The influence of mental fatigue and motivation on neural network dynamics; an EEG coherence study

The interplay of brain neurotransmission and mental fatigue: A research protocol

INTRODUCTION

Mental fatigue (MF) significantly affects both cognitive and physical performance. However, the precise mechanisms, particularly concerning neurotransmission, require further investigation. An implication of the role of dopamine (DA) and noradrenaline (NA) is stated, but empirical evidence for this theory still needs to be provided. To address this gap, we aim to investigate the role of brain neurotransmission in elucidating if, and how prolonged cognitive activity induces MF and its subsequent impact on cognitive performance.

METHODS

This study (registration number: G095422N) will adopt a randomized cross-over design with sixteen healthy participants aged 18-35 years. The sessions include a familiarization, two experimental (DA: 20mg Methylphenidate; NA: 8mg Reboxetine) conditions, and one placebo (lactose tablet: 10mg) condition. A 60-minute individualized Stroop task will be used to investigate whether, and how the onset of MF changes under the influence of reuptake inhibitors. Attention and response inhibition will be assessed before and after the MF-inducing task using a Go/NoGo task. The integration of physiological (electroencephalography, heart rate), behavioral (attention, response inhibition), and subjective indicators (scales and questionnaires) will be used to detect the underlying mechanisms holistically. Data analysis will involve linear mixed models with significance at p<0.05.

DISCUSSION

The integration of diverse techniques and analyses offers a comprehensive perspective on the onset and impact of MF, introducing a novel approach. Future research plans involve extending this protocol to explore the connection between brain neurotransmission and physical fatigue. This protocol will further advance our understanding of the complex interplay between the brain and fatigue.

Sleep deprivation increases the regularity of isometric torque fluctuations

The regularity of the fluctuations present in torque signals represent the adaptability of the motor control. While previous research showed how it is affected by neuromuscular fatigue and ageing, the underlying mechanisms remain unclear. It is currently under debate whether these changes are explained by central or peripheral neuromuscular mechanisms. Here, we experimentally manipulated the sleep of thirteen young adults through a supervised 24 h-sleep deprivation protocol. This study aimed to investigate the effect of sleep deprivation on the regularity of torque fluctuations, and other standard torque-related outcomes (Peak Torque - PT - and Rate of Torque Development - RTD). The participants were asked to perform knee extension maximal voluntary contractions (MVC) and submaximal knee extensions at 40% of MVC for 30 s. PT and RTD were calculated from the MVC and the regularity of the torque fluctuations was determined on the submaximal task through Sample Entropy (SampEn). In addition, rate of perceived effort (RPE) was collected. We found no significant changes in PT and RTD. The regularity of torque fluctuations significantly increased (i.e., a decrease in SampEn) after 24 h-sleep deprivation (PRE = 1.76 ± 0.268, POS24 = 1.71 ± 0.306; p = 0.044). Importantly, we found a negative correlation between RPE and SampEn relative changes after sleep deprivation. This study brings new insights towards the understanding of the underlying mechanisms that explain changes in torque fluctuations, demonstrating that these changes are not limited to neuromuscular processes but are also likely to be affected by other domains, such as psychological profile, which can indirectly affect the neural drive to the muscles.

Structural neural correlates of mental fatigue and reward-induced improvement in performance

Neuroimaging studies investigating the association between mental fatigue (henceforth fatigue) and brain physiology have identified many brain regions that may underly the cognitive changes induced by fatigue. These studies focused on the functional changes and functional connectivity of the brain relating to fatigue. The structural correlates of fatigue, however, have received little attention. To fill this gap, this study explored the associations of fatigue with cortical thickness of frontal and parietal regions. In addition, we aimed to explore the associations between reward-induced improvement in performance and neuroanatomical markers in fatigued individuals. Thirty-nine healthy volunteers performed the psychomotor vigilance task for 15 min (i.e., 3 time-on-task blocks of 5 min) out of scanner; followed by an additional rewarded block of the task lasting 5 min. Baseline high-resolution T1-weigthed MR images were obtained. Reaction time increased with time-on-task but got faster again in the rewarded block. Participants' subjective fatigue increased during task performance. In addition, we found that higher increase in subjective mental fatigue was associated with the cortical thickness of the following areas: bilateral precuneus, right precentral gyrus; right pars triangularis and left superior frontal gyrus. Our results suggest that individual differences in subjective mental fatigue may be explained by differences in the degree of cortical thickness of areas that are associated with motor processes, executive functions, intrinsic alertness and are parts of the default mode network.

Biomolecules of Muscle Fatigue in Metabolic Myopathies

Metabolic myopathies are a group of genetic disorders that affect the normal functioning of muscles due to abnormalities in metabolic pathways. These conditions result in impaired energy production and utilization within muscle cells, leading to limitations in muscle function with concomitant occurrence of related signs and symptoms, among which fatigue is one of the most frequently reported. Understanding the underlying molecular mechanisms of muscle fatigue in these conditions is challenging for the development of an effective diagnostic and prognostic approach to test targeted therapeutic interventions. This paper outlines the key biomolecules involved in muscle fatigue in metabolic myopathies, including energy substrates, enzymes, ion channels, and signaling molecules. Potential future research directions in this field are also discussed.

Computational mechanisms underlying the dynamics of physical and cognitive fatigue

The willingness to exert effort for reward is essential but comes at the cost of fatigue. Theories suggest fatigue increases after both physical and cognitive exertion, subsequently reducing the motivation to exert effort. Yet a mechanistic understanding of how this happens on a moment-to-moment basis, and whether mechanisms are common to both mental and physical effort, is lacking. In two studies, participants reported momentary (trial-by-trial) ratings of fatigue during an effort-based decision-making task requiring either physical (grip-force) or cognitive (mental arithmetic) effort. Using a novel computational model, we show that fatigue fluctuates from trial-to-trial as a function of exerted effort and predicts subsequent choices. This mechanism was shared across the domains. Selective to the cognitive domain, committing errors also induced momentary increases in feelings of fatigue. These findings provide insight into the computations underlying the influence of effortful exertion on fatigue and motivation, in both physical and cognitive domains.

Alpha and gamma EEG coherence during on-task and mind wandering states in schizophrenia

OBJECTIVE

Electroencephalographic (EEG) coherence is one of the most relevant physiological measures used to detect abnormalities in patients with schizophrenia. The present study applies a task-related EEG coherence approach to understand cognitive processing in patients with schizophrenia and healthy controls.

METHODS

EEG coherence for alpha and gamma frequency bands was analyzed in a group of patients with schizophrenia and a group of healthy controls during the performance of an ecological task of sustained attention. We compared EEG coherence when participants presented externally directed cognitive states (On-Task) and when they presented cognitive distraction episodes (Mind-Wandering).

RESULTS

Results reflect cortical differences between groups (higher coherence for schizophrenia in the frontocentral and fronto-temporal regions, and higher coherence for healthy-controls in the postero-central regions), especially in the On-Task condition for the alpha band, compared to Mind-Wandering episodes. Few individual differences in gamma coherence were found.

CONCLUSIONS

The current study provides evidence of neurophysiological differences underlying different cognitive states in schizophrenia and healthy controls.

SIGNIFICANCE

Differences between groups may reflect inhibitory processes necessary for the successful processing of information, especially in the alpha band, given its role in cortical inhibition processes. Patients may activate compensatory inhibitory mechanisms when performing the task, reflected in increased coherence in fronto-temporal regions.

