Active eye modeling: a tool for estimating retinal image quality across the visual field in everyday life

Purpose: The "visual diet," the totality of visual experience, shapes retinal image formation and thereby refractive development, but measuring retinal image statistics during everyday behavior is challenging. Limits in mobile eye tracking, egocentric video, and full-field optical measurement leave gaps in our understanding of how environmental and behavioral factors shape image quality across the retina. Methods: We introduce active eye modeling, a computational platform combining optically validated, wide-field, accommodating eye models (Hastings et al. 2024) with realistic three-dimensional virtual environments and gaze behavior derived from human data. This approach enables systematic estimation of retinal blur across the visual field under parametrically controlled conditions, including varying viewing distances, ambient light levels, and environmental depth structure. Inputs may be simulated and/or drawn from real-world measurements: scene depth, video, and gaze/pupil recordings. Results: During simulated far work, peripheral image quality is depth-tolerant, owing to wide depth-of-field from off-axis aberrations. Near work under dim indoor lighting substantially increases peripheral blur, reducing contrast at mid and high spatial frequencies. This contrast reduction is comparable in magnitude to a moderate diffusing filter (Bangerter 0.4 strength) that affects eye growth when imposed experimentally in animal models. A consistency check with eye-tracked virtual driving confirms peripheral depth-tolerance during far work. Conclusions: Active eye modeling provides a flexible framework for investigating how visual experience shapes the retinal image, relevant to refractive development, display and lens design, and peripheral vision. Applied to common visual behaviors, the platform identifies optical conditions during indoor near work that warrant empirical investigation, complementing measurement-based approaches.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-06
DOI
https://doi.org/10.64898/2026.11.04.764163
Primary Topic
Ophthalmology and Visual Impairment Studies
Type
preprint

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preprint

Active eye modeling: a tool for estimating retinal image quality across the visual field in everyday life

Daniel P. Spiegel, Ian M. Erkelens, Phillip Guan, Charlie S. Burlingham et al.
bioRxiv (Cold Spring Harbor Laboratory)
Ophthalmology and Visual Impairment Studies
preprint

Active eye modeling: a tool for estimating retinal image quality across the visual field in everyday life

Daniel P. Spiegel, Ian M. Erkelens, Phillip Guan, Charlie S. Burlingham, Oliver S. Cossairt, Aaron Nicholls
preprint en

Abstract

Purpose: The "visual diet," the totality of visual experience, shapes retinal image formation and thereby refractive development, but measuring retinal image statistics during everyday behavior is challenging. Limits in mobile eye tracking, egocentric video, and full-field optical measurement leave gaps in our understanding of how environmental and behavioral factors shape image quality across the retina. Methods: We introduce active eye modeling, a computational platform combining optically validated, wide-field, accommodating eye models (Hastings et al. 2024) with realistic three-dimensional virtual environments and gaze behavior derived from human data. This approach enables systematic estimation of retinal blur across the visual field under parametrically controlled conditions, including varying viewing distances, ambient light levels, and environmental depth structure. Inputs may be simulated and/or drawn from real-world measurements: scene depth, video, and gaze/pupil recordings. Results: During simulated far work, peripheral image quality is depth-tolerant, owing to wide depth-of-field from off-axis aberrations. Near work under dim indoor lighting substantially increases peripheral blur, reducing contrast at mid and high spatial frequencies. This contrast reduction is comparable in magnitude to a moderate diffusing filter (Bangerter 0.4 strength) that affects eye growth when imposed experimentally in animal models. A consistency check with eye-tracked virtual driving confirms peripheral depth-tolerance during far work. Conclusions: Active eye modeling provides a flexible framework for investigating how visual experience shapes the retinal image, relevant to refractive development, display and lens design, and peripheral vision. Applied to common visual behaviors, the platform identifies optical conditions during indoor near work that warrant empirical investigation, complementing measurement-based approaches.

bioRxiv (Cold Spring Harbor Laboratory)
Meta (United States) (US)
Meta
Ophthalmology and Visual Impairment Studies
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