Task-evoked pupillometry provides a window into the development of short-term memory capacity

Auditory Challenges and Listening Effort in School-Age Children With Autism: Insights From Pupillary Dynamics During Speech-in-Noise Perception

PURPOSE

This study aimed to investigate challenges in speech-in-noise (SiN) processing faced by school-age children with autism spectrum conditions (ASCs) and their impact on listening effort.

METHOD

Participants, including 23 Mandarin-speaking children with ASCs and 19 age-matched neurotypical (NT) peers, underwent sentence recognition tests in both quiet and noisy conditions, with a speech-shaped steady-state noise masker presented at 0-dB signal-to-noise ratio in the noisy condition. Recognition accuracy rates and task-evoked pupil responses were compared to assess behavioral performance and listening effort during auditory tasks.

RESULTS

No main effect of group was found on accuracy rates. Instead, significant effects emerged for autistic trait scores, listening conditions, and their interaction, indicating that higher trait scores were associated with poorer performance in noise. Pupillometric data revealed significantly larger and earlier peak dilations, along with more varied pupillary dynamics in the ASC group relative to the NT group, especially under noisy conditions. Importantly, the ASC group's peak dilation in quiet mirrored that of the NT group in noise. However, the ASC group consistently exhibited reduced mean dilations than the NT group.

CONCLUSIONS

Pupillary responses suggest a different resource allocation pattern in ASCs: An initial sharper and larger dilation may signal an intense, narrowed resource allocation, likely linked to heightened arousal, engagement, and cognitive load, whereas a subsequent faster tail-off may indicate a greater decrease in resource availability and engagement, or a quicker release of arousal and cognitive load. The presence of noise further accentuates this pattern. This highlights the unique SiN processing challenges children with ASCs may face, underscoring the importance of a nuanced, individual-centric approach for interventions and support.

The pupil dilation response as an indicator of visual cue uncertainty and auditory outcome surprise

In everyday perception, we combine incoming sensory information with prior expectations. Expectations can be induced by cues that indicate the probability of following sensory events. The information provided by cues may differ and hence lead to different levels of uncertainty about which event will follow. In this experiment, we employed pupillometry to investigate whether the pupil dilation response to visual cues varies depending on the level of cue-associated uncertainty about a following auditory outcome. Also, we tested whether the pupil dilation response reflects the amount of surprise about the subsequently presented auditory stimulus. In each trial, participants were presented with a visual cue (face image) which was followed by an auditory outcome (spoken vowel). After the face cue, participants had to indicate by keypress which of three auditory vowels they expected to hear next. We manipulated the cue-associated uncertainty by varying the probabilistic cue-outcome contingencies: One face was most likely followed by one specific vowel (low cue uncertainty), another face was equally likely followed by either of two vowels (intermediate cue uncertainty) and the third face was followed by all three vowels (high cue uncertainty). Our results suggest that pupil dilation in response to task-relevant cues depends on the associated uncertainty, but only for large differences in the cue-associated uncertainty. Additionally, in response to the auditory outcomes, the pupil dilation scaled negatively with the cue-dependent probabilities, likely signalling the amount of surprise.

Pupillometry as a window to detect cognitive aging in the brain

This study investigated whether there are aging-related differences in pupil dilation (pupillometry) while the cognitive load is manipulated using digit- and word-span tasks. A group of 17 younger and 15 cognitively healthy older adults performed digit- and word-span tasks. Each task comprised three levels of cognitive loads with 10 trials for each level. For each task, the recall accuracy and the slope of pupil dilation were calculated and analyzed. The raw signal of measured pupil size was low-pass filtered and interpolated to eliminate blinking artifacts and spike noises. Two-way ANOVA was used for statistical analyses. For the recall accuracy, the significant group differences emerged as the span increases in digit-span (5- vs. 7-digit) and word-span (4- vs. 5-word) tasks, while the group differences were not significant on 3-digit- and 3-word-span tasks with lower cognitive load. In digit-span tasks, there was no aging-related difference in the slope of pupil dilation. However, in word-span tasks, the slope of pupil dilation differed significantly between two groups as cognitive load increased, indicating that older adults presented a higher pupil dilation slope than younger adults especially under the conditions with higher cognitive load. The current study found significant aging effects in the pupil dilations under the more cognitive demanding span tasks when the types of span tasks varied (e.g., digit vs. word). The manipulations successfully elicited differential aging effects, given that the aging effects became most salient under word-span tasks with greater cognitive load especially under the maximum length.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-023-00315-6.

