Abstract Digital behaviour change interventions have emerged as a promising approach for improving health, well-being, and performance, yet relatively few studies have evaluated their effects using objective biological and neurophysiological measures. The present study examined the effectiveness of Autonomic, a neuroscience-informed digital coaching platform designed to improve student well-being through personalized behavioural interventions targeting sleep, stress, mood, energy, and focus. Thirty university students engaged with the platform for ten weeks and completed behavioural assessments, biomarker collection, and electroencephalographic (EEG) testing at baseline, five weeks, and ten weeks. Behavioural outcomes included self-reported ratings of focus, energy, sleep, mood, and stress. Biological measures included salivary cortisol and tear fluid dopamine concentrations. EEG assessments included resting-state recordings, frontal theta activity during a working memory task, and N200/P300 event-related potentials during a visual oddball task. Significant improvements were observed in self-reported focus, energy, and sleep quality across the intervention. Electrophysiological measures demonstrated reduced frontal theta power during working memory and shorter P300 latencies during attentional processing, consistent with more efficient cognitive processing following the intervention. Although cortisol, dopamine, and resting-state EEG measures did not reach statistical significance, all exhibited changes in the predicted direction. Collectively, these findings provide converging behavioural, biological, and neurophysiological evidence supporting the effectiveness of Autonomic. More broadly, the study demonstrates the value of combining objective biomarkers and EEG with traditional behavioural assessments when evaluating digital behaviour change interventions and highlights the potential of neuroscience-informed coaching platforms to improve health, well-being, and cognitive functioning in university students.

PURPOSE:We tested the hypothesis that marathon racing reduces working memory performance and increases frontal theta activity in trained female endurance athletes. We further examined whether changes in cognitive performance or brain activity were associated with either acute and/or chronic risk of low energy availability. METHODS:Sixteen female Tier 2 runners (42 ± 9 yr; VO 2 max 45.6 ± 6 mL·kg - ¹·min - ¹) underwent VO 2 max testing and the Low Energy Availability in Females Questionnaire (LEAF-Q) 7-14 d before a marathon. Participants completed 1-back (low-load) and 3-back (high-load) working memory tasks during electroencephalogram recordings, performed before and immediately after the race (<10 min). Accuracy and reaction time measured cognitive performance, and frontal theta power measured cognitive effort. RESULTS:Sixteen runners completed the marathon in 4:16 ± 37 min (70 ± 6% VO 2 max), with a mean carbohydrate intake of 28 ± 14 g·h -1 . Six athletes exceeded the LEAF-Q threshold (≥8) and eight reported menstrual dysfunction. Postrace, 3-back accuracy declined (-18.8%, P = 0.003) while reaction time shortened for both task versions (5.3%-6.6%, P = 0.002). Frontal theta increased postrace (1-back: +26.8%; 3-back: +29.6%, P < 0.001). Regression models showed that 3-back accuracy changes were predicted by LEAF-Q score (β = 0.494, P = 0.016). In contrast, theta increases were predicted by a combination of lower carbohydrate intake (β = -0.025, P = 0.005), longer race time (β = 0.008, P = 0.005), and higher LEAF-Q score (β = 0.121, P < 0.001). CONCLUSIONS:Working memory performance is reduced and cognitive effort is increased after marathon racing in trained female athletes. These effects are linked to both acute and chronic risk of low energy availability, emphasizing the need for individualized fueling strategies to preserve cognitive performance during endurance events.