Fatigue and Human Performance: An Updated Framework

Fatigue has been defined differently in the literature depending on the field of research. The inconsistent use of the term fatigue complicated scientific communication, thereby limiting progress towards a more in-depth understanding of the phenomenon. Therefore, Enoka and Duchateau (Med Sci Sports Exerc 48:2228-38, 2016, [3]) proposed a fatigue framework that distinguishes between trait fatigue (i.e., fatigue experienced by an individual over a longer period of time) and motor or cognitive task-induced state fatigue (i.e., self-reported disabling symptom derived from the two interdependent attributes performance fatigability and perceived fatigability). Thereby, performance fatigability describes a decrease in an objective performance measure, while perceived fatigability refers to the sensations that regulate the integrity of the performer. Although this framework served as a good starting point to unravel the psychophysiology of fatigue, several important aspects were not included and the interdependence of the mechanisms driving performance fatigability and perceived fatigability were not comprehensively discussed. Therefore, the present narrative review aimed to (1) update the fatigue framework suggested by Enoka and Duchateau (Med Sci Sports Exerc 48:2228-38, 2016, [3]) pertaining the taxonomy (i.e., cognitive performance fatigue and perceived cognitive fatigue were added) and important determinants that were not considered previously (e.g., effort perception, affective valence, self-regulation), (2) discuss the mechanisms underlying performance fatigue and perceived fatigue in response to motor and cognitive tasks as well as their interdependence, and (3) provide recommendations for future research on these interactions. We propose to define motor or cognitive task-induced state fatigue as a psychophysiological condition characterized by a decrease in motor or cognitive performance (i.e., motor or cognitive performance fatigue, respectively) and/or an increased perception of fatigue (i.e., perceived motor or cognitive fatigue). These dimensions are interdependent, hinge on different determinants, and depend on body homeostasis (e.g., wakefulness, core temperature) as well as several modulating factors (e.g., age, sex, diseases, characteristics of the motor or cognitive task). Consequently, there is no single factor primarily determining performance fatigue and perceived fatigue in response to motor or cognitive tasks. Instead, the relative weight of each determinant and their interaction are modulated by several factors.

The neural correlates of mental fatigue and reward processing: A task-based fMRI study

Increasing time spent on the task (i.e., the time-on-task (ToT) effect) often results in mental fatigue. Typical effects of ToT are decreasing levels of task-related motivation and the deterioration of cognitive performance. However, a massive body of research indicates that the detrimental effects can be reversed by extrinsic motivators, for example, providing rewards to fatigued participants. Although several attempts have been made to identify brain areas involved in mental fatigue and related reward processing, the neural correlates are still less understood. In this study, we used the psychomotor vigilance task to induce mental fatigue and blood oxygen-level-dependent functional magnetic resonance imaging to investigate the neural correlates of the ToT effect and the reward effect (i.e., providing extra monetary reward after fatigue induction) in a healthy young sample. Our results were interpreted in a recently proposed neurocognitive framework. The activation of the right middle frontal gyrus, right insula and right anterior cingulate gyrus decreased as fatigue emerged and the cognitive performance dropped. However, after providing an extra reward, the cognitive performance, as well as activation of these areas, increased. Moreover, the activation levels of all of the mentioned areas were negatively associated with reaction times. Our results confirm that the middle frontal gyrus, insula and anterior cingulate cortex play crucial roles in cost-benefit evaluations, a potential background mechanism underlying fatigue, as suggested by the neurocognitive framework.

Investigating the influence of an effort-reward interaction on cognitive fatigue in individuals with multiple sclerosis

This study examined whether an alteration in the effort-reward relationship, a theoretical framework based on cognitive neuroscience, could explain cognitive fatigue. Forty persons with MS and 40 healthy age- and education-matched cognitively healthy controls (HC) participated in a computerized switching task with orthogonal high- and low-demand (effort) and reward manipulations. We used the Visual Analog Scale of Fatigue (VAS-F) to assess subjective state fatigue before and after each condition during the task. We used mixed-effects models to estimate the association and interaction between effort and reward and their relationship to subjective fatigue and task performance. We found the high-demand condition was associated with increased VAS-F scores (p < .001), longer response times (RT) (p < .001) and lower accuracy (p < .001). The high-reward condition was associated with faster RT (p = .006) and higher accuracy (p = .03). There was no interaction effect between effort and reward on VAS-F scores or performance. Participants with MS reported higher VAS-F scores (p = .02). Across all conditions, participants with MS were slower (p < .001) and slower as a function of condition demand compared with HC (p < .001). This behavioural study did not find evidence that an effort-reward interaction is associated with cognitive fatigue. However, our findings support the role of effort in subjective cognitive fatigue and both effort and reward on task performance. In future studies, more salient reward manipulations could be necessary to identify effort-reward interactions on subjective cognitive fatigue.

An Investigation of the Effects of Brain Fatigue on the Sustained Attention of Intelligent Coal Mine VDT Operators

Intelligent mines require much more mental effort from visual display terminal (VDT) operators. Long periods of mental effort can easily result in operator fatigue, which further increases the possibility of operation error. Therefore, research into how brain fatigue affects the sustained attention of VDT operators in intelligent mines is important. The research methods were as follows: (1) Recruit 17 intelligent mine VDT operators as subjects. Select objective physiological indicators, such as reaction time, error rate, task duration, flicker fusion frequency, heart rate, electrodermal activity, and blink frequency, and combine these with the subjective Karolinska Sleepiness Scale to build a comprehensive brain fatigue evaluation system. (2) According to the fatigue-inducing experiment requirements, subjects are required to carry out mathematical operations in accordance with the rules during the presentation time, determine whether the results of the operations fall within the [7, 13] interval, and continue for 120 min to induce brain fatigue. (3) Perform the standard stimulus button response experiment of the sustained attention to response task, before and after brain fatigue, and compare each result. The results show that: (1) When the standard stimulus appeared in the EEG experiment, the amplitude of the early N100 component before and after brain fatigue was significantly different. When the bias stimulus appeared, the average amplitudes of the P200 component and the late positive component, before and after brain fatigue, were significantly different, suggesting that the brain fatigue of VDT workers in coal mines would reduce sustained attention; (2) After the 120 min of the continuous operation task, the subjects showed obvious brain fatigue. The objective brain fatigue was followed by an increase in reaction time, an increase in error rate, a decrease in flicker fusion frequency, an increase in heart rate, an increase in electrodermal current, an increase in the number of blinks, and a larger pupil diameter, and both the subjective and objective data indicated more significant changes in the subjects' brain fatigue at the 45th and 90th min. The results of the study could provide insight into the reduction in operational efficiency and safety of VDT operators in intelligent mines due to brain fatigue and further enrich the research in the area of brain fatigue in VDT operations.

