Exploring Pupil-Brain Dynamics Across Different Grouping Methods in Resting-State fMRI

Motivation: This study is motivated by the need to understand the relationship between pupil dynamics and resting-state brain activity, across different levels of alertness. Goal(s): Our goal is to determine whether different methods of categorizing subjects based on the pupil size influence observed correlations between pupil dynamics and resting-state brain activity. Approach: We categorized subjects into high- and low-alertness groups using four methods. Pupil size and its derivative were analyzed for correlations with brain activity across lags. Results: K-means clustering provided the best separation of alertness groups, with stronger correlations in the pupil derivative, especially in Auditory, Visual, and Motor networks. Impact: This study highlights pupil size variation as a potential indicator of neural dynamics associated with cognitive states like arousal. It emphasizes the influence of categorization methods on brain-pupil correlations, offering insights for both clinical and research applications.