Individualized Mental Fatigue Does Not Impact Neuromuscular Function and Exercise Performance.

INTRODUCTION: Recent studies have questioned previous empirical evidence that mental fatigue negatively impacts physical performance. The purpose of this study was to investigate the critical role of individual differences in mental fatigue susceptibility by analyzing the neurophysiological and physical responses to an individualized mental fatigue task. METHODS: In a preregistered ( https://osf.io/xc8nr/ ), randomized, within-participant design experiment, 22 recreational athletes completed a time to failure test at 80% of their peak power output under mental fatigue (individual mental effort) or control (low mental effort). Before and after the cognitive tasks, subjective feeling of mental fatigue, neuromuscular function of the knee extensors, and corticospinal excitability were measured. Sequential Bayesian analysis until it reached strong evidence in favor of the alternative hypothesis (BF 10 > 6) or the null hypothesis (BF 10 < 1/6) were conducted. RESULTS: The individualized mental effort task resulted in a higher subjective feeling of mental fatigue in the mental fatigue condition (0.50 (95% confidence interval (CI), 0.39-0.62)) arbitrary units compared with control (0.19 (95% CI, 0.06-0.339)) arbitrary unit. However, exercise performance was similar in both conditions (control: 410 (95% CI, 357-463) s vs mental fatigue: 422 (95% CI, 367-477) s, BF 10 = 0.15). Likewise, mental fatigue did not impair knee extensor maximal force-generating capacity (BF 10 = 0.928) and did not change the extent of fatigability or its origin after the cycling exercise. CONCLUSIONS: There is no evidence that mental fatigue adversely affects neuromuscular function or physical exercise; even if mental fatigue is individualized, computerized tasks seem not to affect physical performance.

Passive visual stimulation induces fatigue under conditions of high arousal elicited by auditory tasks.

Theories of cognitive fatigue disagree on whether performance decrement is caused by motivational or functional alterations. Here, drawing inspiration from the habituation and visual adaptation literature, we tested the assumption that keeping neural networks active for an extensive period of time entails consequences at the subjective and objective level-the defining characteristics of fatigue-when confounds such as motivation, boredom, and level of skill are controlled. In Experiment 1, we revealed that passive visual stimulation affected the performance of a subsequent task that was carried out in the same portion of visual space. While under conditions of low cognitive load and arousal, participants improved their performance in the stimulated quadrant; the reverse was observed under high arousal conditions. This latter performance decrement correlated also with the reported subjective level of fatigue and occurred while neural responses to the saturating stimulus remained constant, as assessed through steady-state EEG. In subsequent experiments, we replicated and further characterized this performance deterioration effect, revealing its specificity to the stimulated eye and stimulus orientation. Across the three experiments, the decrease in performance was correlated with pupil-linked arousal, suggesting its mediating effect in this phenomenon. In sum, we show that repeated stimulation of neural networks under high-arousal conditions leads to their altered functional performance, a mechanism which may play a role in the development of global cognitive fatigue. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Impaired Sequential but Preserved Motor Memory Consolidation in Multiple Sclerosis Disease.

Studies investigating motor learning in patients with multiple sclerosis (MS) disease highlighted that MS patients exhibit similar learning performance than healthy controls, but that learning can be hampered by the progression of MS eventually leading to impaired efficiency of subcortical-cortical networks. We aimed at investigating whether the long-term, overnight consolidation of sequential motor memories is preserved in MS disease. Thirty-one patients with MS and two healthy control groups (27 young and 14 middle age) were tested over two consecutive days using a serial reaction time task. Performance was tested (a) 20 min after the end of learning at Day 1 to monitor transient offline, short-term increase in motor and sequential performance and (b) after 24 h on Day 2 to quantify overnight delayed changes in performance reflecting memory consolidation. Besides a slower overall RT in patients with MS, motor performance similarly evolved in all groups. Sequence learning as assessed by interference effects was similar in patients with MS and both control groups on Day 1 (Learning and 20-min test). In contrast, while interference effects keep increasing on Day 2 after 24 h (Relearning) in healthy control groups, it reverted to levels reached at the end of learning for patients with MS. Long-term consolidation of sequential knowledge is impaired in patients with MS. At the motor level, learning and overnight consolidation abilities are preserved in MS disease.

Bimodal EEG-fNIRS in Neuroergonomics. Current Evidence and Prospects for Future Research.

