Abstract
Pupil size is often used to infer central processes, including attention, memory, and emotion. Recent research has spotlighted its relation to behavioral variables from decision-making models and to neural variables such as locus coeruleus activity and cortical oscillations. As yet, a unified and principled approach for analyzing pupil responses is lacking. Here we seek to establish a formal, quantitative forward model for pupil responses by describing them with linear time-invariant systems. Based on empirical data from human participants, we show that a combination of two linear time-invariant systems can parsimoniously explain approximately all variance evoked by illuminance changes. Notably, the model makes a counterintuitive prediction that pupil constriction dominates the responses to darkness flashes, as in previous empirical reports. This prediction was quantitatively confirmed for responses to light and darkness flashes in an independent group of participants. Crucially, illuminance- and nonilluminance-related inputs to the pupillary system are presumed to share a common final pathway, composed of muscles and nerve terminals. Hence, we can harness our illuminance-based model to estimate the temporal evolution of this neural input for an auditory-oddball task, an emotional-words task, and a visual-detection task. Onset and peak latencies of the estimated neural inputs furnish plausible hypotheses for the complexity of the underlying neural circuit. To conclude, this mathematical description of pupil responses serves as a prerequisite to refining their relation to behavioral and brain indices of cognitive processes.
Highlights
Recent research has spotlighted the relationship between pupil size and behavioral variables derived from formal decisionmaking models (Browning, Behrens, Jocham, Reilly, & Bishop, 2015; Nassar et al, 2012; Preuschoff, ’t Hart, & Einhauser, 2011) and with neural variables such as the locus coeruleus–noradrenergic system in humans (Aston-Jones & Cohen, 2005; Eldar, Cohen, & Niv, 2013; Gilzenrat, Nieuwenhuis, Jepma, & Cohen, 2010) or cortical activity in rodents (McGinley, David, & McCormick, 2015; Reimer et al, 2014) and humans (Yellin, Berkovich-Ohana, & Malach, 2015; Zekveld, Heslenfeld, Johnsrude, Versfeld, & Kramer, 2014)
We specify a psychophysiological model for the temporal evolution of pupil responses, based on two linear time-invariant (LTI) systems
These LTI systems were modeled according to the empirical relationship between pupil size and illuminance
Summary
Measures of pupil size have long been used to enlighten the understanding of diverse psychological processes (Granholm & Steinhauer, 2004), including attention (Binda, Pereverzeva, & Murray, 2013; Wang & Munoz, 2015; Wierda, van Rijn, Taatgen, & Martens, 2012), perception (Einhauser, Stout, Koch, & Carter, 2008; Kloosterman et al, 2015), memory (Goldinger & Papesh, 2012; Kafkas & Montaldi, 2011; Qin, Hermans, van Marle, & Fernandez, 2012), and emotion (Bradley, Miccoli, Escrig, & Lang, 2008; Prehn et al, 2013; Preller et al, 2014). The analysis approaches of pupil measurements currently used in the literature are rather diverse and lack formal specifications. This is in contrast to the formal biophysical models used for neuroimaging analysis (Friston, 2005) and to the recent development of principled approaches for psychophysiological model-
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
