Validating the reproducibility of a low-cost single-channel fNIRS device across hierarchical cognitive tasks.

This study evaluates a low-cost, single-channel fNIRS device in cognitive neuroscience, aiming to overcome the financial barriers of commercial systems by testing its efficacy in tasks of varying complexity. Twenty-six participants engaged in motor control (finger-tapping), working memory (n-back), and creativity (AUT) tasks while their prefrontal cortex activity was monitored using the device, with behavioral and cerebral blood flow changes recorded. Results showed the device's capability to detect significant blood flow variations across different tasks, thereby supporting its use in cognitive research. The study confirms the potential of single-channel fNIRS as a cost-effective tool for diverse cognitive assessments, from simple motor actions to complex creative thinking.

Investigating the impact of greenery elements in office environments on cognitive performance, visual attention and distraction: An eye-tracking pilot-study in virtual reality.

The human-nature connection is one of the main aspects determining supportive and comfortable office environments. In this context, the application of eye-tracking-equipped Virtual Reality (VR) devices to support an evaluation on the effect of greenery elements indoors on individuals' efficiency and engagement is limited. A new approach to investigate visual attention, distraction, cognitive load and performance in this field is carried out via a pilot-study comparing three virtual office layouts (Indoor Green, Outdoor Green and Non-Biophilic). 63 participants completed cognitive tasks and surveys while measuring gaze behaviour. Sense of presence, immersivity and cybersickness results supported the ecological validity of VR. Visual attention was positively influenced by the proximity of users to the greenery element, while visual distraction from tasks was negatively influenced by the dimension of the greenery. In the presence of greenery elements, lower cognitive loads and more efficient information searching, resulting in improved performance, were also highlighted.

Spectral Slope and Lempel-Ziv Complexity as Robust Markers of Brain States during Sleep and Wakefulness.

Nonoscillatory measures of brain activity such as the spectral slope and Lempel-Ziv complexity are affected by many neurological disorders and modulated by sleep. A multitude of frequency ranges, particularly a broadband (encompassing the full spectrum) and a narrowband approach, have been used especially for estimating the spectral slope. However, the effects of choosing different frequency ranges have not yet been explored in detail. Here, we evaluated the impact of sleep stage and task engagement (resting, attention, and memory) on slope and complexity in a narrowband (30-45 Hz) and broadband (1-45 Hz) frequency range in 28 healthy male human subjects (21.54 ± 1.90 years) using a within-subject design over 2 weeks with three recording nights and days per subject. We strived to determine how different brain states and frequency ranges affect slope and complexity and how the two measures perform in comparison. In the broadband range, the slope steepened, and complexity decreased continuously from wakefulness to N3 sleep. REM sleep, however, was best discriminated by the narrowband slope. Importantly, slope and complexity also differed between tasks during wakefulness. While narrowband complexity decreased with task engagement, the slope flattened in both frequency ranges. Interestingly, only the narrowband slope was positively correlated with task performance. Our results show that slope and complexity are sensitive indices of brain state variations during wakefulness and sleep. However, the spectral slope yields more information and could be used for a greater variety of research questions than Lempel-Ziv complexity, especially when a narrowband frequency range is used.

Physiology or Psychology: What Drives Human Emissions of Carbon Dioxide and Ammonia?

Humans are the primary sources of CO2 and NH3 indoors. Their emission rates may be influenced by human physiological and psychological status. This study investigated the impact of physiological and psychological engagements on the human emissions of CO2 and NH3. In a climate chamber, we measured CO2 and NH3 emissions from participants performing physical activities (walking and running at metabolic rates of 2.5 and 5 met, respectively) and psychological stimuli (meditation and cognitive tasks). Participants' physiological responses were recorded, including the skin temperature, electrodermal activity (EDA), and heart rate, and then analyzed for their relationship with CO2 and NH3 emissions. The results showed that physiological engagement considerably elevated per-person CO2 emission rates from 19.6 (seated) to 46.9 (2.5 met) and 115.4 L/h (5 met) and NH3 emission rates from 2.7 to 5.1 and 8.3 mg/h, respectively. CO2 emissions reduced when participants stopped running, whereas NH3 emissions continued to increase owing to their distinct emission mechanisms. Psychological engagement did not significantly alter participants' emissions of CO2 and NH3. Regression analysis revealed that CO2 emissions were predominantly correlated with heart rate, whereas NH3 emissions were mainly associated with skin temperature and EDA. These findings contribute to a deeper understanding of human metabolic emissions of CO2 and NH3.

