Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS

Investigating the relationship between CSAT scores and prefrontal fNIRS signals during cognitive tasks using a quantum annealing algorithm

Academic achievement is a critical measure of intellectual ability, prompting extensive research into cognitive tasks as potential predictors. Neuroimaging technologies, such as functional near-infrared spectroscopy (fNIRS), offer insights into brain hemodynamics, allowing understanding of the link between cognitive performance and academic achievement. Herein, we explored the association between cognitive tasks and academic achievement by analyzing prefrontal fNIRS signals. A novel quantum annealer (QA) feature selection algorithm was applied to fNIRS data to identify cognitive tasks correlated with CSAT scores. Twelve features (signal mean, median, variance, peak, number of peaks, sum of peaks, range, minimum, kurtosis, skewness, standard deviation, and root mean square) were extracted from fNIRS signals at two time windows (10- and 60-s) to compare results from various feature variable conditions. The feature selection results from the QA-based and XGBoost regressor algorithms were compared to validate the former's performance. In a two-step validation process using multiple linear regression models, model fitness (adjusted R2) and model prediction error (RMSE) values were calculated. The quantum annealer demonstrated comparable performance to classical machine learning models, and specific cognitive tasks, including verbal fluency, recognition, and the Corsi block tapping task, were correlated with academic achievement. Group analyses revealed stronger associations between Tower of London and N-back tasks with higher CSAT scores. Quantum annealing algorithms have significant potential in feature selection using fNIRS data, and represents a novel research approach. Future studies should explore predictors of academic achievement and cognitive ability.

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.

Cognitive workload estimation using physiological measures: a review

Estimating cognitive workload levels is an emerging research topic in the cognitive neuroscience domain, as participants' performance is highly influenced by cognitive overload or underload results. Different physiological measures such as Electroencephalography (EEG), Functional Magnetic Resonance Imaging, Functional near-infrared spectroscopy, respiratory activity, and eye activity are efficiently used to estimate workload levels with the help of machine learning or deep learning techniques. Some reviews focus only on EEG-based workload estimation using machine learning classifiers or multimodal fusion of different physiological measures for workload estimation. However, a detailed analysis of all physiological measures for estimating cognitive workload levels still needs to be discovered. Thus, this survey highlights the in-depth analysis of all the physiological measures for assessing cognitive workload. This survey emphasizes the basics of cognitive workload, open-access datasets, the experimental paradigm of cognitive tasks, and different measures for estimating workload levels. Lastly, we emphasize the significant findings from this review and identify the open challenges. In addition, we also specify future scopes for researchers to overcome those challenges.

A single bout of aerobic exercise does not alter inhibitory control preparatory set cerebral hemodynamics: Evidence from the antisaccade task

A single bout of exercise improves executive function (EF) and is a benefit - in part -attributed to an exercise-mediated increase in cerebral blood flow enhancing neural efficiency. Limited work has used an event-related protocol to examine postexercise changes in preparatory phase cerebral hemodynamics for an EF task. This is salient given the neural efficiency hypothesis' assertion that improved EF is related to decreased brain activity. Here, event-related transcranial Doppler ultrasound was used to measure pro- (saccade to target) and antisaccades (saccade mirror-symmetrical target) preparatory phase middle cerebral artery velocity (MCAv) prior to and immediately after 15-min of aerobic exercise. Antisaccades produced longer reaction times (RT) and an increased preparatory phase MCAv than prosaccades - a result attributed to greater EF neural activity for antisaccades. Antisaccades selectively produced a postexercise RT reduction (ps < 0.01); however, antisaccade preparatory phase MCAv did not vary from pre- to postexercise (p=0.53) and did not correlate with the antisaccade RT benefit (p = 0.31). Accordingly, results provide no evidence that improved neural efficiency indexed via functional hyperemia is linked to a postexercise EF behavioural benefit. Instead, results support an evolving view that an EF benefit represents the additive interplay between interdependent exercise-mediated neurophysiological changes.

Prefrontal cortex oxygenation during a mentally fatiguing task in normoxia and hypoxia

Mental fatigue (MF) and hypoxia impair cognitive performance through changes in brain hemodynamics. We want to elucidate the role of prefrontal cortex (PFC)-oxygenation in MF. Twelve participants (22.9 ± 3.5 years) completed four experimental trials, (1) MF in (normobaric) hypoxia (MF_HYP) (3.800 m; 13.5%O2), (2) MF in normoxia (MF_NOR) (98 m; 21.0%O2), (3) Control task in HYP (CON_HYP), (4) Control in NOR (CON_NOR). Participants performed a 2-back task, Digit Symbol Substitution test and Psychomotor Vigilance task before and after a 60-min Stroop task or an emotionally neutral documentary. Brain oxygenation was measured through functional Near Infrared Spectroscopy. Subjective feelings of MF and physiological measures (heart rate, oxygen saturation, blood glucose and hemoglobin) were recorded. The Stroop task resulted in increased subjective feelings of MF compared to watching the documentary. 2-back accuracy was lower post task compared to pre task in MF_NOR and CON_NOR, while no differences were found in the other cognitive tasks. The fraction of inspired oxygen did not impact feelings of MF. Although performing the Stroop resulted in higher subjective feelings of MF, hypoxia had no effect on the severity of self-reported MF. Additionally, this study could not provide evidence for a role of oxygenation of the PFC in the build-up of MF.

Estimating Systemic Cognitive States from a Mixture of Physiological and Brain Signals

As human-machine teams are being considered for a variety of mixed-initiative tasks, detecting and being responsive to human cognitive states, in particular systematic cognitive states, is among the most critical capabilities for artificial systems to ensure smooth interactions with humans and high overall team performance. Various human physiological parameters, such as heart rate, respiration rate, blood pressure, and skin conductance, as well as brain activity inferred from functional near-infrared spectroscopy or electroencephalogram, have been linked to different systemic cognitive states, such as workload, distraction, or mind-wandering among others. Whether these multimodal signals are indeed sufficient to isolate such cognitive states across individuals performing tasks or whether additional contextual information (e.g., about the task state or the task environment) is required for making appropriate inferences remains an important open problem. In this paper, we introduce an experimental and machine learning framework for investigating these questions and focus specifically on using physiological and neurophysiological measurements to learn classifiers associated with systemic cognitive states like cognitive load, distraction, sense of urgency, mind wandering, and interference. Specifically, we describe a multitasking interactive experimental setting used to obtain a comprehensive multimodal data set which provided the foundation for a first evaluation of various standard state-of-the-art machine learning techniques with respect to their effectiveness in inferring systemic cognitive states. While the classification success of these standard methods based on just the physiological and neurophysiological signals across subjects was modest, which is to be expected given the complexity of the classification problem and the possibility that higher accuracy rates might not in general be achievable, the results nevertheless can serve as a baseline for evaluating future efforts to improve classification, especially methods that take contextual aspects such as task and environmental states into account.

