The additive nature of the human multisensory evoked pupil response

Abstract

Pupillometry has received increased interest for its usefulness in measuring various sensory processes as an alternative to behavioural assessments. This is also apparent for multisensory investigations. Studies of the multisensory pupil response, however, have produced conflicting results. Some studies observed super-additive multisensory pupil responses, indicative of multisensory integration (MSI). Others observed additive multisensory pupil responses even though reaction time (RT) measures were indicative of MSI. Therefore, in the present study, we investigated the nature of the multisensory pupil response by combining methodological approaches of previous studies while using supra-threshold stimuli only. In two experiments we presented auditory and visual stimuli to observers that evoked a(n) (onset) response (be it constriction or dilation) in a simple detection task and a change detection task. In both experiments, the RT data indicated MSI as shown by race model inequality violation. Still, the multisensory pupil response in both experiments could best be explained by linear summation of the unisensory pupil responses. We conclude that the multisensory pupil response for supra-threshold stimuli is additive in nature and cannot be used as a measure of MSI, as only a departure from additivity can unequivocally demonstrate an interaction between the senses.

Multisensory signals inhibit pupillary light reflex: Evidence from pupil oscillation

“…Dissimilar to the parasympathetic pathway that can be transiently inhibited, we propose the sympathetic pathway may be enhanced by multisensory signals in a slow and sustained manner. This is compatible with previous findings, which demonstrated that the pupil dilation to multisensory signals could on one hand be as early as that of the pupillary light reflex (Wang et al, 2017), while on the other hand arise late and sustain for a relatively long time (Rigato et al, 2016;Van der Stoep et al, 2021). This assumption can also explain the inconsistency between our observation and a recent one (Van der Stoep et al, 2021), which reported no distinction between phasic pupil responses to light and dark with each trial only including one unimodal or bimodal stimuli but with adequate time to observe the pupil change.…”

Decoding binary decisions under differential target probabilities from pupil dilation: A random forest approach

“…One of the most important determinants for the difference found between targets and distractors, be it in visual search, decision-making tasks or applied scenarios, is the relative proportion of targets to distractors (Strauch et al, 2020). Specifically, the rarer a stimulus the stronger the pupillary response relative to more frequent stimuli -a phenomenon commonly referred to as the oddball effect (Murphy, O'connell, O'sullivan, Robertson, & Balsters, 2014).…”

“…Specifically, the rarer a stimulus the stronger the pupillary response relative to more frequent stimuli -a phenomenon commonly referred to as the oddball effect (Murphy, O'connell, O'sullivan, Robertson, & Balsters, 2014). In a recent study, the effects of binary decision-making were investigated together with effects of stimulus probability (Strauch et al, 2020). Although targets always elicited a stronger pupillary response than distractors, the magnitude of the difference between targets and distractors was determined by an effect of stimulus probability.…”

“…If the eyes are a window to the soul, or -more specific -reflect the intention of an observer, how far open is this window and which features let us see through it? Because the pupil dilates more for targets than distractors (de Gee, Knapen, & Donner, 2014;Einhäuser, Koch, & Carter, 2010;Privitera, Renninger, Carney, Klein, & Aguilar, 2010;Strauch, Koniakowsky, & Huckauf, 2020), pupil dilation is one of the most promising features to indicate whether a foveated stimulus is an intended target. Therefore, analyzing the pupil, possibly even in real time, could allow for decoding such intentions, be it by human or machine.…”

PupilEXT: Flexible Open-Source Platform for High-Resolution Pupillometry in Vision Research

“…When using stimulus spectra along the Planckian locus for triggering the pupil light response, it is essential in measurements that amplitudes in the range of 0.1 to 0.4 mm are captured accurately to specify intrasubject variability (Kobashi et al, 2012) in a pupil model. However, a special requirement for pupil measurements arises when the pupil is used as a biomarker for quantifying the cognitive state (Morad et al, 2000;Merritt et al, 2004;Murphy et al, 2014;Ostrin et al, 2017;Tkacz-Domb and Yeshurun, 2018;Hu et al, 2019;Van Egroo et al, 2019;de Winter et al, 2021;Van der Stoep et al, 2021) or clinical symptoms of diseases (Hreidarsson, 1982;Maclean and Dhillon, 1993;Connelly et al, 2014;Lim et al, 2016;Granholm et al, 2017;Wildemeersch et al, 2018;Chougule et al, 2019). Cognitive processes such as memory load, arousal, circadian status, or sleepiness have a transient impact (Watson and Yellott, 2012) on the pupil diameter with aperture changes of 0.015 to 0.53 mm (Beatty and Wagoner, 1978;Beatty, 1982;Schluroff et al, 1986;Jepma and Nieuwenhuis, 2011;Pedrotti et al, 2014;Bombeke et al, 2016;Tsukahara et al, 2016;Winn et al, 2018), making the reproducibility of such effects difficult if the accuracy of the measurement equipment has not been sufficiently validated.…”