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Within the field of hearing science, pupillometry is a widely used method for quantifying listening effort. Its use in research is growing exponentially, and many labs are (considering) applying pupillometry for the first time. Hence, there is a growing need for a methods paper on pupillometry covering topics spanning from experiment logistics and timing to data cleaning and what parameters to analyze. This article contains the basic information and considerations needed to plan, set up, and interpret a pupillometry experiment, as well as commentary about how to interpret the response. Included are practicalities like minimal system requirements for recording a pupil response and specifications for peripheral, equipment, experiment logistics and constraints, and different kinds of data processing. Additional details include participant inclusion and exclusion criteria and some methodological considerations that might not be necessary in other auditory experiments. We discuss what data should be recorded and how to monitor the data quality during recording in order to minimize artifacts. Data processing and analysis are considered as well. Finally, we share insights from the collective experience of the authors and discuss some of the challenges that still lie ahead.

This article provides a tutorial for analyzing pupillometric data. Pupil dilation has become increasingly popular in psychological and psycholinguistic research as a measure to trace language processing. However, there is no general consensus about procedures to analyze the data, with most studies analyzing extracted features from the pupil dilation data instead of analyzing the pupil dilation trajectories directly. Recent studies have started to apply nonlinear regression and other methods to analyze the pupil dilation trajectories directly, utilizing all available information in the continuously measured signal. This article applies a nonlinear regression analysis, generalized additive mixed modeling, and illustrates how to analyze the full-time course of the pupil dilation signal. The regression analysis is particularly suited for analyzing pupil dilation in the fields of psychological and psycholinguistic research because generalized additive mixed models can include complex nonlinear interactions for investigating the effects of properties of stimuli (e.g., formant frequency) or participants (e.g., working memory score) on the pupil dilation signal. To account for the variation due to participants and items, nonlinear random effects can be included. However, one of the challenges for analyzing time series data is dealing with the autocorrelation in the residuals, which is rather extreme for the pupillary signal. On the basis of simulations, we explain potential causes of this extreme autocorrelation, and on the basis of the experimental data, we show how to reduce their adverse effects, allowing a much more coherent interpretation of pupillary data than possible with feature-based techniques.

The measurement of cognitive resource allocation during listening, or listening effort, provides valuable insight in the factors influencing auditory processing. In recent years, many studies inside and outside the field of hearing science have measured the pupil response evoked by auditory stimuli. The aim of the current review was to provide an exhaustive overview of these studies. The 146 studies included in this review originated from multiple domains, including hearing science and linguistics, but the review also covers research into motivation, memory, and emotion. The present review provides a unique overview of these studies and is organized according to the components of the Framework for Understanding Effortful Listening. A summary table presents the sample characteristics, an outline of the study design, stimuli, the pupil parameters analyzed, and the main findings of each study. The results indicate that the pupil response is sensitive to various task manipulations as well as interindividual differences. Many of the findings have been replicated. Frequent interactions between the independent factors affecting the pupil response have been reported, which indicates complex processes underlying cognitive resource allocation. This complexity should be taken into account in future studies that should focus more on interindividual differences, also including older participants. This review facilitates the careful design of new studies by indicating the factors that should be controlled for. In conclusion, measuring the pupil dilation response to auditory stimuli has been demonstrated to be sensitive method applicable to numerous research questions. The sensitivity of the measure calls for carefully designed stimuli.

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.

Conversation is the platform where minds meet: the venue where information is shared, ideas cocreated, cultural norms shaped, and social bonds forged. Its frequency and ease belie its complexity. Every conversation weaves a unique shared narrative from the contributions of independent minds, requiring partners to flexibly move into and out of alignment as needed for conversation to both cohere and evolve. How two minds achieve this coordination is poorly understood. Here we test whether eye contact, a common feature of conversation, predicts this coordination by measuring dyadic pupillary synchrony (a corollary of shared attention) during natural conversation. We find that eye contact is positively correlated with synchrony as well as ratings of engagement by conversation partners. However, rather than elicit synchrony, eye contact commences as synchrony peaks and predicts its immediate and subsequent decline until eye contact breaks. This relationship suggests that eye contact signals when shared attention is high. Furthermore, we speculate that eye contact may play a corrective role in disrupting shared attention (reducing synchrony) as needed to facilitate independent contributions to conversation.

Listening effort is a valuable and important notion to measure because it is among the primary complaints of people with hearing loss. It is tempting and intuitive to accept speech intelligibility scores as a proxy for listening effort, but this link is likely oversimplified and lacks actionable explanatory power. This study was conducted to explain the mechanisms of listening effort that are not captured by intelligibility scores, using sentence-repetition tasks where specific kinds of mistakes were prospectively planned or analyzed retrospectively. Effort measured as changes in pupil size among 20 listeners with normal hearing and 19 listeners with cochlear implants. Experiment 1 demonstrates that mental correction of misperceived words increases effort even when responses are correct. Experiment 2 shows that for incorrect responses, listening effort is not a function of the proportion of words correct but is rather driven by the types of errors, position of errors within a sentence, and the need to resolve ambiguity, reflecting how easily the listener can make sense of a perception. A simple taxonomy of error types is provided that is both intuitive and consistent with data from these two experiments. The diversity of errors in these experiments implies that speech perception tasks can be designed prospectively to elicit the mistakes that are more closely linked with effort. Although mental corrective action and number of mistakes can scale together in many experiments, it is possible to dissociate them to advance toward a more explanatory (rather than correlational) account of listening effort.

