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

Classification of Hearing Status Based on Pupil Measures During Sentence Perception

PURPOSE

Speech understanding in noise can be effortful, especially for people with hearing impairment. To compensate for reduced acuity, hearing-impaired (HI) listeners may be allocating listening effort differently than normal-hearing (NH) peers. We expected that this might influence measures derived from the pupil dilation response. To investigate this in more detail, we assessed the sensitivity of pupil measures to hearing-related changes in effort allocation. We used a machine learning-based classification framework capable of combining and ranking measures to examine hearing-related, stimulus-related (signal-to-noise ratio [SNR]), and task response-related changes in pupil measures.

METHOD

Pupil data from 32 NH (40-70 years old, M = 51.3 years, six males) and 32 HI (31-76 years old, M = 59 years, 13 males) listeners were recorded during an adaptive speech reception threshold test. Peak pupil dilation (PPD), mean pupil dilation (MPD), principal pupil components (rotated principal components [RPCs]), and baseline pupil size (BPS) were calculated. As a precondition for ranking pupil measures, the ability to classify hearing status (NH/HI), SNR (high/low), and task response (correct/incorrect) above random prediction level was assessed. This precondition was met when classifying hearing status in subsets of data with varying SNR and task response, SNR in the NH group, and task response in the HI group.

RESULTS

A combination of pupil measures was necessary to classify the dependent factors. Hearing status, SNR, and task response were predicted primarily by the established measures-PPD (maximum effort), RPC2 (speech processing), and BPS (task anticipation)-and by the novel measures RPC1 (listening) and RPC3 (response preparation) in tasks involving SNR as an outcome or sometimes difficulty criterion.

CONCLUSIONS

A machine learning-based classification framework can assess sensitivity of, and rank the importance of, pupil measures in relation to three effort modulators (factors) during speech perception in noise. This indicates that the effects of these factors on the pupil measures allow for reasonable classification performance. Moreover, the varying contributions of each measure to the classification models suggest they are not equally affected by these factors. Thus, this study enhances our understanding of pupil responses and their sensitivity to relevant factors.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.28225199.

Comparison of Performance for Cochlear-Implant Listeners Using Audio Processing Strategies Based on Short-Time Fast Fourier Transform or Spectral Feature Extraction

OBJECTIVES

We compared sound quality and performance for a conventional cochlear-implant (CI) audio processing strategy based on short-time fast-Fourier transform (Crystalis) and an experimental strategy based on spectral feature extraction (SFE). In the latter, the more salient spectral features (acoustic events) were extracted and mapped into the CI stimulation electrodes. We hypothesized that (1) SFE would be superior to Crystalis because it can encode acoustic spectral features without the constraints imposed by the short-time fast-Fourier transform bin width, and (2) the potential benefit of SFE would be greater for CI users who have less neural cross-channel interactions.

DESIGN

To examine the first hypothesis, 6 users of Oticon Medical Digisonic SP CIs were tested in a double-blind design with the SFE and Crystalis strategies on various aspects: word recognition in quiet, speech-in-noise reception threshold (SRT), consonant discrimination in quiet, listening effort, melody contour identification (MCI), and subjective sound quality. Word recognition and SRTs were measured on the first and last day of testing (4 to 5 days apart) to assess potential learning and/or acclimatization effects. Other tests were run once between the first and last testing day. Listening effort was assessed by measuring pupil dilation. MCI involved identifying a five-tone contour among five possible contours. Sound quality was assessed subjectively using the multiple stimulus with hidden reference and anchor (MUSHRA) paradigm for sentences, music, and ambient sounds. To examine the second hypothesis, cross-channel interaction was assessed behaviorally using forward masking.

RESULTS

Word recognition was similar for the two strategies on the first day of testing and improved for both strategies on the last day of testing, with Crystalis improving significantly more. SRTs were worse with SFE than Crystalis on the first day of testing but became comparable on the last day of testing. Consonant discrimination scores were higher for Crystalis than for the SFE strategy. MCI scores and listening effort were not substantially different across strategies. Subjective sound quality scores were lower for the SFE than for the Crystalis strategy. The difference in performance with SFE and Crystalis was greater for CI users with higher channel interaction.

CONCLUSIONS

CI-user performance was similar with the SFE and Crystalis strategies. Longer acclimatization times may be required to reveal the full potential of the SFE strategy.

