Anticipatory Baseline Pupil Diameter Is Sensitive to Differences in Hearing Thresholds

The Effects of Light Level and Signal-to-Noise Ratio on the Task-Evoked Pupil Response in a Speech-in-Noise Task

PURPOSE

There is increasing interest in the measurement of cognitive effort during listening tasks, for both research and clinical purposes. Quantification of task-evoked pupil responses (TEPRs) is a psychophysiological method that can be used to study cognitive effort. However, light level during cognitively demanding listening tasks may affect TEPRs, complicating interpretation of listening-related changes. The objective of this study was to examine the effects of light level on TEPRs during effortful listening across a range of signal-to-noise ratios (SNRs).

METHOD

Thirty-six adults without hearing loss were asked to repeat target sentences presented in background babble noise while their pupil diameter was recorded. Light level and SNRs were manipulated in a 4 × 4 repeated-measures design. Repeated-measures analyses of variance were used to measure the effects.

RESULTS

Peak and mean dilation were typically larger in more adverse SNR conditions (except for SNR -6 dB) and smaller in higher light levels. Differences in mean and peak dilation between SNR conditions were larger in dim light than in brighter light.

CONCLUSIONS

Brighter light conditions make TEPRs less sensitive to variations in listening effort across levels of SNR. Therefore, light level must be considered and reported in detail to ensure sensitivity of TEPRs and for comparisons of findings across different studies. It is recommended that TEPR testing be conducted in relatively low light conditions, considering both background illumination and screen luminance.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25676538.

Pupil Size and Eye Movements Differently Index Effort in Both Younger and Older Adults

The assessment of mental effort is increasingly relevant in neurocognitive and life span domains. Pupillometry, the measure of the pupil size, is often used to assess effort but has disadvantages. Analysis of eye movements may provide an alternative, but research has been limited to easy and difficult task demands in younger adults. An effort measure must be sensitive to the whole effort profile, including "giving up" effort investment, and capture effort in different age groups. The current study comprised three experiments in which younger (n = 66) and older (n = 44) adults listened to speech masked by background babble at different signal-to-noise ratios associated with easy, difficult, and impossible speech comprehension. We expected individuals to invest little effort for easy and impossible speech (giving up) but to exert effort for difficult speech. Indeed, pupil size was largest for difficult but lower for easy and impossible speech. In contrast, gaze dispersion decreased with increasing speech masking in both age groups. Critically, gaze dispersion during difficult speech returned to levels similar to easy speech after sentence offset, when acoustic stimulation was similar across conditions, whereas gaze dispersion during impossible speech continued to be reduced. These findings show that a reduction in eye movements is not a byproduct of acoustic factors, but instead suggest that neurocognitive processes, different from arousal-related systems regulating the pupil size, drive reduced eye movements during high task demands. The current data thus show that effort in one sensory domain (audition) differentially impacts distinct functional properties in another sensory domain (vision).

Pupil Dilation Reflects Perceptual Priorities During a Receptive Speech Task

OBJECTIVES

The listening demand incurred by speech perception fluctuates in normal conversation. At the acoustic-phonetic level, natural variation in pronunciation acts as speedbumps to accurate lexical selection. Any given utterance may be more or less phonetically ambiguous-a problem that must be resolved by the listener to choose the correct word. This becomes especially apparent when considering two common speech registers-clear and casual-that have characteristically different levels of phonetic ambiguity. Clear speech prioritizes intelligibility through hyperarticulation which results in less ambiguity at the phonetic level, while casual speech tends to have a more collapsed acoustic space. We hypothesized that listeners would invest greater cognitive resources while listening to casual speech to resolve the increased amount of phonetic ambiguity, as compared with clear speech. To this end, we used pupillometry as an online measure of listening effort during perception of clear and casual continuous speech in two background conditions: quiet and noise.

DESIGN

Forty-eight participants performed a probe detection task while listening to spoken, nonsensical sentences (masked and unmasked) while recording pupil size. Pupil size was modeled using growth curve analysis to capture the dynamics of the pupil response as the sentence unfolded.