Pupillometric and blink measures of diverse task loads: Implications for working memory models

BACKGROUND

Inconsistent observations of pupillary response and blink change in response to different specific tasks raise questions regarding the relationship between eye measures, task types and working memory (WM) models. On the one hand, studies have provided mixed evidence from eye measures about tasks: pupil size has mostly been reported to increase with increasing task demand while this expected change was not observed in some studies, and blink rate has exhibited different trends in different tasks. On the other hand, a WM model has been developed to integrate a component to reconcile recent findings that the human motor system plays an important role in cognition and learning. However, how different tasks correlate with WM components has not been experimentally examined using eye activity measurements.

AIMS

The current study uses a four-dimensional task load framework to bridge eye measures, task types and WM models.

SAMPLE

Twenty participants (10 males, 10 females; Age: M = 25.8, SD = 7.17) above 18 years old volunteered. All participants had normal or corrected to normal vision with contact lenses and had no eye diseases causing obvious excessive blinking.

METHODS

We examined the ability of pupil size and blink rate to index low and high levels of cognitive, perceptual, physical and communicative task load. A network of the four load types and WM components was built and analysed to verify the necessity of integrating a physical task-related component into the WM model.

RESULTS

Results demonstrate that pupil size can index cognitive load and communicative load but not perceptual or physical load. Blink rate can index the level of cognitive load but is best at discriminating perceptual tasks from other types of tasks. Furthermore, pupil size measurement of the four task types was explained better during structural and factor analysis by a WM model that integrates a movement-related component.

CONCLUSIONS

This research provides new insights into the relationship between eye measures, task type and WM models and provides a comprehensive understanding from which to predict pupil size and blink behaviours in more complex and practical tasks.

Examining the role of attentional allocation in working memory precision with pupillometry in children and adults

Working memory (WM) precision, or the fidelity with which items can be remembered, is an important aspect of WM capacity that increases over childhood. Why individuals are more or less precise from moment to moment and why WM becomes more stable with age are not yet fully understood. Here, we examined the role of attentional allocation in visual WM precision in children aged 8 to 13 years and young adults aged 18 to 27 years, as measured by fluctuations in pupil dilation during stimulus encoding and maintenance. Using mixed models, we examined intraindividual links between change in pupil diameter and WM precision across trials and the role of developmental differences in these associations. Through probabilistic modeling of error distributions and the inclusion of a visuomotor control task, we isolated mnemonic precision from other cognitive processes. We found an age-related increase in mnemonic precision that was independent of guessing behavior, serial position effects, fatigue or loss of motivation across the experiment, and visuomotor processes. Trial-by-trial analyses showed that trials with smaller changes in pupil diameter during encoding and maintenance predicted more precise responses than trials with larger changes in pupil diameter within individuals. At encoding, this relationship was stronger for older participants. Furthermore, the pupil-performance coupling grew across the delay period-particularly or exclusively for adults. These results suggest a functional link between pupil fluctuations and WM precision that grows over development; visual details may be stored more faithfully when attention is allocated efficiently to a sequence of objects at encoding and throughout a delay period.

EEG and pupillometric signatures of working memory overload

Understanding the physiological correlates of cognitive overload has implications for gauging the limits of human cognition, developing novel methods to define cognitive overload, and mitigating the negative outcomes associated with overload. Most previous psychophysiological studies manipulated verbal working memory load in a narrow range (an average load of 5 items). It is unclear, however, how the nervous system responds to a working memory load exceeding typical capacity limits. The objective of the current study was to characterize the central and autonomic nervous system changes associated with memory overload, by means of combined recording of electroencephalogram (EEG) and pupillometry. Eighty-six participants were presented with a digit span task involving the serial auditory presentation of items. Each trial consisted of sequences of either 5, 9, or 13 digits, each separated by 2 s. Both theta activity and pupil size, after the initial rise, expressed a pattern of a short plateau and a decrease with reaching the state of memory overload, indicating that pupil size and theta possibly have similar neural mechanisms. Based on the described above triphasic pattern of pupil size temporal dynamics, we concluded that cognitive overload causes physiological systems to reset, and release effort. Although memory capacity limits were exceeded and effort was released (as indicated by pupil dilation), alpha continued to decrease with increasing memory load. These results suggest that associating alpha with the focus of attention and distractor suppression is not warranted.