Measuring cognitive workload in the nuclear control room: a review

Despite the substantial literature and human factors guidance, evaluators report challenges in selecting cognitive workload measures for the evaluation of complex human-technology systems. A review of 32 articles found that self-report measures and secondary tasks were systematically sensitive to human-system interface conditions and correlated with physiological measures. Therefore, including a self-report measure of cognitive workload is recommended when evaluating human-system interfaces. Physiological measures were mainly used in method studies, and future research must demonstrate the utility of these measures for human-system evaluation in complex work settings. However, indexes of physiological measures showed promise for cognitive workload assessment. The review revealed a limited focus on the measurement of excessive cognitive workload, although this is a key topic in nuclear process control. To support human-system evaluation of adequate cognitive workload, future research on behavioural measures may be useful in the identification and analysis of underload and overload.

Evaluating Speaker-Listener Cognitive Effort in Speech Communication Through Brain-to-Brain Synchrony: A Pilot Functional Near-Infrared Spectroscopy Investigation

PURPOSE

We explore a new approach to the study of cognitive effort involved in listening to speech by measuring the brain activity in a listener in relation to the brain activity in a speaker. We hypothesize that the strength of this brain-to-brain synchrony (coupling) reflects the magnitude of cognitive effort involved in verbal communication and includes both listening effort and speaking effort. We investigate whether interbrain synchrony is greater in native-to-native versus native-to-nonnative communication using functional near-infrared spectroscopy (fNIRS).

METHOD

Two speakers participated, a native speaker of American English and a native speaker of Korean who spoke English as a second language. Each speaker was fitted with the fNIRS cap and told short stories. The native English speaker provided the English narratives, and the Korean speaker provided both the nonnative (accented) English and Korean narratives. In separate sessions, fNIRS data were obtained from seven English monolingual participants ages 20-24 years who listened to each speaker's stories. After listening to each story in native and nonnative English, they retold the content, and their transcripts and audio recordings were analyzed for comprehension and discourse fluency, measured in the number of hesitations and articulation rate. No story retellings were obtained for narratives in Korean (an incomprehensible language for English listeners). Utilizing fNIRS technique termed sequential scanning, we quantified the brain-to-brain synchronization in each speaker-listener dyad.

RESULTS

For native-to-native dyads, multiple brain regions associated with various linguistic and executive functions were activated. There was a weaker coupling for native-to-nonnative dyads, and only the brain regions associated with higher order cognitive processes and functions were synchronized. All listeners understood the content of all stories, but they hesitated significantly more when retelling stories told in accented English. The nonnative speaker hesitated significantly more often than the native speaker and had a significantly slower articulation rate. There was no brain-to-brain coupling during listening to Korean, indicating a break in communication when listeners failed to comprehend the speaker.

CONCLUSIONS

We found that effortful speech processing decreased interbrain synchrony and delayed comprehension processes. The obtained brain-based and behavioral patterns are consistent with our proposal that cognitive effort in verbal communication pertains to both the listener and the speaker and that brain-to-brain synchrony can be an indicator of differences in their cumulative communicative effort.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25452142.

Classification of mental workload using brain connectivity and machine learning on electroencephalogram data

Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess mental workload from EEG data that use effective brain connectivity for the purpose of extracting features, a hierarchical feature selection algorithm to select the most significant features, and finally machine learning models. We have used the Simultaneous Task EEG Workload (STEW) dataset, an open-access collection of raw EEG data from 48 subjects. We extracted brain-effective connectivities by the direct directed transfer function and then selected the top 30 connectivities for each standard frequency band. Then we applied three feature selection algorithms (forward feature selection, Relief-F, and minimum-redundancy-maximum-relevance) on the top 150 features from all frequencies. Finally, we applied sevenfold cross-validation on four machine learning models (support vector machine (SVM), linear discriminant analysis, random forest, and decision tree). The results revealed that SVM as the machine learning model and forward feature selection as the feature selection method work better than others and could classify the mental workload levels with accuracy equal to 89.53% (± 1.36).

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.

A Window Into the Tired Brain: Neurophysiological Dynamics of Visuospatial Working Memory Under Fatigue

OBJECTIVE

We examine the spatiotemporal dynamics of neural activity and its correlates in heart rate and its variability (HR/HRV) during a fatiguing visuospatial working memory task.

BACKGROUND

The neural and physiological drivers of fatigue are complex, coupled, and poorly understood. Investigations that combine the fidelity of neural indices and the field-readiness of physiological measures can facilitate measurements of fatigue states in operational settings.

METHOD

Sixteen healthy adults, balanced by sex, completed a 60-minute fatiguing visuospatial working memory task. Changes in task performance, subjective measures of effort and fatigue, cerebral hemodynamics, and HR/HRV were analyzed. Peak brain activation, functional and effective connections within relevant brain networks were contrasted against spectral and temporal features of HR/HRV.

RESULTS

Task performance elicited increased neural activation in regions responsible for maintaining working memory capacity. With the onset of time-on-task effects, resource utilization was seen to increase beyond task-relevant networks. Over time, functional connections in the prefrontal cortex were seen to weaken, with changes in the causal relationships between key regions known to drive working memory. HR/HRV indices were seen to closely follow activity in the prefrontal cortex.

CONCLUSION

This investigation provided a window into the neurophysiological underpinnings of working memory under the time-on-task effect. HR/HRV was largely shown to mirror changes in cortical networks responsible for working memory, therefore supporting the possibility of unobtrusive state recognition under ecologically valid conditions.

APPLICATIONS

Findings here can inform the development of a fieldable index for cognitive fatigue.