RESULTS

Pupil size during listening was sensitive to the presence of noise and speech register (clear/casual). Unsurprisingly, listeners had overall larger pupil dilations during speech perception in noise, replicating earlier work. The pupil dilation pattern for clear and casual sentences was considerably more complex. Pupil dilation during clear speech trials was slightly larger than for casual speech, across quiet and noisy backgrounds.

CONCLUSIONS

We suggest that listener motivation could explain the larger pupil dilations to clearly spoken speech. We propose that, bounded by the context of this task, listeners devoted more resources to perceiving the speech signal with the greatest acoustic/phonetic fidelity. Further, we unexpectedly found systematic differences in pupil dilation preceding the onset of the spoken sentences. Together, these data demonstrate that the pupillary system is not merely reactive but also adaptive-sensitive to both task structure and listener motivation to maximize accurate perception in a limited resource system.

Attention Mobilization as a Modulator of Listening Effort: Evidence From Pupillometry

Listening to speech in noise can require substantial mental effort, even among younger normal-hearing adults. The task-evoked pupil response (TEPR) has been shown to track the increased effort exerted to recognize words or sentences in increasing noise. However, few studies have examined the trajectory of listening effort across longer, more natural, stretches of speech, or the extent to which expectations about upcoming listening difficulty modulate the TEPR. Seventeen younger normal-hearing adults listened to 60-s-long audiobook passages, repeated three times in a row, at two different signal-to-noise ratios (SNRs) while pupil size was recorded. There was a significant interaction between SNR, repetition, and baseline pupil size on sustained listening effort. At lower baseline pupil sizes, potentially reflecting lower attention mobilization, TEPRs were more sustained in the harder SNR condition, particularly when attention mobilization remained low by the third presentation. At intermediate baseline pupil sizes, differences between conditions were largely absent, suggesting these listeners had optimally mobilized their attention for both SNRs. Lastly, at higher baseline pupil sizes, potentially reflecting overmobilization of attention, the effect of SNR was initially reversed for the second and third presentations: participants initially appeared to disengage in the harder SNR condition, resulting in reduced TEPRs that recovered in the second half of the story. Together, these findings suggest that the unfolding of listening effort over time depends critically on the extent to which individuals have successfully mobilized their attention in anticipation of difficult listening conditions.

Combining Cardiovascular and Pupil Features Using k-Nearest Neighbor Classifiers to Assess Task Demand, Social Context, and Sentence Accuracy During Listening

In daily life, both acoustic factors and social context can affect listening effort investment. In laboratory settings, information about listening effort has been deduced from pupil and cardiovascular responses independently. The extent to which these measures can jointly predict listening-related factors is unknown. Here we combined pupil and cardiovascular features to predict acoustic and contextual aspects of speech perception. Data were collected from 29 adults (mean  =  64.6 years, SD  =  9.2) with hearing loss. Participants performed a speech perception task at two individualized signal-to-noise ratios (corresponding to 50% and 80% of sentences correct) and in two social contexts (the presence and absence of two observers). Seven features were extracted per trial: baseline pupil size, peak pupil dilation, mean pupil dilation, interbeat interval, blood volume pulse amplitude, pre-ejection period and pulse arrival time. These features were used to train k-nearest neighbor classifiers to predict task demand, social context and sentence accuracy. The k-fold cross validation on the group-level data revealed above-chance classification accuracies: task demand, 64.4%; social context, 78.3%; and sentence accuracy, 55.1%. However, classification accuracies diminished when the classifiers were trained and tested on data from different participants. Individually trained classifiers (one per participant) performed better than group-level classifiers: 71.7% (SD  =  10.2) for task demand, 88.0% (SD  =  7.5) for social context, and 60.0% (SD  =  13.1) for sentence accuracy. We demonstrated that classifiers trained on group-level physiological data to predict aspects of speech perception generalized poorly to novel participants. Individually calibrated classifiers hold more promise for future applications.