The contribution of temporal analysis of pupillometry measurements to cognitive research

Reaction time (RT) is one of the most frequently used measures to detect cognitive processes. When tasks require more cognitive processes/resources, reaction is slower. However, RTs may provide only restricted information regarding the temporal characteristics of cognitive processes. Pupils respond reflexively to light but also to cognitive activation. The more cognitive resources a task requires, the more the pupil dilates. However, despite being able to use temporal changes in pupil size (advanced devices measure changes in pupil diameter with sampling rates of above 1000 samples per second), most past studies using pupil dilation have not investigated temporal changes in pupil response. In the current paper, we discuss the advantage of the temporal approach to analyze pupil changes compared to a more traditional perspective, specifically, singular value methods such as mean value and peak amplitude value. Using data from two recent studies conducted in our laboratory, we demonstrate the differences in findings arising from the various analyses. In particular, we focus on the advantage of temporal analysis in detecting hidden effects, investigating temporal characterizations of the effects, and validating the experimental manipulation.

Luminance effects on pupil dilation in speech-in-noise recognition

There is an increasing interest in the field of audiology and speech communication to measure the effort that it takes to listen in noisy environments, with obvious implications for populations suffering from hearing loss. Pupillometry offers one avenue to make progress in this enterprise but important methodological questions remain to be addressed before such tools can serve practical applications. Typically, cocktail-party situations may occur in less-than-ideal lighting conditions, e.g. a pub or a restaurant, and it is unclear how robust pupil dynamics are to luminance changes. In this study, we first used a well-known paradigm where sentences were presented at different signal-to-noise ratios (SNR), all conducive of good intelligibility. This enabled us to replicate findings, e.g. a larger and later peak pupil dilation (PPD) at adverse SNR, or when the sentences were misunderstood, and to investigate the dependency of the PPD on sentence duration. A second experiment reiterated two of the SNR levels, 0 and +14 dB, but measured at 0, 75, and 220 lux. The results showed that the impact of luminance on the SNR effect was non-monotonic (sub-optimal in darkness or in bright light), and as such, there is no trivial way to derive pupillary metrics that are robust to differences in background light, posing considerable constraints for applications of pupillometry in daily life. Our findings raise an under-examined but crucial issue when designing and understanding listening effort studies using pupillometry, and offer important insights to future clinical application of pupillometry across sites.

Does mathematics anxiety moderate the effect of problem difficulty on cognitive effort?

A negative relationship between mathematics anxiety (MA) and mathematics performance is well documented. One suggested explanation for this relationship is that MA interferes with the cognitive processes needed when solving mathematics problems. A demand for using more cognitive effort (e.g., when performing harder mathematics problems), can be traced as an increase in pupil dilation during the performance. However, we lack knowledge of how MA affects this relationship between the problem difficulty and cognitive effort. This study investigated, for the first time, if MA moderates the effect of arithmetic (i.e., multiplication) problem difficulty on cognitive effort. Thirty-four university students from Norway completed multiplication tasks, including three difficulty levels of problems, while their cognitive effort was also measured by means of pupil dilation using an eye tracker. Further, the participants reported their MA using a questionnaire, and arithmetic competence, general intelligence, and working memory were measured with paper-pencil tasks. A linear mixed model analysis showed that the difficulty level of the multiplication problems affected the cognitive effort so that the pupil dilated more with harder multiplication problems. However, we did not find a moderating effect of MA on cognitive effort, when controlling for arithmetic competence, general intelligence, and working memory. This suggests that MA does not contribute to cognitive effort when solving multiplication problems.

Pupillometry as a Window into Young Children's Sustained Attention

Sustained attention is critical to cognition, social competence, and academic success. Importantly, sustained attention undergoes significant development over the early childhood period. Yet, how sustained attention fluctuates over time on task has not been clearly outlined, particularly in young children. In this study, we provide a first test of whether the pupillary response can be used as an indicator of moment-to-moment sustained attention over time on task in young children. Children aged 5 to 7 years (N = 41) completed a psychomotor vigilance task, where they were asked to press a button as fast as possible at the onset of a target stimulus. We measured reaction times over the course of the task, pupil size prior to target onset (baseline pupil size), and pupil size in response to target onset (task-evoked pupil size). The results showed a stereotypical vigilance decrement in children's response times: as time on task increased, reaction times increased. Critically, children's task-evoked pupil size decreased over time on task, while no such change was present in baseline pupil size. These results suggest that young children's waning sustained attention may be linked to a decrease in alertness while overall arousal is maintained. We discuss the importance of leveraging pupillometry to understand the mechanisms of sustained attention over individuals and development.

