Different rules for binocular combination of luminance flicker in cortical and subcortical pathways.

How does the human brain combine information across the eyes? It has been known for many years that cortical normalization mechanisms implement 'ocularity invariance': equalizing neural responses to spatial patterns presented either monocularly or binocularly. Here, we used a novel combination of electrophysiology, psychophysics, pupillometry, and computational modeling to ask whether this invariance also holds for flickering luminance stimuli with no spatial contrast. We find dramatic violations of ocularity invariance for these stimuli, both in the cortex and also in the subcortical pathways that govern pupil diameter. Specifically, we find substantial binocular facilitation in both pathways with the effect being strongest in the cortex. Near-linear binocular additivity (instead of ocularity invariance) was also found using a perceptual luminance matching task. Ocularity invariance is, therefore, not a ubiquitous feature of visual processing, and the brain appears to repurpose a generic normalization algorithm for different visual functions by adjusting the amount of interocular suppression.

PySilSub: An open-source Python toolbox for implementing the method of silent substitution in vision and nonvisual photoreception research.

The normal human retina contains several classes of photosensitive cell-rods for low-light vision, three cone classes for daylight vision, and intrinsically photosensitive retinal ganglion cells (ipRGCs) expressing melanopsin for non-image-forming functions, including pupil control, melatonin suppression, and circadian photoentrainment. The spectral sensitivities of the photoreceptors overlap significantly, which means that most lights will stimulate all photoreceptors to varying degrees. The method of silent substitution is a powerful tool for stimulating individual photoreceptor classes selectively and has found much use in research and clinical settings. The main hardware requirement for silent substitution is a spectrally calibrated light stimulation system with at least as many primaries as there are photoreceptors under consideration. Device settings that will produce lights to selectively stimulate the photoreceptor(s) of interest can be found using a variety of analytic and algorithmic approaches. Here we present PySilSub (https://github.com/PySilentSubstitution/pysilsub), a novel Python package for silent substitution featuring flexible support for individual colorimetric observer models (including human and mouse observers), multiprimary stimulation devices, and solving silent substitution problems with linear algebra and constrained numerical optimization. The toolbox is registered with the Python Package Index and includes example data sets from various multiprimary systems. We hope that PySilSub will facilitate the application of silent substitution in research and clinical settings.

Pupillometry and the vigilance decrement: Task-evoked but not baseline pupil measures reflect declining performance in visual vigilance tasks.

Baseline and task-evoked pupil measures are known to reflect the activity of the nervous system's central arousal mechanisms. With the increasing availability, affordability and flexibility of video-based eye tracking hardware, these measures may one day find practical application in real-time biobehavioural monitoring systems to assess performance or fitness for duty in tasks requiring vigilant attention. But real-world vigilance tasks are predominantly visual in their nature and most research in this area has taken place in the auditory domain. Here, we explore the relationship between pupil size-both baseline and task-evoked-and behavioural performance measures in two novel vigilance tasks requiring visual target detection: (1) a traditional vigilance task involving prolonged, continuous and uninterrupted performance (n = 28) and (2) a psychomotor vigilance task (n = 25). In both tasks, behavioural performance and task-evoked pupil responses declined as time spent on task increased, corroborating previous reports in the literature of a vigilance decrement with a corresponding reduction in task-evoked pupil measures. Also in line with previous findings, baseline pupil size did not show a consistent relationship with performance measures. Our data offer novel insights into the complex interplay of brain systems involved in vigilant attention and question the validity of the assumption that baseline (prestimulus) pupil size and task-evoked (poststimulus) pupil measures reflect the tonic and phasic firing modes of the locus coeruleus.

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

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.

Component processes in free-viewing visual search: Insights from fixation-aligned pupillary response averaging.

Pupil size changes during a visual search may reflect cognitive processes, such as effort and memory accumulation, but methodological confounds and the general lack of literature in this area leave the reliability of findings open to question. We used a novel synthesis of experimental methods and averaging techniques to explore how cognitive processing unfolds during free-viewing visual search for multiple targets. Twenty-seven participants completed 152 searches across two separate 1-hour sessions. The number of targets present (Targets: 0, 1, 2, and 3) in each trial was the main manipulation and the task was to "find all of the targets" and report the total via mouse-click at the end of the trial. Search time lasted for 10 seconds or until the participant purported to have found all of the targets, in which case they could terminate the search via keypress. Whole-trial pupil analysis revealed a significant effect of button pressing as well as a significant main effect of targets for trials that were not self-terminated via button press. Fixation-aligned pupil responses revealed transient modulations in pupil size following initial fixations on targets but not distractors and refixations on both targets and distractors. Owing to rigorous control over experimental confounds and a detailed analysis and correction of eye-movement-related measurement error, we confidently discuss these findings in terms of task-related processing and underlying brain activity.