The capacity to anticipate and prepare for future events is thought to be critical for cognitive control. Dominant accounts of cognitive control treat the developing system as merely a weaker version of the adult system, progressively strengthening over time. Using the AX Continuous Performance Task (AX-CPT) in combination with high-resolution pupillometry, we find that whereas 8-year-old children resemble adults in their proactive use of cognitive control, 3.5-year-old children exhibit a qualitatively different, reactive form of cognitive control, responding to events only as they unfold and retrieving information from memory as needed in the moment. These results demonstrate the need to reconsider the origins of cognitive control and the basis for children's behaviors across domains.

Acute Respiratory Distress Syndrome (ARDS) is one of the most demanding conditions in an Intensive Care Unit (ICU). Management of analgesia and sedation in ARDS is particularly challenging. An expert panel was convened to produce a “state-of-the-art” article to support clinicians in the optimal management of analgesia/sedation in mechanically ventilated adults with ARDS, including those with COVID-19. Current ICU analgesia/sedation guidelines promote analgesia first and minimization of sedation, wakefulness, delirium prevention and early rehabilitation to facilitate ventilator and ICU liberation. However, these strategies cannot always be applied to patients with ARDS who sometimes require deep sedation and/or paralysis. Patients with severe ARDS may be under-represented in analgesia/sedation studies and currently recommended strategies may not be feasible. With lightened sedation, distress-related symptoms (e.g., pain and discomfort, anxiety, dyspnea) and patient-ventilator asynchrony should be systematically assessed and managed through interprofessional collaboration, prioritizing analgesia and anxiolysis. Adaptation of ventilator settings (e.g., use of a pressure-set mode, spontaneous breathing, sensitive inspiratory trigger) should be systematically considered before additional medications are administered. Managing the mechanical ventilator is of paramount importance to avoid the unnecessary use of deep sedation and/or paralysis. Therefore, applying an “ABCDEF-R” bundle (R = Respiratory-drive-control) may be beneficial in ARDS patients. Further studies are needed, especially regarding the use and long-term effects of fast-offset drugs (e.g., remifentanil, volatile anesthetics) and the electrophysiological assessment of analgesia/sedation (e.g., electroencephalogram devices, heart-rate variability, and video pupillometry). This review is particularly relevant during the COVID-19 pandemic given drug shortages and limited ICU-bed capacity.

With the explosion of digital media and technologies, scholars, educators and the public have become increasingly vocal about the role that an ‘attention economy’ has in our lives 1 . The rise of the current digital culture coincides with longstanding scientific questions about why humans sometimes remember and sometimes forget, and why some individuals remember better than others 2 – 6 . Here we examine whether spontaneous attention lapses—in the moment 7 – 12 , across individuals 13 – 15 and as a function of everyday media multitasking 16 – 19 —negatively correlate with remembering. Electroencephalography and pupillometry measures of attention 20 , 21 were recorded as eighty young adults (mean age, 21.7 years) performed a goal-directed episodic encoding and retrieval task 22 . Trait-level sustained attention was further quantified using task-based 23 and questionnaire measures 24 , 25 . Using trial-to-trial retrieval data, we show that tonic lapses in attention in the moment before remembering, assayed by posterior alpha power and pupil diameter, were correlated with reductions in neural signals of goal coding and memory, along with behavioural forgetting. Independent measures of trait-level attention lapsing mediated the relationship between neural assays of lapsing and memory performance, and between media multitasking and memory. Attention lapses partially account for why we remember or forget in the moment, and why some individuals remember better than others. Heavier media multitasking is associated with a propensity to have attention lapses and forget. Lapses in attention before remembering partially account for why we remember or forget in the moment, why some individuals remember better than others, and why heavier media multitasking is related to worse memory.

In contemporary workspaces, artificial lighting often prevails, despite strong evidence supporting daylight’s cognitive and physiological benefits. This study examines how different daylight–artificial light combinations affect physiological responses, subjective comfort, and cognitive performance. Twenty-two healthy adults (11 female, 11 male) participated in a controlled experiment under four lighting conditions, ranging from full daylight to full artificial light, while maintaining constant horizontal illuminance (450 lux). Sessions included cognitive tasks, subjective surveys, and continuous monitoring of heart rate (HR), low-frequency to high-frequency (LF/HF) ratio from heart rate variability, and pupil diameter (PD). Results from repeated measures ANOVA showed that artificial lighting increased LF/HF and PD, indicating higher sympathetic activity and visual strain. Interestingly, visual satisfaction was highest under balanced lighting (AD12, AD21), rather than full daylight. Cognitive performance peaked under daylight-dominant conditions (AD03) and declined with increasing artificial light, aligning with physiological markers of stress. Spearman’s correlations revealed significant associations between HR, LF/HF, and perceived workload (NASA TLX), while PD showed weaker links. These findings underscore the importance of daylight for physiological regulation and cognitive clarity, while highlighting the perceptual appeal of balanced lighting. Mixed-light scenarios like AD12 offer a practical, human-centric approach to enhancing well-being and performance in spaces with limited daylight access.