The Influence of Hearing Loss on the Pupil Response to Degraded Speech

PURPOSE

Current evidence regarding the influence of hearing loss on the pupil response elicited by speech perception is inconsistent. This might be partially due to confounding effects of age. This study aimed to compare pupil responses in age-matched groups of normal-hearing (NH) and hard of hearing (HH) listeners during listening to speech.

METHOD

We tested the baseline pupil size and mean and peak pupil dilation response of 17 NH participants (Mage = 46 years; age range: 20-62 years) and 17 HH participants (Mage = 45 years; age range: 20-63 years) who were pairwise matched on age and educational level. Participants performed three speech perception tasks at a 50% intelligibility level: noise-vocoded speech and speech masked with either stationary noise or interfering speech. They also listened to speech presented in quiet.

RESULTS

Hearing loss was associated with poorer speech perception, except for noise-vocoded speech. In contrast to NH participants, performance of HH participants did not improve across trials for the interfering speech condition, and it decreased for speech in stationary noise. HH participants had a smaller mean pupil dilation in degraded speech conditions compared to NH participants, but not for speech in quiet. They also had a steeper decline in the baseline pupil size across trials. The baseline pupil size was smaller for noise-vocoded speech as compared to the other conditions. The normalized data showed an additional group effect on the baseline pupil response.

CONCLUSIONS

Hearing loss is associated with a smaller pupil response and steeper decline in baseline pupil size during the perception of degraded speech. This suggests difficulties of the HH participants to sustain their effort investment and performance across the test session.

Copresence Was Found to Be Related to Some Pupil Measures in Persons With Hearing Loss While They Performed a Speech-in-Noise Task

OBJECTIVES

To assess if a manipulation of copresence was related to speech-in-noise task performance, arousal, and effort of persons with hearing loss. Task-related arousal and effort were measured by means of pupillometry.

DESIGN

Twenty-nine participants (mean age: 64.6 years) with hearing loss (4-frequency pure-tone average [4F-PTA] of 50.2 dB HL [SD = 8.9 dB] in the right ear and 51.3 dB HL [SD = 8.7 dB] in the left ear; averaged across 0.5, 1, 2, and 4 kHz) listened to and repeated spoken Danish sentences that were masked by four streams of continuous speech. Participants were presented with blocks of 20 sentences, during which copresence was manipulated by having participants do the task either alone or accompanied by two observers who were recruited from a similar age group. The task was presented at two difficulty levels, which was accomplished by fixing the signal-to-noise ratio of the speech and masker to match the thresholds at which participants were estimated to correctly repeat 50% (difficult) or 80% (easy) of the sentences in a block. Performance was assessed based on whether or not sentences were repeated correctly. Measures of pupil size (baseline pupil size [BPS], peak pupil dilation [PPD], and mean pupil dilation [MPD]) were used to index arousal and effort. Participants also completed ratings of subjective effort and stress after each block of sentences and a self-efficacy for listening-questionnaire.

RESULTS

Task performance was not associated with copresence, but was found to be related to 4F-PTA. An increase in BPS was found for copresence conditions, compared to alone conditions. Furthermore, a post-hoc exploratory analysis revealed that the copresence conditions were associated with a significantly larger pupil size in the second half of the task-evoked pupil response (TEPR). No change in PPD or MPD did was detected between copresence and alone conditions. Self-efficacy, 4F-PTA, and age were not found to be related to the pupil data. Subjective ratings were sensitive to task difficulty but not copresence.

CONCLUSION

Copresence was not found to be related to speech-in-noise performance, PPD, or MPD in persons with HL but was associated with an increase in arousal (as indicated by a larger BPS). This could be related to premobilization of effort and/or discomfort in response to the observers' presence. Furthermore, an exploratory analysis of the pupil data showed that copresence was associated with greater pupil dilations in the second half of the TEPR. This may indicate that participants invested more effort during the speech-in-noise task while in the presence of the observers, but that this increase in effort may not necessarily have been related to listening itself. Instead, other speech-in-noise task-related processes, such as preparing to respond, could have been influenced by copresence.