Improved estimation of general cognitive ability and its neural correlates with a large battery of cognitive tasks.

Elucidating the neural mechanisms of general cognitive ability (GCA) is an important mission of cognitive neuroscience. Recent large-sample cohort studies measured GCA through multiple cognitive tasks and explored its neural basis, but they did not investigate how task number, factor models, and neural data type affect the estimation of GCA and its neural correlates. To address these issues, we tested 1,605 Chinese young adults with 19 cognitive tasks and Raven's Advanced Progressive Matrices (RAPM) and collected resting state and n-back task fMRI data from a subsample of 683 individuals. Results showed that GCA could be reliably estimated by multiple tasks. Increasing task number enhances both reliability and validity of GCA estimates and reliably strengthens their correlations with brain data. The Spearman model and hierarchical bifactor model yield similar GCA estimates. The bifactor model has better model fit and stronger correlation with RAPM but explains less variance and shows weaker correlations with brain data than does the Spearman model. Notably, the n-back task-based functional connectivity patterns outperform resting-state fMRI in predicting GCA. These results suggest that GCA derived from a multitude of cognitive tasks serves as a valid measure of general intelligence and that its neural correlates could be better characterized by task fMRI than resting-state fMRI data.

Abnormal brain activities of cognitive processes in cerebral small vessel disease: A systematic review of task fMRI studies.

Cerebral small vessel disease (CSVD) is characterized by widespread functional changes in the brain, as evident from abnormal brain activations during cognitive tasks. However, the existing findings in this area are not yet conclusive. We systematically reviewed 25 studies reporting task-related fMRI in five cognitive domains in CSVD, namely executive function, working memory, processing speed, motor, and affective processing. The findings highlighted: (1) CSVD affects cognitive processes in a domain-specific manner; (2) Compensatory and regulatory effects were observed simultaneously in CSVD, which may reflect the interplay between the negative impact of brain lesion and the positive impact of cognitive reserve. Combined with behavioral and functional findings in CSVD, we proposed an integrated model to illustrate the relationship between altered activations and behavioral performance in different stages of CSVD: functional brain changes may precede and be more sensitive than behavioral impairments in the early pre-symptomatic stage; Meanwhile, compensatory and regulatory mechanisms often occur in the early stages of the disease, while dysfunction/decompensation and dysregulation often occur in the late stages. Overall, abnormal hyper-/hypo-activations are crucial for understanding the mechanisms of small vessel lesion-induced behavioral dysfunction, identifying potential neuromarker and developing interventions to mitigate the impact of CSVD on cognitive function.

Loosely controlled experimental EEG datasets for higher-order cognitions in design and creativity tasks.