PURPOSE:This study investigated the behavioral and resting-state neural correlates of clinical decision-making among expert gastroenterologists and novice medical students, aiming to understand how diagnostic expertise is reflected in either pre-task and/or post-task brain activity. METHOD:Participants completed a clinical decision-making task while behavioral measures (accuracy and response time) were recorded. Resting-state fMRI data were acquired immediately before and following the task. Group differences in brain connectivity were analyzed using seed-based connectivity and multivariate partial least squares (PLS) analyses, focusing on the frontopolar prefrontal cortex (FPPFC) and its associated networks. FINDING:Experts outperformed novices in diagnostic accuracy and speed, especially on "easy" cases, suggesting enhanced cognitive efficiency. Experts also showed more pronounced response time variation with task difficulty, potentially reflecting strategic modulation. Resting-state fMRI revealed that experts had increased post-task connectivity between the FPPFC and the paracingulate gyrus (PaCG), a brain area associated with the executive control network. Novices, by contrast, showed stronger FPPFC connectivity with the posterior cingulate cortex (PCC), part of the default mode network (DMN), indicating a return to internally directed cognition. PLS analyses further revealed that experts engaged executive and attentional network regions post-task, while novices primarily activated DMN regions. Notably, for the expert group only, increased brain activity in attention-related regions was associated with gastroenterologists who had slower, deliberate responses on easy cases. CONCLUSION:Clinical expertise is associated with sustained engagement of goal-directed neural networks after task completion, potentially reflecting ongoing cognitive evaluation or preparation. In contrast, novices appear to disengage more readily, reverting to self-referential thought. These findings highlight distinct neural mechanisms that may support the development of diagnostic expertise.

Abstract For methodological reasons, reward processing is commonly studied using random feedback and unlearnable tasks. It remains unclear whether task learnability influences reward-related brain activity, and whether this effect depends on individual differences such as reward responsiveness. We addressed this question by administering a behavioural activation system (BAS) scale before recording electroencephalography (EEG) while participants completed learnable and unlearnable versions of the “doors” task, a standard two-choice paradigm. Despite matched outcome likelihoods across conditions, participants reported greater motivation, enjoyment, and perceived performance in the learnable task. Contrary to our predictions, the amplitude of the reward positivity (RewP) – a frontocentral ERP index of reward processing – did not depend on task learnability and reward responsiveness. However, learnability and reward responsiveness effects became apparent when the analysis was restricted to high performers. Within this subgroup, participants low in reward responsiveness showed an enhanced RewP when the task was learnable. These findings suggest that contextual factors such as task learnability can interact with individual differences, informing ongoing efforts to identify the RewP as a biomarker of disordered reward processing.

BACKGROUND:Reduced reward positivity (RewP), an electroencephalography marker elicited by feedback indicating reward, has been associated with an increased risk for depression during adolescence. However, the ability of the RewP to predict the first-lifetime onset of depressive disorders, as opposed to anxiety and suicidal ideation in high-risk populations, has not been thoroughly investigated. In this study, we examined whether the RewP predicts the first-lifetime onset of depression, anxiety, and suicidal ideation over 18 months in familial high-risk adolescents. METHODS:The sample included 145 adolescents (64.8% female), ages 11 to 17 years, who had at least 1 parent with a history of mood or anxiety disorders and completed baseline and at least 1 follow-up measurement. At baseline, the RewP was measured using a simple gambling task; current internalizing symptoms were assessed using self-report questionnaires; and the adolescent's psychiatric diagnoses were evaluated with diagnostic interviews. The same interview was administered to the adolescents again 9 months and 18 months later. RESULTS:Logistic regression models showed that higher RewP scores significantly predicted a lower likelihood of developing a first onset of major depressive disorder over 18 months, even after controlling for sex, age, and baseline internalizing symptoms. In contrast, the RewP did not significantly predict the first onset of anxiety disorders or suicidal ideation. CONCLUSIONS:A reduced RewP precedes the first onset of depression in high-risk adolescents, highlighting the RewP's predictive capability for depression risk in predisposed populations. A blunted RewP could complement self-reported symptoms in screening and prevention.

Medical mistakes made while in a state of cognitive fatigue result in diagnostic errors, psychological distress, poor patient outcomes, and potentially, loss of life. To date, cognitive fatigue in health professionals is assessed via self-report; however, the reliability and validity of these measures are often challenged. Here we propose the use of mobile electroencephalography (mEEG) in a medical context as an objective cognitive fatigue assessment that is cost effective, reliable, and efficient. We had medical students complete a simulated night on call during which they diagnosed a series of simulated medical cases. Before and after their shift, we assessed cognitive fatigue using both behavioural and mEEG measures. Our results demonstrate a decrease in the amplitude of a neural response sensitive to cognitive fatigue from the start to the end of the simulated night on call — a finding associated with an increase in cognitive fatigue. Interestingly, we observed no reltionship between the neural response and subjective self-reported cognitive fatigue scores, supporting the need for objective as opposed to subjective measures when asasessing cognitive fatigue.