Cognitive effects of prolonged continuous human-machine interaction: The case for mental state-based adaptive interfaces

Operators of complex systems across multiple domains (e.g., aviation, automotive, and nuclear power industry) are required to perform their tasks over prolonged and continuous periods of time. Mental fatigue as well as reduced cognitive flexibility, attention, and situational awareness all result from prolonged continuous use, putting at risk the safety and efficiency of complex operations. Mental state-based adaptive systems may be a solution to this problem. These systems infer the current mental state of an operator based on a selection of metrics ranging from operator independent measures (e.g., weather and time of day), to behavioral (e.g., reaction time and lane deviation) as well as physiological markers (e.g., electroencephalography and cardiac activity). The interaction between operator and system may then be adapted in one of many ways to mitigate any detected degraded cognitive state, thereby ensuring continued safety and efficiency. Depending on the task at hand and its specific problems, possible adaptations -usually based on machine learning estimations- e.g., include modifications of information, presentation modality or stimuli salience, as well as task scheduling. Research on adaptive systems is at the interface of several domains, including neuroergonomics, human factors, and human-computer interaction in an applied and ecological context, necessitating careful consideration of each of the aforementioned aspects. This article provides an overview of some of the key questions and aspects to be considered by researchers for the design of mental state-based adaptive systems, while also promoting their application during prolonged continuous use to pave the way toward safer and more efficient human-machine interaction.

Adiponectin and Nitric Oxide Deficiency-Induced Cognitive Impairment in Fatigued Home-Resident in Mature and Older Adults: A Case-Control Study

Objective

The present study explores the underlying factors of cognitive abilities in relation to the expression of adiponectin and nitric oxide, fatigue, and other cofounder variables such as physical activity, diabetes, and adiposity status in healthy home-resident mature and older adults.

Background

Fatigue has been shown to be correlated with many metabolic and psychiatric conditions, such as cognitive, neurological, musculoskeletal, and hormonal disorders, as well as physical and unhealthy lifestyles.

Methods

A total of 85 home residents aged 50-85 years participated in this case-control study. Mental, fatigue, and pain status were assessed by the cognitive assessment (LOTCA), fatigue questionnaire (CIS20r), and pain score (0-10). VO2 max and the prevalidated global physical activity questionnaire were used to estimate physical status. The levels of adiponectin, nitric oxide (NO), and variables related to diabetes, such as blood sugar and glycated hemoglobin (HbA1c %), were assessed using ELISA and spectrophotometric immunoassays.

Results

The participants were classified according to the CIS-fatigue score into two groups: the healthy group (n = 40) and the fatigue group (n = 45). In fatigued subjects, LOTCA scores as a measure of cognitive performance significantly decreased (65.97 ± 7.17; P = 0.01) as compared with healthy subjects (LOTCA scores, 94.2 ± 7.5). The results of cognitive performance domains (LOTCA seven-subset scores) showed a significant decrease in the scores of orientation, visual perception, spatial perception, motor praxis, vasomotor organization, thinking operations, attention, and concentration in older subjects with fatigue compared with healthy subjects. In addition, pain scores significantly increased, and the expression of both nitric oxide (NO) and adiponectin significantly reduced in older adults with fatigue as compared with healthy controls. The decline in cognitive abilities among older adults with fatigue is significantly associated with the CIS-fatigue score, sedentary lifestyle, obesity, pain status, diabetes, and reduction in the levels of nitric oxide (NO), and adiponectin. Moreover, in fatigued cases, the expression of both NO and adiponectin was significantly correlated with CIS-fatigue score, physical activity, obesity, and diabetes, which indicates its availability as diagnostic markers for cognition in mature and older adults with fatigue.

Conclusion

In the present study, the data concluded that cognitive abilities were significantly associated with the lower expression of adiponectin and NO as endothelial vascular markers in association with fatigue among home-resident older adults. In addition, the reduction in cognition was significantly affected by other parameters, such as diabetes, obesity, and unhealthy sedentary life activities. Moreover, the results might recommend the use of cellular adiponectin and NO as diagnostic indicators of cognitive abilities in fatigued mature and older adults. However, more studies on larger sample sizes are required.

Signal Detection Theory as a Novel Tool to Understand Cognitive Fatigue in Individuals With Multiple Sclerosis

Multiple Sclerosis (MS) affects 2.8 million persons worldwide. One of the most persistent, pervasive, and debilitating symptoms of MS is cognitive fatigue. While this has been known for over a century, cognitive fatigue has been difficult to study because patients' subjective (self-reported) cognitive fatigue has consistently failed to correlate with more objective measures, such as reaction time (RT) and accuracy. Here, we investigated whether more nuanced metrics of performance, specifically the metrics of Signal Detection Theory (SDT), would show a relationship to cognitive fatigue even if RT and accuracy did not. We also measured brain activation to see whether SDT metrics were related to activation in brain areas that have been shown to be sensitive to cognitive fatigue. Fifty participants (30 MS, 20 controls) took part in this study and cognitive fatigue was induced using four blocks of a demanding working memory paradigm. Participants reported their fatigue before and after each block, and their performance was used to calculate SDT metrics (Perceptual Certainty and Criterion) and RT and accuracy. The results showed that the SDT metric of Criterion (i.e., response bias) was positively correlated with subjective cognitive fatigue. Moreover, the activation in brain areas previously shown to be related to cognitive fatigue, such as the striatum, was also related to Criterion. These results suggest that the metrics of SDT may represent a novel tool with which to study cognitive fatigue in MS and other neurological populations. These results hold promise for characterizing cognitive fatigue in MS and developing effective interventions in the future.

Dynamic Reorganization of Functional Connectivity During Post-break Task Reengagement

Because of the undesired fatigue-related consequences, accumulating efforts have been made to find an effective intervention to alleviate the suboptimal cognitive function caused by mental fatigue. Nonetheless, limitations of intervention and evaluation methods may hinder the revealing of underlying neural mechanisms of fatigue recovery. Through the newly-developed dynamic functional connectivity (FC) analysis framework, this study aims to investigate the effects of two types of mid-task interventions (i.e., rest-break and moderate-intensity exercise-break) on the dynamic reorganization of FC during the execution of psychomotor vigilance test (PVT). Using a sliding window approach, temporal brain networks within each frequency band (i.e., δ, θ, α, & β) were estimated before and immediate after the intervention, and towards the end of the task to investigate the immediate and delayed effects respectively during post-break task reengagement. Behaviourally, similar beneficial effects of exercise- and rest-break on performance were observed, manifested by the immediate improvements after both interventions and a long-lasting influence towards the end of tasks. Moreover, temporal brain networks assessment showed significant immediate decreases of fluctuability, which followed by an increase of fluctuability towards the end of intervention tasks. Furthermore, the temporal nodal measure revealed the channels with significant differences across tasks were mainly resided in the fronto-parietal areas that exhibited interesting frequency-dependent distribution. The observations of immediate and delayed dynamic FC reorganizations extend previous fatigue-related intervention and static FC studies, and provide new insight into the dynamic characteristics of FC during post-break task reengagement.

Mental Fatigue Over 2 Elite Netball Seasons: A Case for Mental Fatigue to be Included in Athlete Self-Report Measures

PURPOSE

Mental fatigue is emerging as an important consideration for elite sporting performance, yet it is rarely monitored. The present study assessed changes in mental fatigue in professional team-sport athletes across 2 seasons and examined the relationship between mental fatigue and other athlete self-report measures of well-being.

METHODS

Elite netballers contracted to all teams competing in Australia's premier professional netball competition during the 2018 and 2019 seasons (N = 154) participated. Using 5-point Likert scales, mental fatigue, fatigue (physical), tiredness, sleep quality, stress, mood, and motivation were assessed daily across 2 seasons composed of 14 round and finals series.

