pypillometry: A Python package for pupillometric analyses

Abstract

The size of the human pupil is controlled by pairs of constrictor and dilator muscles that allow its opening (dilation) and closing (constriction) in response to varying lighting conditions (Mathôt, 2018). Importantly, it has long been known that the pupil also reacts to psychological important stimuli (Hess & Polt, 1960) and has been a firmly established tool for studying “mental effort” in the research kit of psychologists for many decades (Laeng, Sirois, & Gredebäck, 2012). More recently, pupil-size has been linked to the norepinephrinergic (NE) system originating from area locus coeruleus (LC) in the brainstem (Aston-Jones & Cohen, 2005), a link that has been substantiated experimentally by direct recordings in the brainstem of monkeys (Joshi, Li, Kalwani, & Gold, 2016). This finding of a correlation between NE activity in the brainstem and pupil-dilation has opened the way for researchers investigating the relationship between the LC-NE system and many cognitive functions, such as cognitive control (Gilzenrat, Nieuwenhuis, Jepma, & Cohen, 2010) and mind wandering (Mittner, Hawkins, Boekel, & Forstmann, 2016). Advancing this emerging field requires the decomposition of the pupillometric signal into tonic (baseline) and phasic (response) components that relate to different processing regimes of the LC-NE system.