Neuroergonomics focuses on the brain signatures and associated mental states underlying behavior to design human-machine interfaces enhancing performance in the cognitive and physical domains. Brain imaging techniques such as functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) have been considered key methods for achieving this goal. Recent research stresses the value of combining EEG and fNIRS in improving these interface systems' mental state decoding abilities, but little is known about whether these improvements generalize over different paradigms and methodologies, nor about the potentialities for using these systems in the real world. We review 33 studies comparing mental state decoding accuracy between bimodal EEG-fNIRS and unimodal EEG and fNIRS in several subdomains of neuroergonomics. In light of these studies, we also consider the challenges of exploiting wearable versions of these systems in real-world contexts. Overall the studies reviewed suggest that bimodal EEG-fNIRS outperforms unimodal EEG or fNIRS despite major differences in their conceptual and methodological aspects. Much work however remains to be done to reach practical applications of bimodal EEG-fNIRS in naturalistic conditions. We consider these points to identify aspects of bimodal EEG-fNIRS research in which progress is expected or desired.

Interpersonal brain synchronization with instructor compensates for learner's sleep deprivation in interactive learning.

Recent advances shifted the focus on single-brain functioning toward two-brain communication during learning interactions, following the demonstration that interpersonal brain synchronization (IBS) can track instructor-learner information exchange. Here, we investigated (i) whether sleep deprivation (SD) that potentially impacts both social interactions and learning abilities modulates IBS, and (ii) conversely whether and to what extent IBS might compensate for SD-related learning deficits. Instructors (always with regular sleep, RS) were asked to teach numerical reasoning strategies to learners (either SD or RS), during which the activity of both brains was simultaneously recorded using functional near-infrared spectroscopy (fNIRS). SD learners initially performed below their baseline level, worse than RS learners, but learning improvement was comparable between RS and SD conditions after learning with the instructor. IBS within the instructor-learner dyads was higher in the SD (vs. RS) condition in the left inferior frontal cortex. In addition, clustered IBS (estimated by nonnegative matrix factorization) was correlated with performance improvement. Finally, Granger Causality analyses revealed biased causality with higher instructor-to-learner than learner-to-instructor directionality in brain signal processing. Together, these results indicate that SD-related learning deficits can to some extent be compensated via interactions with an instructor, as reflected by increased IBS and preserved learning ability. It suggests an essential role of the instructor in driving synchrony between teaching and SD learning brains during interactions.

Applications of Functional Near-Infrared Spectroscopy in Fatigue, Sleep Deprivation, and Social Cognition.

Functional near-infrared spectroscopy (fNIRS) is an optical diffusion technique that allows the non-invasive imaging of cortical activity. During the last two decades, rapid technical and methodological advances have made fNIRS a powerful tool to investigate the cerebral correlates of human performance and cognitive functions, including fatigue, sleep deprivation and social cognition. Despite intrinsic limitations such as restricted brain depth and spatial resolution, its applicability, low cost, ecological validity, and tolerance to movements make fNIRS advantageous for scientific research and clinical applications. It can be viewed as a valid and promising brain imaging approach to investigate applied societal problems (e.g., safety, children development, sport science) and complement other neuroimaging techniques. The intrinsic power of fNIRS measurements for the study of social cognition is magnified when applied to the hyperscanning paradigm (i.e., measuring activity in two or more brains simultaneously). Besides consolidating existing findings, future fNIRS research should focus on methodological advances (e.g., artefacts correction, connectivity approaches) and standardization of analysis pipelines, and expand currently used paradigms in more naturalistic but controlled settings.

Decreased prefrontal connectivity parallels cognitive fatigue-related performance decline after sleep deprivation. An optical imaging study.

Fatigue induced by sustained cognitive demands often entails decreased behavioural performance and the unavailability of brain resources, either due to reduced levels or impaired access. In the present study, we investigated the neural dynamics underlying preserved behavioural performance after inducing cognitive fatigue (CF) in a sleep deprivation (SD) condition in which resources are naturally compromised. Using functional near infrared spectroscopy (fNIRS), we recorded cortical brain activity during task-related CF induction in the evening, in the middle of the night and early in the morning. Although cortical oxygenation similarly increased over the 3 sessions, decreased intra-hemispheric connectivity between left anterior frontal and frontal areas paralleled a sudden drop in task performance in the early morning. Our data indicate that decreased sustained attention after the induction of cognitive fatigue in a situation of high sleep pressure results from impaired connectivity between left prefrontal cortical areas rather than from a mere modulation in brain resources.

Cognitive task avoidance correlates with fatigue-induced performance decrement but not with subjective fatigue.

Mentally demanding tasks feel effortful and are usually avoided. Furthermore, prolonged cognitive engagement leads to mental fatigue, consisting of subjective feeling of exhaustion and decline in performance. Despite the intuitive characterization of fatigue as an increase in subjective effort perception, the effect of fatigue on effort cost has never been tested experimentally. To this end, sixty participants in 2 separate experiments underwent a forced-choice working memory task following either a fatigue-inducing (i.e. cognitive task involving working memory, conflict and switch costs) or a control manipulation. We measured fatigue in terms of subjective feeling and performance decrement and assessed effort in terms of subjective perception and task avoidance. Subjects exhibited only weak avoidance of the working memory task, with stronger influence of reward than task difficulty on their decisions. In addition, we found that task avoidance did not systematically change following the fatigue manipulation but that variations in task avoidance correlated with fatigue-induced performance decline. The other measures of fatigue and effort were unrelated to each other. Our findings suggest that subjective fatigue may develop independently of task avoidance and suggest an "anticipatory regulation" model in which fatigue urges subjects to stop in anticipation of possible, future adverse consequences.