RESULTS

The ratings of mental fatigue significantly changed during both seasons. In 2018, lower ratings of mental fatigue were reported in round 1 versus 3, 4, 6, 8, and 14; round 7 versus 6; and round 6 versus 10 (P < .05). In 2019, lower ratings of mental fatigue were identified for round 1 versus 3, 9, 10 to 14, and semifinal; round 2 versus 10 to 13; and 5 versus 10 to 12 (P < .05). Ordinal regression revealed significant differences between mental fatigue and physical fatigue (P < .001), tiredness (P < .001), stress (P < .001), mood (P < .001), and motivation (P < .05).

CONCLUSIONS

The present study found mental fatigue to significantly fluctuate across a season in elite netballers. Moreover, perceived mental fatigue differed from physical fatigue, tiredness, stress, mood, and motivation. The data impress the need for mental fatigue to be included as an independent measure of athlete well-being. Monitoring of mental fatigue can allow practitioners to implement strategies to manage its influence on performance.

Considerations regarding noncredible performance in the neuropsychological assessment of patients with multiple sclerosis: A case series

Determining the validity of data during clinical neuropsychological assessment is crucial for proper interpretation, and extensive literature has emphasized myriad methods of doing so in diverse samples. However, little research has considered noncredible presentation in persons with multiple sclerosis (pwMS). PwMS often experience one or more factors known to impact validity of data, including major neurocognitive impairment, psychological distress/psychogenic interference, and secondary gain. This case series aimed to illustrate the potential relationships between these factors and performance validity testing in pwMS. Six cases from an IRB-approved database containing pwMS referred for neuropsychological assessment at a large, academic medical center involving at least one of the above-stated factors were identified. Backgrounds, neuropsychological test data, and clinical considerations for each were reviewed. Interestingly, no pwMS diagnosed with major neurocognitive impairment was found to have noncredible performance, nor was any patient with noncredible performance in the absence of notable psychological distress. Given the variability of noncredible performance and multiplicity of factors affecting performance validity in pwMS, clinicians are strongly encouraged to consider psychometrically appropriate methods for evaluating validity of cognitive data in pwMS. Additional research aiming to elucidate base rates of, mechanisms begetting, and methods for assessing noncredible performance in pwMS is imperative.

Mental fatigue correlates with depression of task-related network and augmented DMN activity but spares the reward circuit

Long-lasting and demanding cognitive activity typically leads to mental fatigue (MF). Indirect evidence suggests that MF may be caused by altered motivational processes. Here, we hypothesized that if MF consists in an alteration of motivational states, brain functional changes induced by MF could specifically affect the brain motivation circuit. In order to test this hypothesis, we devised a functional neuroimaging protocol to detect altered brain activity in reward-related brain regions in relation to cognitively induced mental fatigue. Twenty-five healthy participants underwent a FATIGUE and a CONTROL session on different days. In the FATIGUE session, MF was induced by performing a demanding cognitive task (adapted Stroop task) during 90 min, whereas in the CONTROL session, participants were asked to read magazines for the same period of time. We measured the neural consequences of the MF induction during a working memory task (Missing Number task) while modulating extrinsic motivation with block-wise variations in monetary reward. We also tracked participants' momentary fatigue, anxiety state and intrinsic motivation prior to and following the MF inducement and measurement. Accuracy on the Missing Number Task was lower in the FATIGUE than in the CONTROL condition. Furthermore, subjective MF, but not its behavioral manifestations, was associated with hypoactivity of the task-evoked neural responses. Importantly, activity in regions modulated by reward showed no differences between FATIGUE and CONTROL sessions. In parallel, subjective MF correlated with increased on-task activity and resting-state functional connectivity in the default mode network. These results indicate that subjective mental fatigue is not associated with altered activity in the brain motivation circuit but rather with hypoactivity in task-specific brain regions as well as relative increases of activity and connectivity in the default mode network during and after the task.

EEG Coherence Metrics for Vigilance: Sensitivity to Workload, Time-on-Task, and Individual Differences

The vigilance decrement in performance is a significant operational issue in various applied settings. Psychophysiological methods for diagnostic monitoring of vigilance have focused on power spectral density measures from the electroencephalogram (EEG). This article addresses the diagnosticity of an alternative set of EEG measures, coherence between different electrode sites. Coherence metrics may index the functional connectivity between brain regions that supports sustained attention. Coherence was calculated for seven pre-defined brain networks. Workload and time-on-task factors primarily influenced alpha and theta coherence in anterior, central, and inter-hemispheric networks. Individual differences in coherence in inter-hemispheric, left intro-hemispheric and posterior networks correlated with performance. These findings demonstrate the potential applied utility of coherence metrics, although several methodological limitations and challenges must be overcome.

Biomarker-Informed Machine Learning Model of Cognitive Fatigue from a Heart Rate Response Perspective

Cognitive fatigue is a psychological state characterised by feelings of tiredness and impaired cognitive functioning arising from high cognitive demands. This paper examines the recent research progress on the assessment of cognitive fatigue and provides informed recommendations for future research. Traditionally, cognitive fatigue is introspectively assessed through self-report or objectively inferred from a decline in behavioural performance. However, more recently, researchers have attempted to explore the biological underpinnings of cognitive fatigue to understand and measure this phenomenon. In particular, there is evidence indicating that the imbalance between sympathetic and parasympathetic nervous activity appears to be a physiological correlate of cognitive fatigue. This imbalance has been indexed through various heart rate variability indices that have also been proposed as putative biomarkers of cognitive fatigue. Moreover, in contrast to traditional inferential methods, there is also a growing research interest in using data-driven approaches to assessing cognitive fatigue. The ubiquity of wearables with the capability to collect large amounts of physiological data appears to be a major facilitator in the growth of data-driven research in this area. Preliminary findings indicate that such large datasets can be used to accurately predict cognitive fatigue through various machine learning approaches. Overall, the potential of combining domain-specific knowledge gained from biomarker research with machine learning approaches should be further explored to build more robust predictive models of cognitive fatigue.

Effects of transcranial direct current stimulation on cognitive dysfunction in multiple sclerosis

BACKGROUND

Around 40%-70% of patients with multiple sclerosis (MS) may experience cognitive impairments during the course of their disease with detrimental effects on social and occupational activities. Transcranial direct current stimulation (tDCS has been investigated in pain, fatigue, and mood disorders related to MS, but to date, few studies have examined effects of tDCS on cognitive performance in MS.

OBJECTIVE

The current study aimed to investigate the effects of a multi-session tDCS protocol on cognitive performance and resting-state brain electrical activities in patients with MS.

METHODS

Twenty-four eligible MS patients were randomly assigned to real (anodal) or sham tDCS groups. Before and after 8 consecutive daily tDCS sessions over the left dorsolateral prefrontal cortex (DLPFC), patients' cognitive performance was assessed using the Cambridge Brain Sciences-Cognitive Platform (CBS-CP). Cortical electrical activity was also evaluated using quantitative electroencephalography (QEEG) analysis at baseline and after the intervention.

RESULTS

Compared to the sham condition, significant improvement in reasoning and executive functions of the patients in the real tDCS group was observed. Attention was also improved considerably but not statistically significantly following real tDCS. However, no significant changes in resting-state brain activities were observed after stimulation in either group.

CONCLUSION

Anodal tDCS over the left DLPFC appears to be a promising therapeutic option for cognitive dysfunction in patients with MS. Larger studies are required to confirm these findings and to investigate underlying neuronal mechanisms.