Understanding neural mechanisms in design and creativity processes remains a challenging endeavor. To address this gap, we present two electroencephalography (EEG) datasets recorded in design and creativity experiments. We have discussed the details, similarities, differences, and corresponding cognitive tasks of the two datasets in the following sections. The design dataset (Dataset A) comprises EEG recordings of 27 participants during loosely controlled design creation experiments. Each experiment included six design problems. In each design problem, participants performed five cognitive tasks, including problem understanding, idea generation, rating idea generation, idea evaluation, and rating idea evaluation. The NASA Task Load Index was used in rating tasks. The creativity dataset (Dataset B) includes EEG signals recorded from 28 participants in creativity experiments which were based on a modified variant of the Torrance Test of Creative Thinking (TTCT-F). Participants were presented with three incomplete sketches and were asked to perform three creativity tasks for each sketch: idea generation, idea evolution, and idea evaluation. In both datasets, we structured the experiments into predefined steps, primarily to ensure participants' comfort and task clarity. This was the only control applied to the experiments. All the tasks were loosely controlled: open-ended (up to 3 min) and self-paced. 64-channel EEG signals were recorded at 500 Hz based on the international 10-10 system by the Brain Vision EEG recording system while the participants were performing their assigned tasks. EEG channels were pre-processed and finally referenced to the Cz channel to remove artifacts. EEGs were pre-processed using popular pipelines widely used in previous studies. Preprocessed EEG signals were finally segmented according to the tasks to facilitate future analyses. The EEG signals are stored in the .mat format. While the present paper mainly addresses pre-processed datasets, it also cites raw EEG recordings in the following sections. We aim to promote research and facilitate the development of experimental protocols and methodologies in design and creativity cognition by sharing these resources. There exist important points regarding the datasets which are worth mentioning. These datasets represent a novel contribution to the field, offering insights into design and creativity neurocognition. To our knowledge, publicly accessible datasets of this nature are scarce, and, to the best of our knowledge, our datasets are the first publicly available ones in design and creativity. Researchers can utilize these datasets directly or draw upon the considerations and technical insights provided to inform their studies. Furthermore, we introduce the concept of loosely controlled cognitive experiments in design and creativity cognition. These experiments strike a balance between flexibility and control, allowing participants to incubate creative ideas over extended response times while maintaining structured experimental sections. Such an approach fosters more natural data recording procedures and holds the potential to enhance the accuracy and reliability of future studies. The loosely controlled approach can be employed in future cognitive studies. This paper also conducts a comparative analysis of the two datasets, offering a holistic view of design and creativity tasks. By exploring various aspects of these cognitive processes, we provide an understanding for future researchers.

Promoting adult health: the neurophysiological benefits of watering plants and engaging in mental tasks within designed environments.

BACKGROUND: Indoor, sedentary lifestyles have disconnected individuals from nature, necessitating interventions to reestablish this bond. Performing horticultural activities, such as watering houseplants, offers a potential solution. This study sought to determine how participating in horticulture activities affected adults' cognitive and emotional moods. METHODS: We compared the benefits of watering houseplants (a gardening task) to those of standing while performing a computer task (a mental task). Chinese participants, aged 20 to 21 years, were recruited; their physiological and psychological reactions were measured using electroencephalograms, blood pressure assessments, and psychological assessments. RESULTS: Fifty participants were included. Watering indoor plants significantly reduced blood pressure, without affecting pulse rate. During the plant watering task as opposed to the mental activity, more dramatic different patterns of very high alpha and beta brainwave activity were identified. Participants reported increased happiness following gardening activities. CONCLUSIONS: The findings of this study highlight the substantial relaxation benefits, both mental and physical, associated with the simple act of watering indoor plants.

The Mediating Role of Affective States in Short-Term Effects of Activity Engagement on Working Memory in Older Age.

INTRODUCTION: It has been shown that activity engagement is associated with cognitive ability in older age, but mechanisms behind the associations have rarely been examined. Following a recent study which showed short-term effects of activity engagement on working memory performance appearing 6 h later, this study examined the mediating role of affective states in this process. METHODS: For 7 times per day over 2 weeks, 150 Swiss older adults (aged 65-91 years) reported their present (sociocognitive/passive leisure) activities and affective states (high-arousal positive, low-arousal positive, high-arousal negative, and low-arousal negative) and completed an ambulatory working memory task on a smartphone. RESULTS: Multilevel vector autoregression models showed that passive leisure activities were associated with worse working memory performance 6 h later. Passive leisure activities were negatively associated with concurrent high-arousal positive affect (and high-arousal negative affect); high-arousal positive affect was negatively associated with working memory performance 6 h later. A Sobel test showed a significant mediation effect of high-arousal positive affect linking the time-lagged relationship between passive leisure activities and working memory. Additionally, sociocognitive activities were associated with better working memory performance 6 h later. Sociocognitive activities were associated with concurrent higher high- and low-arousal positive affect, which, however, were not associated with working memory performance 6 h later. Thus, a mediation related to sociocognitive activities was not found. DISCUSSION: Passive leisure activities could influence working memory performance through high-arousal positive affect within a timeframe of several hours. Results are discussed in relation to an emotional, and possibly a neuroendocrine, pathway explaining the time-lagged effects of affective states on working memory performance.

Similarities and differences between intermittent and continuous resting-state fMRI.

