Visual expertise modulates resting-state brain network dynamics in radiologists: a degree centrality analysis

Area of Science:

• Neuroscience
• Radiology
• Cognitive Science

Background:

• Visual expertise, developed through extensive image review, influences brain function.
• Previous research focused on task-based fMRI, leaving resting-state network dynamics under-explored.
• Understanding how visual experience shapes the brain at rest is crucial for cognitive neuroscience.

Purpose of the Study:

• To investigate the impact of visual experience on resting-state brain network dynamics.
• To identify specific brain regions and network changes associated with visual expertise in radiology.
• To differentiate brain network patterns between radiology interns and healthy controls.

Main Methods:

• Recruited 22 radiology interns (RI) and 22 matched healthy controls.
• Utilized resting-state functional magnetic resonance imaging (rs-fMRI).
• Applied degree centrality (DC) analysis and recursive feature elimination-support vector machine (SVM) for classification.

Main Results:

• Significant differences in degree centrality (DC) were observed between RI and control groups.
• Affected brain regions include those involved in visual processing, decision-making, memory, attention, and working memory.
• An SVM algorithm achieved 88.64% classification accuracy in distinguishing between the groups based on brain network dynamics.

Conclusions:

• Accumulated visual experience in radiologists significantly modulates resting-state brain network dynamics.
• These findings offer novel insights into the neural underpinnings of visual expertise.
• The study highlights the brain's adaptability and plasticity in response to specialized training.