Mentor's brain functional connectivity network during robotic assisted surgery mentorship

Area of Science:

• Neuroscience
• Cognitive Science
• Surgical Education

Background:

• Mentoring complex cognitive-motor tasks is crucial for skill acquisition.
• Mentor's ability to adapt to trainee's evolving expertise is key.
• Hypothesizes changes in mentor's brain functional connectivity with trainee's skill progression.

Purpose of the Study:

• Investigate how mentor's brain functional connectivity network changes with trainee expertise.
• Examine the role of modularity and neural activity efficiency in mentoring.
• Correlate brain network characteristics with mentor's satisfaction and surgical performance.

Main Methods:

• Measured mentor's brain activity using a 24-channel EEG headset during various conditions (mentoring novices/intermediates, observing experts, performing surgery).
• Extracted functional connectivity networks and analyzed modularity and neural efficiency.
• Assessed mentor's subjective performance using NASA-TLX indexes.

Main Results:

• Functional connectivity network modularity was higher during solo performance and expert observation compared to mentoring novices/intermediates.
• Significant positive correlation found between performance level and modularity (r = 0.38, p < 0.005).
• Higher modularity indicates increased automaticity and decreased neural cost with improved performance.

Conclusions:

• Mentor's brain network organization adapts based on trainee's expertise level.
• Increased modularity in the mentor's brain network is associated with better surgical outcomes and efficient cognitive processing.
• Findings highlight the neural basis of effective mentorship in skill-intensive domains.