Eye Movements Decrease during Effortful Speech Listening

Hearing impairment affects many older adults but is often diagnosed decades after speech comprehension in noisy situations has become effortful. Accurate assessment of listening effort may thus help diagnose hearing impairment earlier. However, pupillometry-the most used approach to assess listening effort-has limitations that hinder its use in practice. The current study explores a novel way to assess listening effort through eye movements. Building on cognitive and neurophysiological work, we examine the hypothesis that eye movements decrease when speech listening becomes challenging. In three experiments with human participants from both sexes, we demonstrate, consistent with this hypothesis, that fixation duration increases and spatial gaze dispersion decreases with increasing speech masking. Eye movements decreased during effortful speech listening for different visual scenes (free viewing, object tracking) and speech materials (simple sentences, naturalistic stories). In contrast, pupillometry was less sensitive to speech masking during story listening, suggesting pupillometric measures may not be as effective for the assessments of listening effort in naturalistic speech-listening paradigms. Our results reveal a critical link between eye movements and cognitive load, suggesting that neural activity in the brain regions that support the regulation of eye movements, such as frontal eye field and superior colliculus, are modulated when listening is effortful.SIGNIFICANCE STATEMENT Assessment of listening effort is critical for early diagnosis of age-related hearing loss. Pupillometry is most used but has several disadvantages. The current study explores a novel way to assess listening effort through eye movements. We examine the hypothesis that eye movements decrease when speech listening becomes effortful. We demonstrate, consistent with this hypothesis, that fixation duration increases and gaze dispersion decreases with increasing speech masking. Eye movements decreased during effortful speech listening for different visual scenes (free viewing, object tracking) and speech materials (sentences, naturalistic stories). Our results reveal a critical link between eye movements and cognitive load, suggesting that neural activity in brain regions that support the regulation of eye movements are modulated when listening is effortful.

Use of the first-acquired language modulates pupil size in the processing of island constraint violations

Introduction

Traditional studies of the population called "heritage speakers" (HS) have treated this group as distinct from other bilingual populations, e.g., simultaneous or late bilinguals (LB), focusing on group differences in the competencies of the first-acquired language or "heritage language". While several explanations have been proposed for such differences (e.g., incomplete acquisition, attrition, differential processing mechanisms), few have taken into consideration the individual variation that must occur, due to the fluctuation of factors such as exposure and use that characterize all bilinguals. In addition, few studies have used implicit measures, e.g., psychophysiological methods (ERPs; Eye-tracking), that can circumvent confounding variables such as resorting to conscious metalinguistic knowledge.

Methodology

This study uses pupillometry, a method that has only recently been used in psycholinguistic studies of bilingualism, to investigate pupillary responses to three syntactic island constructions in two groups of Spanish/English bilinguals: heritage speakers and late bilinguals. Data were analyzed using generalized additive mixed effects models (GAMMs) and two models were created and compared to one another: one with group (LB/HS) and the other with groups collapsed and current and historical use of Spanish as continuous variables.

Results

Results show that group-based models generally yield conflicting results while models collapsing groups and having usage as a predictor yield consistent ones. In particular, current use predicts sensitivity to L1 ungrammaticality across both HS and LB populations. We conclude that individual variation, as measured by use, is a critical factor tha must be taken into account in the description of the language competencies and processing of heritage and late bilinguals alike.

Combining Multiple Psychophysiological Measures of Listening Effort: Challenges and Recommendations

About one-third of all recently published studies on listening effort have used at least one physiological measure, providing evidence of the popularity of such measures in listening effort research. However, the specific measures employed, as well as the rationales used to justify their inclusion, vary greatly between studies, leading to a literature that is fragmented and difficult to integrate. A unified approach that assesses multiple psychophysiological measures justified by a single rationale would be preferable because it would advance our understanding of listening effort. However, such an approach comes with a number of challenges, including the need to develop a clear definition of listening effort that links to specific physiological measures, customized equipment that enables the simultaneous assessment of multiple measures, awareness of problems caused by the different timescales on which the measures operate, and statistical approaches that minimize the risk of type-I error inflation. This article discusses in detail the various obstacles for combining multiple physiological measures in listening effort research and provides recommendations on how to overcome them.