Applying functional near-infrared spectroscopy and eye-tracking in a naturalistic educational environment to investigate physiological aspects that underlie the cognitive effort of children during mental rotation tests

Spatial cognition is related to academic achievement in science, technology, engineering, and mathematics (STEM) domains. Neuroimaging studies suggest that brain regions' activation might be related to the general cognitive effort while solving mental rotation tasks (MRT). In this study, we evaluate the mental effort of children performing MRT tasks by measuring brain activation and pupil dilation. We use functional near-infrared spectroscopy (fNIRS) concurrently to collect brain hemodynamic responses from children's prefrontal cortex (PFC) and an Eye-tracking system to measure pupil dilation during MRT. Thirty-two healthy students aged 9-11 participated in this experiment. Behavioral measurements such as task performance on geometry problem-solving tests and MRT scores were also collected. The results were significant positive correlations between the children's MRT and geometry problem-solving test scores. There are also significant positive correlations between dorsolateral PFC (dlPFC) hemodynamic signals and visuospatial task performances (MRT and geometry problem-solving scores). Moreover, we found significant activation in the amplitude of deoxy-Hb variation on the dlPFC and that pupil diameter increased during the MRT, suggesting that both physiological responses are related to mental effort processes during the visuospatial task. Our findings indicate that children with more mental effort under the task performed better. The multimodal approach to monitoring students' mental effort can be of great interest in providing objective feedback on cognitive resource conditions and advancing our comprehension of the neural mechanisms that underlie cognitive effort. Hence, the ability to detect two distinct mental states of rest or activation of children during the MRT could eventually lead to an application for investigating the visuospatial skills of young students using naturalistic educational paradigms.

PuPl: an open-source tool for processing pupillometry data

We present PuPl (Pu pillometry P ipel iner), an Octave-compatible library of Matlab functions for processing pupillometry data with an easy-to-use graphical user interface (GUI). PuPl's preprocessing tools include blink correction, data smoothing, and gaze correction. PuPl can also define and sort trials, and segment data to isolate event-related pupil dilation responses. PuPl's flexible tabular export tools enable a wide variety of statistical analyses. Furthermore, PuPl can translate GUI interactions into a Matlab script, enabling easy creation and reconfiguration of reusable data processing pipelines. Finally, PuPl is designed to be extensible, and users can easily contribute functionality as best practices for pupillometry evolve. Here we demonstrate PuPl by replicating published results using publicly available data. PuPl can be downloaded from github.com/kinleyid/pupl .

Talker discontinuity disrupts attention to speech: Evidence from EEG and pupillometry

Speech is processed less efficiently from discontinuous, mixed talkers than one consistent talker, but little is known about the neural mechanisms for processing talker variability. Here, we measured psychophysiological responses to talker variability using electroencephalography (EEG) and pupillometry while listeners performed a delayed recall of digit span task. Listeners heard and recalled seven-digit sequences with both talker (single- vs. mixed-talker digits) and temporal (0- vs. 500-ms inter-digit intervals) discontinuities. Talker discontinuity reduced serial recall accuracy. Both talker and temporal discontinuities elicited P3a-like neural evoked response, while rapid processing of mixed-talkers' speech led to increased phasic pupil dilation. Furthermore, mixed-talkers' speech produced less alpha oscillatory power during working memory maintenance, but not during speech encoding. Overall, these results are consistent with an auditory attention and streaming framework in which talker discontinuity leads to involuntary, stimulus-driven attentional reorientation to novel speech sources, resulting in the processing interference classically associated with talker variability.

The Bilingual Native Speaker Competence: Evidence From Explicit and Implicit Language Knowledge Using Elicited Production, Sentence-Picture Matching, and Pupillometry

