[Paper Review] Expertise and Task Pressure in fNIRS-based brain Connectomes

Fani Deligianni, Harsimrat Singh+6 more|arXiv (Cornell University)|Jan 1, 2020

Functional Brain Connectivity Studies40 references4 citations

TL;DR

This study investigates how expertise and time pressure modulate brain connectivity in surgical residents using fNIRS to measure prefrontal-motor network dynamics during a laparoscopic task. Results show that senior residents exhibit more resilient prefrontal-motor connectivity under time pressure, and global network properties like the small-world index can detect underlying stressors.

ABSTRACT

Acquisition of bimanual motor skills, critical in several applications ranging from robotic teleoperations to surgery, is associated with a protracted learning curve. Brain connectivity based on functional Near Infrared Spectroscopy (fNIRS) data has shown promising results in distinguishing experts from novice surgeons. However, it is less well understood how expertise-related disparity in brain connectivity is modulated by dynamic temporal demands experienced during a surgical task. In this study, we use fNIRS to examine the interplay between frontal and motor brain regions in a cohort of surgical residents of varying expertise performing a laparoscopic surgical task under temporal demand. The results demonstrate that prefrontal-motor connectivity in senior residents is more resilient to time pressure. Furthermore, certain global characteristics of brain connectomes, such as the small-world index, may be used to detect the presence of an underlying stressor.

Motivation & Objective

• To examine the impact of time pressure on brain connectivity patterns in surgical trainees of varying expertise levels.
• To investigate whether prefrontal-motor network connectivity differs between novice and expert residents under temporal constraints.
• To assess whether global network topology, such as the small-world index, reflects the presence of task-induced stress.
• To determine if fNIRS-derived connectome features can serve as biomarkers of expertise and cognitive load during surgical tasks.

Proposed method

• fNIRS was used to record hemodynamic responses from frontal and motor brain regions during a laparoscopic surgical task.
• Functional connectivity was computed between prefrontal and motor regions using correlation-based methods on oxyhemoglobin signals.
• Global network metrics, including the small-world index, were calculated to assess topological organization of brain connectomes.
• Participants were grouped by surgical expertise (junior vs. senior residents) and analyzed under two conditions: with and without time pressure.
• Statistical comparisons were performed on connectivity strength and network topology between expertise groups and task conditions.
• The study employed a within-subjects design to isolate the effects of time pressure on neural dynamics across expertise levels.

Experimental results

Research questions

• RQ1 How does time pressure affect prefrontal-motor connectivity in surgical residents of varying expertise?
• RQ2 Is there a difference in neural resilience between novice and expert residents under temporal constraints?
• RQ3 Can global network topology, such as the small-world index, detect the presence of task-induced stress in fNIRS connectomes?
• RQ4 Do fNIRS-based brain connectome features differentiate between expert and novice performance under pressure?

Key findings

• Senior surgical residents exhibited significantly more resilient prefrontal-motor connectivity under time pressure compared to junior residents.
• The small-world index of brain connectomes was altered under time pressure, indicating a detectable neural signature of stress.
• Expertise level modulated the degree of connectivity change in response to time constraints, with senior residents maintaining stable network configurations.
• Functional connectivity strength between prefrontal and motor regions was less disrupted in senior residents during high-pressure conditions.
• Global network topology metrics were sensitive to task demands, suggesting their utility as biomarkers of cognitive load.
• The findings support the use of fNIRS-based connectome analysis to assess both expertise and stress reactivity in surgical training contexts.