Transcranial Direct Current Stimulation Does Not Counteract Cognitive Fatigue, but Induces Sleepiness and an Inter-Hemispheric Shift in Brain Oxygenation.

Sustained cognitive demands may result in cognitive fatigue (CF), eventually leading to decreased behavioral performance and compromised brain resources. In the present study, we tested the hypothesis that transcranial direct current stimulation (tDCS) would counteract the behavioral and neurophysiological effects of CF. Twenty young healthy participants were tested in a within-subject counterbalanced order across two different days. Anodal tDCS (real vs. sham) was applied over the left prefrontal cortex. In the real tDCS condition, a current of 1.5 mA was delivered for 25 min. Cortical oxygenation changes were measured using functional Near Infrared Spectroscopy (fNIRS) on the frontal cortices. CF was triggered using the TloadDback task, a sustained working memory paradigm that allows tailoring task demands according to each individual's maximal cognitive capacity. Sustained cognitive load-related effects were assessed using pre- versus post-task subjective fatigue and sleepiness scales, evolution of performance accuracy within the task, indirect markers of dopaminergic activity (eye blinks), and cortical oxygenation changes (fNIRS) both during the task and pre- and post-task resting state periods. Results consistently disclosed significant CF-related effects on performance. Transcranial DCS was not effective to counteract the behavioral effects of CF. In the control (sham tDCS) condition, cerebral oxygen exchange (COE) levels significantly increased in the right hemisphere during the resting state immediately after the induction of CF, suggesting a depletion of brain resources. In contrast, tDCS combined with CF induction significantly shifted interhemispheric oxygenation balance during the post-training resting state. Additionally, increased self-reported sleepiness was associated with brain activity in the stimulated hemisphere after recovery from CF during the tDCS condition only, which might reflect a negative middle-term effect of tDCS application.

Cognitive Fatigue, Sleep and Cortical Activity in Multiple Sclerosis Disease. A Behavioral, Polysomnographic and Functional Near-Infrared Spectroscopy Investigation.

Patients with multiple sclerosis (MS) disease frequently experience fatigue as their most debilitating symptom. Fatigue in MS partially refers to a cognitive component, cognitive fatigue (CF), characterized by a faster and stronger than usual development of the subjective feeling of exhaustion that follows sustained cognitive demands. The feeling of CF might result from supplementary task-related brain activity following MS-related demyelination and neurodegeneration. Besides, CF in MS disease might also stem from disrupted sleep. The present study investigated the association between the triggering of CF, task-related brain activity and sleep features. In a counterbalance mixed design, 10 patients with MS and 11 healthy controls were exposed twice for 16 min to a CF-inducing dual working memory updating task (TloadDback) under low or high cognitive demands conditions, counterbalanced. Considering known inter-individual differences and potential cognitive deficits in MS, the maximal cognitive load of the task was individually adapted to each participant's own upper limits. During the experimental sessions, cortical brain activity was measured using near-infrared spectroscopy (NIRS) during the CF-induction task, and in a resting state immediately before and after. Ambulatory polysomnography recordings were obtained on the nights preceding experimental sessions. When cognitive load was individually adapted to their processing capabilities, patients with MS exhibited similar than healthy controls levels of subjectively perceived CF, evolution of performance during the task, and brain activity patterns. Linear mixed models indicate a negative association between oxygenation level changes in the dorsolateral prefrontal cortex (DLPFC) and the triggering of subjective CF in patients with MS only. Longer total sleep time was also associated with higher CF in MS patients. These results suggest that controlling for cognitive load between individuals with and without MS results in a similar task-related development of subjective CF. Besides comparable performance and cortical brain activity between groups, mixed model analyses suggest a possible association between CF, DLPFC activity and sleep duration in MS disease.

Cognitive fatigue: A Time-based Resource-sharing account.