The present pilot study investigated potential effects of early and late child bilingualism in highly proficient adult bilinguals. It has been shown that some early second language (eL2) speakers stagnate when it comes to complex linguistic phenomena and that they display subtle difficulties in adulthood. Therefore, we have chosen the complex structure of double object constructions. We investigate the long-term achievement in a combined-method approach using elicited production, explicit comprehension by sentence-picture matching and a measure of implicit linguistic knowledge, namely pupillometry. This eye tracking method is suitable for measuring implicit reactions of the pupils to unexpected or ungrammatical stimuli. For production, ditransitive structures were elicited by means of a game. For comprehension, a sentence-picture matching task was conducted. Two pictures were shown on a monitor that were equal with respect to the involved objects, but the thematic roles of direct and indirect objects were interchanged. Items were controlled for length, gender, animacy, semantic likelihood and word order. Reaction times and accuracy scores were analyzed. To this end, N = 18 bilingual adult speakers of German (+ another language, mean age: 26.5) with different ages of onset participated in this study and were compared to N = 26 monolingual German adult speakers (mean age 23.9). All participants had a proficiency of German above 89% correct in placement and cloze tests. Results show fully comparable productive and comprehensive competencies in monolinguals and bilinguals including the reaction times in the sentence-picture matching task and a word order effect on the reaction times in both groups. In the pupillometry task, we found monolinguals and bilinguals to be sensitive to differing conditions with respect to grammatical and ungrammatical utterances. However, we find between group differences in pupil dilations in that bilinguals react differently to strong grammatical violations than monolinguals. These results are discussed with respect to the term of native speaker competence and the variation within both groups.

Machine learning-based analysis of operator pupillary response to assess cognitive workload in clinical ultrasound imaging

Introduction

Pupillometry, the measurement of eye pupil diameter, is a well-established and objective modality correlated with cognitive workload. In this paper, we analyse the pupillary response of ultrasound imaging operators to assess their cognitive workload, captured while they undertake routine fetal ultrasound examinations. Our experiments and analysis are performed on real-world datasets obtained using remote eye-tracking under natural clinical environmental conditions.

Methods

Our analysis pipeline involves careful temporal sequence (time-series) extraction by retrospectively matching the pupil diameter data with tasks captured in the corresponding ultrasound scan video in a multi-modal data acquisition setup. This is followed by the pupil diameter pre-processing and the calculation of pupillary response sequences. Exploratory statistical analysis of the operator pupillary responses and comparisons of the distributions between ultrasonographic tasks (fetal heart versus fetal brain) and operator expertise (newly-qualified versus experienced operators) are performed. Machine learning is explored to automatically classify the temporal sequences into the corresponding ultrasonographic tasks and operator experience using temporal, spectral, and time-frequency features with classical (shallow) models, and convolutional neural networks as deep learning models.

Results

Preliminary statistical analysis of the extracted pupillary response shows a significant variation for different ultrasonographic tasks and operator expertise, suggesting different extents of cognitive workload in each case, as measured by pupillometry. The best-performing machine learning models achieve receiver operating characteristic (ROC) area under curve (AUC) values of 0.98 and 0.80, for ultrasonographic task classification and operator experience classification, respectively.

Conclusion

We conclude that we can successfully assess cognitive workload from pupil diameter changes measured while ultrasound operators perform routine scans. The machine learning allows the discrimination of the undertaken ultrasonographic tasks and scanning expertise using the pupillary response sequences as an index of the operators’ cognitive workload. A high cognitive workload can reduce operator efficiency and constrain their decision-making, hence, the ability to objectively assess cognitive workload is a first step towards understanding these effects on operator performance in biomedical applications such as medical imaging.

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Machine learning-based pupillary response analysis is performed to assess operator cognitive workload in clinical ultrasound.

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A systematic multi-modal data analysis pipeline is proposed using eye-tracking, pupillometry, and sonography data science.

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Pertinent challenges of natural or real-world clinical datasets are addressed.

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Pupillary responses around event triggers, different ultrasonographic tasks, and different operator experiences are studied.

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Machine learning models are learnt to classify undertaken tasks or operator expertise from pupillometric time-series data.

Eye Tracking Measures for Studying Language Comprehension Deficits in Aphasia: A Systematic Search and Scoping Review

Aim The aim of this scoping review is to identify the eye tracking paradigms and eye movement measures used to investigate auditory and reading comprehension deficits in persons with aphasia (PWA). Method MEDLINE via PubMed, Cochrane, CINAHL, Embase, PsycINFO, OTseeker, Scopus, Google Scholar, Grey Literature Database, and ProQuest Search (Dissertations & Theses) were searched for relevant studies. The Covidence software was used to manage the initial and full-text screening process for the search. Results and Discussion From a total of 1,803 studies, 68 studies were included for full-text screening. In addition, 418 records from gray literature were also screened. After full-text screening, 16 studies were included for this review-12 studies for auditory comprehension in PWA and four studies for reading comprehension in PWA. The review highlights the use of common eye tracking paradigms used to study language comprehension in PWA. We also discusse eye movement measures and how they help in assessing auditory and reading comprehension. Methodological challenges of using eye tracking are discussed. Conclusion The studies summarized in this scoping review provide evidence that the eye tracking methods are beneficial for studying auditory and reading comprehension in PWA.

