In our study [1], we presented brain-behavior analysis for the validation of simulators for laparoscopic surgical skill training (figure 1). Specifically, we investigated the brain-behavior relationship during the Fundamentals of Laparoscopic Surgery (FLS) pattern cutting task based on the dorsal stream for action [2] in a physical and a VR simulator [3]. Here, we postulated that the dorsal stream for action during skill training uses sensory afference of a ‘perceptual set’ of the visual scene and the efference copy of the ‘motor set’ of action to build a mental model, which can differ between the physical and VR simulator. A well-developed mental model may also need to be adapted for a related condition, e.g., when experts who previously learned with physical simulators then learned on VR simulator in this study. Therefore, an interaction between the simulator technology (physical, VR) and the skill level (expert, novice) was also expected.

In our study [1], the mobile brain-behavior investigation was performed using functional near-infrared spectroscopy (fNIRS), a portable brain imaging technology that can be conveniently applied with a wearable cap during the performance of the FLS pattern cutting task. We conducted the study on a convenience sample of seven experienced right-handed surgeons (experts, 5th-year residents, and attending surgeons) and six right-handed medical students (novices, 1st- to 3rd-year residents). All subjects were instructed verbally with a standard set of instructions on completing the FLS pattern cutting task on the FLS-certified physical and the VR simulator. All the right-handed subjects were asked to grasp the gauze using the left grasper (for traction) and cut along (and within) the circular stamp with the right laparoscopic scissors (for cutting). Then, the dorsal stream of action was investigated based on the directed information flow that was estimated using a time-varying Granger causality analysis of the fNIRS data.

The result that stood out was the importance of the efference copy information from the cortical motor areas to the prefrontal cortex to reduce behavioral variability. Specifically, the coefficient of variation (CoV) of the FLS performance score was statistically significantly associated with the CoV of the directed functional connectivity from the right primary motor cortex to the left primary motor cortex and from the left primary motor cortex to the left prefrontal cortex during the bimanual FLS pattern cutting task. Indeed, reduction of behavioral variability will require a well-developed mental model that can take the desired tool trajectory and output the corresponding motor command (i.e., inverse models) for accurate action or take an efferent copy of motor command and predict the future state of the body (i.e., forward models) for accurate perceptual decision-making. When there is no internal error or conflict between the sensory afferent signal (from the environment) and the prediction of the forward model, then the subject can achieve a complete sense of control (metacognition) in the simulation environment. Notably, sensory conflict can also generate autonomic signs and symptoms that constitute cybersickness.   

The insights from our study [1] are crucial for not only validating medical simulation technology but also for facilitating skill training in an augmented (AR, MR) simulation environment where virtual sensory stimulation (sensory exafference) can be provided to the ventral stream (figure 2) for ‘bottom-up’ attention for perception [4]. Notably, a lack of subjective sense of control and sensory conflict may trigger the stress response and cybersickness where brain-behavior analysis of various conflict-reducing sensory exafference can help, e.g., fading transitions, blurring, etc. Moreover, sensory exafference under portable brain imaging can be used for motion sickness conditioning, operant conditioning with a disproportionate weighting of feedback [5] as well as explicit stimulus-reward pairing via the ventral stream for the perception that needs investigation in XR simulation training. Then, non-invasive brain stimulation (NIBS) in conjunction with brain-behavior analysis [6] can establish causality of the corresponding brain regions, e.g., by disruption with NIBS [7], as well as can facilitate skill learning [8], e.g., with NIBS of ‘top-down’ executive control [9],[10] from the prefrontal cortex/frontal eye field to the superior parietal lobule of the posterior association cortex [4].

              In conclusion, our study motivated the need for brain-behavior analysis to validate simulation technologies that may have established convergent validity [3]. Then, brain-behavior validation of skilled performance is crucial where XR technologies are increasingly being applied for skill training.

Learn more by reading our research article: Directed information flow during laparoscopic surgical skill acquisition dissociated skill level and medical simulation technology, published by npj Science of Learning. 

References:

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