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Journal Article

PyPlr: A versatile, integrated system of hardware and software for researching the human pupillary light reflex

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Martin, J., Pinto, J., Bulte, D., & Spitschan, M. (2022). PyPlr: A versatile, integrated system of hardware and software for researching the human pupillary light reflex. Behavior Research Methods, 54(6), 2720-2739. doi:10.3758/s13428-021-01759-3.

Cite as: https://hdl.handle.net/21.11116/0000-0009-FE18-F
We introduce PyPlr—a versatile, integrated system of hardware and software to support a broad spectrum of research applications concerning the human pupillary light reflex (PLR). PyPlr is a custom Python library for integrating a research-grade video-based eye-tracker system with a light source and streamlining stimulus design, optimisation and delivery, device synchronisation, and extraction, cleaning, and analysis of pupil data. We additionally describe how full-field, homogenous stimulation of the retina can be realised with a low-cost integrating sphere that serves as an alternative to a more complex Maxwellian view setup. Users can integrate their own light source, but we provide full native software support for a high-end, commercial research-grade 10-primary light engine that offers advanced control over the temporal and spectral properties of light stimuli as well as spectral calibration utilities. Here, we describe the hardware and software in detail and demonstrate its capabilities with two example applications: (1) pupillometer-style measurement and parametrisation of the PLR to flashes of white light, and (2) comparing the post-illumination pupil response (PIPR) to flashes of long and short-wavelength light. The system holds promise for researchers who would favour a flexible approach to studying the PLR and the ability to employ a wide range of temporally and spectrally varying stimuli, including simple narrowband stimuli.