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Brain-Pupil Coupling Revealed Through Deep Learning of Intracranial Recordings
Vicki Li1, Simeon M Wong1,2, Hrishikesh Suresh1,2,3
1Program in Neuroscience and Mental Health, The Hospital for Sick Children, Toronto, Canada.
Human Brain Mapping
|December 10, 2025
Summary
Pupil size changes reflect cognitive processing and brain activity. This study links pupil dynamics to attentional set-shifting performance and neural network engagement in youth.
Area of Science:
- Neuroscience
- Cognitive Science
- Psychology
Background:
- Pupillary responses offer insights into human cognition, but their underlying neural mechanisms remain unclear.
- Understanding brain-pupil coupling is crucial for deciphering cognitive processes.
Purpose of the Study:
- To investigate the neural substrates of pupillary responses during an attentional set-shifting task.
- To explore the relationship between pupil diameter, neural activity, and cognitive performance in children and youth.
Main Methods:
- Intracranial recordings and pupillometry were used in 13 participants (ages 9-18) with epilepsy during an attentional set-shifting task.
- Time-resolved mixed-effects modeling and deep learning models were employed to analyze brain-pupil coupling.
- Salience-based gradient mapping identified task-relevant brain regions.
Main Results:
- Pupillary dynamics showed task-stage dependencies, with pupil size linked to reaction times and performance accuracy.
- Band-limited power in neural networks correlated with pupil size changes during the task.
- Deep learning models predicted pupil size changes from intracranial neural activity with significant accuracy.
Conclusions:
- Pupillary responses are tightly coordinated with goal-oriented cognitive processing, particularly during attentional set-shifting.
- These findings provide a foundation for using pupillary dynamics to model cognitive functions.
- The study highlights a network of cortical and subcortical regions involved in modulating pupil dynamics.
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