Introduction: Functional Magnetic Resonance Imaging (fMRI) block-design experiments typically include active ON-blocks with presentation of cognitive tasks which are contrasted with OFF- blocks with no tasks presented. OFF-blocks in between ON-blocks can however, also be seen as a proxy for intermittent periods of resting, inducing temporary resting-states. We still do not know if brain activity during such intermittent periods reflects the same kind of resting-state activity as that obtained during a continuous period, as is typically the case in studies of the classic Default Mode Network (DMN). The purpose of the current study was therefore to investigate both similarities and differences in brain activity between intermittent and continuous resting conditions. Methods: There were 47 healthy participants in the 3T fMRI experiment. Data for the intermittent resting-state condition were acquired from resting-periods in between active task-processing periods in a standard ON-OFF block design, with three different cognitive tasks presented during ON-blocks. Data for the continuous resting-state condition were acquired during a 5 min resting period after the task-design had been presented. Results and discussion: The results showed that activity was overall similar in the two conditions, but with some differences. These differences were within the DMN network, and for the interaction of DMN with other brain networks. DMN maps showed weak overlap between conditions in the medial prefrontal cortex (MPFC), and in particular for the intermittent compared to the continuous resting-state condition. Moreover, DMN showed strong connectivity with the salience network (SN) in the intermittent resting-state condition, particularly in the anterior insula and the supramarginal gyrus. The observed differences may reflect a "carry-over" effect from task-processing to the next resting-state period, not present in the continuous resting-state condition, causing interference from the ON-blocks. Further research is needed to fully understand the extent of differences between intermittent and continuous resting-state conditions.

Why many studies of individual differences with inhibition tasks may not localize correlations.

Individual difference exploration of cognitive domains is predicated on being able to ascertain how well performance on tasks covary. Yet, establishing correlations among common inhibition tasks such as Stroop or flanker tasks has proven quite difficult. It remains unclear whether this difficulty occurs because there truly is a lack of correlation or whether analytic techniques to localize correlations perform poorly real-world contexts because of excessive measurement error from trial noise. In this paper, we explore how well correlations may localized in large data sets with many people, tasks, and replicate trials. Using hierarchical models to separate trial noise from true individual variability, we show that trial noise in 24 extant tasks is about 8 times greater than individual variability. This degree of trial noise results in massive attenuation in correlations and instability in Spearman corrections. We then develop hierarchical models that account for variation across trials, variation across individuals, and covariation across individuals and tasks. These hierarchical models also perform poorly in localizing correlations. The advantage of these models is not in estimation efficiency, but in providing a sense of uncertainty so that researchers are less likely to misinterpret variability in their data. We discuss possible improvements to study designs to help localize correlations.

Effects of Transcranial Electrical Stimulation on Gambling and Gaming: A Systematic Review of Studies on Healthy Controls, Participants with Gambling/Gaming Disorder, and Substance Use Disorder.

Gambling disorder (GD) and internet gaming disorder (IGD) are formally recognized behavioral addictions with a rapidly growing prevalence and limited treatment options. Recently, transcranial electrical stimulation (tES) techniques have emerged as potentially promising interventions for improving treatment outcomes by ameliorating cognitive functions implicated in addictive behaviors. To systematize the current state of evidence and better understand whether and how tES can influence gambling and gaming-related cognitive processes, we conducted a PRISMA-guided systematic review of the literature, focusing on tES effects on gaming and gambling in a diverse range of population samples, including healthy participants, participants with GD and IGD, as well as participants with substance abuse addictions. Following the literature search in three bibliographic databases (PubMed, Web of Science, and Scopus), 40 publications were included in this review, with 26 conducted on healthy participants, 6 focusing on GD and IGD patients, and 8 including participants with other addictions. Most of the studies targeted the dorsolateral prefrontal cortex, using transcranial direct current stimulation (tDCS), and assessed the effects on cognition, using gaming and gambling computerized cognitive tasks measuring risk taking and decision making, e.g., balloon analogue risk task, Iowa gambling task, Cambridge gambling task, etc. The results indicated that tES could change gambling and gaming task performances and positively influence GD and IGD symptoms, with 70% of studies showing neuromodulatory effects. However, the results varied considerably depending on the stimulation parameters, sample characteristics, as well as outcome measures used. We discuss the sources of this variability and provide further directions for the use of tES in the context of GD and IGD treatment.

