the language learning difficulties of children with DLD.

Hotspots and trends in fNIRS disease research: A bibliometric analysis

Objective

To summarize the general information and hotspots of functional near-infrared spectroscopy (fNIRS)-based clinical disease research over the past 10 years and provide some references for future research.

Methods

The related literature published between 1 January 2011 and 31 January 2022 was retrieved from the Web of Science core database (WoS). Bibliometric visualization analysis of countries/regions, institutions, authors, journals, keywords and references were conducted by using CiteSpace 6.1.R3.

Results

A total of 467 articles were included, and the annual number of articles published over nearly a decade showed an upward trend year-by-year. These articles mainly come from 39 countries/regions and 280 institutions. The representative country and institution were the USA and the University of Tubingen. We identified 266 authors, among which Andreas J Fallgatter and Ann-Christine Ehlis were the influential authors. Neuroimage was the most co-cited journal. The major topics in fNIRS disease research included activation, prefrontal cortex, working memory, cortex, and functional magnetic resonance imaging (fMRI). In recent years, the Frontier topics were executive function, functional connectivity, performance, diagnosis, Alzheimer's disease, children, and adolescents. Based on the burst of co-cited references, gait research has received much attention.

Conclusion

This study conducted a comprehensive, objective, and visual analysis of publications, and revealed the status of relevant studies, hot topics, and trends concerning fNIRS disease research from 2011 to 2022. It is hoped that this work would help researchers to identify new perspectives on potential collaborators, important topics, and research Frontiers.

Programming ability prediction: Applying an attention-based convolutional neural network to functional near-infrared spectroscopy analyses of working memory

Although theoretical studies have suggested that working-memory capacity is crucial for academic achievement, few empirical studies have directly investigated the relationship between working-memory capacity and programming ability, and no direct neural evidence has been reported to support this relationship. The present study aimed to fill this gap in the literature. Using a between-subject design, 17 programming novices and 18 advanced students performed an n-back working-memory task. During the experiment, their prefrontal hemodynamic responses were measured using a 48-channel functional near-infrared spectroscopy (fNIRS) device. The results indicated that the advanced students had a higher working-memory capacity than the novice students, validating the relationship between programming ability and working memory. The analysis results also showed that the hemodynamic responses in the prefrontal cortex can be used to discriminate between novices and advanced students. Additionally, we utilized an attention-based convolutional neural network to analyze the spatial domains of the fNIRS signals and demonstrated that the left prefrontal cortex was more important than other brain regions for programming ability prediction. This result was consistent with the results of statistical analysis, which in turn improved the interpretability of neural networks.

Cortical Activation of Swallowing Using fNIRS: A Proof of Concept Study with Healthy Adults

The purpose of this study was to determine whether functional near-infrared spectroscopy (fNIRS) could reliably identify cortical activation patterns as healthy adults engaged in single sip and continuous swallowing tasks. Thirty-three right-handed adults completed two functional swallowing tasks, one control jaw movement task, and one rest task while being imaged with fNIRS. Swallowing tasks included a single sip of 5 mL of water via syringe and continuous straw drinking. fNIRS patches for acquisition of neuroimaging data were placed parallel over left and right hemispheres. Stimuli presentation was controlled with set time intervals and audio instructions. Using a series of linear mixed effect models, results demonstrated clear cortical activation patterns during swallowing. The continuous swallowing task demonstrated significant differences in blood oxygenation and deoxygenation concentration values across nearly all regions examined, but most notably M1 in both hemispheres. Of note is that there were areas of greater activation, particularly on the right hemisphere, when comparing the single sip swallow to the jaw movement control and rest tasks. Results from the current study support the use of fNIRS during investigation of swallowing. The utilization of healthy adults as a method for acquiring normative data is vital for comparison purposes when investigating individuals with disorders, but also in the development of rehabilitation techniques. Identifying activation areas that pertain to swallowing will have important implications for individuals requiring dysphagia therapy.