Disentangling listening effort and memory load beyond behavioural evidence: Pupillary response to listening effort during a concurrent memory task

Recent research has demonstrated that pupillometry is a robust measure for quantifying listening effort. However, pupillary responses in listening situations where multiple cognitive functions are engaged and sustained over a period of time remain hard to interpret. This limits our conceptualisation and understanding of listening effort in realistic situations, because rarely in everyday life are people challenged by one task at a time. Therefore, the purpose of this experiment was to reveal the dynamics of listening effort in a sustained listening condition using a word repeat and recall task. Words were presented in quiet and speech-shaped noise at different signal-to-noise ratios (SNR): 0dB, 7dB, 14dB and quiet. Participants were presented with lists of 10 words, and required to repeat each word after its presentation. At the end of the list, participants either recalled as many words as possible or moved on to the next list. Simultaneously, their pupil dilation was recorded throughout the whole experiment. When only word repeating was required, peak pupil dilation (PPD) was bigger in 0dB versus other conditions; whereas when recall was required, PPD showed no difference among SNR levels and PPD in 0dB was smaller than repeat-only condition. Baseline pupil diameter and PPD followed different variation patterns across the 10 serial positions within a block for conditions requiring recall: baseline pupil diameter built up progressively and plateaued in the later positions (but shot up when listeners were recalling the previously heard words from memory); PPD decreased at a pace quicker than in repeat-only condition. The current findings demonstrate that additional cognitive load during a speech intelligibility task could disturb the well-established relation between pupillary response and listening effort. Both the magnitude and temporal pattern of task-evoked pupillary response differ greatly in complex listening conditions, urging for more listening effort studies in complex and realistic listening situations.

Does stereopsis improve face identification? A study using a virtual reality display with integrated eye-tracking and pupillometry

Stereopsis is a powerful depth cue for humans, which may also contribute to object recognition. In particular, we surmise that face identification would benefit from the availability of stereoscopic depth cues, since facial perception may be based on three-dimensional (3D) representations. In this study, a virtual reality (VR) headset with integrated eye-tracking was used to present stereoscopic images of faces. As a monoscopic contrast condition, identical images of faces were displayed to the two eyes. We monitored the participants' gaze behavior and pupil diameters while they performed a sample-to-match face identification task. We found that accuracy was superior in the stereoscopic condition compared to the monoscopic condition for frontal and intermediate views, but not profiles. Moreover, pupillary diameters were smaller when identifying stereoscopically seen faces than when viewing them without stereometric cues, which we interpret as lower processing load for the former than the latter conditions. The analysis of gaze showed that participants tended to focus on regions of the face rich in volumetric information, more so in the stereoscopic condition than the monoscopic condition. Together, these findings suggest that a 3D representation of faces may be the natural format used by the visual system when assessing face identity. Stereoscopic information, by providing depth information, assists the construction of robust facial representations in memory.

Putting effort into infant cognition

Working memory allows for the manipulation of information in support of ongoing tasks, providing a workspace for cognitive processes such as learning, reasoning, and decision making. How well working memory works depends, in part, on effort. Someone who pays attention at the right time and place will have better memory, and performance. In adult cognitive research studies, participants' devotion of maximal task-focused effort is often taken for granted, but in infant studies researchers cannot make that assumption. Here we showcase how pupillometry can provide an easy-to-obtain physiological measure of cognitive effort, allowing us to better understand infants' emerging abilities. In our work, we used pupillometry to measure trial-by-trial fluctuations of effort, establishing that, just as in adults, it influences how well infants could encode information in visual working memory. We hope that by using physiological measures such as pupil dilation, there will be a renewed effort to investigate the interaction between infants' attentive states and cognition.

Cognitive performance and cognitive workload in multiple sclerosis: Two different constructs of cognitive functioning?

BACKGROUND

Cognitive impairment in individuals with Multiple Sclerosis (iwMS) is traditionally diagnosed using performance measures on cognitive tests. Yet, performance on cognitive tests does not convey the amount of mental effort or cognitive workload it takes to complete the task. The main aim was to evaluate whether cognitive performance and cognitive workload are two different constructs of cognitive functioning in iwMS.

METHODS

IwMS were categorized into cognitive impairments (iwMS+, n = 10) and no cognitive impairments (iwMS-, n = 12) using their performance on Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). Their scores on BICAMS, Stroop, and trail making tests were compared to age- and education-matched controls (n = 22). Cognitive workload was assessed using the self-reported NASA Task Load Index and the Index of Cognitive Activity, derived from pupillary response.