Mild exercise improves executive function with increasing neural efficiency in the prefrontal cortex of older adults

This study examined whether a 3-month mild-exercise intervention could improve executive function in healthy middle-aged and older adults in a randomized control trial. Ultimately, a total of 81 middle-aged and older adults were randomly assigned to either an exercise group or a control group. The exercise group received 3 months of mild cycle exercise intervention (3 sessions/week, 30-50 min/session). The control group was asked to behave as usual for the intervention period. Before and after the intervention, participants did color-word matching Stroop tasks (CWST), and Stroop interference (SI)-related reaction time (RT) was assessed as an indicator of executive function. During the CWST, prefrontal activation was monitored using functional near-infrared spectroscopy (fNIRS). SI-related oxy-Hb changes and SI-related neural efficiency (NE) scores were assessed to examine the underlying neural mechanism of the exercise intervention. Although the mild-exercise intervention significantly decreased SI-related RT, there were no significant effects of exercise intervention on SI-related oxy-Hb changes or SI-related NE scores in prefrontal subregions. Lastly, changes in the effects of mild exercise on NE with advancing age were examined. The 81 participants were divided into two subgroups (younger-aged subgroup [YA], older-aged subgroup [OA], based on median age [68 years.]). Interestingly, SI-related RT significantly decreased, and SI-related NE scores in all ROIs of the prefrontal cortex significantly increased only in the OA subgroup. These results reveal that a long-term intervention of very light-intensity exercise has a positive effect on executive function especially in older adults, possibly by increasing neural efficiency in the prefrontal cortex.

How a pilot's brain copes with stress and mental load? Insights from the executive control network

In aviation, mental workload and stress are two major factors that can considerably impact a pilot's flight performance and decisions. Their consequences can be even more dramatic in single-pilot aircraft or with the forthcoming single-pilot operations where the pilot will fly alone and will not be able to be assisted in case of difficulty. An accurate and automatic monitoring of the pilot's mental state could help to prevent the potentially dangerous effects of an excess mental workload and stress. For example, some tasks could be allocated to automation or to a ground-based flight crew if a mental overload or significant stress is detected. In the current study, the brain activity of 20 private pilots was recorded with a fNIRS device during two realistic flight simulator scenarios. The mental workload was manipulated with the added difficulty of a secondary task and stress was induced by a social stressor. Our results confirmed the sensitivity of the fNIRS readings to variations in the mental workload, with increased HbO2 concentration in regions of the executive control network (ECN), in particular in the dorsolateral prefrontal cortex and in lateral parietal regions, when the difficulty of the secondary task was high. The social stressor also triggered an HbO2 increase in the ECN, especially when it was combined with high mental workload. This latter result suggests that mental workload and stress together can have cumulative effects, and coping with both factors is possible at the expense of an extra recruitment of the ECN. Finally, results also revealed a time-on-task effect, with a progressive reduction of the HbO2 signal in the ECN during the flight scenario, suggesting that these regions are sensitive to short term habituation to the tasks. Overall, fNIRS efficiently indexed mental load, stress, and practice effects.

Multimodal pre-screening can predict BCI performance variability: A novel subject-specific experimental scheme

BACKGROUND

Brain-computer interface (BCI) systems currently lack the required robustness for long-term daily use due to inter- and intra-subject performance variability. In this study, we propose a novel personalized scheme for a multimodal BCI system, primarily using functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), to identify, predict, and compensate for factors affecting competence-related and interfering factors associated with performance.

METHOD

11 (out of 13 recruited) participants, including five participants with motor deficits, completed four sessions on average. During the training sessions, the subjects performed a short pre-screening phase, followed by three variations of a novel visou-mental (VM) protocol. Features extracted from the pre-screening phase were used to construct predictive platforms using stepwise multivariate linear regression (MLR) models. In the test sessions, we employed a task-correction phase where our predictive models were used to predict the ideal task variation to maximize performance, followed by an interference-correction phase. We then investigated the associations between predicted and actual performances and evaluated the outcome of correction strategies.

RESULT

The predictive models resulted in respective adjusted R-squared values of 0.942, 0.724, and 0.939 for the first, second, and third variation of the task, respectively. The statistical analyses showed significant associations between the performances predicted by predictive models and the actual performances for the first two task variations, with rhos of 0.7289 (p-value = 0.011) and 0.6970 (p-value = 0.017), respectively. For 81.82 % of the subjects, the task/workload correction stage correctly determined which task variation provided the highest accuracy, with an average performance gain of 5.18 % when applying the correction strategies.

CONCLUSION

Our proposed method can lead to an integrated multimodal predictive framework to compensate for BCI performance variability, particularly, for people with severe motor deficits.

Mental workload classification using convolutional neural networks based on fNIRS-derived prefrontal activity

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) is a tool to assess brain activity during cognitive testing. Despite its usefulness, its feasibility in assessing mental workload remains unclear. This study was to investigate the potential use of convolutional neural networks (CNNs) based on functional near-infrared spectroscopy (fNIRS)-derived signals to classify mental workload in individuals with mild cognitive impairment.

METHODS

Spatial images by constructing a statistical activation map from the prefrontal activity of 120 subjects with MCI performing three difficulty levels of the N-back task (0, 1, and 2-back) were used for CNNs. The CNNs were evaluated using a 5 and 10-fold cross-validation method.

RESULTS

As the difficulty level of the N-back task increased, the accuracy decreased and prefrontal activity increased. In addition, there was a significant difference in the accuracy and prefrontal activity across the three levels (p's < 0.05). The accuracy of the CNNs based on fNIRS-derived spatial images evaluated by 5 and 10-fold cross-validation in classifying the difficulty levels ranged from 0.83 to 0.96.

CONCLUSION

fNIRS could also be a promising tool for measuring mental workload in older adults with MCI despite their cognitive decline. In addition, this study demonstrated the feasibility of the classification performance of the CNNs based on fNIRS-derived signals from the prefrontal cortex.

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.

Prefrontal hemodynamic features of older adults with preserved visuospatial working memory function

Memory decline has been observed in the aging population and is a risk factor for the later development of dementia. Understanding how memory is preserved in older adults has been an important topic. The present study examines the hemodynamic features of older adults whose memory is comparable with that of young adults. In the present study, 45 younger and 45 older adults performed the visual memory task with various difficulty levels (i.e., the items to be remembered), and their cerebral hemodynamics at each level were measured by functional near-infrared spectroscopy (fNIRS). The results showed that older adults exhibited higher activation than younger adults under more difficult but not easier levels. In addition, older adults whose performance is comparable with that of young adults (i.e., being able to remember six items) showed more right-lateralized activation. However, those unable to do so showed more left-lateralized activation. The results suggested that high-performing older adults possess successful compensatory mechanisms by recruiting cognitive resources in a specialized brain region.