Cognitive Fatigue (CF) is an important confound impacting cognitive performance. How CF is triggered and what are the features that make a cognitive effort perceived as exhausting remain unclear. In the theoretical framework of the Time-based Resource-sharing (TBRS) model (Barrouillet et al., 2004), we hypothesized that CF is an outcome of increased cognitive load due to constrained time to process ongoing cognitive demands. We tested this cognitive load-related CF hypothesis across 2 experiments manipulating both task complexity and cognitive load induced by the processing time interval. To do so, we used the TloadDback paradigm, a working memory dual task in which high and low cognitive load levels can be individually adjusted. In Experiment 1, participants were administered a high cognitive load (HCL, short processing time interval) and a low cognitive load (LCL, large processing time interval) conditions while complexity of the task was kept constant (1-back dual task). In Experiment 2, two tasks featuring different levels of complexity were both administered at the individual's maximal processing speed capacity for each task (i.e., short processing time interval). Results disclosed higher CF in the HCL than in the LCL condition in Experiment 1. On the contrary, in Experiment 2 similar levels of CF were obtained for different levels of task complexity when processing time interval was individually adjusted to induce a HCL condition. Altogether, our results indicate that processing time-related cognitive load eventually leads to the subjective feeling of CF, and to a decrease in alertness. In this framework, we propose that the development of CF can be envisioned as the result of sustained cognitive demands irrespective of task complexity.

Automatic detection of noisy channels in fNIRS signal based on correlation analysis.

BACKGROUND: fNIRS signals can be contaminated by distinct sources of noise. While most of the noise can be corrected using digital filters, optimized experimental paradigms or pre-processing methods, few approaches focus on the automatic detection of noisy channels. METHODS: In the present study, we propose a new method that detect automatically noisy fNIRS channels by combining the global correlations of the signal obtained from sliding windows (Cui et al., 2010) with correlation coefficients extracted experimental conditions defined by triggers. RESULTS: The validity of the method was evaluated on test data from 17 participants, for a total of 16 NIRS channels per subject, positioned over frontal, dorsolateral prefrontal, parietal and occipital areas. Additionally, the detection of noisy channels was tested in the context of different levels of cognitive requirement in a working memory N-back paradigm. COMPARISON WITH EXISTING METHOD(S): Bad channels detection accuracy, defined as the proportion of bad NIRS channels correctly detected among the total number of channels examined, was close to 91%. Under different cognitive conditions the area under the Receiver Operating Curve (AUC) increased from 60.5% (global correlations) to 91.2% (local correlations). CONCLUSIONS: Our results show that global correlations are insufficient for detecting potentially noisy channels when the whole data signal is included in the analysis. In contrast, adding specific local information inherent to the experimental paradigm (e.g., cognitive conditions in a block or event-related design), improved detection performance for noisy channels. Also, we show that automated fNIRS channel detection can be achieved with high accuracy at low computational cost.

Cognitive Fatigue Facilitates Procedural Sequence Learning.

Enhanced procedural learning has been evidenced in conditions where cognitive control is diminished, including hypnosis, disruption of prefrontal activity and non-optimal time of the day. Another condition depleting the availability of controlled resources is cognitive fatigue (CF). We tested the hypothesis that CF, eventually leading to diminished cognitive control, facilitates procedural sequence learning. In a two-day experiment, 23 young healthy adults were administered a serial reaction time task (SRTT) following the induction of high or low levels of CF, in a counterbalanced order. CF was induced using the Time load Dual-back (TloadDback) paradigm, a dual working memory task that allows tailoring cognitive load levels to the individual's optimal performance capacity. In line with our hypothesis, reaction times (RT) in the SRTT were faster in the high- than in the low-level fatigue condition, and performance improvement was higher for the sequential than the motor components. Altogether, our results suggest a paradoxical, facilitating impact of CF on procedural motor sequence learning. We propose that facilitated learning in the high-level fatigue condition stems from a reduction in the cognitive resources devoted to cognitive control processes that normally oppose automatic procedural acquisition mechanisms.

Sleep and memory consolidation: motor performance and proactive interference effects in sequence learning.

That post-training sleep supports the consolidation of sequential motor skills remains debated. Performance improvement and sensitivity to proactive interference are both putative measures of long-term memory consolidation. We tested sleep-dependent memory consolidation for visuo-motor sequence learning using a proactive interference paradigm. Thirty-three young adults were trained on sequence A on Day 1, then had Regular Sleep (RS) or were Sleep Deprived (SD) on the night after learning. After two recovery nights, they were tested on the same sequence A, then had to learn a novel, potentially competing sequence B. We hypothesized that proactive interference effects on sequence B due to the prior learning of sequence A would be higher in the RS condition, considering that proactive interference is an indirect marker of the robustness of sequence A, which should be better consolidated over post-training sleep. Results highlighted sleep-dependent improvement for sequence A, with faster RTs overnight for RS participants only. Moreover, the beneficial impact of sleep was specific to the consolidation of motor but not sequential skills. Proactive interference effects on learning a new material at Day 4 were similar between RS and SD participants. These results suggest that post-training sleep contributes to optimizing motor but not sequential components of performance in visuo-motor sequence learning.