Cognitive tasks and combined statistical methods to evaluate, model, and predict mental workload.

Mental workload (MWL) is a concept that is used as a reference for assessing the mental cost of activities. In recent times, challenges related to user experience are determining the expected MWL value for a given activity and real-time adaptation of task complexity level to achieve or maintain desired MWL. As a consequence, it is important to have at least one task that can reliably predict the MWL level associated with a given complexity level. In this study, we used several cognitive tasks to meet this need, including the N-Back task, the commonly used reference test in the MWL literature, and the Corsi test. Tasks were adapted to generate different MWL classes measured via NASA-TLX and Workload Profile questionnaires. Our first objective was to identify which tasks had the most distinct MWL classes based on combined statistical methods. Our results indicated that the Corsi test satisfied our first objective, obtaining three distinct MWL classes associated with three complexity levels offering therefore a reliable model (about 80% accuracy) to predicted MWL classes. Our second objective was to achieve or maintain the desired MWL, which entailed the use of an algorithm to adapt the MWL class based on an accurate prediction model. This model needed to be based on an objective and real-time indicator of MWL. For this purpose, we identified different performance criteria for each task. The classification models obtained indicated that only the Corsi test would be a good candidate for this aim (more than 50% accuracy compared to a chance level of 33%) but performances were not sufficient to consider identifying and adapting the MWL class online with sufficient accuracy during a task. Thus, performance indicators require to be complemented by other types of measures like physiological ones. Our study also highlights the limitations of the N-back task in favor of the Corsi test which turned out to be the best candidate to model and predict the MWL among several cognitive tasks.

Explainable fMRI-based brain decoding via spatial temporal-pyramid graph convolutional network.

Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and neural engineering. However, existing machine learning methods for fMRI-based brain decoding either suffer from low classification performance or poor explainability. Here, we address this issue by proposing a biologically inspired architecture, Spatial Temporal-pyramid Graph Convolutional Network (STpGCN), to capture the spatial-temporal graph representation of functional brain activities. By designing multi-scale spatial-temporal pathways and bottom-up pathways that mimic the information process and temporal integration in the brain, STpGCN is capable of explicitly utilizing the multi-scale temporal dependency of brain activities via graph, thereby achieving high brain decoding performance. Additionally, we propose a sensitivity analysis method called BrainNetX to better explain the decoding results by automatically annotating task-related brain regions from the brain-network standpoint. We conduct extensive experiments on fMRI data under 23 cognitive tasks from Human Connectome Project (HCP) S1200. The results show that STpGCN significantly improves brain-decoding performance compared to competing baseline models; BrainNetX successfully annotates task-relevant brain regions. Post hoc analysis based on these regions further validates that the hierarchical structure in STpGCN significantly contributes to the explainability, robustness and generalization of the model. Our methods not only provide insights into information representation in the brain under multiple cognitive tasks but also indicate a bright future for fMRI-based brain decoding.

Cognitive Load and Energy Balance Knowledge in High-School Physical Education.

Purpose: Guided by the cognitive load theory, the purpose of this study was to determine the impacts of cognitive load and school socioeconomic status-related environmental factors on ninth-graders' energy-balanced living knowledge gain. Methods: A stratified random sample of high-school students (N = 150) participated in this study. Data were collected on students' knowledge gain, cognitive load, free and reduced-price meal rates, and student-to-teacher ratio. Results: The path analysis results revealed that the reasoning learning tasks had direct significant effects on students' knowledge gain (ßi-Diet and i-Exercise = 0.34, p < .01). The free and reduced-price meal rates and student-to-teacher ratio did not have significant effects on students' knowledge gain (p > .05). Discussion: These findings advance our understanding of the role cognitive learning tasks play in enhancing student learning in the subjects of energy-balanced knowledge and healthy lifestyle.

Positive and negative personality descriptors: UK dataset of self-referential valence, imageability and subjective frequency ratings of 300 adjectives for use in cognitive-emotional tasks.