Increasing the Clinical Utility of the Paced Auditory Serial Addition Test: Normative Data for Standard, Dyad, and Cognitive Fatigability Scoring

BACKGROUND

No normative data currently exist that would allow clinicians to decide whether the degree of cognitive fatigability (CF) experienced in individuals with neurologic disease is greater than expected when compared with a healthy population.

OBJECTIVE

To establish discrete and regression-based normative data for CF as defined by an objective decrement in performance over the course of a cognitive task; namely, the Paced Auditory Serial Addition Test (PASAT). In addition, to develop discrete and regression-based normative data for PASAT performance scores-dyad and percent dyad-for which data do not currently exist.

METHOD

One hundred and seventy-eight healthy individuals completed the PASAT as part of a larger neuropsychological battery. PASAT performance scores including total correct responses, total dyads, and percent dyad were calculated. CF scores were calculated by comparing the individuals' performance on the first half (or third) of the test to their performance on the last half (or third) in order to capture any within-task performance decrements over time.

RESULTS

Both age- and education-based discrete normative data and demographically adjusted (sex, age, and education) regression-based formulas were established for the PASAT performance scores and the CF scores.

CONCLUSION

The development of these normative data will allow for greater interpretation of an individual's performance on the PASAT, beyond just the total correct score, through the use of dyad and percent dyad scores. With respect to CF, these data will allow clinicians to objectively quantify decrements in cognitive performance over time better in individuals with neurologic diseases.

Brain Microstructural Properties Related to Subjective Well-Being: Diffusion Tensor Imaging Analysis

Although it is known that health is not merely the absence of disease, the positive aspects of mental health have been less comprehensively researched compared with its negative aspects. Subjective well-being (SWB) is one of the indicators of positive psychology, and high SWB is considered to benefit individuals in multiple ways. However, the neural mechanisms underlying individual differences in SWB remain unclear, particularly in terms of brain microstructural properties as detected by diffusion tensor imaging. The present study aimed to investigate the relationship between measurements of diffusion tensor imaging [mean diffusivity (MD) and fractional anisotropy] and the degree of SWB as measured using a questionnaire. Voxel-based analysis was used to investigate the association between MD and SWB scores in healthy young adults (age, 20.7 ± 1.8 years; 695 males and 514 females). Higher levels of SWB were found to be associated with lower MD in areas surrounding the right putamen, insula, globus pallidus, thalamus and caudate. These results indicated that individual SWB is associated with variability in brain microstructural properties.

Quantitative EEG in sports: performance level estimation of professional female soccer players

Purpose

Measuring the peak performance of athletes remains a challenge in movement science and sports psychology. Non-invasive quantitative electroencephalography (QEEG) recordings can be used to analyze various factors in sports psychology.

Method

In this context, sports-related psychological factors were used to estimate the performance of Thai professional female soccer players before a competition. The QEEG recordings of thirty-two players were recorded three times: twice before a competition (once a week) and a week after a competition. Four factors of sports psychology were estimated and observed: anxiety, perceptual response to an acute bout of brain activity, assertiveness, and brain central fatigue. A brain topographic map (absolute power) and brain connectivity (coherence and amplitude asymmetry) data were used to analyze sports-related psychological factors. These factors were measurable based on the brain activity of the athletes and could be used to evaluate their performance during competitions by using QEEG values.

Results

Sports-related psychological performance was estimated by Pearson's correlation coefficients, which revealed that a quick perceptual response to an acute bout of brain activity could predict an athlete's performance during competition (r = .584, p = .000). Additionally, Spearman's correlation coefficients were used to estimate athletes performance. The results revealed a strong relationship ( r s =.634, p = .000), which was derived from the summation of anxiety and perceptual response to an acute bout of brain activity.

Conclusion

Consequently, the results of the present study can provide information to help staff coaches to choose the best performing players, representing an alternative method for accurately selecting key players in the competitive sports community.

Resistance-induced brain activity changes during cycle ergometer exercises

Background

EEGs are frequently employed to measure cerebral activations during physical exercise or in response to specific physical tasks. However, few studies have attempted to understand how exercise-state brain activity is modulated by exercise intensity.

Methods

Ten healthy subjects were recruited for sustained cycle ergometer exercises at low and high resistance, performed on two separate days a week apart. Exercise-state EEG spectral power and phase-locking values (PLV) are analyzed to assess brain activity modulated by exercise intensity.

Results

The high-resistance exercise produced significant changes in beta-band PLV from early to late pedal stages for electrode pairs F3-Cz, P3-Pz, and P3-P4, and in alpha-band PLV for P3-P4, as well as the significant change rate in alpha-band power for electrodes C3 and P3. On the contrary, the evidence for changes in brain activity during the low-resistance exercise was not found.

Conclusion

These results show that the cortical activation and cortico-cortical coupling are enhanced to take on more workload, maintaining high-resistance pedaling at the required speed, during the late stage of the exercise period.

Mental Fatigue and Sport-Specific Psychomotor Performance: A Systematic Review

BACKGROUND

Mental fatigue (MF) is a psychobiological state that impairs endurance performance in healthy athletes. Recently, multiple studies indicated that MF could also impair sport-specific psychomotor performance (SSPP). Nevertheless, a systematic overview detailing the effects of MF on SSPP is currently lacking.

OBJECTIVE

The objective of this study is to collate relevant literature and examine the effect of MF on SSPP. A secondary aim was to create an overview of the potential subjective and physiological factors underlying this MF effect.

METHODS

PubMed (MEDLINE), Web of Science, PsycINFO and SPORTDiscus were searched (5th of November 2020). Studies were eligible when study outcomes encompassed any form of SSPP skill in a sport-specific context, the intervention was targeted to induce MF, and the population included healthy individuals. The presence of a manipulation check, to indicate the successful induction of MF, was obligatory for inclusion. Secondary outcomes were all outcomes (either physiological or psychological) that could explain the underlying mechanisms of the effect of MF on SSPP.

RESULTS

In total, 21 papers were included. MF was successfully induced in all but two studies, which were excluded from further analysis. MF negatively impacts a myriad of SSPP outcomes, including decision-making, reaction time and accuracy outcomes. No changes in physiological outcomes, that could underlie the effect of MF, were reported. Subjectively, only ratings of perceived of exertion increased due to MF in some studies.

CONCLUSIONS

Overall, the selected papers indicated that MF negatively affects SSPP. Research that assesses brain function, while evaluating the effect of MF on SSPP is essential to create further insight.

Using Signal Detection Theory to Better Understand Cognitive Fatigue

When we are fatigued, we feel that our performance is worse than when we are fresh. Yet, for over 100 years, researchers have been unable to identify an objective, behavioral measure that covaries with the subjective experience of fatigue. Previous work suggests that the metrics of signal detection theory (SDT)-response bias (criterion) and perceptual certainty (d')-may change as a function of fatigue, but no work has yet been done to examine whether these metrics covary with fatigue. Here, we investigated cognitive fatigue using SDT. We induced fatigue through repetitive performance of the n-back working memory task, while functional magnetic resonance imaging (fMRI) data was acquired. We also assessed cognitive fatigue at intervals throughout. This enabled us to assess not only whether criterion and d' covary with cognitive fatigue but also whether similar patterns of brain activation underlie cognitive fatigue and SDT measures. Our results show that both criterion and d' were correlated with changes in cognitive fatigue: as fatigue increased, subjects became more conservative in their response bias and their perceptual certainty declined. Furthermore, activation in the striatum of the basal ganglia was also related to cognitive fatigue, criterion, and d'. These results suggest that SDT measures represent an objective measure of cognitive fatigue. Additionally, the overlap and difference in the fMRI results between cognitive fatigue and SDT measures indicate that these measures are related while also separate. In sum, we show the relevance of SDT measures in the understanding of fatigue, thus providing researchers with a new set of tools with which to better understand the nature and consequences of cognitive fatigue.