We present a method for spatially resolving the electric field potential throughout the entire volume of the human brain from electroencephalography (EEG) data. The method is not a variation of the well-known 'source reconstruction' methods, but rather a direct solution to the EEG inverse problem based on our recently developed model for brain waves that demonstrates the inadequacy of the standard 'quasi-static approximation' that has fostered the belief that such a reconstruction is not physically possible. The method retains the high temporal/frequency resolution of EEG yet has spatial resolution comparable to (or better than) functional MRI (fMRI), without its significant inherent limitations. The method is validated using simultaneous EEG/fMRI data in healthy subjects, intracranial EEG data in epilepsy patients, comparison with numerical simulations, and a direct comparison with standard state-of-the-art EEG analysis in a well-established attention paradigm. The method is then demonstrated on a very large cohort of subjects performing a standard gambling task designed to activate the brain's 'reward circuit'. The technique uses the output from standard extant EEG systems and thus has potential for immediate benefit to a broad range of important basic scientific and clinical questions concerning brain electrical activity. By offering an inexpensive and portable alternative to fMRI, it provides a realistic methodology to efficiently promote the democratization of medicine.

OBJECTIVE:A body of electroencephalographic (EEG) research demonstrates that executive functioning (EF) differences exist in autistic people. Here, we aimed to investigate how and to what extent these EF differences appear in people with high autistic traits in contrast to a low autistic traits comparison. METHODS:The present study used a series of EEG markers (frontal theta power, frontal beta power, the reward positivity ERP component, and the P300 ERP component) to examine potential differences in EF over the course of gambling and oddball tasks. Qualitative research measures to include the perspectives of the autistic people who took part in the study were also used. RESULTS:While frontal theta and beta power differed between groups, we observed no significant component or correlational differences. However, it was found that high autistic traits participants perceived their task performance as worse than low autistic traits participants despite task performance being equal across groups. CONCLUSIONS:EF differences as measured by frontal theta and beta power were observed across groups. Self-perception of task performance may differ in high autistic traits participants when asked to complete tasks under a time constraint.

Here we report the first large-sample electrophysiological evidence that ultramarathon racing reduces neural activity associated with executive function, leading to shorter but less precise behavioral responses.

Acute exercise has been shown to enhance cognitive abilities, particularly those governed by the prefrontal cortex, such as executive function. However, the effects of prolonged exercise on cognition and brain activity, especially over extended recovery periods, remain underexplored. This pilot study investigated the effects of two hours of moderate-intensity running on oscillatory brain activity and working memory performance, monitored across a 24-hour recovery period—an interval not previously studied. Using electroencephalography (EEG) and a 2-back task, resting-state brain activity and task-specific frontal theta power were assessed. While task accuracy and reaction times showed no significant changes, frontal theta power increased one hour post-exercise, reflecting heightened cognitive effort. Resting-state EEG demonstrated a sustained increase in high-alpha power, which persisted until the 24-hour mark and indicated cortical recovery processes. While limited by the lack of a control group, these findings suggest that prolonged moderate-intensity exercise may elicit complex and delayed neurophysiological responses, supporting recovery and neural resilience in trained individuals. Therefore, our research offers new insights into the interplay between exercise, cognition, and recovery, with implications for optimizing performance in physically demanding contexts.

In the current study, electroencephalographic (EEG) data was recorded to study the impact of hand and target visibility on neural processing during both the planning and execution of upper limb reaches. Prior to each movement, participants were informed if the hand and/or the target would be available in four conditions: (1) hand and target visible, (2) hand only, (3) target only, and (4) no hand, no target. Visual evoked potentials (VEPs) were assessed after target onset (i.e., prior to the reaching movement: P2), which revealed larger positive components when vision of the target was not going to be available during the reaching movement (i.e., hand only, no hand-no target) compared to when the target would be present (i.e., hand and target, target only). Further, the motor-related evoked potentials (MEPs) observed in relation to the reaching movement onset showed that a second negative peak generated during the execution of the reaching movement was significantly greater for reaches without vision of the hand, as compared to reaches with vision of the hand. Our results indicate a sequential importance of seeing the target and the hand, prior-to and during the movement, respectively. This work provides neurophysiological evidence to better understand the utilization of vision of the hand and target during goal-directed reaching.

