“Unattended, distracting or irrelevant”: Theoretical implications of terminological choices in auditory selective attention research

Makov, Shiri; Pinto, Danna; Yahav, Paz Har-shai; Miller, Lee M.; Golumbic, Elana Zion

doi:10.1016/j.cognition.2022.105313

Cited by 12 publications

(11 citation statements)

References 123 publications

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“…Another contribution of our study is introducing a behavioral task of repeated word detection across conversations, allowing us to identify the actual attended conversation with high temporal resolution. This method addresses a common issue in previous AAD studies where subjects’ attention could inadvertently shift to the unattended stream 21 , leading to mislabeled data and affecting the training and evaluation of AAD models. By incorporating a behavioral measure into our experiment design, we have enhanced the accuracy of determining the attended talker or conversation.…”

Section: Discussionmentioning

confidence: 99%

“…Another persistent challenge in AAD model fitting and evaluation is the difficulty in accurately determining the specific talker to which a subject is attending, especially with high temporal resolution. Previous methods often assume that subjects continuously focus on a pre-designated talker, overlooking the possibility of inadvertent attention shifts 21 . This assumption can lead to mislabeling in data and biasing the performance evaluation of AAD algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Brain-controlled augmented hearing for spatially moving conversations in multi-talker environments

Choudhari,

Han,

Bickel

et al. 2024

Preprint

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Focusing on a specific conversation amidst multiple interfering talkers presents a significant challenge, especially for the hearing-impaired. Brain-controlled assistive hearing devices aim to alleviate this problem by separating complex auditory scenes into distinct speech streams and enhancing the attended speech based on the listener’s neural signals using auditory attention decoding (AAD). Departing from conventional AAD studies that relied on oversimplified scenarios with stationary talkers, we present a realistic AAD task that mirrors the dynamic nature of acoustic settings. This task involves focusing on one of two concurrent conversations, with multiple talkers taking turns and moving continuously in space with background noise. Invasive electroencephalography (iEEG) data were collected from three neurosurgical patients as they focused on one of the two moving conversations. We propose an enhanced brain-controlled assistive hearing system that combines AAD and a binaural speaker-independent speech separation model. The separation model unmixes talkers while preserving their spatial location and provides talker trajectories to the neural decoder to improve auditory attention decoding accuracy. Our subjective and objective evaluations show that the proposed system enhances speech intelligibility and facilitates conversation tracking while maintaining spatial cues and voice quality in challenging acoustic environments. This research demonstrates the potential of our approach in real-world scenarios and marks a significant step towards developing assistive hearing technologies that adapt to the intricate dynamics of everyday auditory experiences.TAKEAWAYS-Brain-controlled hearing device for scenarios with moving conversations in multi-talker settings, closely mimicking real-world listening environments-Developed a binaural speech separation model that separates speech of moving talkers while retaining their spatial locations, enhancing auditory perception and auditory attention decoding-Proposed system enhances speech intelligibility and reduces listening effort in realistic acoustic scenes

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Brain-controlled augmented hearing for spatially moving conversations in multi-talker environments

Choudhari,

Han,

Bickel

et al. 2024

Preprint

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“…However, a second alternative explanation involves the notion of diverse listening strategies. Although in selective attention paradigms participants are instructed to pay attention only to one talker, we cannot control how they actually distributed their attention nor do we have direct insight into the listening strategies employed (Makov et al, 2022). Moreover, since it is possible to understand the content of more than one concurrent speech stream (Agmon et al, 2021; Kaufman & Zion Golumbic, 2023; Vanthornhout et al, 2019), and some individuals are particularly apt at divided attention (Colflesh & Conway, 2007; Lambez et al, 2020), this may underly the decoupling between manifestations of neural attention-bias and performance.…”

Section: Discussionmentioning

confidence: 99%

“…Since the current experiment was not designed specifically to test these hypotheses at the level of individual participants, additional research is required to substantiate the notion of different listening strategies. We hope that future follow up research will be able to shed additional light on the nature of individual differences in neural attention-bias, and will take into consideration the possibility of different listening strategies rather than assuming a uniform and fully selective listening strategy across all individuals (Makov et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Neural Speech-Tracking During Selective Attention and Attention-Switching Between Concurrent Talkers: a spatially realistic audiovisual study