Sustaining Attention for a Prolonged Duration Affects Dynamic Organizations of Frequency-Specific Functional Connectivity

Sustained attention encompasses a cascade of fundamental functions. The human ability to implement a sustained attention task is supported by brain networks that dynamically formed and dissolved through oscillatory synchronization. The decrement of vigilance induced by prolonged task engagement affects sustained attention. However, little is known about which stage or combinations are affected by vigilance decrement. Here, we applied an analysis framework composed of weighted phase lag index (wPLI) and tensor component analysis (TCA) to an EEG dataset collected during 80 min sustained attention task to examine the electrophysiological basis of such effect. We aimed to characterize the phase-coupling networks to untangle different phases involved in sustained attention and study how they are modulated by vigilance decrement. We computed the time–frequency domain wPLI from each block and subject and constructed a fourth-order tensor, containing the time, frequency, functional connectivity (FC), and blocks × subjects. This tensor was subjected to the TCA to identify the interacted and low-dimensional components representing the frequency-specific dynamic FC (fdFC). We extracted four types of neuromakers during a sustained attention task, namely the pre-stimulus alpha right-lateralized parieto-occipital FC, the post-stimulus theta fronto-parieto-occipital FC, delta fronto-parieto-occipital FC, and beta right/left sensorimotor FCs. All these fdFCs were impaired by vigilance decrement. These fdFCs, except for the beta left sensorimotor network, were restored by rewards, although the restoration by reward in the beta right sensorimotor network was transient. These findings provide implications for dissociable effects of vigilance decrement on sustained attention by utilizing the tensor-based framework.

Effects of Midfrontal Brain Stimulation on Sustained Attention

Sustained attention is defined as the ability to maintain attention over longer periods of time, which typically declines with time on task (i.e., the vigilance decrement). Previous studies have suggested an important role for the dorsomedial prefrontal cortex (mPFC) in sustained attention. In two experiments, we aimed to enhance sustained attention by applying transcranial electrical current stimulation over the mPFC during a sustained attention task. In the first experiment, we applied transcranial direct current stimulation (tDCS) in a between-subject design (n = 97): participants received either anodal, cathodal, or sham stimulation. Contrary to our prediction, we found no effect of stimulation on the vigilance decrement. In the second experiment, participants received theta and alpha transcranial alternating current stimulation (tACS) in two separate sessions (n = 47, within-subject design). Here, we found a frequency-dependent effect on the vigilance decrement, such that contrary to our expectation, participants’ performance over time became worse after theta compared with alpha stimulation. However, this result needs to be interpreted with caution given that this effect could be driven by differential side effects between the two stimulation frequencies. To conclude, across two studies, we were not able to reduce the vigilant decrement using tDCS or theta tACS.

The Maximum Eigenvalue of the Brain Functional Network Adjacency Matrix: Meaning and Application in Mental Fatigue Evaluation

The maximum eigenvalue of the adjacency matrix (AM) has been supposed to contain rich information about the corresponding network. An experimental study focused on revealing the meaning and application of the maximum eigenvalue is missing. To this end, AM was constructed using mutual information (MI) to determine the functional connectivity with electroencephalogram (EEG) data recorded with a mental fatigue model, and then was converted into both binary and weighted brain functional network (BFN) and corresponding random networks (RNs). Both maximum eigenvalue and corresponding network characters in BFNs and RNs were considered to explore the changes during the formation of mental fatigue. The results indicated that large maximum eigenvalue means more edges in the corresponding network, along with a high degree and a short characteristic path length both in weighted and binary BFNs. Interestingly, the maximum eigenvalue of AM was always a little larger than that of the corresponding random matrix (RM), and had an obvious linearity with the sum of the AM elements, indicating that the maximum eigenvalue can be able to distinguish the network structures which have the same mean degree. What is more, the maximum eigenvalue, which increased with the deepening of mental fatigue, can become a good indicator for mental fatigue estimation.

EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy

Background

Electroencephalography (EEG)-based brain-computer interface (BCI) systems are mainly divided into three major paradigms: motor imagery (MI), event-related potential (ERP), and steady-state visually evoked potential (SSVEP). Here, we present a BCI dataset that includes the three major BCI paradigms with a large number of subjects over multiple sessions. In addition, information about the psychological and physiological conditions of BCI users was obtained using a questionnaire, and task-unrelated parameters such as resting state, artifacts, and electromyography of both arms were also recorded. We evaluated the decoding accuracies for the individual paradigms and determined performance variations across both subjects and sessions. Furthermore, we looked for more general, severe cases of BCI illiteracy than have been previously reported in the literature.

Results

Average decoding accuracies across all subjects and sessions were 71.1% (± 0.15), 96.7% (± 0.05), and 95.1% (± 0.09), and rates of BCI illiteracy were 53.7%, 11.1%, and 10.2% for MI, ERP, and SSVEP, respectively. Compared to the ERP and SSVEP paradigms, the MI paradigm exhibited large performance variations between both subjects and sessions. Furthermore, we found that 27.8% (15 out of 54) of users were universally BCI literate, i.e., they were able to proficiently perform all three paradigms. Interestingly, we found no universally illiterate BCI user, i.e., all participants were able to control at least one type of BCI system.

Conclusions

Our EEG dataset can be utilized for a wide range of BCI-related research questions. All methods for the data analysis in this study are supported with fully open-source scripts that can aid in every step of BCI technology. Furthermore, our results support previous but disjointed findings on the phenomenon of BCI illiteracy.

Effects of Mental Fatigue on Small-World Brain Functional Network Organization

Brain functional network has been widely applied to investigate brain function changes among different conditions and proved to be a small-world-like network. But seldom researches explore the effects of mental fatigue on the small-world brain functional network organization. In the present study, 20 healthy individuals were included to do a consecutive mental arithmetic task to induce mental fatigue, and scalp electroencephalogram (EEG) signals were recorded before and after the task. Correlations between all pairs of EEG channels were determined by mutual information (MI). The resulting adjacency matrices were converted into brain functional networks by applying a threshold, and then, the clustering coefficient (C), characteristic path length (L), and corresponding small-world feature were calculated. Through performing analysis of variance (ANOVA) on the mean MI for every EEG rhythm, only the data of α1 rhythm during the task state were emerged for the further explorations of mental fatigue. For a wide range of thresholds, C increased and L and small-world feature decreased with the deepening mental fatigue. The pattern of the small-world characteristic still existed when computed with a constant degree. Our present findings indicated that more functional connectivities were activated at the mental fatigue stage for efficient information transmission and processing, and mental fatigue can be characterized by a reduced small-world network characteristic. Our results provide a new perspective to understand the neural mechanisms of mental fatigue based on complex network theories.

