Non-image-forming vision as measured through ipRGC-mediated pupil constriction is not modulated by covert visual attention.

In brightness, the pupil constricts, while in darkness, the pupil dilates; this is known as the pupillary light response (PLR). The PLR is driven by all photoreceptors: rods and cones, which contribute to image-forming vision, and intrinsically photosensitive retinal ganglion cells (ipRGCs), which mainly contribute to non-image-forming vision. Rods and cones cause immediate pupil constriction upon light exposure, whereas ipRGCs cause sustained constriction throughout light exposure. Recent studies have shown that covert attention modulated the initial PLR; however, it remains unclear whether the same holds for the sustained PLR. We tested this by leveraging ipRGCs' responsiveness to blue light, causing the most prominent sustained constriction. While replicating previous studies by showing that pupils constricted more when either directly looking at, or covertly attending to, bright as compared to dim stimuli (with the same color), we also found that the pupil constricted more when directly looking at blue as compared to red stimuli (with the same luminosity). Crucially, however, in two high-powered studies (n = 60), we did not find any pupil-size difference when covertly attending to blue as compared to red stimuli. This suggests that ipRGC-mediated pupil constriction, and possibly non-image-forming vision more generally, is not modulated by covert attention.

Functional benefits of cognitively driven pupil-size changes.

Pupil-size changes are typically associated with the pupil light response (PLR), where they are driven by the physical entry of light into the eye. However, pupil-size changes are also influenced by various cognitive processes, where they are driven by higher-level cognition. For example, the strength of the PLR is not solely affected by physical properties of the light but also by cognitive factors, such as whether the source of light is attended or not, which results in an increase or decrease in the strength of the PLR. Surprisingly, although cognitively driven pupil-size changes have been the focus of extensive research, their possible functions are rarely discussed. Here we consider the relative (dis)advantages of small versus large pupils in different situations from a theoretical point of view, and compare these to empirical results showing how pupil size actually changes in these situations. Based on this, we suggest that cognitively driven pupil-size changes optimize vision either through preparation, embodied representations, or a differential emphasis on central or peripheral vision. More generally, we argue that cognitively driven pupil-size changes are a form of sensory tuning: a subtle adjustment of the eyes to optimize vision for the current situation and the immediate future. This article is categorized under: Neuroscience > Cognition Neuroscience > Physiology Neuroscience > Behavior.

Effects of pupil size as manipulated through ipRGC activation on visual processing.

The size of the eyes' pupils determines how much light enters the eye and also how well this light is focused. Through this route, pupil size shapes the earliest stages of visual processing. Yet causal effects of pupil size on vision are poorly understood and rarely studied. Here we introduce a new way to manipulate pupil size, which relies on activation of intrinsically photosensitive retinal ganglion cells (ipRGCs) to induce sustained pupil constriction. We report the effects of both experimentally induced and spontaneous changes in pupil size on visual processing as measured through EEG. We compare these to the effects of stimulus intensity and covert visual attention, because previous studies have shown that these factors all have comparable effects on some common measures of early visual processing, such as detection performance and steady-state visual evoked potentials; yet it is still unclear whether these are superficial similarities, or rather whether they reflect similar underlying processes. Using a mix of neural-network decoding, ERP analyses, and time-frequency analyses, we find that induced pupil size, spontaneous pupil size, stimulus intensity, and covert visual attention all affect EEG responses, mainly over occipital and parietal electrodes, but-crucially-that they do so in qualitatively different ways. Induced and spontaneous pupil-size changes mainly modulate activity patterns (but not overall power or intertrial coherence) in the high-frequency beta range; this may reflect an effect of pupil size on oculomotor activity and/ or visual processing. In addition, spontaneous (but not induced) pupil size tends to correlate positively with intertrial coherence in the alpha band; this may reflect a non-causal relationship, mediated by arousal. Taken together, our findings suggest that pupil size has qualitatively different effects on visual processing from stimulus intensity and covert visual attention. This shows that pupil size as manipulated through ipRGC activation strongly affects visual processing, and provides concrete starting points for further study of this important yet understudied earliest stage of visual processing.

Emphasis on peripheral vision is accompanied by pupil dilation.

People are best able to detect stimuli in peripheral vision when their pupils are large, and best able to discriminate stimuli in central vision when their pupils are small. However, it is unclear whether our visual system makes use of this by dilating the pupils when attention is directed towards peripheral vision. Therefore, throughout three experiments (N = 100), we tested whether pupil size adapts to the "breadth" of attention. We found that pupils dilate with increasing attentional breadth, both when attention is diffusely spread and when attention is directed at specific locations in peripheral vision. Based on our results and others, we propose that cognitively driven pupil dilation is not an epiphenomenal marker of locus coeruleus activity, as is often assumed, but rather is an adaptive response that reflects an emphasis on peripheral vision.

Methods in cognitive pupillometry: Design, preprocessing, and statistical analysis.

Cognitive pupillometry is the measurement of pupil size to investigate cognitive processes such as attention, mental effort, working memory, and many others. Currently, there is no commonly agreed-upon methodology for conducting cognitive-pupillometry experiments, and approaches vary widely between research groups and even between different experiments from the same group. This lack of consensus makes it difficult to know which factors to consider when conducting a cognitive-pupillometry experiment. Here we provide a comprehensive, hands-on guide to methods in cognitive pupillometry, with a focus on trial-based experiments in which the measure of interest is the task-evoked pupil response to a stimulus. We cover all methodological aspects of cognitive pupillometry: experimental design, preprocessing of pupil-size data, and statistical techniques to deal with multiple comparisons when testing pupil-size data. In addition, we provide code and toolboxes (in Python) for preprocessing and statistical analysis, and we illustrate all aspects of the proposed workflow through an example experiment and example scripts.

Proactive distractor suppression elicited by statistical regularities in visual search.

Irrelevant salient objects may capture our attention and interfere with visual search. Recently, it was shown that distraction by a salient object is reduced when it is presented more frequently at one location than at other locations. The present study investigates whether this reduced distractor interference is the result of proactive spatial suppression, implemented prior to display onset, or reactive suppression, occurring after attention has been directed to that location. Participants were asked to search for a shape singleton in the presence of an irrelevant salient color singleton which was presented more often at one location (the high-probability location) than at all other locations (the low-probability locations). On some trials, instead of the search task, participants performed a probe task, in which they had to detect the offset of a probe dot. The results of the search task replicated previous findings showing reduced distractor interference in trials in which the salient distractor was presented at the high-probability location as compared with the low-probability locations. The probe task showed that reaction times were longer for probes presented at the high-probability location than at the low-probability locations. These results indicate that through statistical learning the location that is likely to contain a distractor is suppressed proactively (i.e., prior to display onset). It suggests that statistical learning modulates the first feed-forward sweep of information processing by deprioritizing locations that are likely to contain a distractor in the spatial priority map.