Patterns of eye blinks are modulated by auditory input in humans

Interpersonal eye-tracking reveals the dynamics of interacting minds

The human eye is a rich source of information about where, when, and how we attend. Our gaze paths indicate where and what captures our attention, while changes in pupil size can signal surprise, revealing our expectations. Similarly, the pattern of our blinks suggests levels of alertness and when our attention shifts between external engagement and internal thought. During interactions with others, these cues reveal how we coordinate and share our mental states. To leverage these insights effectively, we need accurate, timely methods to observe these cues as they naturally unfold. Advances in eye-tracking technology now enable real-time observation of these cues, shedding light on mutual cognitive processes that foster shared understanding, collaborative thought, and social connection. This brief review highlights these advances and the new opportunities they present for future research.

Attentional modulation of eye blinking is altered by sex, age, and task structure

Spontaneous eye blinking is gaining popularity as a proxy for higher cognitive functions, as it is readily modulated by both environmental demands and internal processes. Prior studies were impoverished in sample size, sex representation and age distribution, making it difficult to establish a complete picture of the behavior. Here we present eye-tracking data from a large cohort of normative participants (n=604, 393 F, aged 5-93 years) performing two tasks: one with structured, discrete trials (interleaved pro/anti-saccade task; IPAST) and one with a less structured, continuous organization in which participants watch movies (free-viewing; FV). Sex- and age-based analyses revealed that females had higher blink rates between the ages of 22 and 58 years in the IPAST, and 22 and 34 years in FV. We derived a continuous measure of blink probability to reveal behavioral changes driven by stimulus appearance in both paradigms. In the IPAST, blinks were suppressed near stimulus appearance, particularly on correct anti-saccade trials, which we attribute to the stronger inhibitory control required for anti-saccades compared to pro-saccades. In FV, blink suppression occurred immediately after scene changes, and the effect was sustained on scenes where gaze clustered among participants (indicating engagement of attention). Females were more likely than males to blink during appearance of novel stimuli in both tasks, but only within the age bin of 18-44 years. The consistency of blink patterns in each paradigm endorses blinking as a sensitive index for changes in visual processing and attention, while sex and age differences drive interindividual variability.Significance Statement Eye-tracking is becoming useful as a non-invasive tool for detecting preclinical markers of neurological and psychiatric disease. Blinks are understudied despite being an important supplement to saccade and pupil eye-tracking metrics. The present study is a crucial step in developing a healthy baseline for blink behavior to compare to clinical groups. While many prior blink studies suffered from small sample sizes with relatively low age- and sex-diversity (review by Jongkees & Colzato, 2016), our large cohort of healthy participants has permitted a more detailed analysis of sex and age effects in blink behavior. Furthermore, our analysis techniques are robust to temporal changes in blink probability, greatly clarifying the relationship between blinking, visual processing, and inhibitory control mechanisms on visual tasks.

Spontaneous Eye Blinks Map the Probability of Perceptual Reinterpretation During Visual and Auditory Ambiguity

Spontaneous eye blinks are modulated around perceptual events. Our previous study, using a visual ambiguous stimulus, indicated that blink probability decreases before a reported perceptual switch. In the current study, we tested our hypothesis that an absence of blinks marks a time in which perceptual switches are facilitated in- and outside the visual domain. In three experiments, presenting either a visual motion quartet in light or darkness or a bistable auditory streaming stimulus, we found a co-occurrence of blink rate reduction with increased perceptual switch probability. In the visual domain, perceptual switches induced by a short interruption of visual input (blank) allowed an estimate of the timing of the perceptual event with respect to the motor response. This provided the first evidence that the blink reduction was not a consequence of the perceptual switch. Importantly, by showing that the time between switches and the previous blink was significantly longer than the inter-blink interval, our studies allowed to conclude that perceptual switches did not happen at random but followed a prolonged period of nonblinking. Correspondingly, blink rate and switch rate showed an inverse relationship. Our study supports the idea that the absence or presence of blinks maps perceptual processes independent of the sensory modality.