The prevalence of electronic screens in modern society has significantly increased our exposure to high-energy blue and violet light wavelengths. Accumulating evidence links this exposure to adverse visual and cognitive effects and sleep disturbances. To mitigate these effects, the optical industry has introduced a variety of filtering glasses. However, the scientific validation of these glasses has often been based on subjective reports and a narrow range of objective measures, casting doubt on their true efficacy. In this study, we used electroencephalography (EEG) to record brain wave activity to evaluate the effects of glasses that filter multiple wavelengths (blue, violet, indigo, and green) on human brain activity. Our results demonstrate that wearing these multi-colour light filtering glasses significantly reduces beta wave power (13–30 Hz) compared to control or no glasses. Prior research has associated a reduction in beta power with the calming of heightened mental states, such as anxiety. As such, our results suggest that wearing glasses such as the ones used in this study may also positively change mental states, for instance, by promoting relaxation. This investigation is innovative in applying neuroimaging techniques to confirm that light-filtering glasses can induce measurable changes in brain activity.

Human mobility requires neurocognitive inputs to safely navigate the environment. Previous research has examined neural processes that underly walking using mobile neuroimaging technologies, yet few studies have incorporated true real-world methods without a specific task imposed on participants (e.g., dual-task, motor demands). The present study included 40 young adults (M = 22.60, SD = 2.63, 24 female) and utilized mobile electroencephalography (EEG) to examine and compare theta, alpha, and beta frequency band power (mu V-2) during sitting and walking in laboratory and real-world environments. EEG data was recorded using the Muse S brain sensing headband, a portable system equipped with four electrodes (two frontal, two temporal) and one reference sensor. Qualitative data detailing the thoughts of each participant were collected after each condition. For the quantitative data, a 2 x 2 repeated measures ANOVA with within subject factors of environment and mobility was conducted with full participant datasets (n = 17, M = 22.59, SD = 2.97, 10 female). Thematic analysis was performed on the qualitative data (n = 40). Our findings support that mobility and environment may modulate neural activity, as we observed increased brain activation for walking compared to sitting, and for real-world walking compared to laboratory walking. We identified five qualitative themes across the four conditions 1) physical sensations and bodily awareness, 2) responsibilities and planning, 3) environmental awareness, 4) mobility, and 5) spotlight effect. Our study highlights the importance and potential for real-world methods to supplement standard research practices to increase the ecological validity of studies conducted in the fields of neuroscience and kinesiology.

We preferentially process self-related information. However, less is known about how this advantage extends to reward processing and if this process is sensitive to a continuum of self-relevance. Specifically, do we dissociate ourselves from all others when processing rewards, or do those we know personally also enjoy self-related biases? To address this, we recorded electroencephalographic (EEG) data from 30 undergraduate student participants who played a simple two-choice “bandit” gambling game where a photo presented before each gamble indicated whether it benefited either the participant, an individual they knew, or a person they did not know. Temporal spatial principal components analysis (tsPCA) of EEG data evoked by target photos revealed a component consistent with attention and early perceptual processing (the P200), while analysis of data evoked by the feedback stimuli revealed a component consistent with reward processing (the reward positivity). Results demonstrated that P200 component scores were larger for self-gambles than both known- and unknown-other target photos. Interestingly, and contrary to previous findings, reward positivity component scores were similar for all gambles independent of perceived ownership. Our findings suggest that, when gambling for individuals on a continuum of self-relevance, the potential for monetary gain based on the self-relevance cues is differentially processed for ourselves while the actual reward is not. We suggest that the known-other gambling target introduced an empathy-like effect, contesting the self-bias in reward processing.

On the centenary of the first human EEG recording, more than 500 experts reflect on the impact that this discovery has had on our understanding of the brain and behaviour. We document their priorities and call for collective action focusing on validity, democratization and responsibility to realize the potential of EEG in science and society over the next 100 years.