64 research outputs found

    Toward a more comprehensive understanding of the impact of masker type and signal-to-noise ratio on the pupillary response while performing a speech-in-noise test

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    Difficulties arising in everyday speech communication often result from the acoustical environment, which may contain interfering background noise or competing speakers. Thus, listening and understanding speech in noise can be exhausting. Two experiments are presented in the current study that further explored the impact of masker type and Signal-to-Noise Ratio (SNR) on listening effort by means of pupillometry. In both studies, pupillary responses of participants were measured while performing the Danish Hearing in Noise Test (HINT; Nielsen and Dau, 2011). The first experiment aimed to replicate and extend earlier observed effects of noise type and semantic interference on listening effort (Koelewijn et al., 2012). The impact of three different masker types, i.e. a fluctuating noise, a 1-talker masker and a 4-talker masker on listening effort was examined at a fixed speech intelligibility. In a second experiment, effects of SNR on listening effort were examined while presenting the HINT sentences across a broad range of fixed SNRs corresponding to intelligibility scores ranging from 100% to 0% correct performance. A peak pupil dilation (PPD) was calculated and a Growth Curve Analysis (GCA) was performed to examine listening effort involved in speech recognition as a function of SNR. The results of two experiments showed that the pupil dilation response is highly affected by both masker type and SNR when performing the HINT. The PPD was highest, suggesting the highest level of effort, for speech recognition in the presence of the 1-talker masker in comparison to the 4-talker babble and the fluctuating noise masker. However, the disrupting effect of one competing talker disappeared for intelligibly levels around 50%. Furthermore, it was demonstrated that the pupillary response strongly varied as a function of SNRs. Listening effort was highest for intermediate SNRs with performance accuracies ranging between 30% and 70% correct. GCA revealed time-dependent effects of the SNR on the pupillary response that were not reflected in the PPD

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

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

    Competition between auditory and visual spatial cues during visual task performance

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    There is debate in the crossmodal cueing literature as to whether capture of visual attention by means of sound is a fully automatic process. Recent studies show that when visual attention is endogenously focused sound still captures attention. The current study investigated whether there is interaction between exogenous auditory and visual capture. Participants preformed an orthogonal cueing task, in which, the visual target was preceded by both a peripheral visual and auditory cue. When both cues were presented at chance level, visual and auditory capture was observed. However, when the validity of the visual cue was increased to 80% only visual capture and no auditory capture was observed. Furthermore, a highly predictive (80% valid) auditory cue was not able to prevent visual capture. These results demonstrate that crossmodal auditory capture does not occur when a competing predictive visual event is presented and is therefore not a fully automatic process

    FORUM:Remote testing for psychological and physiological acoustics

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    Acoustics research involving human participants typically takes place in specialized laboratory settings. Listening studies, for example, may present controlled sounds using calibrated transducers in sound-attenuating or anechoic chambers. In contrast, remote testing takes place outside of the laboratory in everyday settings (e.g., participants' homes). Remote testing could provide greater access to participants, larger sample sizes, and opportunities to characterize performance in typical listening environments at the cost of reduced control of environmental conditions, less precise calibration, and inconsistency in attentional state and/or response behaviors from relatively smaller sample sizes and unintuitive experimental tasks. The Acoustical Society of America Technical Committee on Psychological and Physiological Acoustics launched the Task Force on Remote Testing (https://tcppasa.org/remotetesting/) in May 2020 with goals of surveying approaches and platforms available to support remote testing and identifying challenges and considerations for prospective investigators. The results of this task force survey were made available online in the form of a set of Wiki pages and summarized in this report. This report outlines the state-of-the-art of remote testing in auditory-related research as of August 2021, which is based on the Wiki and a literature search of papers published in this area since 2020, and provides three case studies to demonstrate feasibility during practice

    Oscillatory hyperactivity and hyperconnectivity in young APOE-ɛ4 carriers and hypoconnectivity in Alzheimer's disease

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    We studied resting-state oscillatory connectivity using magnetoencephalography in healthy young humans (N = 183) genotyped for APOE-ɛ4, the greatest genetic risk for Alzheimer’s disease (AD). Connectivity across frequencies, but most prevalent in alpha/beta, was increased in APOE-ɛ4 in a set of mostly right-hemisphere connections, including lateral parietal and precuneus regions of the Default Mode Network. Similar regions also demonstrated hyperactivity, but only in gamma (40–160 Hz). In a separate study of AD patients, hypoconnectivity was seen in an extended bilateral network that partially overlapped with the hyperconnected regions seen in young APOE-ɛ4 carriers. Using machine-learning, AD patients could be distinguished from elderly controls with reasonable sensitivity and specificity, while young APOE-e4 carriers could also be distinguished from their controls with above chance performance. These results support theories of initial hyperconnectivity driving eventual profound disconnection in AD and suggest that this is present decades before the onset of AD symptomology

    The absence of an auditory-visual attentional blink is not due to echoic memory.

