Editorial: Mental imagery: ‘you can observe a lot by watching!’
Urethrovesical anastomosis (UVA), like any other surgical anastomosis, is a key example of motor muscle memory, where aligning two hollow structures should result in a watertight anastomosis defining its success and help avoid complications. The authors  investigated the importance of cognitive training during UVA, which has been shown to be a promising supplement to skill‐based training. The authors utilised the Global Evaluative Assessment of Robotic Skills (GEARS), which has been validated for assessment of general robotic rather than procedure‐specific skills. As the authors chose UVA to evaluate training, they could have used the Robotic Anastomosis Competency Evaluation (RACE), which has been developed and validated for specific evaluation of UVA . However, the study eloquently revealed higher scores, using the validated movement imagery questionnaire modified for robot‐assisted surgery whilst evaluating mental imagery.
Motor imagery utilises imagining action without its physical execution and this leads to eliciting activity in regions of brain normally activated during performance. Motor imagery has shown significant neural activity in important brain area involved in somatosensory perception, especially kinesthetic information from motor perception and muscle spindles. Such areas become active when a motor illusion is induced that ultimately share the same basis with areas active during executing movement. Mental imagery also yields more benefits if its sessions are interposed between periods of training . Unfortunately, the ability to imagine more complex tasks is less accurate when utilising mental imagery . In future, studies using procedure‐specific evaluation, such as RACE, may help us understand in depth the role of mental imagery during various steps of complex task, such as UVA. The hypothesis of improvement of skills whilst utilising supplemental cognitive training is reasonable; future studies will benefit from utilising an elaborate cognitive assessment. Metrics such as electroencephalograms (EEGs) and eye tracking, or even less sophisticated tools like the National Aeronautics and Space Administration Task Load Index (NASA‐TLX) self‐assessment questionnaires, have previously been used for assessment of cognitive load . Objective feedback provided by a brain–computer interface (BCI) can increase the brain activation levels produced during motor imagery and thereby help in improving performance .
Motor imagery has been used as a popular input for BCI and in future could be used as a link to establishing instruction to semi‐autonomous robotic systems . Meanwhile, a motor imagery BCI using EEG is utilising intention recognition through decoding brain activity, which ultimately could allow for intuitive control of devices like robotic systems.
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