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

A tale of too many tasks: task fragmentation in motor learning and a call for model task paradigms

Motor learning encompasses a broad set of phenomena that requires a diverse set of experimental paradigms. However, excessive variation in tasks across studies creates fragmentation that can adversely affect the collective advancement of knowledge. Here, we show that motor learning studies tend toward extreme fragmentation in the choice of tasks, with almost no overlap between task paradigms across studies. We argue that this extreme level of task fragmentation poses serious theoretical and methodological barriers to advancing the field. To address these barriers, we propose the need for developing common 'model' task paradigms which could be widely used across labs. Combined with the open sharing of methods and data, we suggest that these model task paradigms could be an important step in increasing the robustness of the motor learning literature and facilitate the cumulative process of science.

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.

Detecting Mental Workload in Surgical Teams Using a Wearable Single-Channel Electroencephalographic Device

OBJECTIVE

To assess the sensitivity of an electroencephalographic (EEG)-based index, the prefrontal beta power, to quantify the mental workload in surgeons in real scenarios. Such EEG-based index might offer unique and unbiased measures of overload, a crucial factor when designing learning and training surgical programs.

DESIGN

The experiment followed a 2 × 2 × 2 within subjects design with 3 factors: (1) Surgical Role during the surgery (primary surgeon vs. assistant surgeon), (2) the Surgical Procedure (laparo-endoscopic single-site [LESS] surgery vs. multiport laparoscopic surgery [MPS]), and (3) the Suturing Techniques (interrupted vs. continuous suture).

SETTING

The study was carried out at the Advanced Multi-Purpose Simulation and Technological Innovation Complex situated at IAVANTE (Granada, Spain).

METHODS

Four surgical teams (primary surgeon and assistant surgeon, experts in MPS) performed 8 surgical exercises on porcine models, under different task complexities. They performed 2 suturing techniques (continuous and interrupted), employing a low complex procedure (MPS) and a high complex procedure (LESS). Surgeons acted as the primary surgeon during half of the exercises, and, as the assistant surgeon, during the rest of them. Simultaneously, we monitored EEG prefrontal EEG beta power spectra of both surgeons, using 2 synchronized wearable EEG devices. We also collected performance and subjective data.

RESULTS

Surgical complexity modulated prefrontal beta power. LESS surgery caused significant higher prefrontal beta power for both suturing techniques for both surgical roles which indicates higher demands than MPS. Perceived task complexity, overall surgical evaluation, and laparoscopic execution time confirmed EEG-based results. Finally, subjective ratings of surgical complexity differentiated between surgical roles within the same exercise, even when prefrontal beta power did not.

CONCLUSIONS

To detect mental overload when surgeons are engaged with complex surgeries, real or simulated, is still guesswork. EEG-based indices have great potential as objective and nonintrusive measures to assess mental overload in surgeons. Furthermore, EEG-based indices might play a relevant role in monitoring surgeons and residents' cognitive state during their training.

Biomechanical and neurocognitive performance outcomes of walking with transtibial limb loss while challenged by a concurrent task

Individuals who have sustained loss of a lower limb may require adaptations in sensorimotor and control systems to effectively utilize a prosthesis, and the interaction of these systems during walking is not clearly understood for this patient population. The aim of this study was to concurrently evaluate temporospatial gait mechanics and cortical dynamics in a population with and without unilateral transtibial limb loss (TT). Utilizing motion capture and electroencephalography, these outcomes were simultaneously collected while participants with and without TT completed a concurrent task of varying difficulty (low- and high-demand) while seated and walking. All participants demonstrated a wider base of support and more stable gait pattern when walking and completing the high-demand concurrent task. The cortical dynamics were similarly modulated by the task demand for both groups, to include a decrease in the novelty-P3 component and increase in the frontal theta/parietal alpha ratio power when completing the high-demand task, although specific differences were also observed. These findings confirm and extend prior efforts indicating that dual-task walking can negatively affect walking mechanics and/or neurocognitive performance. However, there may be limited additional cognitive and/or biomechanical impact of utilizing a prosthesis in a stable, protected environment in TT who have acclimated to ambulating with a prosthesis. These results highlight the need for future work to evaluate interactions between these cognitive-motor control systems for individuals with more proximal levels of lower limb loss, and in more challenging (ecologically valid) environments.

Changes in Mental Workload and Motor Performance Throughout Multiple Practice Sessions Under Various Levels of Task Difficulty

The allocation of mental workload is critical to maintain cognitive-motor performance under various demands. While mental workload has been investigated during performance, limited efforts have examined it during cognitive-motor learning, while none have concurrently manipulated task difficulty. It is reasonable to surmise that the difficulty level at which a skill is practiced would impact the rate of skill acquisition and also the rate at which mental workload is reduced during learning (relatively slowed for challenging compared to easier tasks). This study aimed to monitor mental workload by assessing cortical dynamics during a task practiced under two difficulty levels over four days while perceived task demand, performance, and electroencephalography (EEG) were collected. As expected, self-reported mental workload was reduced, greater working memory engagement via EEG theta synchrony was observed, and reduced cortical activation, as indexed by progressive EEG alpha synchrony was detected during practice. Task difficulty was positively related to the magnitude of alpha desynchrony and accompanied by elevations in the theta-alpha ratio. Counter to expectation, the absence of an interaction between task difficulty and practice days for both theta and alpha power indicates that the refinement of mental processes throughout learning occurred at a comparable rate for both levels of difficulty. Thus, the assessment of brain dynamics was sensitive to the rate of change of cognitive workload with practice, but not to the degree of difficulty. Future work should consider a broader range of task demands and additional measures of brain processes to further assess this phenomenon.