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    Als binnen een halve seconde twee visuele items in een serieel aangeboden stroom moeten worden geselecteerd, is de prestatie voor het tweede item vaak relatief slecht (er treedt een “attentional blink” op); wanneer het eerste echter item auditief wordt aangeboden, verdwijnt de blink meestal. We hebben aangetoond dat dit laatste niet wordt veroorzaakt doordat proefpersonen hun echoïsch geheugen gebruiken om de verwerking van het auditieve item uit te stellen tot na het einde van de visuele stroom

    Observational Learning of New Movement Sequences Is Reflected in Fronto-Parietal Coherence

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    Mankind is unique in her ability for observational learning, i.e. the transmission of acquired knowledge and behavioral repertoire through observation of others' actions. In the present study we used electrophysiological measures to investigate brain mechanisms of observational learning. Analysis investigated the possible functional coupling between occipital (alpha) and motor (mu) rhythms operating in the 10Hz frequency range for translating “seeing” into “doing”. Subjects observed movement sequences consisting of six consecutive left or right hand button presses directed at one of two target-buttons for subsequent imitation. Each movement sequence was presented four times, intervened by short pause intervals for sequence rehearsal. During a control task subjects observed the same movement sequences without a requirement for subsequent reproduction. Although both alpha and mu rhythms desynchronized during the imitation task relative to the control task, modulations in alpha and mu power were found to be largely independent from each other over time, arguing against a functional coupling of alpha and mu generators during observational learning. This independence was furthermore reflected in the absence of coherence between occipital and motor electrodes overlaying alpha and mu generators. Instead, coherence analysis revealed a pair of symmetric fronto-parietal networks, one over the left and one over the right hemisphere, reflecting stronger coherence during observation of movements than during pauses. Individual differences in fronto-parietal coherence were furthermore found to predict imitation accuracy. The properties of these networks, i.e. their fronto-parietal distribution, their ipsilateral organization and their sensitivity to the observation of movements, match closely with the known properties of the mirror neuron system (MNS) as studied in the macaque brain. These results indicate a functional dissociation between higher order areas for observational learning (i.e. parts of the MNS as reflected in 10Hz coherence measures) and peripheral structures (i.e. lateral occipital gyrus for alpha; central sulcus for mu) that provide low-level support for observation and motor imagery of action sequences

    Genetic erosion impedes adaptive responses to stressful environments

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    Biodiversity is increasingly subjected to human-induced changes of the environment. To persist, populations continually have to adapt to these often stressful changes including pollution and climate change. Genetic erosion in small populations, owing to fragmentation of natural habitats, is expected to obstruct such adaptive responses: (i) genetic drift will cause a decrease in the level of adaptive genetic variation, thereby limiting evolutionary responses; (ii) inbreeding and the concomitant inbreeding depression will reduce individual fitness and, consequently, the tolerance of populations to environmental stress. Importantly, inbreeding generally increases the sensitivity of a population to stress, thereby increasing the amount of inbreeding depression. As adaptation to stress is most often accompanied by increased mortality (cost of selection), the increase in the ‘cost of inbreeding’ under stress is expected to severely hamper evolutionary adaptive processes. Inbreeding thus plays a pivotal role in this process and is expected to limit the probability of genetically eroded populations to successfully adapt to stressful environmental conditions. Consequently, the dynamics of small fragmented populations may differ considerably from large nonfragmented populations. The resilience of fragmented populations to changing and deteriorating environments is expected to be greatly decreased. Alleviating inbreeding depression, therefore, is crucial to ensure population persistence

    PICKA-XL: The effects of lexical content, acoustic and linguistic variability, and vocoding on voice cue perception

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    The data presented here were collected as part of the PICKA-XL project and are associated with the publication linked below. The dataset contains the JND scores of the human participants they obtained in the experiment (scores.csv)
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