Time Scales and Moments of Listening Effort Revealed in Pupillometry

This article offers a collection of observations that highlight the value of time course data in pupillometry and points out ways in which these observations create deeper understanding of listening effort. The main message is that listening effort should be considered on a moment-to-moment basis rather than as a singular amount. A review of various studies and the reanalysis of data reveal distinct signatures of effort before a stimulus, during a stimulus, in the moments after a stimulus, and changes over whole experimental testing sessions. Collectively these observations motivate questions that extend beyond the "amount" of effort, toward understanding how long the effort lasts, and how precisely someone can allocate effort at specific points in time or reduce effort at other times. Apparent disagreements between studies are reconsidered as informative lessons about stimulus selection and the nature of pupil dilation as a reflection of decision making rather than the difficulty of sensory encoding.

Strategic Pauses Relieve Listeners from the Effort of Listening to Fast Speech: Data Limited and Resource Limited Processes in Narrative Recall by Adult Users of Cochlear Implants

Speech that has been artificially accelerated through time compression produces a notable deficit in recall of the speech content. This is especially so for adults with cochlear implants (CI). At the perceptual level, this deficit may be due to the sharply degraded CI signal, combined with the reduced richness of compressed speech. At the cognitive level, the rapidity of time-compressed speech can deprive the listener of the ordinarily available processing time present when speech is delivered at a normal speech rate. Two experiments are reported. Experiment 1 was conducted with 27 normal-hearing young adults as a proof-of-concept demonstration that restoring lost processing time by inserting silent pauses at linguistically salient points within a time-compressed narrative ("time-restoration") returns recall accuracy to a level approximating that for a normal speech rate. Noise vocoder conditions with 10 and 6 channels reduced the effectiveness of time-restoration. Pupil dilation indicated that additional effort was expended by participants while attempting to process the time-compressed narratives, with the effortful demand on resources reduced with time restoration. In Experiment 2, 15 adult CI users tested with the same (unvocoded) materials showed a similar pattern of behavioral and pupillary responses, but with the notable exception that meaningful recovery of recall accuracy with time-restoration was limited to a subgroup of CI users identified by better working memory spans, and better word and sentence recognition scores. Results are discussed in terms of sensory-cognitive interactions in data-limited and resource-limited processes among adult users of cochlear implants.

Identifying Listeners Whose Speech Intelligibility Depends on a Quiet Extra Moment After a Sentence

PURPOSE

An extra moment after a sentence is spoken may be important for listeners with hearing loss to mentally repair misperceptions during listening. The current audiologic test battery cannot distinguish between a listener who repaired a misperception versus a listener who heard the speech accurately with no need for repair. This study aims to develop a behavioral method to identify individuals who are at risk for relying on a quiet moment after a sentence.

METHOD

Forty-three individuals with hearing loss (32 cochlear implant users, 11 hearing aid users) heard sentences that were followed by either 2 s of silence or 2 s of babble noise. Both high- and low-context sentences were used in the task.

RESULTS

Some individuals showed notable benefit in accuracy scores (particularly for high-context sentences) when given an extra moment of silent time following the sentence. This benefit was highly variable across individuals and sometimes absent altogether. However, the group-level patterns of results were mainly explained by the use of context and successful perception of the words preceding sentence-final words.

CONCLUSIONS

These results suggest that some but not all individuals improve their speech recognition score by relying on a quiet moment after a sentence, and that this fragility of speech recognition cannot be assessed using one isolated utterance at a time. Reliance on a quiet moment to repair perceptions would potentially impede the perception of an upcoming utterance, making continuous communication in real-world scenarios difficult especially for individuals with hearing loss. The methods used in this study-along with some simple modifications if necessary-could potentially identify patients with hearing loss who retroactively repair mistakes by using clinically feasible methods that can ultimately lead to better patient-centered hearing health care.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21644801.

