Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Error Related Brain Microstate Analysis during A Complex Surgical Motor Task

Version 1 : Received: 18 April 2022 / Approved: 19 April 2022 / Online: 19 April 2022 (05:48:50 CEST)

A peer-reviewed article of this Preprint also exists.

Walia, P.; Fu, Y.; Norfleet, J.; Schwaitzberg, S.D.; Intes, X.; De, S.; Cavuoto, L.; Dutta, A. Error Related FNIRS-EEG Microstate Analysis during a Complex Surgical Motor Task. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2022, doi:10.1109/embc48229.2022.9871175. Walia, P.; Fu, Y.; Norfleet, J.; Schwaitzberg, S.D.; Intes, X.; De, S.; Cavuoto, L.; Dutta, A. Error Related FNIRS-EEG Microstate Analysis during a Complex Surgical Motor Task. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2022, doi:10.1109/embc48229.2022.9871175.

Abstract

Fundamentals of Laparoscopic Surgery (FLS) is a training module designed to provide basic surgical skills. During skill training of the FLS "suturing and intracorporeal knot-tying" task – the most difficult among the five psychomotor FLS tasks, learning from errors is one of the basic principles of motor skill acquisition where appropriate contextual switching of the brain state on error is postulated. This study investigated changes in the brain state following an error event based on the fusion of simultaneously acquired functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) signals. Here, human error processing is postulated to differentiate experts from novices based on the differences in the error-related chain of mental processes. Thirteen right-handed novice medical students and nine expert surgeons participated in this study. Error-related microstate analysis was performed using 32-channel EEG data at a high temporal resolution. Six microstate prototypes were identified from combined EEG data from experts and novices during the FLS task. Analysis of variance (ANOVA) found that the proportion of the total time spent in different microstates during the 10 sec error epoch 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). Then, the EEG band power (1-40Hz) related to slower oxyhemoglobin (HbO) changes were found using regularized temporally embedded Canonical Correlation Analysis of the fNIRS-EEG signals. The HbO signal from the fNIRS channel overlying ‘Frontal_Inf_Oper_L’, ‘Frontal_Mid_Orb_L’, ‘Postcentral_L’, ‘Temporal_Sup_L’, ‘Frontal_Mid_Orb_R’ cortical areas from Automatic Anatomical Labelling showed significant (p<0.05) difference between experts and novices in the 10-sec error epoch. Here, the frontal/prefrontal cortical areas are postulated to be related to the perception and the activation of the primary somatosensory cortex at the postcentral cortical area is hypothesized to be related to the action underpinning perception-action coupling model for the error-related chain of mental processes. Therefore, our study highlighted the importance of error-related brain states from portable brain imaging when comparing complex surgical skill levels.

Keywords

error; motor learning; surgical skills; EEG; fNIRS; neurovascular coupling

Subject

Medicine and Pharmacology, Surgery

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