Scale invariance in fNIRS as a measurement of cognitive load

Scale invariant neural dynamics are a relatively new but effective means of measuring changes in brain states as a result of varied cognitive load and task difficulty. This study tests whether scale invariance (as measured by the Hurst exponent, H) can be used with functional near-infrared spectroscopy (fNIRS) to quantify cognitive load, paving the way for scale-invariance to be measured in a variety of real-world settings. We analyzed H extracted from the fNIRS time series while participants completed an N-back working memory task. Consistent with what has been demonstrated in fMRI, the current results showed that scale-invariance analysis significantly differentiated between task and rest periods as calculated from both oxy- (HbO) and deoxy-hemoglobin (HbR) concentration changes. Results from both channel-averaged H and a multivariate partial least squares approach (Task PLS) demonstrated higher H during the 1-back task than the 2-back task. These results were stronger for H derived from HbR than from HbO. This suggests that scale-free brain states are a robust signature of cognitive load and not limited by the specific neuroimaging modality employed. Further, as fNIRS is relatively portable and robust to motion-related artifacts, these preliminary results shed light on the promising future of measuring cognitive load in real life settings.

Investigating mental workload-induced changes in cortical oxygenation and frontal theta activity during simulated flights

Monitoring pilots' cognitive states becomes increasingly important in aviation. Physiological measurement can detect increased mental workload (MWL) even before performance declines. Yet, changes in MWL are rarely varied systematically and few studies control for confounding effects of other cognitive states. The present study targets these shortcomings by analysing the effects of stepwise increased MWL on cortical activation, while controlling for mental fatigue (MF). 35 participants conducted a simulated flight with an incorporated adapted n-back and monitoring task. We recorded cortical activation with concurrent EEG and fNIRS measurement, performance, self-reported MWL and MF. Our results show the successful manipulation of MWL without confounding effects of MF. Higher task difficulty elicited higher subjective MWL ratings, performance decline, higher frontal theta activity and reduced frontal deoxyhaemoglobin (Hbr) concentration. Using both EEG and fNIRS, we could discriminate all induced MWL levels. fNIRS was more sensitive to tasks with low difficulty, and EEG to tasks with high difficulty. Our findings further suggest a plateau effect for high MWL that could present an upper boundary to individual cognitive capacity. Our results highlight the benefits of physiological measurement in aviation, both for assessment of cognitive states and as a data source for adaptive assistance systems.

Classification of Game Demand and the Presence of Experimental Pain Using Functional Near-Infrared Spectroscopy

Pain tolerance can be increased by the introduction of an active distraction, such as a computer game. This effect has been found to be moderated by game demand, i.e., increased game demand = higher pain tolerance. A study was performed to classify the level of game demand and the presence of pain using implicit measures from functional Near-InfraRed Spectroscopy (fNIRS) and heart rate features from an electrocardiogram (ECG). Twenty participants played a racing game that was configured to induce low (Easy) or high (Hard) levels of demand. Both Easy and Hard levels of game demand were played with or without the presence of experimental pain using the cold pressor test protocol. Eight channels of fNIRS data were recorded from a montage of frontal and central-parietal sites located on the midline. Features were generated from these data, a subset of which were selected for classification using the RELIEFF method. Classifiers for game demand (Easy vs. Hard) and pain (pain vs. no-pain) were developed using five methods: Support Vector Machine (SVM), k-Nearest Neighbour (kNN), Naive Bayes (NB) and Random Forest (RF). These models were validated using a ten fold cross-validation procedure. The SVM approach using features derived from fNIRS was the only method that classified game demand at higher than chance levels (accuracy = 0.66, F1 = 0.68). It was not possible to classify pain vs. no-pain at higher than chance level. The results demonstrate the viability of utilising fNIRS data to classify levels of game demand and the difficulty of classifying pain when another task is present.

Interdisciplinary Approaches to the Study of Listening Effort in Young Children with Cochlear Implants

Very early bilateral implantation is thought to significantly reduce the attentional effort required to acquire spoken language, and consequently offer a profound improvement in quality of life. Despite the early intervention, however, auditory and communicative outcomes in children with cochlear implants remain poorer than in hearing children. The distorted auditory input via the cochlear implants requires more auditory attention resulting in increased listening effort and fatigue. Listening effort and fatigue may critically affect attention to speech, and in turn language processing, which may help to explain the variation in language and communication abilities. However, measuring attention to speech and listening effort is demanding in infants and very young children. Three objective techniques for measuring listening effort are presented in this paper that may address the challenges of testing very young and/or uncooperative children with cochlear implants: pupillometry, electroencephalography, and functional near-infrared spectroscopy. We review the studies of listening effort that used these techniques in paediatric populations with hearing loss, and discuss potential benefits of the systematic evaluation of listening effort in these populations.