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.

Effects of Personalized Cognitive Training Using Mental Workload Monitoring on Executive Function in Older Adults With Mild Cognitive Impairment

Although a variety of cognitive training has been performed, its optimally personalized delivery is still unknown. This study established the mental workload classification model using a convolutional neural network based on functional near-infrared spectroscopy-derived data. The dorsolateral prefrontal cortex (DLPFC) while thirty individuals with mild cognitive impairment (MCI) performed spatial working memory testing was found to be a considerable indicator to classify 3 levels of mental workload with an accuracy of over 86%. In the next step, forty subjects with MCI were randomly allocated into the experimental group (EG) that received cognitive training with mental workload-based difficulty adjustment or the control group (CG) that received conventional cognitive training. To compare both groups, the Trail Making Test Part B (TMT-B) and hemodynamic responses in the DLPFC during the TMT-B were measured. After the 16 training sessions, the EG subjects achieved a greater improvement in the TMT-B than the CG subjects (p < 0.05). Also, the EG subject showed a significantly lower DLPFC activity during the TMT-B than the CG subject (p < 0.05). In sum, the EG subjects better performed executive function with lower energy from the DLPFC. These findings imply that the importance of mental workload monitoring to provide personalized cognitive training.

Exploring the potential of eye tracking on personalized learning and real-time feedback in modern education

Eye tracking is one of the techniques used to investigate cognitive mechanisms involved in the school context, such as joint attention and visual perception. Eye tracker has portability, straightforward application, cost-effectiveness, and infant-friendly neuroimaging measures of cognitive processes such as attention, engagement, and learning. Furthermore, the ongoing software enhancements coupled with the implementation of artificial intelligence algorithms have improved the precision of collecting eye movement data and simplified the calibration process. These characteristics make it plausible to consider eye-tracking technology a promising tool to assist the teaching-learning process in school routines. However, eye tracking needs to be explored more as an educational instrument for real-time classroom activities and teachers' feedback. This perspective article briefly presents the fundamentals of the eye-tracking technique and four illustrative examples of employing this method in everyday school life. The first application shows how eye tracker information may contribute to teacher assessment of students' computational thinking in coding classes. In the second and third illustrations, we discuss the additional information provided by the eye-tracker to the teacher assessing the student's strategies to solve fraction problems and chart interpretation. The last illustration demonstrates the potential of eye tracking to provide Real-time feedback on learning difficulties/disabilities. Thus, we highlight the potential of the eye tracker as a complementary tool to promote personalized education and discuss future perspectives. In conclusion, we suggest that an eye-tracking system could be helpful by providing real-time student gaze leading to immediate teacher interventions and metacognition strategies.

Neurophysiological and gait outcomes during a dual-task gait assessment in concussed adolescents

BACKGROUND

Gait deficits are common after concussion in adolescents. However, the neurophysiological underpinnings of these gait deficiencies are currently unknown. Thus, the goal of this study was to compare spatiotemporal gait metrics, prefrontal cortical activation, and neural efficiency between concussed adolescents several weeks from injury and uninjured adolescents during a dual-task gait assessment.

METHODS

Fifteen concussed (mean age[SD]: 17.4[0.6], 13 female, days since injury: 26.3[9.9]) and 17 uninjured adolescents (18.0[0.7], 10 female) completed a gait assessment with three conditions repeated thrice: single-task walking, single-task subtraction, and dual-task, which involved walking while completing a subtraction task simultaneously. Gait metrics were measured using an inertial sensor system. Prefrontal cortical activation was captured via functional near-infrared spectroscopy. Neural efficiency was calculated by relating gait metrics to prefrontal cortical activity. Differences between groups and conditions were examined, with corrections for multiple comparisons.

FINDINGS

There were no significant differences in gait metrics between groups. Compared to uninjured adolescents, concussed adolescents displayed significantly greater prefrontal cortical activation during the single-task subtraction (P = 0.01) and dual-task (P = 0.01) conditions with lower neural efficiency based on cadence (P = 0.02), gait cycle duration (P = 0.03), step duration (P = 0.03), and gait speed (P = 0.04) during the dual-task condition.

INTERPRETATION

Our findings suggest that several weeks after injury concussed adolescents demonstrate lower neural efficiency and display a cost to gait performance when cognitive demand is high, e.g., while multitasking, suggesting that the concussed adolescent brain is less able to compensate when attention is divided between two concurrent tasks.

Driving risk cognition of passengers in highly automated driving based on the prefrontal cortex activity via fNIRS

For high-level automated vehicles, the human being acts as the passenger instead of the driver and does not need to operate vehicles, it makes the brain-computer interface system of high-level automated vehicles depend on the brain state of passengers rather than that of drivers. Particularly when confronting challenging driving situations, how to implement the mental states of passengers into safe driving is a vital choice in the future. Quantifying the cognition of the driving risk of the passenger is a basic step in achieving this goal. In this paper, the passengers' mental activities in low-risk episode and high-risk episode were compared, the influences on passengers' mental activities caused by driving scenario risk was first explored via fNIRS. The results showed that the mental activities of passengers caused by driving scenario risk in the Brodmann area 10 are very active, which was verified by examining the real-driving data collected in corresponding challenging experiments, and there is a positive correlation between the cerebral oxygen and the driving risk field. This initial finding provides a possible solution to design a human-centred intelligent system to promise safe driving for high-level automated vehicles using passengers' driving risk cognition.

