Oftentimes we find ourselves in situations in which we need to perform concurrent motor and cognitive tasks like simple locomotion while being cognitively involved. In the present study, we investigated in how far cognitive and motor functioning interfere in an outdoor environment. Our participants performed an auditory oddball task while concurrently completing various motor tasks on the outside premises of our institute. Beside behavioural responses and subjective workload ratings, we also analysed electrophysiological data recorded with a 30-channel mobile EEG montage. We observed an increase of subjective workload and decrease of performance with increasing movement complexity. Accordingly, we also found a decrease in the parietal P3 amplitude as well as in frontal midline Theta power with higher motor load. These results indicate that an increased movement complexity imposes a higher workload to the cognitive system, which, in turn, effectively reduces the availability of cognitive resources for the cognitive task. Overall this experiment demonstrates the feasibility of transferring classical paradigms of cognitive research to real-world settings. The findings support the notion of shared resources for motor and cognitive functions by demonstrating distinct modulations of correlates of cognitive processes across different motor tasks.

Mind wandering during ongoing tasks can impede task performance and increase the risk of failure in the laboratory as well as in daily‐life tasks and work environments. Neurocognitive measures like the electroencephalography (EEG) offer the opportunity to assess mind wandering non‐invasively without interfering with the primary task. However, the literature on electrophysiological correlates of mind wandering is rather inconsistent. The present study aims toward clarifying this picture by breaking down the temporal dynamics of mind wandering encounters using a cluster‐based permutation approach. Participants performed a switching task during which mind wandering was occasionally assessed via thought probes applied after trial completion at random time points. In line with previous studies, response accuracy was reduced during mind wandering. Moreover, alpha power during the inter‐trial interval was a significantly increased on those trials on which participants reported that they had been mind‐wandering. This spatially widely distributed effect is theoretically well in line with recent findings linking an increased alpha power to an internally oriented state of attention. Measurements of alpha power may, therefore, be used to detect mind wandering online during critical tasks in traffic and industry in order to prevent failures.

Adaptively changing between different tasks while in locomotion is a fundamental prerequisite of modern daily life. The cognitive processes underlying dual tasking have been investigated extensively using EEG. Due to technological restrictions, however, this was not possible for dual-task scenarios including locomotion. With new technological opportunities, this became possible and cognitive-motor interference can be studied, even in outside-the-lab environments. In the present study, par-How to cite this article: Reiser JE, Wascher E, Rinkenauer G, Arnau S. Cognitive-motor interference in the wild: Assessing the effects of movement complexity on task switching using mobile EEG. Eur

Film based round the ear electrodes (cEEGrids) provide both, the accessibility of unobtrusive mobile EEG as well as a rapid EEG application in stationary settings when extended measurements are not possible. In a large-scale evaluation of driving abilities of older adults (N > 350) in a realistic driving simulation, we evaluated to what extent mental demands can be measured using cEEGrids in a completely unrestricted environment. For a first frequency-based analysis, the driving scenario was subdivided into different street segments with respect to their task loads (low, medium, high) that was a priori rated by an expert. Theta activity increased with task load but no change in Alpha power was found. Effects gained clarity after removing pink noise effects, that were potentially high in this data set due to motion artifacts. Theta fraction increased with task load and Alpha fraction decreased. We mapped this effect to specific street segments by applying a track-frequency analysis. Whilst participants drove with constant speed and without high steering wheel activity, Alpha was high and theta low. The reverse was the case in sections that required either high activity or increased attentional allocation to the driving context. When calculating mental demands for different street segments based on EEG, this measure is highly significant correlated with the experts’ rating of task load. Deviances can be explained by specific features within the segments. Thus, modulations in spectral power of the EEG were validly reflected in the cEEGrids data. All findings were in line with the prominent literature in the field. The results clearly demonstrate the usability of this low-density EEG method for application in real-world settings where an increase in ecological validity might outweigh the loss of certain aspects of internal validity.

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Blinking is a natural user-induced response which paces visual information processing. This study investigates whether blinks are viable for segmenting continuous electroencephalography (EEG) activity, for inferring cognitive demands in ecologically valid work environments. We report the blink-related EEG measures of participants who performed auditory tasks either standing, walking on grass, or whilst completing an obstacle course. Blink-related EEG activity discriminated between different levels of cognitive demand during walking. Both behavioral parameters (e.g., blink duration or head motion) and blink-related EEG activity varied with walking conditions. Larger occipital N1 was observed during walking, relative to standing and traversing an obstacle course, which reflects differences in bottom-up visual perception. In contrast, the amplitudes of top-down components (N2, P3) significantly decreased with increasing walking demands, which reflected narrowing attention. This is consistent with blink-related EEG, specifically in Theta and Alpha power that, respectively, increased and decreased with increasing demands of the walking task. This work presents a novel and robust analytical approach to evaluate the cognitive demands experienced in natural work settings, which precludes the use of artificial task manipulations for data segmentation.

Ergonomic assessment of a workplace requires the evaluation of physical as well as cognitive aspects of a particular working situation. In particular the latter is hardly possible without interfering in the natural setting. Mobile acquisition of neurophysiological measures (such as parameters of the EEG) may close this gap. At a simulated workplace we tracked older and younger participants with mobile EEG during a 4–5 h work shift. They had to perform either a monotonous cognitive task, a self-paced cognitive task or a self-paced physical task in a predefined order. Self assessment, behavioral performance and spectral measures of the EEG (before most alpha power) indicated that younger participants suffered from monotony. Older adults, on the other hand, were overall impaired by inefficient information processing. This was visible in EEG variations time-locked to eye blinks (blink-related synchronizations), a new measure to investigate cognitive processing in real life environments. Thus, we were able to distinguish between active and passive task-related aspects of mental fatigue without impinging on the natural working situation.

Healthy aging is associated with a decline in cognitive functions. This may become an issue when complex tasks have to be performed like driving a car in a demanding traffic situation. On the other hand, older people are able to compensate for age-related deficits, e.g., by deploying extra mental effort and other compensatory strategies. The present study investigated the interplay of age, task workload, and mental effort using EEG measures and a proactive driving task, in which 16 younger and 16 older participants had to keep a virtual car on track on a curvy road. Total oscillatory power and relative power in Theta and Alpha bands were analyzed, as well as event-related potentials (ERPs) to task-irrelevant regular and irregular sound stimuli. Steering variability and Theta power increased with increasing task load (i.e., with shaper bends of the road), while Alpha power decreased. This pattern of workload and mental effort was found in both age groups. However, only in the older group a relationship between steering variability and Theta power occurred: better steering performance was associated with higher Theta power, reflecting higher mental effort. Higher Theta power while driving was also associated with a stronger increase in reported subjective fatigue in the older group. In the younger group, lower steering variability came along with lower ERP responses to deviant sound stimuli, reflecting reduced processing of task-irrelevant environmental stimuli. In sum, better performance in proactive driving (i.e., more alert steering behavior) was associated with increased mental effort in the older group, and higher attentional focus on the task in the younger group, indicating age-specific strategies in the way younger and older drivers manage demanding (driving) tasks.