RESULTS

IwMS+ performed worse on most cognitive tests compared to iwMS- and controls. However, iwMS+ did not report or exhibit greater cognitive workload compared to the other groups. Potential confounding variables, such as sex, use of antidepressants, and symptoms of depression, fatigue, and dysautonomia did not influence the lack of correlation between cognitive performance and cognitive workload in all three groups.

CONCLUSION

Cognitive performance and cognitive workload seem to measure different cognitive constructs of cognitive functioning in MS. Our results suggest that iwMS+ do not show effective allocation of cognitive resources to compensate for deteriorated performance in cognitive tests.

Focused attention predicts visual working memory performance in 13-month-old infants: A pupillometric study

Attention turns looking, into seeing. Yet, little developmental research has examined the interface of attention and visual working memory (VWM), where what is seen is maintained for use in ongoing visual tasks. Using the task-evoked pupil response - a sensitive, real-time, involuntary measure of focused attention that has been shown to correlate with VWM performance in adults and older children - we examined the relationship between focused attention and VWM in 13-month-olds. We used a Delayed Match Retrieval paradigm, to test infants' VWM for object-location bindings - what went where - while recording anticipatory gaze responses and pupil dilation. We found that infants with greater focused attention during memory encoding showed significantly better memory performance. As well, trials that ended in a correct response had significantly greater pupil response during memory encoding than incorrect trials. Taken together, this shows that pupillometry can be used as a measure of focused attention in infants, and a means to identify those individuals, or moments, where cognitive effort is maximized.

The Pupil Dilation Response to Auditory Stimuli: Current State of Knowledge

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.

How the inference of hierarchical rules unfolds over time

Inductive reasoning, which entails reaching conclusions that are based on but go beyond available evidence, has long been of interest in cognitive science. Nevertheless, knowledge is still lacking as to the specific cognitive processes that underlie inductive reasoning. Here, we shed light on these processes in two ways. First, we characterized the timecourse of inductive reasoning in a rule induction task, using pupil dilation as a moment-by-moment measure of cognitive load. Participants' patterns of behavior and pupillary responses indicated that they engaged in rule inference on-line, and were surprised when additional evidence violated their inferred rules. Second, we sought to gain insight into how participants represented rules on this task - specifically, whether they would structure the rules hierarchically when possible. We predicted the cognitive load imposed by hierarchical representations, as well as by non-hierarchical, flat ones. We used task-evoked pupil dilation as a metric of cognitive load to infer, based on these predictions, which participants represented rules with flat or hierarchical structures. Participants categorized as representing the rules hierarchically or flat differed in task performance and self-reports of strategy. Hierarchical rule representation was associated with more efficient performance and more pronounced pupillary responses to rule violations on trials that afford a higher-order regularity, but with less efficient performance on trials that do not. Thus, differences in rule representation can be inferred from a physiological measure of cognitive load, and are associated with differences in performance. These results illustrate how pupillometry can provide a window into reasoning as it unfolds over time.

Pupil dilation as an index of effort in cognitive control tasks: A review

Pupillometry research has experienced an enormous revival in the last two decades. Here we briefly review the surge of recent studies on task-evoked pupil dilation in the context of cognitive control tasks with the primary aim being to evaluate the feasibility of using pupil dilation as an index of effort exertion, rather than task demand or difficulty. Our review shows that across the three cognitive control domains of updating, switching, and inhibition, increases in task demands typically leads to increases in pupil dilation. Studies show a diverging pattern with respect to the relationship between pupil dilation and performance and we show how an effort account of pupil dilation can provide an explanation of these findings. We also discuss future directions to further corroborate this account in the context of recent theories on cognitive control and effort and their potential neurobiological substrates.

Neurocognitive mechanisms of emotion-related impulsivity: The role of arousal

Prior research suggests that a traitlike tendency to experience impulsivity during states of high emotion is robustly associated with many forms of psychopathology. Several studies tie emotion-related impulsivity to response inhibition deficits, but these studies have not focused on the role of emotion or arousal within subjects. The present study tested whether arousal, measured by pupil dilation, amplifies deficits in response inhibition for those high in emotion-related impulsivity. Participants (N = 85) completed a measure of emotion-related impulsivity, underwent a positive mood induction procedure that reduced heterogeneity in mood states, and completed a response inhibition task. Pupil dilation was used to index arousal during the response inhibition task. Generalized linear mixed effect modeling yielded the hypothesized interaction between arousal (pupil dilation) and emotion-related impulsivity in predicting response inhibition performance at the trial level. Emotion-related impulsivity relates to more difficulties with response inhibition during moments of high arousal.