Dose-Response of Creatine Supplementation on Cognitive Function in Healthy Young Adults

To determine if creatine (Cr) supplementation could influence cognitive performance and whether any changes were related to changes in prefrontal cortex (PFC) activation during such cognitive tasks, thirty (M = 11, F = 19) participants were evenly randomized to receive supplementation with Cr (CR10:10 g/day or CR20:20 g/day) or a placebo (PLA:10 g/day) for 6 weeks. Participants completed a cognitive test battery (processing speed, episodic memory, and attention) on two separate occasions prior to and following supplementation. Functional near-infrared spectroscopy (fNIRS) was used to measure PFC oxyhemoglobin (O2Hb) during the cognitive evaluation. A two-way repeated measures ANOVA was used to determine the differences between the groups and the timepoints for the cognitive performance scores and PFC O2Hb. In addition, a one-way ANOVA of % change was used to determine pre- and post-differences between the groups. Creatine (independent of dosage) had no significant effect on the measures of cognitive performance. There was a trend for decreased relative PFC O2Hb in the CR10 group versus the PLA group in the processing speed test (p = 0.06). Overall, six weeks of Cr supplementation at a moderate or high dose does not improve cognitive performance or change PFC activation in young adults.

Cognitive training based on functional near-infrared spectroscopy neurofeedback for the elderly with mild cognitive impairment: a preliminary study

Introduction

Mild cognitive impairment (MCI) is often described as an intermediate stage of the normal cognitive decline associated with aging and dementia. There is a growing interest in various non-pharmacological interventions for MCI to delay the onset and inhibit the progressive deterioration of daily life functions. Previous studies suggest that cognitive training (CT) contributes to the restoration of working memory and that the brain-computer-interface technique can be applied to elicit a more effective treatment response. However, these techniques have certain limitations. Thus, in this preliminary study, we applied the neurofeedback paradigm during CT to increase the working memory function of patients with MCI.

Methods

Near-infrared spectroscopy (NIRS) was used to provide neurofeedback by measuring the changes in oxygenated hemoglobin in the prefrontal cortex. Thirteen elderly MCI patients who received CT-neurofeedback sessions four times on the left dorsolateral prefrontal cortex (dlPFC) once a week were recruited as participants.

Results

Compared with pre-intervention, the activity of the targeted brain region increased when the participants first engaged in the training; after 4 weeks of training, oxygen saturation was significantly decreased in the left dlPFC. The participants demonstrated significantly improved working memory compared with pre-intervention and decreased activity significantly correlated with improved cognitive performance.

Conclusion

Our results suggest that the applications for evaluating brain-computer interfaces can aid in elucidation of the subjective mental workload that may create additional or decreased task workloads due to CT.

Decoding Mental Effort in a Quasi-Realistic Scenario: A Feasibility Study on Multimodal Data Fusion and Classification

Humans' performance varies due to the mental resources that are available to successfully pursue a task. To monitor users' current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 participants (nine female, M = 25.9 with SD = 3.8 years). In this study, we recorded respiratory, ocular, cardiac, and brain activity using functional near-infrared spectroscopy (fNIRS) while participants performed an adapted version of the warship commander task with concurrent emotional speech distraction. We tested the feasibility of decoding the experienced mental effort with a multimodal machine learning architecture. The architecture comprised feature engineering, model optimisation, and model selection to combine multimodal measurements in a cross-subject classification. Our approach reduces possible overfitting and reliably distinguishes two different levels of mental effort. These findings contribute to the prediction of different states of mental effort and pave the way toward generalised state monitoring across individuals in realistic applications.

Photobiomodulation may enhance cognitive efficiency in older adults: a functional near-infrared spectroscopy study

Introduction

The relative oxygenated hemoglobin (HbO) measured using functional near-infrared spectroscopy (fNIRS) has been considered as an index for cognitive loading, with the more difficult the task, the higher the level. A previous study reported that young adults who received transcranial photobiomodulation (tPBM) showed a reduced HbO of a difficult task, suggesting that tPBM may enhance cognitive efficiency. The present study further investigated the effect of tPBM on cognitive efficiency in older adults.

Methods

Thirty participants received a single tPBM on the forehead for 350 s. Before and after tPBM, their HbO in the visual span task with various difficulties was measured with fNIRS.

Results

After tPBM, participants exhibited significantly lower HbO in a harder (span 7) but not an easier level (span 2) of the task, but their behavioral performance remained unchanged. In addition, factors affecting the reduction of HbO were examined, and the results showed that individuals with better memory (as measured by a 30-min delayed recall test) showed more reduction of HbO.

Discussion

The results suggest that tPBM may enhance cognitive efficiency, with individuals with better memory tend to benefit more.

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.

Virtual (Zoom) Interactions Alter Conversational Behavior and Interbrain Coherence

A growing number of social interactions are taking place virtually on videoconferencing platforms. Here, we explore potential effects of virtual interactions on observed behavior, subjective experience, and neural "single-brain" and "interbrain" activity via functional near-infrared spectroscopy neuroimaging. We scanned a total of 36 human dyads (72 participants, 36 males, 36 females) who engaged in three naturalistic tasks (i.e., problem-solving, creative-innovation, socio-emotional task) in either an in-person or virtual (Zoom) condition. We also coded cooperative behavior from audio recordings. We observed reduced conversational turn-taking behavior during the virtual condition. Given that conversational turn-taking was associated with other metrics of positive social interaction (e.g., subjective cooperation and task performance), this measure may be an indicator of prosocial interaction. In addition, we observed altered patterns of averaged and dynamic interbrain coherence in virtual interactions. Interbrain coherence patterns that were characteristic of the virtual condition were associated with reduced conversational turn-taking. These insights can inform the design and engineering of the next generation of videoconferencing technology.SIGNIFICANCE STATEMENT Videoconferencing has become an integral part of our lives. Whether this technology impacts behavior and neurobiology is not well understood. We explored potential effects of virtual interaction on social behavior, brain activity, and interbrain coupling. We found that virtual interactions were characterized by patterns of interbrain coupling that were negatively implicated in cooperation. Our findings are consistent with the perspective that videoconferencing technology adversely affects individuals and dyads during social interaction. As virtual interactions become even more necessary, improving the design of videoconferencing technology will be crucial for supporting effective communication.

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.

Sex differences in neural processing of speech in neonates

The large majority of studies shows that girls develop their language skills faster than boys in the first few years of life. Are girls born with this advantage in language development? The present study used fNIRS in neonates to investigate sex differences in neural processing of speech within the first days of life. We found that speech stimuli elicited significantly more brain activity than non-speech stimuli in both groups of male and female neonates. However, whereas girls showed significant HbO changes to speech stimuli only within the left hemisphere, boys exhibited simultaneous neural activations in both hemispheres, with a larger and more significant fronto-temporal cluster in the right hemisphere. Furthermore, in boys, the variation in time-to-peak latencies was considerably greater than in girls. These findings suggest an earlier maturation of language-related brain areas in girls and highlight the importance of sex-specific investigations of neural language networks in infants.