Baseline pupil size encodes task-related information and modulates the task-evoked response in a speech-in-noise task

Pupillometry data are commonly reported relative to a baseline value recorded in a controlled pre-task condition. In this study, the influence of the experimental design and the preparatory processing related to task difficulty on the baseline pupil size was investigated during a speech intelligibility in noise paradigm. Furthermore, the relationship between the baseline pupil size and the temporal dynamics of the pupil response was assessed. The analysis revealed strong effects of block presentation order, within-block sentence order and task difficulty on the baseline values. An interaction between signal-to-noise ratio and block order was found, indicating that baseline values reflect listener expectations arising from the order in which the different blocks were presented. Furthermore, the baseline pupil size was found to affect the slope, delay and curvature of the pupillary response as well as the peak pupil dilation. This suggests that baseline correction might be sufficient when reporting pupillometry results in terms of mean pupil dilation only, but not when a more complex characterization of the temporal dynamics of the response is considered. By clarifying which factors affect baseline pupil size and how baseline values interact with the task-evoked response, the results from the present study can contribute to a better interpretation of the pupillary response as a marker of cognitive processing.

A decrease in physiological arousal accompanied by stable behavioral performance reflects task habituation

Despite the evidence of a positive relationship between task demands and listening effort, the Framework for Understanding Effortful Listening (FUEL) highlights the important role of arousal on an individual’s choice to engage in challenging listening tasks. Previous studies have interpreted physiological responses in conjunction with behavioral responses as markers of task engagement. The aim of the current study was to investigate the effect of potential changes in physiological arousal, indexed by the pupil baseline, on task engagement over the course of an auditory recall test. Furthermore, the aim was to investigate whether working memory (WM) capacity and the signal-to-noise ratio (SNR) at which the test was conducted had an effect on changes in arousal. Twenty-one adult hearing aid users with mild to moderately severe symmetrical sensorineural hearing loss were included. The pupil baseline was measured during the Sentence-final Word Identification and Recall (SWIR) test, which was administered in a background noise composed of sixteen talkers. The Reading Span (RS) test was used as a measure of WM capacity. The findings showed that the pupil baseline decreased over the course of the SWIR test. However, recall performance remained stable, indicating that the participants maintained the necessary engagement level required to perform the task. These findings were interpreted as a decline in arousal as a result of task habituation. There was no effect of WM capacity or individual SNR level on the change in pupil baseline over time. A significant interaction was found between WM capacity and SNR level on the overall mean pupil baseline. Individuals with higher WM capacity exhibited an overall larger mean pupil baseline at low SNR levels compared to individuals with poorer WM capacity. This may be related to the ability of individuals with higher WM capacity to perform better than individual with poorer WM capacity in challenging listening conditions.

The relationship between pupillary baseline manipulated by mental effort or luminance and subsequent pupillary responses

Measuring pupillary response is a prevalent technique to evaluate mental states. It is indispensable to conduct a correction procedure for the pupillary baseline to get a meaningful conclusion from the pupillary response. However, the relationship between pupillary baseline and subsequent stimulus-evoked pupillary response varies among studies. In this study, we used the subtractive and proportional baseline corrections to analyze the results. Furthermore, we manipulated the pupillary baseline through mental effort or luminance in the baseline period and investigated whether the subsequent stimulus-evoked pupillary responses were affected. We found that the mental effort–evoked pupillary response was attenuated with a larger pupillary baseline manipulated by a higher mental effort, whereas it was unaffected with the baseline manipulated by luminance. Also, the luminance-evoked pupillary response was attenuated with a smaller pupillary baseline manipulated by a brighter disk, whereas it was unaffected with the baseline manipulated by mental effort. The results could be obtained from subtractive and proportional baseline corrections. Our results suggest that mental effort manipulated pupillary baseline interacts with the subsequent mental effort elicited pupillary response, but not with the luminance elicited pupillary response; the luminance manipulated pupillary baseline interacts with the subsequent luminance elicited pupillary response, but not with the mental effort elicited pupillary response. It is important to consider the ways of controlling the pupillary baseline and subsequent pupillary response simultaneously.