Experimental tasks comparing participants' performance for categorising, remembering, and recognising positive and negative words are widely used in the emotional cognitive domain. Such tasks are commonly used in experimental psychology and psychiatry research, and have been shown to be sensitive biomarkers of depression and antidepressant drug action [1,2]. In addition, several of these tasks investigate self-referential processing i.e., the processing of information relevant to oneself; this has been shown to modify the way emotional words are encoded and remembered and may be a target that is amenable to treatment [3,4]. In practice, the development of such tasks for implementation in research studies often depends on the selection and matching of words according to characteristics such as valence or arousal, imageability, word frequency and word length to investigate differences in a chosen domain of interest whilst keeping important confounds constant. This introduces a need for ratings covering a range of word attributes that have been shown to affect processing. In particular, ratings of self-referential valence (how positively or negatively subjects feel about a word when this is used to describe themselves/their circumstances) have been seldom included in databases, despite the frequent investigation of the concept in research [1,5]. Other important attributes often considered in the process of matching and selection are word imageability and subjective frequency [6,7]. To facilitate the word selection and matching process required in cognitive-emotional task development, the present dataset provides subjective ratings for 150 positive and 150 negative adjectives describing personality characteristics. Across four online surveys, the 300 words were rated on self-referential valence, imageability and subjective frequency by representative samples of 200 UK-based, English-speaking adults. Basic demographics and data on depressive symptoms and state anxiety were collected from all participants. Comprehensive descriptive statistics and word length were calculated for each of the 300 words. All data cleaning and statistical analysis was performed in R. Our work is based on years of experience using the Oxford Emotional Task Battery [1,5] and may be particularly relevant for researchers using self-referential cognitive tasks with UK-based samples.

Positive Impacts of a Four-Week Neuro-Meditation Program on Cognitive Function in Post-Acute Sequelae of COVID-19 Patients: A Randomized Controlled Trial.

Study objective: Long COVID patients can experience high levels of impairment in their cognitive function and mental health. Using a parallel randomized control trial, we evaluated the effectiveness of a neuro-meditation program to reduce cognitive impairment in patients with long COVID. Methods: A total of 34 patients with long COVID were randomized to an intervention group (G-Int; n = 17) or a control group (G-Con; n = 17) and 15 healthy participants were constitutive of a normative group (G-Nor). The intervention consisted of ten 30-min sessions of Rebalance® over a period of five weeks. Each session included sound therapy and coach-guided meditation associated with light stimulations (i.e., chromotherapy). Primary outcomes were performance on five computerized cognitive tasks (choice response time, pattern comparison, Simon, pursuit rotor task, and Corsi block-tapping task), mental and physical fatigue (Chalder fatigue scale), perceived stress (perceived stress scale) and mood (profiles of mood states). Secondary outcomes were anxiety and depressive symptoms (hospital anxiety and depression scale), muscular pain, joint pain, and headaches using visual analog scales (VAS) as well as sleep quality (Spiegel sleep questionnaire). Assessments were conducted at baseline and at 1−2 and 7−8 days of follow-up. Results: Compared to healthy subjects, long COVID patients showed significant differences at baseline on all the self-report questionnaires, and a Rebalance® program improved all the subjective reports, as well as cognitive performances, especially on reaction time-based tasks. In particular, only the G-Int group revealed shortened reaction times in the choice reaction time (RTbaseline = 593 ± 121 ms vs. RTpost2 = 521 ± 86 ms, p < 0.001), Simon (RTbaseline = 539 ± 123 ms vs. RTpost2 = 494 ± 134 ms, p < 0.01), and pattern comparison tasks (RTbaseline = 1244 ± 315 ms vs. RTpost2 = 1079 ± 213 ms, p < 0.001). Conclusions) Initial evidence suggests that neuro-meditation reduces cognitive impairment and improves physical and mental fatigue, muscle and joint pain, symptoms of depression and anxiety, mood disturbances as well as sleep quality. The Rebalance® program hence constitutes a promising non-pharmacological intervention for the treatment of long-term psychological/cognitive outcomes of COVID-19.

Mental effort and recovery from task-induced fatigue in people with traumatic brain injury.