On the Application of Developmental Cognitive Neuroscience in Educational Environments

The paper overviews components of neurologic processing efficiencies to develop innovative methodologies and thinking to school-based applications and changes in educational leadership based on sound findings in the cognitive neurosciences applied to schools and learners. Systems science can allow us to better manage classroom-based learning and instruction on the basis of relatively easily evaluated efficiencies or inefficiencies and optimization instead of simply examining achievement. "Medicalizing" the learning process with concepts such as "learning disability" or employing grading methods such as pass-fail does little to aid in understanding the processes that learners employ to acquire, integrate, remember, and apply information learned. The paper endeavors to overview and provided reference to tools that can be employed that allow a better focus on nervous system-based strategic approaches to classroom learning.

Aviation and neurophysiology: A systematic review

This paper systematically reviews 20 years of publications (N = 54) on aviation and neurophysiology. The main goal is to provide an account of neurophysiological changes associated with flight training with the aim of identifying neurometrics indicative of pilot's flight training level and task relevant mental states, as well as to capture the current state-of-art of (neuro)ergonomic design and practice in flight training. We identified multiple candidate neurometrics of training progress and workload, such as frontal theta power, the EEG Engagement Index and the Cognitive Stability Index. Furthermore, we discovered that several types of classifiers could be used to accurately detect mental states, such as the detection of drowsiness and mental fatigue. The paper advances practical guidelines on terminology usage, simulator fidelity, and multimodality, as well as future research ideas including the potential of Virtual Reality flight simulations for training, and a brain-computer interface for flight training.

Load-Dependent Prefrontal Cortex Activation Assessed by Continuous-Wave Near-Infrared Spectroscopy during Two Executive Tasks with Three Cognitive Loads in Young Adults

The present study examined the evolution of the behavioral performance, subjectively perceived difficulty, and hemodynamic activity of the prefrontal cortex as a function of cognitive load during two different cognitive tasks tapping executive functions. Additionally, it investigated the relationships between these behavioral, subjective, and neuroimaging data. Nineteen right-handed young adults (18–22 years) were scanned using continuous-wave functional near-infrared spectroscopy during the performance of n-back and random number generation tasks in three cognitive load conditions. Four emitter and four receptor optodes were fixed bilaterally over the ventrolateral and dorsolateral prefrontal cortices to record the hemodynamic changes. A self-reported scale measured the perceived difficulty. The findings of this study showed that an increasing cognitive load deteriorated the behavioral performance and increased the perceived difficulty. The hemodynamic activity increased parametrically for the three cognitive loads of the random number generation task and in a two-back and three-back compared to a one-back condition. In addition, the hemodynamic activity was specifically greater in the ventrolateral prefrontal cortex than in the dorsolateral prefrontal cortex for both cognitive tasks (random number generation and n-back tasks). Finally, the results highlighted some links between cerebral oxygenation and the behavioral performance, but not the subjectively perceived difficulty. Our results suggest that cognitive load affects the executive performance and perceived difficulty and that fNIRS can be used to specify the prefrontal cortex’s implications for executive tasks involving inhibition and working memory updating.

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.

Understanding and Measuring the Cognitive Load of Amputees for Rehabilitation and Prosthesis Development

Objective

To derive a definition of cognitive load that is applicable for amputation as well as analyze suitable research models for measuring cognitive load during prosthesis use. Defining cognitive load for amputation will improve rehabilitation methods and enable better prosthesis design.

Data Sources

Elsevier, Springer, PLoS, IEEE Xplore, and PubMed.

Study Selection

Studies on upper limb myoelectric prostheses and neuroprostheses were prioritized. For understanding measurement, lower limb amputations and studies with individuals without lower limb amputations were included.

Data Extraction

Queries including “cognitive load,” “neural fatigue,” “brain plasticity,” “neuroprosthetics,” “upper limb prosthetics,” and “amputation” were used with peer-reviewed journals or articles. Articles published within the last 6 years were prioritized. Articles on foundational principles were included regardless of date. A total of 69 articles were found: 12 on amputation, 15 on cognitive load, 8 on phantom limb, 22 on sensory feedback, and 12 on measurement methods.

Data Synthesis

The emotional, physiological, and neurologic aspects of amputation, prosthesis use, and rehabilitation aspects of cognitive load were analyzed in conjunction with measurement methods, including resolution, invasiveness, and sensitivity to user movement and environmental noise.

Conclusions

Use of “cognitive load” remains consistent with its original definition. For amputation, 2 additional elements are needed: “emotional fatigue,” defined as an amputee's emotional response, including mental concentration and emotions, and “neural fatigue,” defined as the physiological and neurologic effects of amputation on brain plasticity. Cognitive load is estimated via neuroimaging techniques, including electroencephalography, functional magnetic resonance imaging, and functional near-infrared spectroscopy (fNIRS). Because fNIRS measures cognitive load directly, has good temporal and spatial resolution, and is not as restricted by user movement, fNIRS is recommended for most cognitive load studies.

Applying functional near-infrared spectroscopy and eye-tracking in a naturalistic educational environment to investigate physiological aspects that underlie the cognitive effort of children during mental rotation tests

Spatial cognition is related to academic achievement in science, technology, engineering, and mathematics (STEM) domains. Neuroimaging studies suggest that brain regions' activation might be related to the general cognitive effort while solving mental rotation tasks (MRT). In this study, we evaluate the mental effort of children performing MRT tasks by measuring brain activation and pupil dilation. We use functional near-infrared spectroscopy (fNIRS) concurrently to collect brain hemodynamic responses from children's prefrontal cortex (PFC) and an Eye-tracking system to measure pupil dilation during MRT. Thirty-two healthy students aged 9-11 participated in this experiment. Behavioral measurements such as task performance on geometry problem-solving tests and MRT scores were also collected. The results were significant positive correlations between the children's MRT and geometry problem-solving test scores. There are also significant positive correlations between dorsolateral PFC (dlPFC) hemodynamic signals and visuospatial task performances (MRT and geometry problem-solving scores). Moreover, we found significant activation in the amplitude of deoxy-Hb variation on the dlPFC and that pupil diameter increased during the MRT, suggesting that both physiological responses are related to mental effort processes during the visuospatial task. Our findings indicate that children with more mental effort under the task performed better. The multimodal approach to monitoring students' mental effort can be of great interest in providing objective feedback on cognitive resource conditions and advancing our comprehension of the neural mechanisms that underlie cognitive effort. Hence, the ability to detect two distinct mental states of rest or activation of children during the MRT could eventually lead to an application for investigating the visuospatial skills of young students using naturalistic educational paradigms.