Assessment methods for determining small changes in hearing performance over time

Although the behavioral pure-tone threshold audiogram is considered the gold standard for quantifying hearing loss, assessment of speech understanding, especially in noise, is more relevant to quality of life but is only partly related to the audiogram. Metrics of speech understanding in noise are therefore an attractive target for assessing hearing over time. However, speech-in-noise assessments have more potential sources of variability than pure-tone threshold measures, making it a challenge to obtain results reliable enough to detect small changes in performance. This review examines the benefits and limitations of speech-understanding metrics and their application to longitudinal hearing assessment, and identifies potential sources of variability, including learning effects, differences in item difficulty, and between- and within-individual variations in effort and motivation. We conclude by recommending the integration of non-speech auditory tests, which provide information about aspects of auditory health that have reduced variability and fewer central influences than speech tests, in parallel with the traditional audiogram and speech-based assessments.

Adults with cochlear implants can use prosody to determine the clausal structure of spoken sentences

Speech prosody, including pitch contour, word stress, pauses, and vowel lengthening, can aid the detection of the clausal structure of a multi-clause sentence and this, in turn, can help listeners determine the meaning. However, for cochlear implant (CI) users, the reduced acoustic richness of the signal raises the question of whether CI users may have difficulty using sentence prosody to detect syntactic clause boundaries within sentences or whether this ability is rescued by the redundancy of the prosodic features that normally co-occur at clause boundaries. Twenty-two CI users, ranging in age from 19 to 77 years old, recalled three types of sentences: sentences in which the prosodic pattern was appropriate to the location of a clause boundary within the sentence (congruent prosody), sentences with reduced prosodic information, or sentences in which the location of the clause boundary and the prosodic marking of a clause boundary were placed in conflict. The results showed the presence of congruent prosody to be associated with superior sentence recall and a reduced processing effort as indexed by the pupil dilation. The individual differences in a standard test of word recognition (consonant-nucleus-consonant score) were related to the recall accuracy as well as the processing effort. The outcomes are discussed in terms of the redundancy of the prosodic features, which normally accompany a clause boundary and processing effort.

The Effects of Task Difficulty Predictability and Noise Reduction on Recall Performance and Pupil Dilation Responses

OBJECTIVES

Communication requires cognitive processes which are not captured by traditional speech understanding tests. Under challenging listening situations, more working memory resources are needed to process speech, leaving fewer resources available for storage. The aim of the current study was to investigate the effect of task difficulty predictability, that is, knowing versus not knowing task difficulty in advance, and the effect of noise reduction on working memory resource allocation to processing and storage of speech heard in background noise. For this purpose, an "offline" behavioral measure, the Sentence-Final Word Identification and Recall (SWIR) test, and an "online" physiological measure, pupillometry, were combined. Moreover, the outcomes of the two measures were compared to investigate whether they reflect the same processes related to resource allocation.

DESIGN

Twenty-four experienced hearing aid users with moderate to moderately severe hearing loss participated in this study. The SWIR test and pupillometry were measured simultaneously with noise reduction in the test hearing aids activated and deactivated in a background noise composed of four-talker babble. The task of the SWIR test is to listen to lists of sentences, repeat the last word immediately after each sentence and recall the repeated words when the list is finished. The sentence baseline dilation, which is defined as the mean pupil dilation before each sentence, and task-evoked peak pupil dilation (PPD) were analyzed over the course of the lists. The task difficulty predictability was manipulated by including lists of three, five, and seven sentences. The test was conducted over two sessions, one during which the participants were informed about list length before each list (predictable task difficulty) and one during which they were not (unpredictable task difficulty).