How the eyes respond to sounds

Eye movements have been extensively studied with respect to visual stimulation. However, we live in a multisensory world, and how the eyes are driven by other senses has been explored much less. Here, we review the evidence on how audition can trigger and drive different eye responses and which cortical and subcortical neural correlates are involved. We provide an overview on how different types of sounds, from simple tones and noise bursts to spatially localized sounds and complex linguistic stimuli, influence saccades, microsaccades, smooth pursuit, pupil dilation, and eye blinks. The reviewed evidence reveals how the auditory system interacts with the oculomotor system, both behaviorally and neurally, and how this differs from visually driven eye responses. Some evidence points to multisensory interaction, and potential multisensory integration, but the underlying computational and neural mechanisms are still unclear. While there are marked differences in how the eyes respond to auditory compared to visual stimuli, many aspects of auditory-evoked eye responses remain underexplored, and we summarize the key open questions for future research.

Eye blinking, musical processing, and subjective states-A methods account

Affective sciences often make use of self-reports to assess subjective states. Seeking a more implicit measure for states and emotions, our study explored spontaneous eye blinking during music listening. However, blinking is understudied in the context of research on subjective states. Therefore, a second goal was to explore different ways of analyzing blink activity recorded from infra-red eye trackers, using two additional data sets from earlier studies differing in blinking and viewing instructions. We first replicate the effect of increased blink rates during music listening in comparison with silence and show that the effect is not related to changes in self-reported valence, arousal, or to specific musical features. Interestingly, but in contrast, felt absorption reduced participants' blinking. The instruction to inhibit blinking did not change results. From a methodological perspective, we make suggestions about how to define blinks from data loss periods recorded by eye trackers and report a data-driven outlier rejection procedure and its efficiency for subject-mean analyses, as well as trial-based analyses. We ran a variety of mixed effects models that differed in how trials without blinking were treated. The main results largely converged across accounts. The broad consistency of results across different experiments, outlier treatments, and statistical models demonstrates the reliability of the reported effects. As recordings of data loss periods come for free when interested in eye movements or pupillometry, we encourage researchers to pay attention to blink activity and contribute to the further understanding of the relation between blinking, subjective states, and cognitive processing.

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.

Carbohydrate polymer-based bioadhesive formulations and their potentials for the treatment of ocular diseases: A review

Eyes are directly exposed to the outer environment and susceptible to infections, leading to various ocular disorders. Local medication is preferred to treat eye diseases due to its convenience and compliance. However, the rapid clearance of the local formulations highly limits the therapeutic efficacy. In the past decades, several carbohydrate bioadhesive polymers (CBPs), such as chitosan and hyaluronic acid, have been used in ophthalmology for sustained ocular drug delivery. These CBP-based delivery systems have improved the treatment of ocular diseases to a large extent but also caused some undesired effects. Herein, we aim to summarize the applications of some typical CBPs (including chitosan, hyaluronic acid, cellulose, cyclodextrin, alginate and pectin) in treating ocular diseases from the general view of ocular physiology, pathophysiology and drug delivery, and to provide a comprehensive understanding of the design of the CBP-based formulations for ocular use. The patents and clinical trials of CBPs for ocular management are also discussed. In addition, a discussion on the concerns of CBPs in clinical use and the possible solutions is presented.

Task-synchronized eye blink modulation neither requires visual stimulation nor active motor response and is modulated by task predictability

It has been repeatedly shown that temporal task features are reflected in eye blink dynamics during attention tasks. Eye blinks occur with increased likeliness particularly when demands on external attention allocation are low. Both predictive, top-down and reactive, bottom-up processes were shown to be involved in blink regulation. However, whether temporal stimulus prediction is a generally active component of the attention system or rather specific to the visual domain has not been fully elaborated yet. By monitoring eye blinking of 99 students during an auditory attention task and analyzing particularly the dynamics of eye blink onsets relative to stimuli timings, we show here that prediction does, in principle, not require visual stimulation, and is also not merely a consequence of the involvement of manual responses during the task. We further show that both the inclusion of manual response to stimuli and elevated task predictability enhance the prediction component reflected in eye blink dynamics, whereas for the latter we experimentally manipulate objective task predictability by adjusting the frequency dependence of the power spectral densities of the series of inter-stimulus time intervals. This allows us finally to explain why, for specific choices of experimental conditions, the generally active and present prediction component involved in attention can become difficult to detect in non-visual, auditory tasks. Conversely, this comes with the important implication that, if tasks aim for elaborating particularly temporal prediction, distributing stimuli over time such that inter-stimulus-intervals conform to a sample of Gaussian noise represents a specifically unfavorable choice.