Cross-Modal Conflict Increases With Time-on-Task in a Temporal Discrimination Task

The modality appropriateness hypothesis argues that the auditory modality is preferred over the visual modality in tasks demanding temporal operations; hence, we predicted that responses to visual stimuli would be more sensitive to the detrimental effect of Time-on-Task. We used a bimodal temporal discrimination task. The factors were durational congruency between the modalities and the direction of modality-transmission. Participants needed to decide the duration of the cued stimulus (visual or auditory). The first five blocks of the task lasted about 1.5 h without rest [Time-on-Task (ToT) period]. The participants then had a 12-min break followed by an additional block of trials. Subjective fatigue, reaction time, error rates, and electrocardiographic data were recorded. In the visual modality, we found an enhanced congruency effect as a function of ToT. The cost of attentional shifting was higher in the auditory modality, but remained constant, suggesting that processing of auditory stimuli is robust against the effects of fatigue. Performance did not improve after the break, indicating that the effects of fatigue could not be overcome by taking a brief break. The heart rate variability (HRV) data showed that vagal inhibition increased with ToT, but this increase was not associated with the changes in performance.

Electroencephalography theta/beta ratio covaries with mind wandering and functional connectivity in the executive control network

The ratio between frontal resting‐state electroencephalography (EEG) theta and beta frequency power (theta/beta ratio, TBR) is negatively related to cognitive control. It is unknown which psychological processes during resting state account for this. Increased theta and reduced beta power are observed during mind wandering (MW), and MW is related to decreased connectivity in the executive control network (ECN) and increased connectivity in the default mode network (DMN). The goal of this study was to test if MW‐related fluctuations in TBR covary with such functional variation in ECN and DMN connectivity and if this functional variation is related to resting‐state TBR. Data were analyzed for 26 participants who performed a 40‐min breath‐counting task and reported the occurrence of MW episodes while EEG was measured and again during magnetic resonance imaging. Frontal TBR was higher during MW than controlled thought and this was marginally related to resting‐state TBR. DMN connectivity was higher and ECN connectivity was lower during MW. Greater ECN connectivity during focus than MW was correlated to lower TBR during focus than MW. These results provide the first evidence of the neural correlates of TBR and its functional dynamics and further establish TBR's usefulness for the study of executive control, in normal and potentially abnormal psychology.

Brain Complex Network Characteristic Analysis of Fatigue during Simulated Driving Based on Electroencephalogram Signals

Fatigued driving is one of the major causes of traffic accidents. Frequent repetition of driving behavior for a long time may lead to driver fatigue, which is closely related to the central nervous system. In the present work, we designed a fatigue driving simulation experiment and collected the electroencephalogram (EEG) signals. Complex network theory was introduced to study the evolution of brain dynamics under different rhythms of EEG signals during several periods of the simulated driving. The results show that as the fatigue degree deepened, the functional connectivity and the clustering coefficients increased while the average shortest path length decreased for the delta rhythm. In addition, there was a significant increase of the degree centrality in partial channels on the right side of the brain for the delta rhythm. Therefore, it can be concluded that driving fatigue can cause brain complex network characteristics to change significantly for certain brain regions and certain rhythms. This exploration may provide a theoretical basis for further finding objective and effective indicators to evaluate the degree of driving fatigue and to help avoid fatigue driving.

Effects of scheduled manual driving on drowsiness and response to take over request: A simulator study towards understanding drivers in automated driving

Because current automated vehicles have operational limitations, it is important to ensure that the fallback-ready driver is able to perform appropriately when required to take over control of the vehicle. However, time-related increase in driver drowsiness is well-known, and drowsy driving can affect response to take-over request (TOR). It was previously reported that a scheduled period of manual driving during automated driving was beneficial in maintaining driver arousal level. The present driving simulator study investigates the effects of scheduled manual driving on driver drowsiness and performance, as well as age differences therein. A total of 115 participants, whose gender was balanced and age was distributed uniformly from 20 to 70 years, drove an automated vehicle for 31 min, and a TOR was prompted before a collision event. A between-subjects design comprised two conditions: with versus without a scheduled 10-min interval of manual driving that ended 10 min before TOR. The Karolinska Sleepiness Scale and eyeblink durations estimated from electrooculograms (EOG) were used to subjectively and objectively measure participant's drowsiness. Reaction time, standard deviation of steering wheel angle, and minimum Time-to-Collison (TTC) were extracted to measure driver performance in response to TOR. The alleviating effect on drowsiness of 10-min scheduled manual driving became non-significant after another 10-min period of automated driving. Although the scheduled manual driving had no significant effect for younger drivers, older drivers reacted significantly more slowly in both steering and braking at the critical event. These findings provide essential insights for human-vehicle interactions: Scheduled manual driving cannot maintain drivers' arousal level for 10 min afterwards, and for older drivers, it would be better to avoid unnecessary task-switching between manual and automated driving.

Sustaining attention for a prolonged period of time increases temporal variability in cortical responses

Our ability to stay focused is limited: prolonged performance of a task typically results in mental fatigue and decrements in performance over time. This so-called vigilance decrement has been attributed to depletion of attentional resources, though other factors such as reductions in motivation likely also play a role. In this study, we examined three electroencephalography (EEG) markers of attentional control, to elucidate which stage of attentional processing is most affected by time-on-task and motivation. To elicit the vigilance decrement, participants performed a sustained attention task for 80 min without breaks. After 60 min, participants were motivated by an unexpected monetary incentive to increase performance in the final 20 min. We found that task performance and self-reported motivation declined rapidly, reaching stable levels well before the motivation manipulation was introduced. Thereafter, motivation increased back up to the initial level, and remained there for the final 20 min. While task performance also increased, it did not return to the initial level, and fell to the lowest level overall during the final 10 min. This pattern of performance changes was mirrored by the trial-to-trial consistency of the phase of theta (3-7 Hz) oscillations, an index of the variability in timing of the neural response to the stimulus. As task performance decreased, temporal variability increased, suggesting that attentional stability is crucial for sustained attention performance. The effects of attention on our two other EEG measures-early P1/N1 event-related potentials (ERPs) and pre-stimulus alpha (9-14 Hz) power-did not change with time-on-task or motivation. In sum, these findings show that the vigilance decrement is accompanied by a decline in only some facets of attentional control, which cannot be fully brought back online by increases in motivation. The vigilance decrement might thus not occur due to a single cause, but is likely multifactorial in origin.

Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment

Previous studies exploring driving drowsiness utilized spectral power and functional connectivity without considering between-frequency and more complex synchronizations. To complement such lacks, we explored inter-regional synchronizations based on the topographical and dynamic properties between frequency bands using high-order functional connectivity (HOFC) and envelope correlation. We proposed the dynamic interactions of HOFC, associated-HOFC, and a global metric measuring the aggregated effect of the functional connectivity. The EEG dataset was collected from 30 healthy subjects, undergoing two driving sessions. The two-session setting was employed for evaluating the metric reliability across sessions. Based on the results, we observed reliably significant metric changes, mainly involving the alpha band. In HOFC_θα , HOFC_αβ , associated- HOFC_θα , and associated- HOFC_αβ , the connection-level metrics in frontal-central, central-central, and central-parietal/occipital areas were significantly increased, indicating a dominance in the central region. Similar results were also obtained in the HOFC_θαβ and aHOFC_θαβ . For dynamic-low-order-FC and dynamic-HOFC, the global metrics revealed a reliably significant increment in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated- HOFC_α and associated- HOFC_θα also exhibited reliably significant differences. This paper demonstrated that within-band and between-frequency topographical and dynamic FC can provide complementary information to the traditional individual-band LOFC for assessing driving drowsiness.