Pupillometry reveals effects of pitch manipulation within and across words on listening effort and short-term memory

For individuals with hearing loss, even successful speech communication comes at a cost. Cochlear implants transmit degraded information, specifically for voice pitch, which demands extra and sustained listening effort. The current study hypothesized that abnormal pitch patterns contribute to the additional listening effort, even in non-tonal language native speaking normally hearing listeners. We manipulated the fundamental frequency (F0) within and across words, while participants listen and repeat (simple intelligibility task), or listen, repeat, and later recall (concurrent encoding task) the words. In both experiments, the F0 manipulations resulted in small changes in intelligibility but no difference in free recall or subjective effort ratings. Pupillary metrics were yet sensitive to these manipulations: pupil dilations were larger when words were monotonized (flat contour) or inverted (the natural contour flipped upside-down), and larger when successive words were organized into a melodic pattern. The most likely interpretation is that the natural or expected F0 contour of a word contributes to its identity and facilitate its matching and retrieval from the phonological representation stored in long-term memory. Consequently, degrading words' F0 contour can result in extra listening effort. Our results call for solutions to improve pitch saliency and naturalness in future development of cochlear implants' signal processing strategies, even for non-tonal languages.

Normatively irrelevant disgust interferes with decision under uncertainty: Insights from the Iowa gambling task

This study investigates whether a not informative, irrelevant emotional reaction of disgust interferes with decision-making under uncertainty. We manipulate the Iowa Gambling Task (IGT) by associating a disgust-eliciting image with selections from Disadvantageous/Bad decks (Congruent condition) or Advantageous/Good decks (Incongruent condition). A Control condition without manipulations is also included. Results indicate an increased probability of selecting from a Good deck as the task unfolds in all conditions. However, this effect is modulated by the experimental manipulation. Specifically, we detect a detrimental effect (i.e., a significant decrease in the intercept) of the disgust-eliciting image in Incongruent condition (vs. Control), but this effect is limited to the early stages of the task (i.e., first twenty trials). No differences in performance trends are detected between Congruent and Control conditions. Anticipatory Skin Conductance Response, heart rate, and pupil dilation are also assessed as indexes of anticipatory autonomic activation following the Somatic Marker Hypothesis, but no effects are shown for the first two indexes in any of the conditions. Only a decreasing trend is detected for pupil dilation as the task unfolds in Control and Incongruent conditions. Results are discussed in line with the "risk as feelings" framework, the Somatic Marker Hypothesis, and IGT literature.

Impact of SNR, peripheral auditory sensitivity, and central cognitive profile on the psychometric relation between pupillary response and speech performance in CI users

Despite substantial technical advances and wider clinical use, cochlear implant (CI) users continue to report high and elevated listening effort especially under challenging noisy conditions. Among all the objective measures to quantify listening effort, pupillometry is one of the most widely used and robust physiological measures. Previous studies with normally hearing (NH) and hearing-impaired (HI) listeners have shown that the relation between speech performance in noise and listening effort (as measured by peak pupil dilation) is not linear and exhibits an inverted-U shape. However, it is unclear whether the same psychometric relation exists in CI users, and whether individual differences in auditory sensitivity and central cognitive capacity affect this relation. Therefore, we recruited 17 post-lingually deaf CI adults to perform speech-in-noise tasks from 0 to 20 dB SNR with a 4 dB step size. Simultaneously, their pupillary responses and self-reported subjective effort were recorded. To characterize top-down and bottom-up individual variabilities, a spectro-temporal modulation task and a set of cognitive abilities were measured. Clinical word recognition in quiet and Quality of Life (QoL) were also collected. Results showed that at a group level, an inverted-U shape psychometric curve between task difficulty (SNR) and peak pupil dilation (PPD) was not observed. Individual shape of the psychometric curve was significantly associated with some individual factors: CI users with higher clinical word and speech-in-noise recognition showed a quadratic decrease of PPD over increasing SNRs; CI users with better non-verbal intelligence and lower QoL showed smaller average PPD. To summarize, individual differences in CI users had a significant impact on the psychometric relation between pupillary response and task difficulty, hence affecting the interpretation of pupillary response as listening effort (or engagement) at different task difficulty levels. Future research and clinical applications should further characterize the possible effects of individual factors (such as motivation or engagement) in modulating CI users' occurrence of 'tipping point' on their psychometric functions, and develop an individualized method for reliably quantifying listening effort using pupillometry.