Best Practices and Advice for Using Pupillometry to Measure Listening Effort: An Introduction for Those Who Want to Get Started

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.

Beyond eye gaze: What else can eyetracking reveal about cognition and cognitive development?

This review provides an introduction to two eyetracking measures that can be used to study cognitive development and plasticity: pupil dilation and spontaneous blink rate. We begin by outlining the rich history of gaze analysis, which can reveal the current focus of attention as well as cognitive strategies. We then turn to the two lesser-utilized ocular measures. Pupil dilation is modulated by the brain's locus coeruleus-norepinephrine system, which controls physiological arousal and attention, and has been used as a measure of subjective task difficulty, mental effort, and neural gain. Spontaneous eyeblink rate correlates with levels of dopamine in the central nervous system, and can reveal processes underlying learning and goal-directed behavior. Taken together, gaze, pupil dilation, and blink rate are three non-invasive and complementary measures of cognition with high temporal resolution and well-understood neural foundations. Here we review the neural foundations of pupil dilation and blink rate, provide examples of their usage, describe analytic methods and methodological considerations, and discuss their potential for research on learning, cognitive development, and plasticity.

Pupil Sizes Scale with Attentional Load and Task Experience in a Multiple Object Tracking Task

Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted on three consecutive days. We found that pupil sizes increased with each increment in attentional load. Across days, we found systematic pupil size reductions. We compared the model fit for predicting pupil size modulations using attentional load, task experience, and task performance as predictors. We found that a model which included attentional load and task experience as predictors had the best model fit while adding performance as a predictor to this model reduced the overall model fit. Overall, results suggest that pupillometry provides a viable metric for precisely assessing attentional load and task experience in visuospatial tasks.

Pupil size influences the eye-tracker signal during saccades

While it is known that scleral search coils-measuring the rotation of the eye globe--and modern, video based eye trackers-tracking the center of the pupil and the corneal reflection (CR)--produce signals with different properties, the mechanisms behind the differences are less investigated. We measure how the size of the pupil affects the eye-tracker signal recorded during saccades with a common pupil-CR eye-tracker. Eye movements were collected from four healthy participants and one person with an aphakic eye while performing self-paced, horizontal saccades at different levels of screen luminance and hence pupil size. Results show that pupil-, and gaze-signals, but not the CR-signal, are affected by the size of the pupil; changes in saccade peak velocities in the gaze signal of more than 30% were found. It is important to be aware of this pupil size dependent change when comparing fine grained oculomotor behavior across participants and conditions.

Pupil diameter reflects uncertainty in attentional selection during visual search

Pupil diameter has long been used as a metric of cognitive processing. However, recent advances suggest that the cognitive sources of change in pupil size may reflect LC-NE function and the calculation of unexpected uncertainty in decision processes (Aston-Jones and Cohen, 2005; Yu and Dayan, 2005). In the current experiments, we explored the role of uncertainty in attentional selection on task-evoked changes in pupil diameter during visual search. We found that task-evoked changes in pupil diameter were related to uncertainty during attentional selection as measured by reaction time (RT) and performance accuracy (Experiments 1-2). Control analyses demonstrated that the results are unlikely to be due to error monitoring or response uncertainty. Our results suggest that pupil diameter can be used as an implicit metric of uncertainty in ongoing attentional selection requiring effortful control processes.

Visual working memory continues to develop through adolescence

The capacity of visual working memory (VWM) refers to the amount of visual information that can be maintained in mind at once, readily accessible for ongoing tasks. In healthy young adults, the capacity limit of VWM corresponds to about three simple objects. While some researchers argued that VWM capacity becomes adult-like in early years of life, others claimed that the capacity of VWM continues to develop beyond middle childhood. Here we assessed whether VWM capacity reaches adult levels in adolescence. Using an adaptation of the visual change detection task, we measured VWM capacity estimates in 13-year-olds, 16-year-olds, and young adults. We tested whether the capacity estimates observed in early or later years of adolescence were comparable to the estimates obtained from adults. Our results demonstrated that the capacity of VWM continues to develop throughout adolescence, not reaching adult levels even in 16-year-olds. These findings suggest that VWM capacity displays a prolonged development, similar to the protracted trajectories observed in various other aspects of cognition.