Neuroergonomic assessment of developmental coordination disorder

Until recently, neural assessments of gross motor coordination could not reliably handle active tasks, particularly in realistic environments, and offered a narrow understanding of motor-cognition. By applying a comprehensive neuroergonomic approach using optical mobile neuroimaging, we probed the neural correlates of motor functioning in young people with Developmental Coordination Disorder (DCD), a motor-learning deficit affecting 5-6% of children with lifelong complications. Neural recordings using fNIRS were collected during active ambulatory behavioral task execution from 37 Typically Developed and 48 DCD Children who performed cognitive and physical tasks in both single and dual conditions. This is the first of its kind study targeting regions of prefrontal cortical dysfunction for identification of neuropathophysiology for DCD during realistic motor tasks and is one of the largest neuroimaging study (across all modalities) involving DCD. We demonstrated that DCD is a motor-cognitive disability, as gross motor /complex tasks revealed neuro-hemodynamic deficits and dysfunction within the right middle and superior frontal gyri of the prefrontal cortex through functional near infrared spectroscopy. Furthermore, by incorporating behavioral performance, decreased neural efficiency in these regions were revealed in children with DCD, specifically during motor tasks. Lastly, we provide a framework, evaluating disorder impact in ecologically valid contexts to identify when and for whom interventional approaches are most needed and open the door for precision therapies.

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.

Air Force Pilot Expertise Assessment with Regard to Mental Effort Requested during Unusual Attitude Recovery Flight Training Simulations

Pilot training and expertise are key aspects in aviation. A traditional way of evaluating pilot expertise is to measure performance output. However, this approach provides a narrow view of the pilot’s capacity, especially with regard to mental and emotional profile. The aim of this study is hence to investigate whether neurophysiological data can be employed as an additional objective measure to assess the expertise of pilots. In this regard, it has been demonstrated that mental effort can be used as an indirect measure of operator expertise and capacity. An increase in mental effort, for instance, can automatically result in a decrease in the remaining capacity of the operator. To better investigate this aspect, we ask two groups of Italian Air Force pilots, experienced (Experts) and unexperienced (Novices), to undergo unusual attitude recovery flight training simulations. Their behavioral (unusual attitude recovery time), subjective (mental effort demand perception) and neurophysiological data (Electroencephalogram, EEG; Electrocardiogram, ECG) are collected during the entire flight simulations. Although the two groups do not exhibit differences in terms of unusual attitude recovery time and mental effort demand perception, the EEG-based mental effort index shows how Novices request significantly higher mental effort during unusual conditions.

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.

Evaluating mental workload during multitasking in simulated flight

BACKGROUND

Pilots must process multiple streams of information simultaneously. Mental workload is one of the main issues in man-machine interactive mode when dealing with multiple tasks. This study aimed to combine functional near-infrared spectroscopy (fNIRS) and electrocardiogram (ECG) to detect changes in mental workload during multitasking in a simulated flight.

METHODS

Twenty-six participants performed three multitasking tasks at different mental workload levels. These mental workload levels were set by varying the number of subtasks. fNIRS and ECG signals were recorded during tasks. Participants filled in the national aeronautics and space administration task load index (NASA-TLX) scale after each task. The effects of mental workload on scores of NASA-TLX, performance of tasks, heart rate (HR), heart rate variability (HRV), and the prefrontal cortex (PFC) activation were analyzed.

RESULTS

Compared to multitasking in lower mental workload conditions, participants exhibited higher scores of NASA-TLX, HR, and PFC activation when multitasking in high mental workload conditions. Their performance was worse during the high mental workload multitasking condition, as evidenced by the higher average tracking distance, smaller number of response times, and longer response time of the meter. The standard deviation of the RR intervals (SDNN) was negatively correlated with subjective mental workload in the low task load condition and PFC activation was positively correlated with HR and subjective mental workload in the medium task load condition.

CONCLUSION

HR and PFC activation can be used to detect changes in mental workload during simulated flight multitasking tasks.

Neural correlates of dual-task walking in people with central neurological disorders: a systematic review

BACKGROUND

People with central neurological disorders experience difficulties with dual-task walking due to disease-related impairments. The objective of this review was to provide a comprehensive examination of the neural correlates (structural/functional brain changes) of dual-task walking in people with Parkinson's disease (PD), multiple sclerosis (MS), stroke, and Alzheimer's disease (AD).

METHODS

A systematic review of the literature was conducted, following PRISMA guidelines, on Medline, Embase, and Scopus. Included studies examined the relationship between structural and functional brain imaging and dual-task walking performance in people with PD, MS, stroke, and AD. Articles that met the inclusion criteria had baseline characteristics, study design, and behavioral and brain outcomes extracted. Twenty-three studies were included in this review.

RESULTS

Most structural imaging studies (75%) found an association between decreased brain integrity and poor dual-task performance. Specific brain regions that showed this association include the striatum regions and hippocampus in PD and supplementary motor area in MS. Functional imaging studies reported an association between increased prefrontal activity and maintained (compensatory recruitment) or decreased dual-task walking performance in PD and stroke. A subset (n = 2) of the stroke papers found no significant correlations. Increased supplementary motor area activity was associated with decreased performance in MS and stroke. No studies on AD were identified.

CONCLUSION

In people with PD, MS, and stroke, several neural correlates of dual-task walking have been identified, however, the direction of the association between neural and performance outcomes varied across the studies. The type of cognitive task used and presentation modality (e.g., visual) may have contributed to these mixed findings.

