Abstract

The pupils of the eyes reflexively constrict in light and dilate in dark to optimize retinal illumination. Non-visual cognitive factors, like attention, arousal, decision-making, etc., also influence pupillary light response (PLR). During passive viewing, the eccentricity of a stimulus modulates the pupillary aperture size driven by spatially weighted corneal flux density (CFD), which is the product of luminance and the area of the stimulus. Whether the scope of attention also influences PLR remains unclear. In this study, we contrasted the pupil dynamics between diffused and focused attentional conditions during decision-making, while the global CFD remained the same in the two conditions. A population of 20 healthy humans participated in a pair of forced choice tasks. They distributed attention to the peripheral decision cue in one task, and concentrated at the center in the other to select the target from four alternatives for gaze orientation. The location of this cue did not influence participants’ reaction time (RT). However, the magnitude of constriction was significantly less in the task that warranted attention to be deployed at the center than on the periphery. We observed similar pupil dynamics when participants either elicited or canceled a saccadic eye movement, which ruled out pre-saccadic obligatory attentional orientation contributing to PLR. We further addressed how the location of attentional deployment might have influenced PLR. We simulated a biomechanical model of PLR with visual stimulation of different strengths as inputs corresponding to the two attentional conditions. In this homeomorphic model, the computational characteristic of each element was derived from the physiological and/or mechanical properties of the corresponding biological element. The simulation of this model successfully mimicked the observed data. In contrast to common belief that the global ambient luminosity drives pupillary response, the results of our study suggest that the effective CFD (eCFD) determined via the luminance multiplied by the size of the stimulus at the location of deployed attention in the visual space is critical for the magnitude of pupillary constriction.

Highlights

  • Pupillary light response (PLR) maintains retinal illumination when the intensity of ambient light changes

  • The overall stimulus quality remained the same between the tasks, except the locations of a decision cue for the selection of the target were different—in one task, the cue appeared near the center of a display monitor [central choice countermanding (CCC task)], and in another, it appeared on the periphery [peripheral choicecountermanding (CCP) task]

  • These results indicate that participants carefully discriminated the target from the distractors irrespective of the placement of a decision cue at the parafoveal or perifoveal location, and deliberately attempted to inhibit a planned gaze shift toward the target in response to sudden appearance of the stop signal

Read more

Summary

Introduction

Pupillary light response (PLR) maintains retinal illumination when the intensity of ambient light changes. PLR is not completely reflexive; many non-visual cognitive factors, including attention (e.g., Binda et al, 2013; Naber et al, 2013), saccadic eye movement preparation (Jainta et al, 2011; Mathôt et al, 2015; Wang et al, 2018; Pandey and Ray, 2021; Wang and Munoz, 2021), decision-making. Attentional Breadth Influences Pupil Size (e.g., de Gee et al, 2014; Sheng et al, 2020), and even subliminal stimuli can influence PLR (Laeng et al, 2012; Einhäuser, 2017; Mathôt, 2018). A change in the peripheral luminance, while fixation was maintained at the center of the display, affected PLR more when this change in the light intensity happened at the attended hemifield than at the unattended hemifield (Binda and Murray, 2015). Temporal attention (Wierda et al, 2012), featurebased selective attention (Einhäuser et al, 2008; Binda et al, 2014; Turi et al, 2018; but see Hupé et al, 2008), and obligatory pre-saccadic attention (Mathôt et al, 2015) influence PLR

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

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 call