Differences in Performance of ASD and ADHD Subjects Facing Cognitive Loads in an Innovative Reasoning Experiment

We aim to investigate whether EEG dynamics differ in adults with ASD (Autism Spectrum Disorders) and ADHD (attention-deficit/hyperactivity disorder) compared with healthy subjects during the performance of an innovative cognitive task, Aristotle's valid and invalid syllogisms, and how these differences correlate with brain regions and behavioral data for each subject. We recorded EEGs from 14 scalp electrodes (channels) in 21 adults with ADHD, 21 with ASD, and 21 healthy, normal subjects. The subjects were exposed in a set of innovative cognitive tasks (inducing varying cognitive loads), Aristotle's two types of syllogism mentioned above. A set of 39 questions were given to participants related to valid-invalid syllogisms as well as a separate set of questionnaires, in order to collect a number of demographic and behavioral data, with the aim of detecting shared information with values of a feature extracted from EEG, the multiscale entropy (MSE), in the 14 channels ('brain regions'). MSE, a nonlinear information-theoretic measure of complexity, was computed to extract a feature that quantifies the complexity of the EEG. Behavior-Partial Least Squares Correlation, PLSC, is the method to detect the correlation between two sets of data, brain, and behavioral measures. -PLSC, a variant of PLSC, was applied to build a functional connectivity of the brain regions involved in the reasoning tasks. Graph-theoretic measures were used to quantify the complexity of the functional networks. Based on the results of the analysis described in this work, a mixed 14 × 2 × 3 ANOVA showed significant main effects of group factor and brain region* syllogism factor, as well as a significant brain region* group interaction. There are significant differences between the means of MSE (complexity) values at the 14 channels of the members of the 'pathological' groups of participants, i.e., between ASD and ADHD, while the difference in means of MSE between both ASD and ADHD and that of the control group is not significant. In conclusion, the valid-invalid type of syllogism generates significantly different complexity values, MSE, between ASD and ADHD. The complexity of activated brain regions of ASD participants increased significantly when switching from a valid to an invalid syllogism, indicating the need for more resources to 'face' the task escalating difficulty in ASD subjects. This increase is not so evident in both ADHD and control. Statistically significant differences were found also in the behavioral response of ASD and ADHD, compared with those of control subjects, based on the principal brain and behavior saliences extracted by PLSC. Specifically, two behavioral measures, the emotional state and the degree of confidence of participants in answering questions in Aristotle's valid-invalid syllogisms, and one demographic variable, age, statistically and significantly discriminate the three groups' ASD. The seed-PLC generated functional connectivity networks for ASD, ADHD, and control, were 'projected' on the regions of the Default Mode Network (DMN), the 'reference' connectivity, of which the structural changes were found significant in distinguishing the three groups. The contribution of this work lies in the examination of the relationship between brain activity and behavioral responses of healthy and 'pathological' participants in the case of cognitive reasoning of the type of Aristotle's valid and invalid syllogisms, using PLSC, a machine learning approach combined with MSE, a nonlinear method of extracting a feature based on EEGs that captures a broad spectrum of EEGs linear and nonlinear characteristics. The results seem promising in adopting this type of reasoning, in the future, after further enhancements and experimental tests, as a supplementary instrument towards examining the differences in brain activity and behavioral responses of ASD and ADHD patients. The application of the combination of these two methods, after further elaboration and testing as new and complementary to the existing ones, may be considered as a tool of analysis in helping detecting more effectively such types of disorders.

The Validation of a Portable Functional NIRS System for Assessing Mental Workload

Portable functional near-infrared spectroscopy (fNIRS) systems have the potential to image the brain in naturalistic settings. Experimental studies are essential to validate such fNIRS systems. Working memory (WM) is a short-term active memory that is associated with the temporary storage and manipulation of information. The prefrontal cortex (PFC) brain area is involved in the processing of WM. We assessed the PFC brain during n-back WM tasks in a group of 25 college students using our laboratory-developed portable fNIRS system, WearLight. We designed an experimental protocol with 32 n-back WM task blocks with four different pseudo-randomized task difficulty levels. The hemodynamic response of the brain was computed from the experimental data and the evaluated brain responses due to these tasks. We observed the incremental mean hemodynamic activation induced by the increasing WM load. The left-PFC area was more activated in the WM task compared to the right-PFC. The task performance was seen to be related to the hemodynamic responses. The experimental results proved the functioning of the WearLight system in cognitive load imaging. Since the portable fNIRS system was wearable and operated wirelessly, it was possible to measure the cognitive load in the naturalistic environment, which could also lead to the development of a user-friendly brain–computer interface system.