Voluntary Behavior and Training Conditions Modulate in vivo Extracellular Glucose and Lactate in the Mouse Primary Motor Cortex

Learning or performing new behaviors requires significant neuronal signaling and is metabolically demanding. The metabolic cost of performing a behavior is mitigated by exposure and practice which result in diminished signaling and metabolic requirements. We examined the impact of novel and habituated wheel running, as well as effortful behaviors on the modulation of extracellular glucose and lactate using biosensors inserted in the primary motor cortex of mice. We found that motor behaviors produce increases in extracellular lactate and decreases in extracellular glucose in the primary motor cortex. These effects were modulated by experience, novelty and intensity of the behavior. The increase in extracellular lactate appears to be strongly associated with novelty of a behavior as well as the difficulty of performing a behavior. Our observations are consistent with the view that a main function of aerobic glycolysis is not to fuel the current neuronal activity but to sustain new bio-infrastructure as learning changes neural networks, chiefly through the shuttling of glucose derived carbons into the pentose phosphate pathway for the biosynthesis of nucleotides.

Cities and neuroscience research: A systematic literature review

BACKGROUND

Cities are becoming the socio-economic hubs for most of the world's population. Understanding how our surroundings can mentally affect everyday life has become crucial to integrate environmental sustainability into urban development. The present review aims to explore the empirical studies investigating neural mechanisms underlying cognitive and emotional processes elicited by the exposure to different urban built and natural spaces. It also tries to identify new research questions and to leverage neurourbanism as a framework to achieve healthier and sustainable cities.

METHODS

By following the PRISMA framework, we conducted a structured search on PubMed, ProQuest, Web of Science, and Scopus databases. Only articles related to how urban environment-built or natural-affects brain activity through objective measurement (with either imaging or electrophysiological techniques) were considered. Further inclusion criteria were studies on human adult populations, peer-reviewed, and in English language.

RESULTS

Sixty-two articles met the inclusion criteria. They were qualitatively assessed and analyzed to determine the main findings and emerging concepts. Overall, the results suggest that urban built exposure (when compared to natural spaces) elicit activations in brain regions or networks strongly related to perceptual, attentional, and (spatial) cognitive demands. The city's-built environment also triggers neural circuits linked to stress and negative affect. Convergence of these findings was observed across neuroscience techniques, and for both laboratory and real-life settings. Additionally, evidence also showed associations between neural social stress processing with urban upbringing or current city living-suggesting a mechanistic link to certain mood and anxiety disorders. Finally, environmental diversity was found to be critical for positive affect and individual well-being.

CONCLUSION

Contemporary human-environment interactions and planetary challenges imply greater understanding of the neurological underpinnings on how the urban space affects cognition and emotion. This review provides scientific evidence that could be applied for policy making on improved urban mental health. Several studies showed that high-quality green or blue spaces, and bio-diverse urban areas, are important allies for positive neural, cognitive, and emotional processes. Nonetheless, the spatial perception in social contexts (e.g., city overcrowding) deserves further attention by urban planners and scientists. The implications of these observations for some theories in environmental psychology and research are discussed. Future work should take advantage of technological advancements to better characterize behavior, brain physiology, and environmental factors and apply them to the remaining complexity of contemporary cities.

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.

Study of EEG characteristics while solving scientific problems with different mental effort

Studying the mental effort in problem-solving is important to the understanding of how the brain allocates cognitive resources to process information. The electroencephalogram is a promising physiological approach to assessing the online mental effort. In this study, we investigate the EEG indicators of mental effort while solving scientific problems. By manipulating the complexity of the scientific problem, the level of mental effort also changes. With the increase of mental effort, theta synchronization in the frontal region and lower alpha desynchronization in the parietal and occipital regions significantly increase. Also, upper alpha desynchronization demonstrates a widespread enhancement across the whole brain. According to the functional topography of brain activity in the theta and alpha frequency, our results suggest that the mental effort while solving scientific problems is related to working memory, visuospatial processing, semantic processing and magnitude manipulation. This study suggests the reliability of EEG to evaluate the mental effort in an educational context and provides valuable insights into improving the problem-solving abilities of students in educational practice.

Facing successfully high mental workload and stressors: An fMRI study

The present fMRI study aimed at highlighting patterns of brain activations and autonomic activity when confronted with high mental workload and the threat of auditory stressors. Twenty participants performed a complex cognitive task in either safe or aversive conditions. Our results showed that increased mental workload induced recruitment of the lateral frontoparietal executive control network (ECN), along with disengagement of medial prefrontal and posterior cingulate regions of the default mode network (DMN). Mental workload also elicited an increase in heart rate and pupil diameter. Task performance did not decrease under the threat of stressors, most likely due to efficient inhibition of auditory regions, as reflected by a large decrement of activity in the superior temporal gyri. The threat of stressors was also accompanied with deactivations of limbic regions of the salience network (SN), possibly reflecting emotional regulation mechanisms through control from dorsal medial prefrontal and parietal regions, as indicated by functional connectivity analyses. Meanwhile, the threat of stressors induced enhanced ECN activity, likely for improved attentional and cognitive processes toward the task, as suggested by increased lateral prefrontal and parietal activations. These fMRI results suggest that measuring the balance between ECN, SN, and DMN recruitment could be used for objective mental state assessment. In this sense, an extra recruitment of task‐related regions and a high ratio of lateral versus medial prefrontal activity may represent a relevant marker of increased but efficient mental effort, while the opposite may indicate a disengagement from the task due to mental overload and/or stressors.

Neural and biomechanical tradeoffs associated with human-exoskeleton interactions

Industrial passive low-back exoskeletons have gained recent attention as ergonomic interventions to manual handling tasks. This research utilized a two-armed experimental approach (single vs dual-task paradigms) to quantify neural and biomechanical tradeoffs associated with short-term human-exoskeleton interaction (HEI) during asymmetrical lifting in twelve healthy adults balanced by gender. A dynamic, electromyography-assisted spine model was employed that indicated statistical, but marginal, biomechanical benefits of the tested exoskeleton, which diminished with the introduction of the cognitive dual-task. Using Near Infrared Spectroscopy (fNIRS)-based brain connectivity analyses, we found that the tested exoskeleton imposed greater neurocognitive and motor adaptation efforts by engaging action monitoring and error processing brain networks. Collectively, these findings indicate that a wearer's biomechanical response to increased cognitive demands in the workplace may offset the mechanical advantages of exoskeletons. We also demonstrate the utility of ambulatory fNIRS to capture the neural cost of HEI without the need for elaborate dual-task manipulations.