RESULTS

The sentence baseline dilation was higher when task difficulty was unpredictable compared to predictable, except at the start of the list, where there was no difference. The PPD tended to be higher at the beginning of the list, this pattern being more prominent when task difficulty was unpredictable. Recall performance was better and sentence baseline dilation was higher when noise reduction was on, especially toward the end of longer lists. There was no effect of noise reduction on PPD.

CONCLUSIONS

Task difficulty predictability did not have an effect on resource allocation, since recall performance was similar independently of whether task difficulty was predictable or unpredictable. The higher sentence baseline dilation when task difficulty was unpredictable likely reflected a difference in the recall strategy or higher degree of task engagement/alertness or arousal. Hence, pupillometry captured processes which the SWIR test does not capture. Noise reduction frees up resources to be used for storage of speech, which was reflected in the better recall performance and larger sentence baseline dilation toward the end of the list when noise reduction was on. Thus, both measures captured different temporal aspects of the same processes related to resource allocation with noise reduction on and off.

Effects of Noise and Serial Position on Free Recall of Spoken Words and Pupil Dilation during Encoding in Normal-Hearing Adults

This preliminary study assessed the effects of noise and stimulus presentation order on recall of spoken words and recorded pupil sizes while normal-hearing listeners were trying to encode a series of words for a subsequent recall task. In three listening conditions (stationary noise in Experiment 1; quiet versus four-talker babble in Experiment 2), participants were assigned to remember as many words as possible to recall them in any order after each list of seven sentences. In the two noise conditions, lists of sentences fixed at 65 dB SPL were presented at an easily audible level via a loudspeaker. Reading span (RS) scores were used as a grouping variable, based on a median split. The primacy effect was present apart from the noise interference, and the high-RS group significantly outperformed the low-RS group at free recall measured in the quiet and four-talker babble noise conditions. RS scores were positively correlated with free-recall scores. In both quiet and four-talker babble noise conditions, sentence baselines after correction to the initial stimulus baseline increased significantly with increasing memory load. Larger sentence baselines but smaller peak pupil dilations seemed to be associated with noise interruption. The analysis method of pupil dilation used in this study is likely to provide a more thorough understanding of how listeners respond to a later recall task in comparison with previously used methods. Further studies are needed to confirm the applicability of our method in people with impaired hearing using multiple repetitions to estimate the allocation of relevant cognitive resources.

Pupil Reactions to Tactile Stimulation: A Systematic Review

Pupil dynamics can represent an indirect measure of perception; thus, it has been broadly explored in the auditory and visual fields. Although it is crucial for experiencing the outside world, tactile perception is not well-explored. Considering that, we sought to answer the following question via a systematic review: does normal tactile perception processing modulate pupil dilation in mammals (human or not)? The review process was conducted according to PRISMA Statement. We searched on Periódicos CAPES (Brazil) for the following terms: [(touch) OR (cutaneous stimulation) OR (tactile perception) OR (somatosensory) AND (pupil OR pupillary) NOT blind NOT reflex NOT pain NOT fear NOT noxious NOT autism NOT nerve NOT (pupillary block) NOT glaucoma NOT cataract NOT aneurysm NOT syndrome NOT treatment NOT special education]. From the 6,488 papers found, 4,568 were duplicates, and nine fulfilled the inclusion criteria. All papers found a positive relationship between pupil diameter and tactile perception. We found that the pupil is a reliable indirect measure of brain states and can evaluate norepinephrine (NE)/locus coeruleus (LC) action, stimulus inhibition, arousal, cognitive processes, and affection independently of the stimuli category (visual, auditory, or tactile). We also found that the perceptual tactile processing occurs in similar ways as the other perceptual modalities. We verified that more studies should be done, mostly avoiding low sampling rate recording systems, confounders as cue signs, not automated stimulation, and concurrent stimulus and using more reliable equipment.

Deep learning-based pupil model predicts time and spectral dependent light responses

Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil's time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 [Formula: see text] 1 K, 4983 [Formula: see text] 3 K, 10,138 [Formula: see text] 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m2. This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour.