Cerebral cortical networking for mental workload assessment under various demands during dual-task walking.

While several studies have examined attentional reserve (via event-related potentials) and mental effort (via EEG spectral content) from various cortical regions during dual-task walking, none have assessed changes in the magnitude of interregional (cortico-cortical) communication as a measure of mental workload. Therefore, by deploying a traditional montage of electrode sites centered over the motor planning region as well as a more comprehensive graph theory-based approach encompassing the entire scalp, this study aimed to systematically examine changes in the magnitude of functional connectivity underlying cortico-cortical communication to assess changes in mental workload under various levels of challenge. Specifically, the Weighted Phase Lag Index (WPLI) was computed to assess the changes in magnitude of functional connectivity as participants performed a cognitive task under two demands (low and high) and two conditions (seated and walking). The results revealed enhanced fronto-centro-temporo-parietal theta connectivity during dual-task walking relative to being seated as well as a reduced inhibition of fronto-centro-temporo-parieto-occipital alpha networking as the demand on the secondary cognitive task increased. Collectively, these findings may reflect greater recruitment of task relevant processes to respond to increased cognitive-motor demands and thus an elevation of mental workload in an effort to maintain performance under varying levels of challenge. This work has the potential to inform future mental workload assessment applications in patient populations, including those who employ prostheses during cognitive-motor performance under various task demands.

Changes in motor performance and mental workload during practice of reaching movements: a team dynamics perspective.

Few investigations have examined mental workload during motor practice or learning in a context of team dynamics. This study examines the underlying cognitive-motor processes of motor practice by assessing the changes in motor performance and mental workload during practice of reaching movements. Individuals moved a robotic arm to reach targets as fast and as straight as possible while satisfying the task requirement of avoiding a collision between the end-effector and the workspace limits. Individuals practiced the task either alone (HA group) or with a synthetic teammate (HRT group), which regulated the effector velocity to help satisfy the task requirements. The findings revealed that the performance of both groups improved similarly throughout practice. However, when compared to the individuals of the HA group, those in the HRT group (1) had a lower risk of collisions, (2) exhibited higher performance consistency, and (3) revealed a higher level of mental workload while generally perceiving the robotic teammate as interfering with their performance. As the synthetic teammate changed the effector velocity in specific regions near the workspace boundaries, individuals may have been constrained to learn a piecewise visuomotor map. This piecewise map made the task more challenging, which increased mental workload and perception of the synthetic teammate as a burden. The examination of both motor performance and mental workload revealed a combination of both adaptive and maladaptive team dynamics. This work is a first step to examine the human cognitive-motor processes underlying motor practice in a context of team dynamics and contributes to inform human-robot applications.

Motor Performance, Mental Workload and Self-Efficacy Dynamics during Learning of Reaching Movements throughout Multiple Practice Sessions.

The human capability to learn new motor skills depends on the efficient engagement of cognitive-motor resources, as reflected by mental workload, and psychological mechanisms (e.g., self-efficacy). While numerous investigations have examined the relationship between motor behavior and mental workload or self-efficacy in a performance context, a fairly limited effort focused on the combined examination of these notions during learning. Thus, this study aimed to examine their concomitant dynamics during the learning of a novel reaching skill practiced throughout multiple sessions. Individuals had to learn to control a virtual robotic arm via a human-machine interface by using limited head motion throughout eight practice sessions while motor performance, mental workload, and self-efficacy were assessed. The results revealed that as individuals learned to control the robotic arm, performance improved at the fastest rate, followed by a more gradual reduction of mental workload and finally an increase in self-efficacy. These results suggest that once the performance improved, less cognitive-motor resources were recruited, leading to an attenuated mental workload. Considering that attention is a primary cognitive resource driving mental workload, it is suggested that during early learning, attentional resources are primarily allocated to address task demands and not enough are available to assess self-efficacy. However, as the performance becomes more automatic, a lower level of mental workload is attained driven by decreased recruitment of attentional resources. These available resources allow for a reliable assessment of self-efficacy resulting in a subsequent observable change. These results are also discussed in terms of the application to the training and design of assistive technologies.

Combined assessment of attentional reserve and cognitive-motor effort under various levels of challenge with a dry EEG system.

A novel ERP approach was proposed to index variations in mental workload, particularly in attentional reserve, which is complementary to EEG spectral content thought to reflect mental effort. To our knowledge, no study has assessed mental effort and attentional reserve simultaneously in EEG gel-based and, importantly, dry systems, which are particularly well suited for real-world settings. Therefore, by systematically considering ERP, EEG spectral, and importantly the combination of both, this study examined if a small set of dry EEG electrodes could detect changes in both spectral and ERP metrics to assess the mental workload under various challenges with a similar fidelity to their gel-based counterparts in a laboratory setting. By employing both EEG gel-based and dry systems, the ERP and spectral markers were computed while participants executed a visuomotor task under three levels of challenge. For both EEG systems, more challenging levels of difficulty were associated with concomitant changes in ERP amplitude, and spectral power reflected a reduction of the attentional reserve and an increase in cognitive-motor effort, respectively. Those variations in attentional reserve and cognitive-motor effort collectively indexed mental workload with nearly identical fidelity for both gel-based and dry EEG systems. These findings promise to assess the mental workload in situations where the use of dry EEG systems could be advantageously employed to examine human cognitive-motor performance.

Mental workload and motor performance dynamics during practice of reaching movements under various levels of task difficulty.

The assessment of mental workload can inform attentional resource allocation during task performance that is essential for understanding the underlying principles of human cognitive-motor behavior. While many studies have focused on mental workload in relation to human performance, a modest body of work has examined it in a motor practice/learning context without considering individual variability. Thus, this work aimed to examine mental workload by employing the NASA TLX as well as the changes in motor performance resulting from the practice of a novel reaching task. Two groups of participants practiced a reaching task at a high and low nominal difficulty during which a group-level analysis assessed the mental workload, motor performance and motor improvement dynamics. A secondary cluster analysis was also conducted to identify specific individual patterns of cognitive-motor responses. Overall, both group- and cluster-level analyses revealed that: (i) all participants improved their performance throughout motor practice, and (ii) an increase in mental workload was associated with a reduction of the quality of motor performance along with a slower rate of motor improvement. The results are discussed in the context of the optimal challenge point framework and in particular it is proposed that under the experimental conditions employed here, functional task difficulty: (i) would possibly depend on an individuals' information processing capabilities, and (ii) could be indexed by the level of mental workload which, when excessively heightened can decrease the quality of performance and more generally result in delayed motor improvements.