The relationship between outcome prediction and cognitive fatigue: A convergence of paradigms

Cognitive fatigue is common after strenuous cognitive effort. A large body of literature has implicated a network of brain areas in fatigue, including the basal ganglia and cortical areas including ventro-medal prefrontal cortex and anterior cingulate cortex (ACC). Furthermore, the ACC has been shown to be involved in processes such as error and conflict monitoring, outcome prediction, and effort processing. Thus, the ACC appears to be one common denominator between clinical work on fatigue and research on outcome prediction and effort. In the present study, we examined whether the same region of the ACC is activated during the processing of errors and fatigue. Cognitive fatigue was induced by having subjects perform a difficult working memory task, during which they rated on-task fatigue. Activation associated with error processing was determined by using error trials on the working memory task. After localizing the region engaged in error processing, we evaluated whether there was a relationship between BOLD activation of that region and on-task fatigue scores. The results showed that as subjects became more fatigued, they responded with longer latencies and increased accuracy for the more difficult task. Moreover, the ACC areas that were activated by error processing were also associated with fatigue. These results suggest that cognitive fatigue may be related to changes in effort and reward. We speculate that as the brain detects these changes, cognitive fatigue is generated as a way for the brain to signal itself that the effort required for the task no longer merits the rewards received for performing it.

The Effects of Mental Fatigue on Physical Performance: A Systematic Review

BACKGROUND

Mental fatigue is a psychobiological state caused by prolonged periods of demanding cognitive activity. It has recently been suggested that mental fatigue can affect physical performance.

OBJECTIVE

Our objective was to evaluate the literature on impairment of physical performance due to mental fatigue and to create an overview of the potential factors underlying this effect.

METHODS

Two electronic databases, PubMed and Web of Science (until 28 April 2016), were searched for studies designed to test whether mental fatigue influenced performance of a physical task or influenced physiological and/or perceptual responses during the physical task. Studies using short (<30 min) self-regulatory depletion tasks were excluded from the review.

RESULTS

A total of 11 articles were included, of which six were of strong and five of moderate quality. The general finding was a decline in endurance performance (decreased time to exhaustion and self-selected power output/velocity or increased completion time) associated with a higher than normal perceived exertion. Physiological variables traditionally associated with endurance performance (heart rate, blood lactate, oxygen uptake, cardiac output, maximal aerobic capacity) were unaffected by mental fatigue. Maximal strength, power, and anaerobic work were not affected by mental fatigue.

CONCLUSION

The duration and intensity of the physical task appear to be important factors in the decrease in physical performance due to mental fatigue. The most important factor responsible for the negative impact of mental fatigue on endurance performance is a higher perceived exertion.

A Longitudinal Evaluation of Cognitive Fatigue on a Task of Sustained Attention in Early Relapsing-Remitting Multiple Sclerosis

Background

Cognitive fatigue can be objectively measured on tasks of sustained attention and can be defined as decreased performance as a result of sustained cognitive effort. Individuals with multiple sclerosis (MS) early in their disease are vulnerable to cognitive fatigue, although this has yet to be evaluated longitudinally. We aimed to evaluate cognitive fatigue over a 3-year interval in individuals with early-phase relapsing-remitting MS (RRMS). The sensitivity of the Paced Auditory Serial Addition Test (PASAT) at detecting cognitive fatigue was evaluated, as was the impact of scoring method.

Methods

32 people with MS and 32 controls completed the 3- and 2-second PASAT (PASAT-3″ and -2″) as a measure of sustained attention at baseline and 3-year follow-up.

Results

Performance on the PASAT remained stable across time, with improvement noted on the PASAT-2″ likely due to practice and the small sample size. Cognitive fatigue was noted at both times, although sensitivity varied based on scoring method. No evidence of worsening cognitive fatigue was noted over time. The MS group performed worse only when cognitive fatigue was the outcome variable.

Conclusions

Although individuals with MS continue to be vulnerable to cognitive fatigue at follow-up, severity does not seem to increase with time. Cognitive fatigue may be a more sensitive marker of cognitive impairment than overall task performance in those with early-phase RRMS, which has important implications given that clinically only task performance is typically assessed.

A Taxonomy of Fatigue Concepts and Their Relation to Hearing Loss

Fatigue is common in individuals with a variety of chronic health conditions and can have significant negative effects on quality of life. Although limited in scope, recent work suggests persons with hearing loss may be at increased risk for fatigue, in part due to effortful listening that is exacerbated by their hearing impairment. However, the mechanisms responsible for hearing loss-related fatigue, and the efficacy of audiologic interventions for reducing fatigue, remain unclear. To improve our understanding of hearing loss-related fatigue, as a field it is important to develop a common conceptual understanding of this construct. In this article, the broader fatigue literature is reviewed to identify and describe core constructs, consequences, and methods for assessing fatigue and related constructs. Finally, the current knowledge linking hearing loss and fatigue is described and may be summarized as follows: Hearing impairment may increase the risk of subjective fatigue and vigor deficits; adults with hearing loss require more time to recover from fatigue after work and have more work absences; sustained, effortful, listening can be fatiguing; optimal methods for eliciting and measuring fatigue in persons with hearing loss remain unclear and may vary with listening condition; and amplification may minimize decrements in cognitive processing speed during sustained effortful listening. Future research is needed to develop reliable measurement methods to quantify hearing loss-related fatigue, explore factors responsible for modulating fatigue in people with hearing loss, and identify and evaluate potential interventions for reducing hearing loss-related fatigue.

Mean Diffusivity in the Dopaminergic System and Neural Differences Related to Dopaminergic System

BACKGROUND

The mean diffusivity (MD) parameter obtained by diffusion tensor imaging provides a measure of how freely water molecules move in brain tissue. Greater tissue density conferred by closely arrayed cellular structures is assumed to lower MD by inhibiting the free diffusion of water molecules.

METHODS

In this paper, we review studies showing MD variation among regions of the brain dopaminergic system (MDDS), especially subcortical structures such as the putamen, caudate nucleus, and globus pallidus, in different conditions with known associations to dopaminergic system function or dysfunction. The methodologies and background related to MD and MDDS are also discussed.

RESULTS

Past studies indicate that MDDS is sensitive to pathological derangement of dopaminergic activity, neural changes caused by cognitive and pharmacological interventions that are known to affect the dopaminergic system, and individual character traits related to dopaminergic function.

CONCLUSION

These results suggest that MDDS can be one useful tool to tap the neural differences related to the dopaminergic system.

Effect of Enzogenol® Supplementation on Cognitive, Executive, and Vestibular/Balance Functioning in Chronic Phase of Concussion

This study examined the feasibility of Enzogenol® as a potential treatment modality for concussed individuals with residual symptoms in the chronic phase. Forty-two student-athletes with history of sport-related concussion were enrolled, comparing Enzogenol® versus placebo. Testing was conducted using virtual reality (VR) and electroencephalography (EEG), with neuropsychological (NP) tasks primarily used to induce cognitive challenges. After six weeks, the Enzogenol® group showed enhanced frontal-midline theta, and decreased parietal theta power, indicating reduced mental fatigue. Subjects enrolled in the Enzogenol® group also self-reported reduced mental fatigue and sleep problems. This suggests that Enzogenol® has the potential to improve brain functioning in the chronic phase of concussion.