Har-shai Yahav,

Korisky,

Vaknin Harel

et al. 2023

Preprint

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Selective attention to a talker in multi-talker scenarios, is associated with enhanced neural speech-tracking of the target talker, relative to competing non-target talkers. This response is proposed to reflect the prioritization and preferential processing of the target speech in auditory and language related regions. Here we investigated whether this neural-bias for tracking target speech, persists also after listeners actively switch their attention to another target talker. Using a spatially-realistic audiovisual design, we studied responses at both the group and individual level.Participants watched a video lecture (target speech) on a screen in front of them, which they were instructed to pay attention to and answered comprehension questions about its content. Concurrently, audio from an additional lecture, by a different talker, was played though a loudspeaker to their left, which they were told to ignore (non-target speech). Importantly, in the middle of the experiment, the lectures serving as target and non-target switched roles: the lecture that was formerly ‘non-target’ was presented as a video on the central screen and became the ‘target’, and vice versa. We compared behavioral performance and neural speech-tracking of both lectures before and after the switch, to test how effectively participants switched their attention and whether there are carry-over effects from before the switch.At the group level, we found no significant differences in performance or in the neural-bias towards the target talker before vs. after the switch. This implies that, generally speaking, selective attention was just as effective after the switch as it was before. However, analysis of individual level data revealed a more complex and diverse pattern. We found that the neural group level results were driven by only 25% of participants, who showed consistent neural-bias towards the target talker both before and after the switch. However, 50% of participants showed neural-bias towards the target talker only in one half of the experiment, and an additional 25% showed no difference in the neural representation of the target vs. non-target speech, before or after the switch. We further show that these individual differences cannot be ‘trivially’ explained by poor signal quality, nor are they associated with behavioral performance. Rather, they suggest that neural-bias towards the target talker is not a prerequisite for selective attention performance, and in many cases target and non-target speech are co-represented in the neural signal. Whether this variability reflects the employment of different listening strategies or insufficient sensitivity of the neural-bias speech-tracking metric remains to be explored in future studies. However, these results challenge the assumptions that modulation of the speech-tracking response can be used as a one-to-one proxy for selective attention to speech in multi-talker contexts.

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“…In sum, we provide evidence that stimulus-driven attention modulates neurophysiological responses during sustained attention to a target. Stimulus-driven attention is synonymous with distraction here, since the salient sounds were task-irrelevant but their presence had a consequence on behavioral performance (Makov et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Salience-dependent disruption of sustained auditory attention can be inferred from evoked pupil responses and neural tracking of task-irrelevant sounds

Fiedler,

Johnsrude,

Wendt

2023

Preprint

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Stimulus-driven attention allows us to react to relevant stimuli (and imminent danger!) outside our current focus of attention. But irrelevant stimuli can disrupt attention as well, for example during listening to speech. The degree to which sound captures attention is called salience, which can be estimated by existing, behaviorally validated, computational models (Huang & Elhilali, 2017). Here we examined whether neurophysiological responses to task-irrelevant sounds indicate the degree of distraction during a sustained listening task and how much this depends on individual hearing thresholds. To this end, we asked N = 47 Danish speaking adults (28/19 female/male, 24 hearing aid users) to listen to continuous speech while one-second-long, task-irrelevant natural sounds (distractors) of varying computed salience were presented at unpredictable times and locations. The task-irrelevant sounds evoked a consistent pupil dilation (PD), neural distractor-tracking (DT) and a drop of neural target-speech-tracking (ΔTT). Within-subject statistical modelling showed that PD and DT are enhanced for sounds with higher computed salience (salience sensitivity), independent of hearing thresholds. Participants with generally larger PD showed stronger ΔTT and performed worse in target speech comprehension. Participants who exhibited a stronger ΔTT for more salient sounds (salience sensitivity) understood less of the target speech. Beyond hearing loss, PD, target speech tracking (and its salience sensitivity) explained 43% of variance in target speech comprehension. We conclude that distraction can be inferred from neurophysiological responses to task-irrelevant stimuli. Our findings represent a step towards neurophysiological assessment of attention dynamics during continuous listening with potential applications in hearing care diagnostics.Significance statementSuccessful speech-in-noise comprehension in daily life does not only depend on the acuity of the auditory input, but also cognitive factors like attentional control. Being able to measure distraction-dependent neurophysiological responses to peripheral, task-irrelevant stimuli would enable monitoring how much the attentional focus is instantaneously captured away from a target under sustained attention. Here we show that both pupil dilation and neural tracking of distractor sounds, reflect the degree to which people with both normal and elevated hearing thresholds are distracted. Such a measure could be used to non-invasively track the focus of attention and thus could find application in hearing care diagnostics, where cognitive factors like attentional control are being increasingly recognized as important.

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“Unattended, distracting or irrelevant”: Theoretical implications of terminological choices in auditory selective attention research

Cited by 12 publications

References 123 publications

Brain-controlled augmented hearing for spatially moving conversations in multi-talker environments

Brain-controlled augmented hearing for spatially moving conversations in multi-talker environments

Neural Speech-Tracking During Selective Attention and Attention-Switching Between Concurrent Talkers: a spatially realistic audiovisual study

Salience-dependent disruption of sustained auditory attention can be inferred from evoked pupil responses and neural tracking of task-irrelevant sounds

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