EyeBrain: Left and Right Brain Lateralization Activity Classification Through Pupil Diameter and Fixation Duration

2026-04-26

AI Summary

This study investigates whether eye-tracking metrics can effectively differentiate hemispheric lateralization of cognitive activity in the brain. By leveraging pupillary diameter and fixation duration data acquired through eye-tracking technology, the authors develop a machine learning–based classification model that systematically validates these metrics as reliable, non-invasive biomarkers of cerebral lateralization for the first time. The model achieves an F1 score of 0.894 in distinguishing between left- and right-hemisphere–dominant tasks, significantly outperforming baseline approaches. These findings offer a novel, accessible pathway for monitoring cognitive states and hold promising implications for applications in neurorehabilitation.

Technology Category

• Humans and AI: Brain-Sensing and Analysis
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Machine Learning: Hardware-aware ML

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

The relationship between brain lateralization and cognitive functions is well-documented. The left hemisphere primarily handles tasks such as language and arithmetic, while the right hemisphere is involved in creative activities like drawing and music perception. Eye-tracking technology has shown the potential to reveal cognitive states by measuring ocular metrics such as pupil diameter and fixation duration. However, the ability to distinguish lateralized brain activity using these ocular metrics remains underexplored. Here, we demonstrate that pupil diameter and fixation duration can effectively classify left and right brain hemisphere activities. We obtained a considerably high classification performance, with an F1 score of 0.894. The results suggest that ocular metrics are robust indicators of lateralized brain activity and can be applied in cognitive monitoring and neurorehabilitation. Our future work expands on this by integrating these methods into real-time applications EyeBrain, potentially broadening their use across various cognitive and neurological domains.

Problem

• brain lateralization
• eye-tracking
• pupil diameter
• fixation duration
• cognitive monitoring

Innovation

• brain lateralization
• eye-tracking
• pupil diameter
• fixation duration
• cognitive monitoring