Error related fNIRS-EEG microstate analysis during a complex surgical motor task

Fundamentals of Laparoscopic Surgery (FLS) is a standard education and training module with a set of basic surgical skills. During surgical skill acquisition, novices need to learn from errors due to perturbations in their performance which is one of the basic principles of motor skill acquisition. This study on thirteen healthy novice medical students and nine expert surgeons aimed to capture the brain state during error epochs using multimodal brain imaging by combining functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). We performed error-related microstate analysis in the latent space that was found using regularized temporally embedded Canonical Correlation Analysis from fNIRS-EEG recordings during the performance of FLS 'suturing and intracorporeal knot-tying' task - the most difficult among the five psychomotor FLS tasks. We found from two-way analysis of variance (ANDVA) with factors, skill level (expert, novice), and microstate type (1-6) that the proportion of the total time spent in microstates in the error epochs was significantly affected by the skill level (p < 0.01), microstate type (p < 0.01), and the interaction between the skill level and the microstate type (p < 0.01). Therefore, our study highlighted the relevance of portable brain imaging to capture error behavior when comparing the skill level during a complex surgical task. Clinical Relevance - This establishes the brain-behavior relationship for monitoring complex surgical motor task errors that differentiated experts from novices.