PURPOSE: This exploratory case-controlled study examined whether the same amount of effort leads to similar feelings of fatigue and whether feelings of fatigue decline at the same rate in people with traumatic brain injury (pwTBI) compared to controls. METHODS: Twenty pwTBI and 20 healthy controls (HC) completed an adaptive n-back task to induce fatigue and reported mental effort upon task completion and state-fatigue pre-task and several times during 30-minutes rest-period post-task. Task difficulty adapted to performance allowing both groups to invest substantial amounts of mental effort. RESULTS: Fatigue and effort levels were higher in pwTBI compared to controls. Multiple linear regression analyses showed that effort was positively related to post-task fatigue and this relationship did not differ between groups. Pre-task fatigue was the only predictor of post-task fatigue. Multilevel models showed no significant difference in decline of fatigue over the rest-period between groups. CONCLUSIONS: Excessive feelings of fatigue following TBI could not be explained by a higher vulnerability to the fatigue-inducing effects of mental effort needed to perform a specific task. In pwTBI pre-task fatigue levels might be more related to the complex demands of everyday life. Future studies should investigate recovery of fatigue and applications of this knowledge to rehabilitation interventions.Implications for rehabilitationPeople with TBI experience long-term fatigue as one of the most frequent and disabling symptoms and this long-term fatigue is a risk factor for development of secondary psychiatric symptoms such as depression or anxiety.Since people with TBI did not show a higher vulnerability to the fatigue-inducing effects of mental effort, fatigue following TBI might be better explained by the complex demands of everyday life such as external (environment) and internal (emotions) factors.Rehabilitation programs should be directed to this complex and highly individual interplay of fatigue in relation to other factors.

Challenging neurovascular coupling through complex and variable duration cognitive paradigms: A subcomponent analysis.

A similar pattern of cerebral blood velocity (CBv) response has been observed for neurovascular coupling (NVC) assessment with cognitive tasks of varying complexity and duration. This lack of specificity could result from parallel changes in arterial blood pressure (BP) and PaCO2, which could confound the estimates of NVC integrity. Healthy participants (n = 16) underwent recordings at rest (5 min sitting) and during randomized paradigms of different complexity (naming words (NW) beginning with P-, R-, V- words and serial subtractions (SS) of 100-2, 100-7, 1000-17, with durations of 5, 30 and 60 s). Bilateral CBv (middle cerebral arteries, transcranial Doppler), end-tidal CO2 (EtCO2, capnography), blood pressure (BP, Finapres) and heart rate (HR, ECG) were recorded continuously. The bilateral CBv response to all paradigms was classified under objective criteria to select only responders, then the repeated data were averaged between visits. Bilateral CBv change to tasks was decomposed into the relative contributions (subcomponents) of arterial BP (VBP; neurogenic), critical closing pressure (VCrCP; metabolic) and resistance area product (VRAP; myogenic). A temporal effect was demonstrated in bilateral VBP and VRAP during all tasks (p<0.002), increased VBP early (between 0 and 10 s) and followed by decreases of VRAP late (25-35 s) in the response. VCrCP varied by complexity and duration (p<0.046). The main contributions to CBv responses to cognitive tasks of different complexity and duration were VBP and VRAP, whilst a smaller contribution from VCrCP would suggest sensitivity to metabolic demands. Further studies are needed to assess the influence of different paradigms, ageing and cerebrovascular conditions.

Is Anodal Transcranial Direct Current Stimulation an Effective Ergogenic Technology in Lower Extremity Sensorimotor Control for Healthy Population? A Narrative Review.

Anodal transcranial direct current stimulation (a-tDCS) aims to hone motor skills and improve the quality of life. However, the non-repeatability of experimental results and the inconsistency of research conclusions have become a common phenomenon, which may be due to the imprecision of the experimental protocol, great variability of the participant characteristics within the group, and the irregularities of quantitative indicators. The aim of this study systematically summarised and analysed the effect of a-tDCS on lower extremity sensorimotor control under different experimental conditions. This narrative review was performed following the PRISMA guidelines until June 2022 in Web of Science, PubMed, Science Direct, Google Scholar, and Scopus. The findings of the present study demonstrated that a-tDCS can effectively improve the capabilities of lower extremity sensorimotor control, particularly in gait speed and time-on-task. Thus, a-tDCS can be used as an effective ergogenic technology to facilitate physical performance. In-depth and rigorous experimental protocol with larger sample sizes and combining brain imaging technology to explore the mechanism have a profound impact on the development of tDCS.